Advocating_for_Advocacy_An_Exploratory_Survey_on_Student

Advocating for Advocacy: An Exploratory Survey on Student Advocacy Skills and Training in Counseling Psychology

Alyssa M. Ramírez Stege, Dustin Brockberg, and William T. Hoyt University of Wisconsin—Madison

Advocacy is considered a core competency within the field of counseling psychology, however more attention is needed to the training and assessment of advocacy competence for counselors-in-training. This study utilized Ratts and Ford’s (2010) Advocacy Competencies Self-Assessment survey to measure self-perceived advocacy competence of master’s and doctoral students within counseling (Council for Accreditation of Counseling and Related Educational Programs–accredited) and counseling psychology (American Psychological Association–accredited) programs. An exploratory factor analysis suggested 3 underlying factors in self-reported advocacy competence: Alliance Building and Systems Collaboration, Action and Assessment, and Awareness Building. Master’s and doctoral students displayed marginal differences in Advocacy Competencies Self-Assessment scores with doctoral students scoring slightly higher in the Awareness Building factor. Respondents’ perceived level of advocacy importance was a significant predictor of advocacy competence. Program characteristics (advocacy-related resources and opportunities to engage in advocacy activities) were also significant predictors of perceived competence. We propose a developmental model of advocacy competency acquisition as a basis for future research on assessment and training of advocacy skills.

Keywords: psychology training, advocacy, competence, social justice, assessment

Counseling psychologists and other counseling professionals have recognized the need to move beyond the confines of the traditional counseling space and into the communities in which they serve (Vera & Speight, 2003). Consequently, counseling professionals have made efforts to become agents of social change through advocacy—seeking to confront, challenge, and eliminate institutional and social barriers that harm clients’ well-being (Kiselica & Robinson, 2001; Ratts, 2009; Myers, Sweeney, & White, 2002; Smith, Reynolds, & Rovnak, 2009). Advocacy can be defined as “the process or act of arguing or pleading for a cause or proposal” to promote social change (Myers et al., 2002, p. 394) and is often linked to the social justice ideals of the counseling field.

Advocacy has been recognized as an important skill in the counseling profession (Myers et al., 2002; Ratts, D’Andrea, & Arredondo, 2004). At the master’s level of training, the American Counseling Association (ACA) has endorsed the advocacy com- petencies (Lewis, Arnold, House, & Toporek, 2003), considering advocacy happens at multiple levels (e.g., client, underprivileged groups, legislative) and is achieved by counselors acting with or on behalf of clients to increase their ability to utilize and access resources that impede their development (Lewis et al., 2003). There are six ACA advocacy competency domains within three levels that move from micro- to macrolevels of intervention (Lewis et al., 2003). In the client/student level, there are two domains: client/student empowerment and client/student advo- cacy. The school/community level includes community collabora- tion and systems advocacy. Finally, the public arena level includes public information and social/political advocacy (Lewis et al., 2003). At the doctoral level of training, advocacy is one of the American Psychological Association (APA) competency bench- marks and includes two components: empowerment and systems change. Each component is assessed within three levels of stu- dents’ professional development: readiness for practicum, readi- ness for internship, and readiness for entry to practice (Fouad et al., 2009). For the empowerment component, students are expected to move from an awareness of the factors that unjustly influence individuals, institutions, and systems, to an ability to intervene and promote direct action. In systems change, students are expected to move from an understanding of the differences between interven- tions at individual and institutional levels, to promoting change at multiple levels (Fouad et al., 2009).

Overall, the role of advocacy in counseling acknowledges the need for professionals to intervene at individual and systemic levels to promote change that positively influences clients’ well-

This article was published Online First April 6, 2017. ALYSSA M. RAMÍREZ STEGE is a doctoral student in the Department of

Counseling Psychology at the University of Wisconsin-Madison. Her re- search interests include counselor training in cultural competence, and development of culturally-grounded psychotherapeutic interventions.

DUSTIN BROCKBERG is a doctoral student in the Department of Counsel- ing Psychology at the University of Wisconsin-Madison. He is a member of APAGS and has served as the State Advocacy Coordinator of Wiscon- sin. His research interests include advocacy training, help-seeking decision making processes with veterans, and reintegration issues for student service members/veterans (SSMV’s).

WILLIAM T. HOYT is professor and chair of the Department of Counsel- ing Psychology at the University of Wisconsin-Madison. His research interests include relational processes related to psychological well-being; psychotherapy process and outcome; and research methods and measure- ment.

CORRESPONDENCE CONCERNING THIS ARTICLE should be addressed to Alyssa M. Ramírez Stege. E-mail: [email protected]

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being (Goodman et al., 2004). Yet despite general professional goals and objectives, there is still little known about what advo- cacy efforts actually look like (Goodman et al., 2004). In a national survey in 2004, Myers and Sweeney reported that most profes- sional counselors and counselor educator respondents believed that advocacy was a moderately to highly needed professional activity. Respondents reported implementing the following advocacy ef- forts: being on a committee or volunteering (68%), literature and information about advocacy (63%), coalitions with other profes- sional groups (59%), government relations liaisons (55%), media opportunities (48%), advocacy training packet (47%), paid staff (31%), paid consultants (24%), and other (10%). These efforts were rated by respondents to be only moderately successful (My- ers & Sweeney, 2004).

In a study by the National Council of Schools and Programs of Professional Psychology, a majority of faculty and student respondents (62%) reported that advocacy training was not offered (Lating, Barnett, & Horowitz, 2009). Nevertheless, data from this study suggested that issues related to community and public service were addressed in courses, and programs offered community service opportunities. Mallinckrodt, Miles, and Levy (2014) developed a tripartite scientist–practitioner– advocate model to address social justice advocacy training in graduate counseling programs. These authors propose that add- ing an advocate role to the currently widespread scientist- practitioner training model can help enhance the application of science and practice by facilitating students’ development of skills that help them intervene and advocate for clients’ needs at organizational and systemic levels. For example, students are encouraged to use advocacy goals to inform research questions and interventions. This model focuses on developing four main domains of competency to serve as advocate: knowledge, skills, attitudes, and values (e.g., equity, liberty). They base their curriculum on Bronfenbrenner’s (1979) ecological model, the ACA competencies (Lewis et al., 2003), the APA competency benchmarks (Fouad et al., 2009) and emerging research on students’ experiences in advocacy (Mallinckrodt et al., 2014). According to Mallinckrodt and colleagues (2014), this alterna- tive training model equips students with the skills needed to address and intervene on problems rooted in sociocultural con- texts of oppression and social injustice that affect mental health. These authors note students are generally very satisfied with this training, feel a commitment to doing social justice work, and social justice research has increased (Mallinckrodt et al., 2014).

Hof, Dinsmore, Barber, Suhr, and Scofield (2009) proposed the TRAINER model, an acronym for a 7-step collaborative process, to help counselors integrate social and professional advocacy into practice. The TRAINER model steps are (a) target advocacy needs, (b) respond by implementing an advocacy competency that can address the needs, (c) articulate a plan to accomplish advo- cacy, (d) implement the plan, (e) network for advocacy during training, (f) evaluate the training, and (g) retarget to meet other advocacy needs (Hof et al., 2009). This model provides instruction on how to implement social and professional advocacy efforts by collaboratively identifying steps toward action, and gaining feed- back on the success of the implementation (Hof et al., 2009). The authors note that this model has been implemented in three training settings, generating 52 plans to implement social and professional

advocacy, but do not provide specific outcome measures (Hof et al., 2009).

Although both training models previously described provide some preliminary evidence of their effectiveness in counselor advocacy training, there is little knowledge of what advocacy training, resources, and engagement is available in counseling programs nation-wide. Thus, the current study sought to under- stand how future clinicians are being trained and equipped with the necessary tools to become effective advocates. The authors con- ducted a nation-wide survey of master’s and doctoral students in counseling and counseling psychology to understand students’ self-evaluated advocacy competencies as measured by the Advo- cacy Competencies Self-Assessment (ACSA; Ratts & Ford, 2010). The ACSA has been designed to assess the multiple areas of advocacy as endorsed by the ACA. Because the ACSA has not been used on a large scale, we also sought to understand what dimensions of advocacy are represented on this scale through the use of factor analysis. Finally, we sought to understand students’ levels of self-assessed advocacy competency or self-efficacy ac- cording to different advocacy dimensions and whether there were differences according to program of study (master’s and doctoral) or year in the program. We hypothesized that the longer students were engaged in a program, the more opportunity they would have to develop advocacy competencies, consequently scoring higher on the ACSA.

Another goal of this study was to understand the possible contextual factors that might influence students’ self-assessed ad- vocacy competency such as the advocacy-related resources and training available to them, their current engagement in advocacy efforts, and the importance they ascribe to advocacy as part of their professional endeavors. We hypothesized that students who had more training and advocacy resources, and were engaged in more advocacy efforts would have higher self-assessed advocacy com- petency.

Method

Participants

Recruitment of participants was conducted through email cor- respondence with both APA-accredited counseling psychology doctoral programs (n ! 78), including programs with master’s- level programs of study, and Council for Accreditation of Coun- seling and Related Educational Programs (CACREP)–accredited master’s programs that listed clinical mental health counseling as a training focus (n ! 158). After obtaining Institutional Review Board approval from a Midwest university, we contacted doctoral programs through training directors listed on the website of the Council of Counseling Psychology Training Programs, and mas- ter’s programs through the program director listed on the CACREP website. Our invitation email included a link to an electronic survey, which outlined informed consent, purpose, and instructions to complete the survey. At their discretion, the email prompt was then circulated to current students affiliated with their academic program.

Of both APA and CACREP programs contacted (n ! 236), 297 graduate student participants partially or fully completed the on- line survey, of which 188 participants (106 master’s and 82 doc- toral students) completed the entire survey and were used for the

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191ADVOCATING FOR ADVOCACY

final analysis. The electronic survey consisted of a variety of questions including (a) demographic questions (ethnic identity, age, gender identity, geographical location) and (b) training pro- gram questions (type of counseling program: master’s level— CACREP, master’s level—non-CACREP, doctoral level—APA), as well as year in program.

Measures

Advocacy Competencies Self-Assessment (ACSA) survey. The ACSA survey is a 30-item questionnaire that uses a 3-point Likert scale (0 ! almost never, 2 ! sometimes, 4 ! almost always; Ratts & Ford, 2010). For three questions, higher scores reflect lower advocacy competence; these were reverse coded as recommended by the authors. The items were written to assess competency in six domains of advocacy: client/student empowerment, community collaboration, public information, client/student advocacy, systems advocacy, and social/political advocacy, based on the ACA’s advocacy competencies model (Lewis et al., 2003; Ratts & Ford, 2010). Each domain was assessed by five items. Domains and example items include (a) client/student empowerment (e.g., “It is difficult for me to identify clients’ strengths and resources”), (b) community col- laboration (e.g., “I develop alliances with groups working for social change”), (c) public information (e.g., “I disseminate information about oppression to media outlets”), (d) client/ student advocacy (e.g., “I am skilled at helping clients/students gain access to needed resources”), (e) systems advocacy (e.g., “I use data to demonstrate urgency for systemic change”), and (f) social/political advocacy (e.g., “I lobby legislators and poli- cymakers to create social change”). Total ACSA scores have a possible range between 0 and 120; higher scores indicate stron- ger advocacy competency.

Types of advocacy resources and training. To understand possible contextual factors influencing students’ self-assessed ad- vocacy competencies, we asked students whether their programs offered courses or specific training related to advocacy-based skills, and whether faculty in their program played an active role in advocacy efforts within their community. Each of these ques- tions was presented as a dichotomous item (1 ! yes; 0 ! no). Based on studies assessing student advocacy training (Hof et al., 2009; Lating et al., 2009; Lyons et al., 2015; Mallinckrodt et al., 2014; Myers & Sweeney, 2004) we also asked participants to identify the following advocacy resources available to them: (a) committees/volunteer opportunities, (b) advocacy literature/infor- mation, (c) advocacy training packet, (d) coalitions with profes- sional groups, (e) government relation liaisons, (f) media/presen- tation opportunities, (g) none, and/or (h) other (and describe). Each of these items was presented together and participants could select multiple items.

Types of advocacy engagement; level of importance. Based on previous literature on advocacy competencies and activities (Lewis, 2011; Lewis, Ratts, Paladino, & Toporek, 2011; Lyons et al., 2015; Myers & Sweeney, 2004), we asked participants to identify what types of advocacy efforts they had been involved in during their time within their academic program: (a) legislative policy writing, (b) community awareness building, (c) attending community meetings/committees, (d) attending a rally or protest for a social justice issue, (e) advocating for a client to receive

services, (f) leading an open discussion with community leaders about needed services, (g) participating in a professional group (APA, American Psychological Association of Graduate Students [APAGS], ACA, etc.) event around advocacy, (h) volunteering, (i) none, and/or (j) other (and describe). Each of these items was presented together and participants could select multiple items. We also asked participants to rate the level of importance they ascribed to advocacy within the counseling profession measured on a 4-point Likert scale (1 ! not important to 4 ! very important).

Results

The initial sample included N ! 296 participants; however, 108 participants were excluded from the final sample due to complet- ing fewer than 5% of the items in the survey. The final sample included N ! 188 counseling and counseling psychology students, of whom 56% (n ! 106) were pursuing master’s and 44% (n ! 82) were pursuing doctoral degrees. A majority of participants (52%) were enrolled in master’s programs with CACREP accreditation, a very small percentage (4%) in non-CACREP accredited master’s programs, and the rest (44%) in doctoral counseling psychology programs. Master’s students included 24.5% (n ! 26) first-year students, 69.8% (n ! 74) second-year students, and 5.7% (n ! 6) third-year students. Doctoral students included 22.9% (n ! 19) first-year students, 30.1% (n ! 25) second-year students, 15.7% (n ! 13) third-year students, 13.3% (n ! 11) fourth-year students, and 18.1% (n ! 14) fifth-year and other students. Most partici- pants (84%) identified as female, another 14% as male, and 2% identified outside of the gender binary. The mean age was 31.15 (SD ! 9.18; minimum ! 20; maximum ! 60). With regard to race/ethnicity, 8% of participants identified as Black, 7% as Asian or Pacific Islander, 6% as Hispanic or Latino, 1% as Native American, and 78% as White. The largest proportion of survey participants attended training programs in the Midwest region of the United States (45%), with 22% in the south, 19% in the northeast, 11% in the west, and 4% in the Pacific region.

Factor Structure of ACSA

We conducted a principal axis factor analysis of the 30 ACSA items using oblimin rotation (to allow for correlated factors). A scree plot (Cattell, 1966) suggested either three or four interpre- table factors, and parallel analysis (Horn, 1965) suggested a three- factor solution. We therefore focused on a three-factor solution, but also examined the four-factor solution to determine whether the fourth factor was meaningful.

Factor loadings for the three rotated factors are shown in Table 1. The first factor included moderate or high loadings (i.e., stan- dardized factor loading ".35) from 10 items describing systems- level advocacy, and was called Alliance Building and Systems Collaboration. Seven items loading on Factor 2 reflected Action and Assessment usually with individual clients, and five items loading on Factor 3 reflected the process of Awareness Building, by which counselors explore with their clients contextual or sys- temic factors that may affect the presenting problem. Three items cross-loaded on Factors 1 and 2, and one item cross-loaded on Factors 2 and 3. Four of the ACSA items did not load above .35 on any of the three factors. Correlations among the three factors ranged from .45 to .60.

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192 RAMÍREZ STEGE, BROCKBERG, AND HOYT

The four-factor model produced dimensions similar to Factors 1, 2, and 3 from the original model, with a fourth factor that was mainly defined by the three items that described use of data to influence social systems. These items were represented on Factor 1 of the three-factor solution, and did not in our view represented a particular technique rather than a distinct dimension of advocacy. Therefore, we focused on subscales derived from the three-factor solution for our analyses. Unit-weighted subscales based on items

with loadings above .35 on these factors showed acceptable reli- ability (# ! .86, .85, and .71 for Factors 1, 2, and 3, respectively) in our sample.

Table 2 shows the means and SDs for each of the three ACSA subscales separately for master’s and doctoral participants. The pattern of responses was similar for the two training levels, with participants rating themselves as most competent in awareness building and application of advocacy skills in the clinical context

Table 1 Factor Loadings for Advocacy Competencies Self-Assessment (ASCA) Survey Scale

Item (and ACSA domain)

Factor 1: Alliance Building and Systems

Collaboration

Factor 2: Action and Assessment

Factor 3: Awareness Building

24. Collaborate using data to promote social change (6) .738 .056 .001 4. Use data for systemic change (5) .678 –.100 .055

12. Join allies to confront oppression (6) .632 –.120 .313 9. Develop alliances with groups (2) .610 .071 .172 5. Presentation on environmental barriers influencing client/student (3) .605 .067 –.175

29. Assess own public influence (3) .548 .280 –.085 30. Lobby legislators/policymakers for social change (6) .544 –.089 –.097 17. Inform media about oppression (3) .504 –.013 –.233 10. Analyze sources of power in systems (5) .441 –.200 .320 3. Alert groups about concerns (2) .439 .117 .180

28. Assess systems advocacy effectiveness (5) .539 .369 –.150 22. Deal with systemic resistance (5) .405 .368 .142 23. Collaborate to inform public (3) .388 .367 .072 20. Develop action plan to confront barriers influencing client/student (4) –.113 .876 .024 16. Develop action plan for systems change (5) .270 .665 –.076 26. Identify allies who confront barriers influencing client/student (4) .161 .463 .274 8. Help client access resources (4) .068 .444 .191

21. Assess own effectiveness interacting with groups (2) .214 .436 .105 15. Identify community member strengths and resources (2) .249 .419 .192 27. Collaborate with diverse groups (2) .261 .390 .210 19. Help clients identify external barriers (1) –.078 .447 .448 14. Identify barriers to well-being (4) –.113 .228 .591 13. Recognize when concerns are due to oppression (1) .097 –.064 .552 7. Identify whether environmental conditions affect clients (1) .102 –.114 .498

11. Communicate ethically about oppression when speaking publicly (3) .099 .222 .470 18. Support movements for social change (6) .344 .139 .379 1. Identify client strengths –.034 .156 .178 2. Negotiate for services (4) .121 .278 .285 6. Distinguish when advocacy is needed (6) .304 .175 .276

25. Assist clients’ self-advocacy (1) .155 .336 .289 Correlations among factors

Factor 1 — Factor 2 .62 — Factor 3 .48 .59 —

Note. Factor loadings ".35 are displayed in boldface. Numbers in parentheses represent the ACSA survey domain: 1 ! client/student empowerment, 2 ! community collaboration, 3 ! public information, 4 ! client/student advocacy, 5 ! systems advocacy, and 6 ! social/political advocacy).

Table 2 Advocacy Competencies Self-Assessment (ASCA) Total and Subscale Scores for Doctoral and Master’s Students

Doctoral Master’s

Factor M SD M SD Cohen’s d 95% CI

Factor 1: Alliance Building and Systems Collaboration 2.04a .95 1.85a .93 .20 [$.09, .49] Factor 2: Action and Assessment 2.78b .94 2.70b 1.03 .08 [$.21, .37] Factor 3: Awareness Building 3.26c .76 2.95c .80 .40

!!! [.11, .69] ACSA Total 2.64 .73 2.45 .79 .25 [$.04, .54]

Note. CI ! confidence interval. Alphabetic subscripts are based on dependent samples t tests. Means in the same column that do not share a subscript differ significantly (p % .01). !!! p % .001.

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193ADVOCATING FOR ADVOCACY

(Factor 3: Awareness Building; Factor 2: Action and Assessment), and somewhat lower (near the midpoint of the scale) on the subscale reflecting systems-level advocacy (Factor 1: Alliance Building and Systems Collaboration). Our results show that overall self-assessed advocacy competencies decreased as participants moved from microlevel efforts (i.e., within the counseling rela- tionship such as the Awareness Building and Action & Assessment scales) to macrolevel systems-based efforts (i.e., Alliance Building and Systems Collaboration scale). The only statistically significant difference between master’s and doctoral participants in self- reported competency was on the Awareness Building subscale (d ! 0.40 95% CI [0.11, 0.69]). Dependent samples t tests show significant mean differences between factors (see Table 2). For master’s and doctoral participants, the Awareness Building (Factor 3) mean was significantly higher than the Action and Assessment (Factor 2) mean. Alliance Building and Systems Collaboration (Factor 1) was the significantly lowest mean for all participants.

We hypothesized that participants’ year in an academic program would significantly predict total ACSA score, with participants who have had more time in their master’s or doctoral program scoring higher on the ACSA scale presumably because they have had more time to develop advocacy skills. However, year in program was not a significant predictor of ACSA total score for either master’s (B ! 0.06 [$0.13, 0.25], p ! .55) or doctoral (B ! $0.06 [$0.28, 0.16], p ! .59) participants.

Advocacy Resources and Training

Figure 1 shows the percentage of participants who reported having access to each type of advocacy resources. These percent- ages are reported separately for master’s and doctoral participants, and odds ratios (OR) greater than 1.0 indicate that doctoral par- ticipants report greater access to a given resource than master’s participants. The 95% confidence intervals (CIs) for these odds ratios all include OR ! 1.0, which means that the odds of having access to each of these resources did not differ significantly for master’s and doctoral participants. A majority of participants (80%) reported that their program faculty engaged in some form of advocacy, and fewer than 1% (n ! 2) of participants reported not having any available advocacy-related resources in their program.

We also assessed whether having access to advocacy-specific training and/or resources predicted students’ self-assessed advo- cacy competencies. A measure of advocacy resources available was computed by counting all the types of advocacy resources reported per participant, excluding responses of “other.” The pos- sible range for this score was 0 to 6 (M ! 2.14; SD ! 1.40). When the ACSA total score was regressed onto this resources score, B ! 0.15 [0.08, 0.23]. This shows that each added resource accessible to a student predicts a 0.15-unit increase in ACSA total score (which is about 0.2 SDs on this scale—see Table 2). Participants with more training and/or resources available to them tended to report higher advocacy self-efficacy.

Engagement in Advocacy

Figure 2 shows the percentage of participants who reported having engaged in each type of advocacy activity. As in Figure 1, OR " 1.0 indicates that doctoral participants reported higher engagement levels than master’s participants. For three of these activity types, doctoral participants reported significantly higher engagement levels than master’s participants (as indicated by 95% CIs that exclude OR ! 1.0). Doctoral participants reported more than three times the odds of attending a rally or protest for a social justice issue, more than 2.5 times the odds of advocating for a client to receive services, and more than 2.5 times the odds of participating in a professional group or event around advocacy, compared with master’s participants (see Figure 2). All other odds ratio calculations indicate no differences between master’s and doctoral participants.

Most participants (50%) reported engaging in one to two types of advocacy activities, with 28% engaging in three to four types of activities, and 10% engaging in five or more. Thirteen percent of the total sample did not report engaging in any advocacy activities.

A measure of advocacy engagement was computed by counting all types of advocacy efforts participants reported they engaged in, excluding responses of “other.” The possible range for this score was 0 to 8 (M ! 2.15; SD ! 1.58). When ACSA total scores were regressed onto advocacy engagement, B ! 0.18 [0.11, 0.24]. This indicates that a 1-unit change in engagement in advocacy activities predicts a 0.18-unit change in ACSA (about 0.25 SDs; see Table

0.9

3.8

7.5

31.1

43.4

48.1

69.8

3.7

8.5

9.8

32.9

53.7

0 20 40 60 80 100

Other

Advocacy Training Packet

Government Relation Liasions

Media or Presentation Opportunities

Coalitions with Professional Groups

Advocacy Literature or Information

Volunteering Opportunities

Percentage of Types of Advocacy Resources Available

Doctoral Master's

OR = 1.09 [0.59, 2.09]

OR = 1.25 [0.70, 2.22]

OR = 2.38 [0.67, 8.41]

OR = 0.83 [0.46, 1.50]

OR = 1.32 [0.47, 3.69]

OR = 1.08 [0.58, 2.01]

Figure 1. Percentage of types of advocacy resources available to master’s and doctoral students in counseling assessed by self-report. For each category the calculated odds ratio is shown with the respective 95% confidence interval.

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194 RAMÍREZ STEGE, BROCKBERG, AND HOYT

2). Participants reporting greater levels of advocacy engagement also reported higher levels of advocacy competency.

Perceived Importance of Advocacy

A significant exploratory finding was related to the importance students place on advocacy as part of their professional activities. Most participants (68%) reported believing advocacy is “very important” for the counseling profession; 27% reported it was “important,” and only 5% “somewhat important.” An analysis of variance test revealed significant group differences in total advo- cacy scores according to the level of importance of advocacy reported by participants. Participants who reported that advocacy efforts were “very important” to the field had a significantly higher mean ACSA total score compared to those who said it was only “important,” d ! 0.80 95% CI [0.46, 1.14].

Discussion

The counseling profession has proposed advocacy as a neces- sary professional activity and skill needed to address social ineq- uities faced by the clients and populations counselors and coun- seling psychologists work with (Lewis et al., 2011; Ratts, 2009; Ratts et al., 2004; Vera & Speight, 2003). Indeed, most (68%) of our survey participants indicated that advocacy efforts are “very important” in the counseling field. Furthermore, perceived impor- tance significantly predicted self-reported advocacy competency, similar to previously reported results (Myers & Sweeney, 2004; Nilsson & Schmidt, 2005).

Some results of this study provide additional information on the resources and activities that help predict graduate counseling stu- dents’ self-reported advocacy competency. Participants who had access to more advocacy-related training and/or resources and who engaged in more advocacy-related activities reported higher levels of advocacy competency. The resources most commonly reported by participants in this study (e.g., volunteering) and activities most commonly engaged in (e.g., community awareness building) sug- gest students are aware of the challenges faced by communities and work with them to address these needs. The resources and activities less commonly reported (e.g., having access to govern- ment liaisons, legislative policy writing) suggest students have yet

to develop skills to intervene at organizational and societal levels. Training such as the TRAINER model (Hof et al., 2009) that directly targets students’ development of action-oriented imple- mentation plans could help further develop advocacy skills.

There were no differences between master’s and doctoral par- ticipants in the types of advocacy resources available to them, however, they did differ in a few areas of advocacy engagement, with a higher proportion of doctoral relative to master’s partici- pants reporting higher engagement in attending a social justice rally or protest, advocating for a client to receive services, and participating in a professional advocacy group or event. Although we hypothesized that more years in a training program could provide more opportunity for students to develop “advanced” advocacy skills, when assessed, year in program did not signifi- cantly predict self-reported advocacy competency. Therefore, the differences in advocacy engagement among master’s and doctoral students remains unclear. It could be that these results reflect substantive variations in training practices. Developmental differ- ences could also play a role as students enter doctoral programs later in life, possibly having already developed an identity working toward social justice and more readily identify and connect with advocacy activities.

Although the ACSA survey (Ratts & Ford, 2010) intended to measure advocacy competence in the six competency domains proposed by the ACA (Lewis et al., 2003), trainees’ responses suggest that the items represent three underlying factors: Alliance Building and Systems Collaboration, Action and Assessment, and Awareness Building. These factors indicate different levels of advocacy intervention, from a micro- (i.e., client-focused) to a macro- (i.e., systems-level) approach. This continuum is implicit in the ACA advocacy competencies (Lewis et al., 2003) moving from advocacy at the client level to advocacy in the public arena. Factor 1, Alliance Building and Systems Collaboration, is mainly defined by the items intended to capture the social-political advo- cacy, systems advocacy, and public information domains in which advocacy techniques are applied at a public, systems, or political level (ACSA Domains 6, 5, and 3). Factor 2, Action and Assess- ment, is primarily defined by the client/student advocacy and community collaboration domains intended to embody efforts to allot resources for a particular client or to connect with potential

1.9

5.7

9.4

13.2

26.4

27.4

36.8

47.2

2.4

7.3

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13.4

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36.6

59.8

51.2

0 20 40 60 80 100

Volunteering Other

Legislative policy writing Lead discussion w/ community leaders on needed services

Attend a rally or protest for a social justice issue Attend community meetings/committees

Participate in a professional group or event Advocating for a client to receive services

Community awareness building

Percentage of Types of Advocacy Engagement

Doctoral Master's

OR = 1.3 [0.18, 9.43]

OR = 0.49 [0.15, 1.63]

OR = 1.18 [0.66, 2.09]

OR = 1.61 [0.86, 3.00]

OR = 3.41 [1.65, 7.03]

OR = 2.55 [1.41, 4.61]

OR = 1.49 [0.60, 3.69]

OR = 2.65 [1.44, 4.88]

Figure 2. Percentage of types of advocacy master’s and doctoral students in counseling engaged in assessed by self-report. Survey respondents could choose more than one option. For each category the calculated odds ratio is shown with the respective 95% confidence interval.

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195ADVOCATING FOR ADVOCACY

allies in the community (ACSA Domains 4 and 2). Factor 3, Awareness Building, is the least conceptually unified but the main items that define this factor can be interpreted as reflecting respon- dent sensitivity to the importance of context in affecting clients’ experience, and efforts to raise client awareness of these contextual factors (a few items from ACSA Domains 6, 4, 3, and 1). These results are consistent with how advocacy is conceptualized in the APA competency benchmarks (Fouad et al., 2009) in which be- ginning trainees (ready for practicum experiences) are expected to gain awareness of the systemic issues that influence clients, and later (ready for internship and entry to practice) develop skills to intervene at institutional and societal levels (Fouad et al., 2009).

Training Implications

Our factor analytic results suggest a developmental model of advocacy, revealed in the mean differences on the three ACSA factor scores. Overall, both master’s and doctoral participants scored highest on the Awareness Building factor, followed by the Action and Assessment factor, and scored lowest on the Alliance Building & Systems Collaboration factor. First, students may begin building awareness of the barriers faced by clients due to oppression and are able to recognize the environmental conditions that affect them (Awareness Building). Second, students may begin developing skills to intervene with clients to confront the barriers they face, connect them to appropriate resources, and assess their strengths (Action and Assessment). Third, students may begin broadening their intervention skills to other arenas to promote social change by developing alliances with groups and influencing policy (Alliance Building and Systems Collaboration).

This developmental model reflects traditional training models that often encourage students to build awareness of self and others to intervene effectively in the counseling relationship yet less commonly address how to develop broader interventions focused on seeking justice for oppressed groups. These conclusions are necessarily tentative and additional research is warranted on how and when students acquire skills in advocacy at these different levels, for example, incorporating data from new training models such as the scientist–practitioner–advocate (Mallinckrodt et al., 2014) that integrate advocacy into training. This theoretical devel- opment could be paired with efforts to devise advocacy measures that more robustly capture these different levels or dimensions of advocacy in practice.

Limitations

The field of psychology is at an early stage in its efforts to identify and measure advocacy competence among graduate stu- dents, and also among professionals. According to Kaslow et al. (2009), competency measures must focus on demonstrable ele- ments such as knowledge, skills, and attitudes, and their integra- tion to address specific client or group issues.

The ACSA survey (Ratts & Ford, 2010) is the only scale to date that measures students’ advocacy competencies, however, it has been used minimally in research. According to Ratts and Ford (2010), the ACSA survey is in early stages of development and no psychometric properties have been published to date. Conse- quently, further research and development of advocacy compe- tency assessments is needed. An additional barrier of this and other

self-report measures are the potential challenges to validity when self-report is used to assess competence. Therefore, we believe ACSA scores may best be interpreted as self-efficacy measures rather than direct measures of competence, with development of performance-based measures of advocacy competence as a fertile area for future research.

A possible limitation to this study relates to the characteristics of our participants. This was not a random sample and students who volunteered to respond to the survey may place a higher impor- tance on advocacy training than those declining to respond. More- over, the study did not collect data on the number of students enrolled in each institution. However, we recruited broadly from a national sample and our sample is representative of active students in both levels of study, with more master’s than doctoral students. Nevertheless, this is an important consideration relative to the generalizability of results.

The ACSA survey was used during one time-point in this study, thus limiting the ability to see changes in students’ competence over time, limiting our ability to interpret correlational findings. Although we offer a speculative developmental model for the acquisition of advocacy competence, this model is best tested using a longitudinal design in which cohorts of students are fol- lowed over their time in a training program.

Future Directions

Longitudinal data could increase our understanding of what, how, and when advocacy efforts are initiated, utilized and main- tained by counseling students, and tracked or evaluated by coun- seling programs. This could provide information needed for train- ing programs to follow the guidelines espoused by professional governing bodies, and help improve training efforts for students’ advocacy skills development (Jacobs et al., 2011; Jones, Sander, & Booker, 2013).

The results from this study provide important information on the current state of advocacy development and self-efficacy in grad- uate students in the counseling field. Generally, there is a need to clearly define and operationalize different types of advocacy and advocating. Future research could incorporate this study’s findings to develop new measures theoretically grounded in the three main factors found to characterize students’ advocacy competency de- velopment. The ability to assess students’ advocacy competency over time can help inform training methods, teaching practices, and future research initiatives to increase students’ self-efficacy implementing interventions at multiple levels to redress the mental health disparities their clients and communities face.

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Received October 18, 2016 Revision received March 19, 2017

Accepted March 20, 2017 !

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Received 03/02/15 Revised 05/13/15

Accepted 05/19/15 DOI: 10.1002/jcad.12115

Earn CE credit. Visit http://www.prolibraries.com/counseling to purchase and complete the test online.

Conduct disorder (CD) involves the violation of societal norms and/or the basic rights of others as a result of enduring patterns of aggressive behavior (American Psychiatric Asso- ciation [APA], 2013). For children and adolescents through age 19 years, prevalence rates range between 2% and 10% of the population (APA, 2013; Burke, Loeber, & Birmaher, 2002; Erskine et al., 2013; Loeber, Burke, Lahey, Winters, & Zera, 2000). Variation in these rates was accounted for by sample-dependent developmental, cultural, and psychosocial factors such as age, gender, and socioeconomic status. In a nationally representative epidemiological study on lifetime prevalence and age of onset of mental health disorders, Kes- sler et al. (2005) found that 9.5% of the more than 9,000 participants had been diagnosed with CD. This finding reflects the highest prevalence of the three disruptive disorders cur- rently diagnosable in childhood (APA, 2013). It should not be overlooked that epidemiological estimates of CD vary pursuant to substantive modifications of diagnostic criteria in each edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM; Loeber et al., 2000).

Characteristics of CD include verbal and physical hostil- ity and violence toward people or animals, with and without weapons; the deliberate destruction of property via fire setting or other means; lying or stealing; and the disregard of house- hold and/or societal rules, such as making curfew or attending school (APA, 2013). Consequences of CD in the short term include an increased risk for criminal charges, anxiety, de- pression, suicide, substance abuse, peer rejection, relational difficulty, and low academic achievement (Berkout, Young,

Bradley T. Erford, Margaret Ross, and Chelsea Gunther, Education Specialties Department, Loyola University Maryland; Gerta Bardhoshi, Department of Rehabilitation and Counselor Education, University of Iowa; Kelly Duncan, School of Education, Northern State University. Correspondence concerning this article should be addressed to Bradley T. Erford, Education Special- ties Department, Loyola University Maryland, Timonium Graduate Center, 2034 Greenspring Drive, Timonium, MD 21093 (e-mail: [email protected]).

Meta-Analysis of Counseling Outcomes for Youth With Conduct Disorders Bradley T. Erford, Gerta Bardhoshi, Margaret Ross, Chelsea Gunther, and Kelly Duncan

Twenty-one clinical trials were synthesized using a random-effects model, which substantiated that counseling gener- ally produces a medium effect in treating conduct disorder in youth at termination (d+ = 0.30 to 0.57; k = 28). However, the lasting effects at follow-up were unclear because few follow-up studies (k = 13) have been conducted (d+ = –0.53 to 0.58), and only 2 randomized controlled follow-up studies were located. No effects of moderating variables were evident. Implications for counseling practice and outcome research are addressed.

Keywords: meta-analysis, conduct disorder, children, adolescents, counseling

& Gross, 2011; Loeber et al., 2000; Pardini & Fite, 2010). Unfortunately, these outcomes often persist and manifest in adulthood, with poor prognoses and considerable costs to society. Prevalence rates of CD increase between childhood and adolescence, with childhood onset usually involving aggressive boys, and adolescent onset equal across gender, characterized by less physically aggressive behavior, and more likely to involve relational aggression (APA, 2013). Although the majority of individuals with CD remit by adulthood, re- search has consistently found that children with early-onset CD (diagnosed prior to the age of 10 years) are at an increased risk for developing antisocial personality disorder (APD) in adulthood (APA, 2013; Loeber et al., 2000; Pardini & Frick, 2013). This is because childhood-onset individuals with CD tend to be aggressive boys, and because symptoms of CD prior to the age of 18 years are required for an APD diagnosis (APA, 2013). The diagnosis of CD is consistently displayed across race/ethnicity and nationality, although APD is more prevalent among urban environments and lower socioeconomic strata. For individuals to be diagnosed with CD, at least three of 15 DSM-5 (APA, 2013) criteria must be present in the previous 12 months, with at least one of the three present in the previ- ous 6 months. In addition, the child’s behaviors must cause clinically significant impairment to functioning.

Comorbidity between CD and other mental health dis- orders has long been a topic of interest to researchers. In a review of the empirical research on disruptive behavior disor- ders, Loeber et al. (2000) asserted that CD is diagnosed earlier in boys who have attention-deficit/hyperactivity disorder and

Journal of Counseling & Development ■ January 2017 ■ Volume 9536

Erford, Bardhoshi, Ross, Gunther & Duncan

is commonly preceded by a diagnosis of oppositional defi- ant disorder (ODD). CD also co-occurs with anxiety, mood, learning, and substance use disorders (APA, 2013; Berkout et al., 2011; Loeber et al., 2000). Psychosocial factors (e.g., socioeconomic status, parenting, experience with trauma), biological factors (e.g., genetics, prenatal environment, neu- roanatomy, gender), and personal factors (e.g., temperament, intelligence, cognitive functioning) are important risk and treatment factors (Burke et al., 2002). Gender, in particular, has been the cause of much empirical attention in the 21st century, given that males have consistently been diagnosed with disruptive disorders more often than females, especially with regard to early-onset CD (APA, 2013; Berkout et al., 2011; Kessler et al., 2005; Loeber et al., 2000). In addition, CD often manifests differently in females than in males, with females having a more discernible tendency toward internal- izing behaviors, relational aggression, and verbal aggression compared with males.

CD has historically been rather impervious to treatment compared with other childhood disorders (Burke et al., 2002). In light of its prevalence, risk factors, and negative outcomes, it is imperative to understand the strengths and weaknesses of various treatment approaches to develop more effective options. It should be noted that most treatment approaches address symptomatology, because underlying mechanisms of CD are not yet clear (Blair, Leibenluft, & Pine, 2014). Burke et al. (2002) found that preventive approaches targeting specific risk factors were somewhat successful with young children identified as at risk. Along these lines, Farmer, Comp- ton, Burns, and Robertson (2002) reported that participants in parent-training trials in several studies saw better outcomes than control group participants who did not receive parent training. They also noted a dearth in available literature on the efficacy of these programs for parents with children older than 9 years. Outpatient, clinic-based treatments included in their review varied in theory and included psychoanalytic, cognitive behavior, and psychoeducational approaches. All of these interventions reported success, specifically when treat- ment addressed realistic day-to-day situations. Community- based interventions over the past 2 decades have had a mix of positive and negative results, leading to increased caution in the field regarding group work, particularly with delinquent adolescents (Burke et al., 2002; Farmer et al., 2002). Both Burke et al. and Farmer et al. found the most empirical sup- port for multimodal approaches. These approaches, which are based in ecological theory, aim to mediate multiple domains of a child’s life, including school, neighborhood, family, and peer group. The most well-documented and cost-effective of the multimodal approaches was multisystemic therapy, in which therapists intervene with the child one-on-one, in group counseling, and in family therapy to target child-specific risk factors. Given the prevalence of CD in society and the mixed results from clinical trials regarding the short-term

and long-term effectiveness of counseling in the treatment of CD, the purpose of this meta-analysis was to answer two primary questions: (a) Is counseling effective in reducing CD symptoms in school-age youth? and (b) If so, do the effects of counseling last after treatment for CD is terminated?

Method Figure 1 provides a summary of the article selection proce- dures. Counseling in this meta-analysis was defined as any treatment or intervention, provided by a mental health profes- sional or professional-in-training, aimed at the alleviation of conduct symptoms or disorders. We did not include studies of intervention for ODD or another behavior-based disorder un- less those studies also provided treatment for a diagnosed CD.

Inclusion and Exclusion Criteria

The following nine criteria were applied to all clinical trial studies selected for inclusion: (a) Interventions were focused on the reduction of CD symptoms in participants identified with CD; (b) articles were available in English, with no country-of-origin restriction; (c) the study included at least six participants; (d) participants were between the ages of 6 and 18 years; (e) mean difference or mean gain effect-size

Potentially relevant articles (published between 1990 and 2014) identified through computerized searches (j = 685)

FIGURE 1

Flowchart of Included Studies

Note. j = number of articles; k = number of studies/comparisons.

Potentially relevant additional articles identified through search of article reference lists and hand search of prominent journals (j = 48)

Articles excluded after full text review for failure to meet all inclusion criteria (j = 712)

Total number of relevant articles identified and screened for inclusion (j = 733)

Articles finally included in the meta-analysis with usable information (j = 21; k = 28 posttest comparisons [n = 1,733]; k = 15 follow-up comparisons [n = 643]), including: • Wait-list control groups (j = 4; k = 7 posttest comparisons

[n = 570]; k = 0 follow-up comparisons [n = 0]) • Placebo study groups (j = 1; k = 1 posttest comparisons

[n = 91]; k = 1 follow-up comparisons [n = 87]) • Treatment-as-usual comparison groups (j = 10; k = 10

posttest comparisons [n = 771]; k = 1 follow-up comparisons [n = 55])

• Single-study groups (j = 6; k = 10 posttest comparisons [n = 301]; k = 13 follow-up comparisons [n = 501])

Journal of Counseling & Development ■ January 2017 ■ Volume 95 37

Meta-Analysis of Counseling Outcomes for Youth With Conduct Disorders

estimates could be computed from the available data; (f) a standardized instrument was used to measure CD symptoms; (g) individual, group, or family counseling was implemented (drug trials were eliminated); (h) articles appeared in print be- tween 1990 and 2014; and (i) clinical trials used an experimental or quasi-experimental research design, including a single-group or comparison group condition (e.g., wait-list [inactive], pla- cebo [active], or treatment-as-usual [TAU; active] comparison). Sample independence was maintained throughout all analyses. We used publication as a proxy for quality and therefore elimi- nated dissertations, theses, and unpublished manuscripts. We conducted subsequent analyses for publication bias.

Search Strategies

Electronic, reference list, and hand searches of the most relevant journals were used to obtain candidate studies. We searched PsycINFO, Academic Search Premier, and MED- LINE articles from 1990 to 2014 using keywords related to condition (i.e., CD) and intervention (i.e., counseling and psychotherapy). Search parameter restrictions used to identify candidate studies included children and adolescents, English language, peer review, and clinical trials. We then searched reference lists of synthesis articles and selected clinical trials on childhood conduct problems to locate additional candidate studies. Finally, we conducted hand searches of the tables of contents of journals most frequently publishing clinical tri- als on CD (i.e., two or more) from the previous two search procedures (i.e., Journal of the American Academy of Child and Adolescent Psychiatry, Journal of Consulting and Clini- cal Psychology, and Journal of Abnormal Child Psychology).

The title, abstract, and full text of each article were re- viewed, and selection criteria were applied. The third and fourth authors independently determined whether each article met all selection criteria, and the full text of each selected article was submitted for coding and analysis.

Coding Procedures

Selected studies were coded for various participant, design, and method characteristics using a coding manual to allow for subse- quent investigation of moderator or mediator variables in the event that effect-size homogeneity was absent. Participant characteristics included sample size, race/ethnicity, age, gender, completion rate, and nationality. Design characteristics included treatment type, control group type, treatment setting, method of diagnosis, method of recruitment, and use of randomization. Method characteristics included blind assessment, supervision, treatment manual, indi- vidual or group method, number of sessions, duration of sessions, length of study, completion rates, homework, use of therapists specializing in the area of treatment, and characteristics of the counselor/therapist (i.e., degree, discipline, and training level).

These 25 participant, design, and method characteristics were coded and effect sizes computed for each of the 21 included articles. Two judges, each a graduate student who

had previously completed course work in research, statistics, and assessment, and who had completed a training process with practice in coding under supervision of the first author, coded each study independently. The first author mediated coding disagreements between the judges by examining the full text of the article in question and reaching a consensus with the judges. Because of the peer review, randomization, and stringent criteria for study inclusion, a formal evaluation process of study quality was not conducted.

Outcome Measures

The majority of outcome measures used in the 21 included studies were standardized self-report or parent-report mea- sures. Only measures directly assessing conduct problems were included as outcome measures. The most recent version of measures used in more than one study were some form of the Achenbach System of Empirically Based Assessment (e.g., Child Behavior Checklist, Teacher Rating Form, Youth Self-Report; Achenbach & Rescorla, 2001; j = 8, or 38.1% of the 21 included studies), the Revised Problem Behavior Checklist (Quay & Peterson, 1987; j = 5, or 23.8%), the Self- Report Delinquency Checklist (Elliott, Ageton, Huzinga, Knowles, & Canter, 1983; j = 3, or 14.3%), the Eyberg Child Behavior Inventory/Sutter–Eyberg School Behavior Inventory (Eyberg & Pincus, 1999; j = 3, or 14.3%), the Conners–3 Rating Scales (Conners, 2008; j = 2, or 9.5%), and the Parent Daily Report (Chamberlain & Reid, 1987; j = 2, or 9.5%).

Statistical Methods

Only comparable study designs (i.e., all wait-list, all placebo, all TAU, or all single-group designs, independently) with similar effect sizes (e.g., only mean difference effect sizes) were combined (Erford, Savin-Murphy, & Butler, 2010). If studies used multiple outcome measures, we averaged these effect sizes so that a single independent effect size was for- warded for analysis. With regard to follow-up studies, if a study produced several follow-up effect sizes (e.g., 1 year, 2 years), the longest follow-up effect size was forwarded for analysis to give the most conservative follow-up estimate.

Standardized mean difference effect sizes for wait-list, TAU, and placebo group samples were computed using Co- hen’s d. Standardized mean gain effect sizes for single-group samples were calculated using a formula provided by Lipsey and Wilson (2001), with a conservative default value of .70 used in the absence of study-specific reliability values. A positive d indicated that the treatment was effective.

Sample size bias corrections (d′) were made using d′ = d[1 – 3(4N – 9)]. We applied an additional inverse weighting (Erford et al., 2010; Lipsey & Wilson, 2001) to d′ to produce the corrected effect size (d+) prior to combining and averaging study effect sizes for hypothesis testing and homogeneity analyses using the random-effects model. A random-effects model was applied because it assumes that the selected studies were a subset of a

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Erford, Bardhoshi, Ross, Gunther & Duncan

larger set of studies in existence in the extant literature rather than an all-inclusive finite set. As a result, the random-effects model provides greater external generalizability than a fixed-effects model (Hedges & Olkin, 1985).

In a meta-analysis, two primary hypotheses must be tested for each comparison: (a) Is the mean effect size greater than zero? and (b) Is the distribution of effect sizes homogeneous? To answer the first question, we computed 95% confidence intervals (CIs) for the mean effect sizes (d+; Erford et al., 2010; Lipsey & Wilson, 2001) as a simple assessment to de- termine whether an average effect size was greater than zero. For example, if d+ = 0.15, 95% CI [0.05, 0.25], then the null hypothesis of d+ = 0 can be rejected; the complete range for d+ is greater than zero. However, if d+ = 0.15, 95% CI [–0.05, 0.35], then the null hypothesis is retained because a portion of the 95% CI range is less than or equal to zero.

To answer the second question, we assessed the homogene- ity of the effect-size distributions using Cochran’s Q and an applicable chi-square distribution. If ρ is less than .05, then heterogeneity exists across studies, and the null hypothesis of homogeneity should be rejected. Heterogeneity means that po- tential mediator or moderator variables should be examined using applicable analysis of variance or regression analogs (Hedges & Olkin, 1985; Lipsey & Wilson, 2001). As an additional check on heterogeneity, an inconsistency index (I 2; Higgins, Thompson, Deeks, & Altman, 2003) was computed and interpreted as fol- lows: 0% = no inconsistency, 25% = low inconsistency, 50% = moderate inconsistency, 75% = high inconsistency, and 100% = total inconsistency (total heterogeneity). If I 2 is greater than 50%, significant heterogeneity probably exists and exploration of mediator and moderator variables ensues.

Publication Bias

Multiple methods for assessing publication bias should be under- taken (Beretvas, 2010) in meta-analytic studies, and we subjected each design result to Duval and Tweedie’s (2000; Richardson, Abraham, & Bond, 2012) trim-and-fill procedure, funnel plot analysis, and Rosenthal’s (1979) fail-safe N. Even though the number of studies in each analysis was small, no distributions fell outside of the usual pattern, so publication bias was probably insignificant across the analyses.

Results Computerized and hand searches identified 733 potential can- didate articles, of which 712 were eliminated in subsequent selection reviews of full text because they violated at least one inclusion criterion (see Figure 1). The agreement rate between the two judges was 97% (κ = .94).

Study Characteristics

Of the 21 articles advanced to the coding process (see Figure 1), four (k = 7, where k is the number of studies/comparisons) used

wait-list comparisons, one (k = 1) used a placebo comparison, 10 (k = 10) used a TAU comparison, and six (k = 10) used a single-sample pretest–posttest design. Summary characteristics of these 21 studies (N = 1,733) are provided in Table 1.

Is Counseling Effective With Youth With CD?

We evaluated the treatment effectiveness at termination of CD counseling using wait-list (j = 4, k = 7), placebo (j = 1, k = 1), and TAU (j = 10, k = 10) comparison group studies, and single-group studies (j = 6, k = 10), where j is the number of articles and k is the number of studies/comparisons (some articles presented more than one study or comparison). Mod- ern meta-analytic standards often eliminate studies without control conditions (Higgins & Green, 2011), but because so few randomized controlled clinical trials were located in the literature (i.e., 15) we retained the six single-group articles yielding 10 viable studies as supplemental analyses. When interpreting d, Lipsey and Wilson (2001) suggested that 0 means no effect, less than .30 is a small effect, .50 is a medium effect, and greater than .67 is a large effect. Furthermore, because d is actually a specialized z score, it can be directly transformed into a percentile rank and used to reveal how much improvement the average participant in the treatment condition made compared with the average participant in the comparison group (Erford et al., 2010).

Wait-list comparison groups. Seven comparisons (n = 570) across four studies (Kumar, 2009; McNeil, Eyberg, Eisenstadt, Newcomb, & Funderburk, 1991; Sanders, Markie-Dadds, Tully, & Bor, 2000; van Manen, Prins, & Emmelkamp, 2004) yielded an average corrected effect size (d+) of 0.53, 95% CI [0.35, 0.71]. Because the entire 95% CI range is greater than zero, the null hypothesis of d+ = 0 can be rejected, and it can be concluded that counseling was effective at termination. A d+ of 0.53 is a medium effect and means that the average participant at termination scored at the 70th percentile of the control group’s score distribu- tion. In a seven-study analysis, a d+ of 0.53 has a fail-safe N of 364, meaning that 364 wait-list studies would need to be located with an effect size of zero to mitigate the d+ of 0.53 down to 0.01. The funnel plot showed no outliers, and the trim-and-fill procedure resulted in ρ greater than .05. These three analyses indicated a very low probability of publication bias. Results indicated that the test for homogene- ity of these seven comparisons was statistically nonsignificant, Cochran’s Q(6) = 5.30, ρ > .05, meaning that the null hypothesis for homogeneity was retained and the set of seven effect sizes was homogeneous and consistent. To corroborate this result, we computed I2, which, at 0%, also indicated homogeneity (i.e., I2 < 50%). Because the distribution of effect sizes was homogeneous, there was no need to conduct moderator or mediator analyses.

Placebo comparison groups. The single mean difference comparison for the single article (Rohde, Clarke, Mace,

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Meta-Analysis of Counseling Outcomes for Youth With Conduct Disorders

Jorgensen, & Seeley, 2004) reporting a placebo comparison (n = 91) yielded a d+ equal to 0.30, 95% CI [–0.11, 0.71], which was not significantly greater than zero. The average participant in the treatment condition performed at the 62nd percentile of the placebo comparison group’s score distribution, indicating no treatment effect. Analysis resulted in a fail-safe N of only 29 studies. Because there was only one effect size, no funnel plot or trim-and-fill procedure was conducted, and homogeneity was evident by default.

TAU comparison groups. Ten comparisons from the 10 ar- ticles (Apsche, Bass, Zeiter, & Houston, 2008; Bank, Marlowe, Reid, Patterson, & Weinrott, 1991; Borduin et al., 1995; Cham- berlain & Reid, 1998; Henggeler, Melton, Brondino, Scherer, & Hanley, 1997; Henggeler, Melton, & Smith, 1992; Kendall, Reber, McLeer, Epps, & Ronan, 1990; Scherer, Brondino, Henggeler, Melton, & Hanley, 1994; Vitaro & Tremblay, 1994; Weisz et al., 2012) reporting TAU designs (n = 771) combined for a d+ equal to 0.55, 95% CI [0.40, 0.70], a result that was

Note. unk = unknown; TAU = treatment as usual; CBT = cognitive behavior therapy; REBT = rational-emotive behavior therapy; ODD = op- positional defiant disorder. aMean age in years.

TABLE 1

Characteristics of Individual Studies Used in the Conduct Disorder (CD) Meta-Analysis

Apsche et al. (2008)

Bank et al. (1991) Borduin et al.

(1995) Chamberlain &

Reid (1998) Dadds & McHugh

(1992) Henggeler et al.

(1992)

Henggeler et al. (1997)

Kazdin et al. (1992)

Kendall et al. (1990)

Kumar (2009)

McNeil et al. (1991)

Rohde et al. (2004)

Sanders et al. (2000)

Scherer et al. (1994)

Schneider (1991)

Stadler et al. (2008)

van Manen et al. (2004)

Vitaro & Tremblay (1994)

Webster-Stratton (1994)

Weisz et al. (2012)

Whitmore et al. (2000)

Study Agean % MaleSummary unk

14.0 14.8

14.9

4.5

15.2

10.3

10.7

unk

4.7

unk

15.1

10.5

10.4

11.2

6.1

5.0

10.6

15.5

55 126

140

200

104

174

unk

100 68

100

unk

100

Family mode deactivation therapy

Parent-training interventions Multisystemic treatment

Multidimensional foster care

Child management and ally support training

Multisystemic therapy

Cognitive problem-solving skills and parent manage- ment training

CBT

REBT

Parent–child interaction therapy

CBT with comorbid CD and depression

Comparing enhanced, standard, and self-directed behavioral family interventions

Multisystemic family preservation therapy

Social skills training and desensitization strategies

CBT

Social skills training and social- cognitive group treatment

Prevention of aggression program

Videotape and live parent training

Modular and standard condi- tion

Outpatient treatment

Conduct Outcome Measure% White Control

Group Type Child Behavior Checklist–Externalizing

Total offenses Revised Problem Behavior Checklist

Elliott Behavior Checklist; runaway; days in lockup

Revised Problem Behavior Checklist

Revised Problem Behavior Checklist; Self-Report Delinquency Checklist; Missouri Peer Relationship Inventory

Revised Problem Behavior Checklist; Self-Report Delinquency Checklist

Child Behavior Checklist; Teacher Rating Form; Parent Daily Report; Interview for Antisocial Behavior; Self- Report Delinquency Checklist

Child Behavior Checklist–Externalizing; Conners Teacher Questionnaire

Youth Self-Report Conduct Problems subscale

Revised Conners Teacher Rating Scale; Sutter–Eyberg School Behavior Inventory

Child Behavior Checklist–Externalizing

Eyberg Child Behavior Inventory; Par- ent Daily Report; Parent Problem Checklist

Revised Problem Behavior Checklist

Observed aggression

Child Behavior Checklist; number of CD/ ODD symptoms

Child Behavior Checklist

Social Behavior Questionnaire

Child Behavior Checklist; Eyberg Child Behavior Inventory

Brief Problem Checklist; Top Problems Assessment

CD symptoms

0 70

unk

100

unk

TAU

TAU TAU

TAU

single

TAU

single

TAU

wait list

placebo

wait list

TAU

single

wait list

TAU

single

TAU

single

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significantly greater than zero. Analysis resulted in a fail-safe N of 540 studies, a funnel plot analysis with no outliers, and a trim-and-fill procedure with no appreciable effect. Thus, the average participant in the treatment condition performed at the 71st percentile of the TAU comparison group’s score dis- tribution, indicating a small-to-large treatment effect. Again, the distribution of effect sizes was very homogeneous, Q(9) = 7.43, ρ > .05, with an I 2 of 0%.

Single-group studies. Across six articles, 10 single-group comparison studies (n = 301) were reported (Dadds & McHugh, 1992; Kazdin, Siegel, & Bass, 1992; Schneider, 1991; Stadler et al., 2008; Webster-Stratton, 1994; Whit- more, Mikulich, Ehlers, & Crowley, 2000), yielding a d+ of 0.57, 95% CI [0.47, 0.67]. This d+ is greater than zero and has a fail-safe N of 280 studies, with funnel plot and trim-and-fill results that are within normal limits. Thus, these results are quite robust. The homogeneity analysis indicated substantial homogeneity, Q(4) = 10.41, ρ > .05, which was corroborated by an I 2 of 14%. A d+ of 0.57 is a medium effect, indicating the average treatment group participant at termination displayed fewer conduct problems than did 72% of the pretest participants.

In summary, all except the placebo condition (k = 1) yielded weighted effect sizes (d+) significantly greater than zero at termination, meaning that the treatments for CD were effective and that the average treatment participant was be- tween the 62nd and 72nd percentile of the comparison group’s score distribution at termination. Furthermore, Cochran’s Q and I 2 for each analysis indicated significant homogeneity, and therefore no effects of moderating or mediating variables. Table 2 provides a summary of these effect-size statistics.

Do the Effects of Counseling Last for Youth With CD?

To determine the effectiveness of counseling after termina- tion, we used the follow-up point furthest from termination to yield the most conservative estimate. No wait-list follow-up studies were located.

Placebo comparison group studies. One sample from one placebo study (Rohde et al., 2004) provided follow-up data (n = 87), resulting in a d+ of –0.53, 95% CI [–0.96, –0.10], which is not greater than zero. Indeed, the d+ was negative, meaning that the average treatment group member performed at the 30th percentile and was worse off than the average pla- cebo condition participant. A single trial means that no funnel plot, trim-and-fill, or homogeneity analysis was necessary. These results should be interpreted with caution because of the single study involved.

TAU comparison group studies. The effects of counsel- ing in the treatment of CD in school-age children at longest follow-up for the single study (Vitaro & Tremblay, 1994) providing TAU follow-up data (n = 55) resulted in a d+ of 0.08, 95% CI [–0.45, 0.61]. Because this result was not greater than zero, the null hypothesis was retained. The fail-safe N was only seven studies. Funnel plot, trim-and-fill, and homogene- ity procedures were not needed because of the single-study analysis. A d+ of 0.08 indicates no effect of treatment and means that the average participant in the treatment condition displayed fewer conduct problems than did approximately 53% of the TAU group participants at follow-up.

Single-group studies. Several TAU and wait-list studies provided single-group follow-up studies because the TAU control conditions received the treatments immediately after termination of the study. Thus, k = 13 samples provided follow-up data (n = 501), yielding a d+ of 0.58, 95% CI [0.50, 0.66], which was greater than zero. The fail-safe N was 741 studies, and the funnel plot analysis and trim-and-fill procedure yielded nonsignificant results. A d+ of 0.58 is a medium effect, indicating that the average participant in the treatment condition at follow-up displayed fewer conduct problems than did approximately 72% of the pretest partici- pants. This distribution of 13 effect sizes was homogeneous, Q(12) = 15.58, ρ > .05, with an I 2 of 23%. Therefore, no analysis for moderator or mediator variables was conducted. Some evidence exists (see Table 3) that treatment gains were maintained beyond 2 years after termination, given that we

TABLE 2

Summary of Posttest and Follow-Up Results

Condition

Termination (posttest) results Wait list Placebo Treatment as usual Single group

Longest interval follow-up results Wait list Placebo Treatment as usual Single group

570 91 771 301

87 55 501

Note: j = number of articles; k = number of studies/comparisons. ad+ > 0 (p < .05).

.53a .30 .55a .57a

–.53 .08 .58a

[0.35, 0.71] [–0.11, 0.71] [0.40, 0.70] [0.47, 0.67]

[–0.96, –0.10] [–0.45, 0.61] [0.50, 0.66]

ρ > .05

ρ > .05 ρ > .05

ρ > .05

70 62 71 72

30 53 72

Q95% CId+n Percentile

7 1 10 10

0 1 1 13

4 1 10 6

0 1 1 6

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Meta-Analysis of Counseling Outcomes for Youth With Conduct Disorders

observed the following progression for the studies reporting follow-up effects: posttest d+ = 0.58 (k = 13), 1- to 6-month follow-up d+ = 0.81 (k = 2), 7- to 12-month follow-up d+ = 1.18 (k = 2), and 2-year follow-up d+ = 0.53 (k = 9). Again, these results should be interpreted with caution because of the small number of studies involved and the fact that different studies composed the different follow-up intervals.

In summary, only the single-group conditions resulted in an average weighted effect size (d+) that was significantly greater than zero at follow-up intervals, whereas the d+ values of the placebo and TAU comparisons were not significantly greater than zero. Because we were unable to locate any wait-list follow-up studies and given the low power resulting from a small sample analysis, results regarding the long-term treatment effectiveness of counseling on CD should be interpreted with caution. However, single-group treatment gains appeared to have been maintained up to 2 years after termination, with the average participant in the single-group treatment condition at follow-up standing at the 72nd percentile of the pretest group’s score distribution. All tests of homogeneity (Cochran’s Q and I2) suggested significant homogeneity, and therefore no effects of moderating or mediating variables. Table 3 provides a sum- mary of the follow-up effect-size statistics.

Discussion Given the poor prognosis and potential for long-term and per- sistent psychopathology in youth with CD (Blair et al., 2014), it is imperative that evidence-based practices be available for practitioners working with this population. The studies contained in this meta-analysis used a variety of treatment modalities, including parent training, multisystemic therapy, individual approaches, and group therapy, with effectiveness at termination being evaluated using wait-list, placebo, and TAU comparisons, and single-group studies. A random- effects model synthesizing effect sizes from 21 clinical trials published between 1990 and 2014 produced mostly medium effect-size statistics, with the average participant displaying fewer conduct symptoms than 62% to 72% of control group participants at termination. The results of study comparisons at termination lend evidence that counseling is effective in treating CD in youth.

Very few controlled, follow-up studies with this population have been undertaken to date; thus, it is unclear whether the results of counseling can be viewed as long lasting in treating CD. We located a single placebo, single TAU, and 13 single- group comparisons to evaluate the treatment effectiveness furthest from termination, aiming for a conservative estimate. An analysis of 13 single-group follow-up comparisons rang- ing from 6 months to beyond 2 years produced evidence of a medium effect of treatment, with gains potentially being maintained beyond 2 years. Indeed, the average participant in the treatment group displayed less symptomatology at the longest interval follow-up than did approximately 72% of par- ticipants at pretest. However, this conclusion should be viewed as tentative because of the low number of follow-up studies.

Selected studies also included a wide range of therapeutic approaches (e.g., cognitive behavior therapy, multisystemic therapy) and modalities (i.e., individual, group, or family methods). Because the purpose of this meta-analysis was to determine the effectiveness and potential staying power of counseling in reducing CD symptomatology in school-age youth, questions regarding the advantage of one approach or modality over another may arise. However, our analysis indicated homogeneity of the effect-size distributions, thereby rejecting the existence of potential mediator or moderator variables that could affect treatment effectiveness in this population. Therefore, no moderating effects were noted for any of the 25 coded study characteristics, including client, counselor, and treatment modality factors. The treatment effectiveness of counseling remained consistent across mul- tiple study comparisons with diverse participant, design, and method characteristics, a notably robust result.

The overall conclusions of this study regarding treatment effectiveness at termination and the potential for lasting ef- fects at follow-up can be applied across relevant populations and treatment variations. Reported mean ages of clients across studies ranged from 4.5 to 15.5 years, and client age along with gender and race/ethnicity did not appear to influence the effectiveness of counseling. The most frequently used treatment interventions with school-age youth among the 21 studies included in this meta-analysis appeared to be multi- systemic therapy and cognitive behavior therapy, which is reflective of the larger literature, with parent training, family therapy, and social skills training following suit. Similarly, the length of treatment, the use of a treatment manual, or the use of a therapist specializing in the area of treatment did not result in significant differences in effect sizes, further strengthening the generalizability of these results to a wide range of practices and clinicians.

Limitations of This Meta-Analysis

Stringent methodological practices were used in conducting this meta-analysis. They included (a) nine inclusion criteria, (b) comprehensive literature search strategies, (c) use of

TABLE 3

Follow-Up Studies Continuum

Condition

Wait list Placebo Treatment as usual Single group

Note. M d+

= mean effect-size estimate. ak = 1. bk = 2. ck = 9.

None None None 0.81b

None –0.53a None 1.18b

None None 0.08a 0.53c

7–12 Months M

<6 Months M

24+ Months M

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Erford, Bardhoshi, Ross, Gunther & Duncan

standardized instruments to measure conduct symptoms, (d) random-effects modeling, (e) sample size bias correc- tion, (f) multiple methods for assessing publication bias and homogeneity, and (g) inverse variance weighting procedures. Although the rigorous criteria for inclusion enhanced the quality of this meta-analysis, it is possible that some viable research studies with signif icant results were excluded. Indeed, the small number of articles that met the inclusion criteria is possibly the most significant limitation of this study. However, despite a limited number of studies, using a conservative methodology led to estimates that are more reflective of real-life outcomes in counseling, which will better inform clinicians than results obtained from including less rigorous studies.

Because this meta-analysis included only 21 candidate published articles and very few randomized controlled clinical trials were located, we decided to include six single-group articles as a supplemental analysis, which yielded 10 follow- up comparisons. The inclusion of studies without control conditions is a potential limitation of this meta-analysis. Unfortunately, only two randomized controlled follow-up trials were located, so the noncontrolled, single-group, follow- up studies are the best evidence of the long-term effects of counseling at this time. In addition, many of the follow-up study comparisons evaluating the long-lasting effects of treatment were from TAU and wait-list trials that resulted in single-group follow-up studies, given that control group par- ticipants received the treatment immediately after termination. Although this practice is ethically and clinically justifiable, it did limit the number of available comparisons at follow-up intervals. Finally, we could locate only one study using pla- cebo comparisons for posttreatment or follow-up, one study using a TAU comparison for follow-up, and no studies using wait-list comparisons for follow-up, thus leading to limita- tions in terms of stability and sufficient power of the respective analyses. In short, a primary limitation of this meta-analysis is the small number of clinical trials studying the immediate and long-term effectiveness of counseling youth with CD.

Implications for Counseling Practice

The present study provides evidence that counseling produces a medium effect in treating school-age youth diagnosed with CD. Indeed, counseling appears to be quite effective whether the approach is individual or group, and irrespective of treat- ment setting or the specific therapeutic approach applied. This finding provides counselors with opportunities to make treatment decisions based on client needs, available resources, and cost considerations, without having to sacrifice the quality or effectiveness of the intervention with school-age youth.

More information is needed on how counseling profes- sionals can best extend effectiveness after treatment ends to improve longer term results (APA, 2013). It is possible that continuing treatment by extending session intervals or

implementing posttreatment booster sessions could help maintain treatment effects over the long term (Erford et al., 2011, 2013). More clinical trials examining the effec- tiveness of counseling in various follow-up phases will help clarify the progression of treatment effects and the potential optimal stages of intervention to maintain significant gains. Using booster sessions with children and adolescents who have already received treatment for CD at optimal postintervention intervals and based on evaluated treatment schedules could further improve the practice of counseling with this population.

The school-age years are an extremely important time period in a child’s development (Broderick & Blewitt, 2014). Although focusing on the effectiveness and staying power of counseling in treating CD in children is important, an emphasis should also be placed on the prevention and early intervention of mental health disorders (APA, 2013; Burke et al., 2002; Farmer et al., 2002). Given the dismal prognosis for early-onset CD and the increased risk of diagnosis of APD in adulthood (APA, 2013), clinicians who understand and screen for risk factors and periodically assess function- ing at school and home may better mobilize resources and available interventions.

Implications for Counseling Research

Intensive early intervention is key, and published studies with comprehensive assessment practices are needed to identify and evaluate the effectiveness of CD treatment in youth. The majority of outcome measures used in the included studies were either self-report or parent-report measures. Inclusion of family members, caregivers, and school personnel is vital in implementing a multisystemic approach, and future research evaluating treatment effectiveness should be grounded in a multi-informant approach. Although 10 of the 21 identified studies used more than one outcome measure to evaluate treatment in youth diagnosed with CD, only one study used a combination of self-report, parent, teacher, and counselor evaluation to determine treatment outcome. Future research should consistently use assessment best practices by triangu- lating reports from parents, teachers, and clients along with clinical judgment.

More studies are needed that adequately examine the lasting effects of counseling by using follow-up comparisons at multiple intervals. Because of the serious long-lasting problems that youth with CD may experience even as adults, studies of the effects of interventions beyond termination are needed. Designing and conducting outcome studies that adequately quantify interventions and examine treatment effects beyond 2 years will not only allow for rigorous evalu- ation of services, but also provide much-needed information regarding the prognosis of this hard-to-treat disorder and opportunities for replicating and enhancing effectiveness. It is imperative that counseling professionals working with this population identify evidence-based treatments that reduce CD

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Meta-Analysis of Counseling Outcomes for Youth With Conduct Disorders

symptomatology in children and adolescents and continue exploring opportunities for innovation and improved, long- lasting outcomes.

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The Case of Bill

Sixteen-year-old Bill was brought to the office by his mother because of several incidents at school. The last incident was so severe that Bill is required to have a mental health evaluation and letter before he is able to return to school. Bill was suspended indefinitely for bringing a weapon to school. Bill has also been suspended in the past for marijuana possession, fighting with peers, assaulting a teacher, and misconduct in a bathroom. Mom reports that Bill leaves the apartment for days at a time, does not listen to anything she says or asks him to do, and has stolen money from her purse. She is “at her wits end,” and does not know what to do with him.

Bill says that everything that he does is blown out of proportion. He leaves the house for days at a time after what he calls a “blow out” fight with his mother. Bill’s father is incarcerated and he has no recollection of any significant relationship with him. Bill complains that his mother regularly works at night and on the weekends and leaves him in charge of his two younger siblings.

Disorders With Typical Childhood Onset

Introduction

You may have an idea of the population you most want to work with as a counselor. Perhaps you’re fascinated by adolescents, with their mix of cognitive complexity and emotional volatility. Perhaps you’d rather change professions all together than work with middle schoolers. Some of us are motivated to work with the elderly, a population which is rapidly growing across cultures and in need of experienced counselors to help navigate the changes and challenges of aging; others want to work with children.

In reality, none of us really knows where we will end up, or what population will be our specialized focus. This text is intended to prepare you for working with a wide range of clients, of varying ages, developmental stages, cultures, and presenting problems. In this chapter, we focus on several of the most common disorders occurring in childhood. But, before we begin, ask yourself what might be different when working with this specific population.

Mental health issues commonly diagnosed in childhood or adolescence are divided into two main categories: childhood onset disorders and learning disorders. These disorders are usually first diagnosed in infancy, childhood, or adolescence, and are described in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (APA, 2013) in several different sections. Here we focus on the disorders that counselors will see and treat most often. This is by no means a suggestion about which issues are more severe; as in other sections of this book, we focused our attention on the presenting problems most likely encountered in counseling settings. These include autism spectrum disorder and attention deficit/hyperactivity disorder, which are found in the Neurodevelopmental Disorders chapter, as well as Oppositional Defiant Disorder and Conduct Disorder, which are found in the Disruptive, Impulse-Control, and Conduct Disorders chapter of the DSM-5.

Autism Spectrum Disorder (ASD)

Autism Spectrum Disorder, generally referred to as Autism, encompasses a group of complex and varying neurodevelopmental disorders which can severely impact a child’s ability to understand and interact with others and their environment. The use of the term “spectrum” speaks to the wide range of severity and symptoms included under this umbrella term. Prior to the DSM-5, autistic disorder, childhood disintegrative disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS), and Asperger’s Syndrome were all distinct diagnostic categories with specified criteria.

The revisions in the DSM-5 reflect current research that identifies social/communication deficits and repetitive/restrictive behaviors as the core features of ASD. Researchers believe that the new diagnostic criteria will result in fewer children being misdiagnosed with autism (Ozonoff, 2012). The DSM-5 also added a new diagnosis of Social (pragmatic) Communication Disorder (SCD). Some clients who do not qualify for an ASD diagnosis may qualify for SCD, which is defined as an impairment of pragmatics. Individuals with SCD have difficulty with the appropriate social use of verbal and nonverbal communication in real-life contexts. For example, there may be impaired ability to change communication styles to match a changed context, difficulty making inferences, or following the rules of conversation. Social relationships and ability to understand social conversation are adversely impacted. A diagnosis of ASD must be ruled out before the diagnosis of SCD is applied.

The new category of ASD in DSM-5 is intended to include DSM-IV diagnoses of Autism, Asperger’s Syndrome, and Pervasive Developmental Disorder-Not Otherwise Specified. Although Asperger’s syndrome is no longer in the DSM as a diagnosis, some may continue to use the term to refer to those on the mild end of autism spectrum disorder. There is some concern among practitioners that discontinuing the separate diagnosis of Asperger’s Syndrome will impact the ability of those individuals at the high functioning end of the spectrum to have access to appropriate services. Other changes in the DSM-5 include the removal of language delay as a criterion for ASD.

In addition, there is a more inclusive age-of-onset criterion so that while symptoms must be present since early childhood, it is recognized that they may not fully manifest until later in life when social demands exceed the capacity of the individual to cope (Lai, Lombardo, Chakabarti, & Baron-Cohen, 2013). Rather than requiring a diagnosis in early childhood, DSM-5 facilitates adult diagnosis by acknowledging that some symptoms may not become apparent until adolescence or adulthood, when social demands increase. There must be symptoms in the early developmental period, but these may not be evident until later when situational demands overtax coping skills. Developmental history, delays, and regression are also taken into account by the DSM-5 criteria.

ASD is characterized by deficits in communication skills and reciprocal communication, repetitive patterns of behavior, and neurological and developmental delays. Although every diagnosis of ASD presents somewhat differently, children suffering from this disorder typically show little interest in making or retaining friendships or initiating social interaction, and can become engrossed with a single object or idea to the exclusion of whatever is going on around them. ASD can also be associated with intellectual disabilities, motor coordination issues, and other health issues (i.e., sleep and gastrointestinal disturbances). On the other hand, some with ASD can excel in such areas as visual skills, music, math, or art.

The number of cases of ASD has increased drastically over the past few decades, with the most current studies reporting that approximately one child in every 88 could potentially fit the diagnosis (Volkmar, Paul, Rogers, & Pelphrey, 2014). More conservative estimates are that prevalence is approaching 1% of the population, both children and adults (American Psychiatric Association, 2013), which makes ASD one of the most common developmental disabilities. It is unclear if the recent rise in reported cases is due to increased awareness, lower thresholds for diagnosis, or a true increase in prevalence. The disorder usually appears quite early, between 12 and 24 months of age (APA, 2013). Depending on the severity, ASD can be a devastating diagnosis for a child and family.

DSM-5 groups the diagnostic criteria for ASD in two general categories: persistent deficits in communication and interaction across multiple contexts, and restrictive and repetitive patterns of behavior.

Deficits in social communication and interaction must not be accounted for by general developmental delays, and are manifested by problems with social-emotional reciprocity; for example, difficulty having a normal back and forth conversation, or in developing or maintaining friendships. This may look like a reduced sharing of interests or emotions, or a failure to initiate social interaction at all. The individual also must have deficits in nonverbal communication, such as abnormal eye contact, facial expressions, or body language. There is also a distinctly abnormal approach to social interaction and difficulty developing and maintaining relationships. The child may display little or no affect, have difficulty engaging in pretend play, or display little interest in interpersonal communication. Unfortunately, these shortfalls result in difficulty making friends, understanding verbal and nonverbal cues, and adjusting behaviors to fit various social situations.

The second diagnostic criteria centers on restrictive, repetitive patterns, interests, behaviors, or activities. Typical behaviors might include repetitive speech, use of objects, or motor movements. Examples include such things as lining up toys by size or repeating a teacher’s instructions numerous times. The child may be highly restrictive, rigid, and inflexible, and very resistant to change. Children may insist on having the same thing for lunch every day, or having a specific bathroom or bedtime ritual. Some children may be interested in studying only one subject, or one topic. In addition, individuals with ASD may be either hypersensitive or hyposensitive to sensory input. For example, children may seem indifferent to pain, or have a severe reaction to loud noises or vibrant colors. Alternatively, children may show an unusually strong interest in sensory aspects of their environment that can result in excessive smelling or touching of certain objects or a fascination with objects that are lit or spin.

In the DSM-5, severity and specifiers are also important concepts to keep in mind when considering an ASD diagnosis. The severity scale is designed to be more descriptive of the impact that ASD has on everyday functioning, and refers to the level of care or support the individual is likely to need. Practitioners are hopeful that the severity scale will help substantiate the need for workplace accommodations and a more supportive workplace environment for individuals diagnosed with ASD.

There are three severity levels: requiring support, requiring substantial support, and requiring very substantial support. An example of level one severity may be a child who is able to communicate in complete sentences, but has trouble engaging in peer communication and back and forth conversation, and has trouble engaging socially with peers. The child may also have rituals and repetitive behaviors that are difficult to interrupt.

Level two is typified by marked deficits in both verbal and nonverbal social communication skills. The child may speak only in simple sentences, have limited and stunted social interaction, and exhibit marked repetitive behaviors that are noticeable to casual observers and interfere with functioning.

Level three is marked by severe communication deficits in verbal and nonverbal communication. The child rarely initiates interaction with peers, and needs substantial help with day-to-day activities. There is marked distress if there is any interference with repetitive behaviors and rituals. Specifiers include: with or without accompanying intellectual impairment; with or without accompanying language impairment; and associated with a known medical or genetic condition or environmental factor.

Social Communication Disorder, in contrast, involves impairment of pragmatics and low communication abilities and social participation, but not the restricted, repetitive patterns of behavior and interests that would result in an ASD diagnosis.

Comorbidity

ASD frequently co-occurs with intellectual impairment and language difficulties. A majority of those with ASD will also have another mental health diagnosis (van Steensel, Bögels, & de Bruin, 2013; Volkmar, Paul, Rogers, & Pelphrey, 2014). Specific learning disabilities, eating and sleeping issues, and developmental coordination disorder are common co-occurring disorders (APA, 2013).

There are some overlapping symptoms with ADHD, such as hyperactivity, inattention, and distractibility. A diagnosis of ADHD would be made if those symptoms are above and beyond what you would expect to see with ASD and for that developmental stage. An individual can be diagnosed with both, but only if he or she meets the criteria for both disorders.

Cultural Considerations and Population Factors

Although there may be differences in communication styles and early childhood developmental expectations from culture to culture, those with ASD would be considered out of the norm in any context. The DSM-5 takes into account varying norms for social interaction, and requires that the individual’s behavior and communication patterns be out of the norm for that social cultural group. Recognition and diagnosis may be delayed for specific populations, especially those of lower socioeconomic status and those with limited access to adequate health care. This is an important consideration, since early intervention is thought to be a key to treatment.

ASD is four to five times more likely in boys than girls. Again, there is no specific causal link for this discrepancy, although some experts believe that this is due in part to underdiagnosis in females (Volkmar, Paul, Rogers, Pelphrey, 2014). DSM-5 uses identical diagnostic criteria for ASD for males and females, but some researchers believe that gender-specific criteria would be more accurate, and might shed light on potential underdiagnosis of females. Some researchers speculate that the higher incidence in males may be related to fetal testosterone levels and sex differences in brain structure (Baron-Cohen et al., 2011)

An alternative explanation that has been proposed for the male bias is that females, especially those with milder symptoms, may be misdiagnosed with other conditions that also involve the exercise of excessive attempts to control the environment or others, such as Borderline Personality Disorder or Anorexia. Females could also be underdiagnosed if they are more motivated to learn to conform socially (Baron-Cohen et al., 2011).

Etiology and Risk Factors

Although ASD has no identified cause, there are many theories regarding what risk factors are associated with the diagnosis, including low birth rate or premature birth, advanced age of parents, and fetal exposure to carcinogens. Although once popular in mainstream media, the belief that the use of vaccines has a link to ASD has been disproven by many research and meta-analysis studies (Volkmar, Paul, Rogers, & Pelphrey, 2014). Given the wide variance in symptoms and severity, there is most likely a complex etiology that includes genetics, brain development, and environmental factors. Studies are focusing on issues, such as viral infections, complications during pregnancy, and pollutants to see if any of these are contributing factors.

Some children may have a genetic vulnerability that environmental variables can compound. There appear to be several different genes associated with ASD, which may influence brain chemistry and development, throwing off the brain’s delicate balance and ability to develop normally. These genes may be inherited or disrupted by trauma or other factors. Many studies have found autistic syndromes, symptoms, or traits in the close relatives of children diagnosed with ASD, including individuals whose personality traits are similar to autistic symptoms (Pickles et al., 2000). A recent study reported that for the 85% of cases of ASD where specific multigenic influences could not be identified, it was found that in approximately one quarter of families affected by autism, multiple family members had either clinical or subclinical autistic traits (Constantino, Zhang, Frazier, Abbachhi, & Law, 2010; Virkud, Todd, Abbacchi, Zhang, & Constantino, 2009).

Treatment Interventions

Research shows that early intervention is key. This usually involves several educational, compensatory (helping the child use areas of strength to address areas of need), and behavioral interventions (Handleman & Harris, 2000; National Research Council, 2001). These services typically include help with communication, gross and fine motor skills, and social interaction. Children diagnosed with or at high risk for developing ASD may be eligible for services through the Individuals with Disabilities Education Act (IDEA), so it is important to coordinate intervention efforts with other professionals and to help the family look for resources within their community.

Treatment most often focuses on symptom reduction and supporting developmental and communication skills (Sicile-Kira, 2014). Educational interventions concentrate on improving academic and cognitive skills and are intended to be administered in school-based settings. Allied health interventions include therapies typically provided by speech and language, occupational, and physical therapists, and may include auditory and sensory integration, music therapy, and language therapies.

Behavioral interventions focus on minimizing behaviors that interfere with daily functions, such as self-injury or repetitive movements. Counselors are more likely to be involved in teaching children how to act in social situations, developing social skills, and helping the family develop structured environments and coping strategies. Most of these interventions use principles of applied behavioral analysis (ABA), but may vary in specific methods or environmental setting. One example of a studied ABA intervention is Pivotal Response Treatment (PRT). PRT is a play-based intervention that concentrates on “pivotal” areas of childhood development, including self-management, emotional regulation, motivation, and behavioral cues in social interaction. PRT highlights naturally occurring reinforcement and motivational strategies. The belief is that by targeting these important developmental hurdles, the effects of PRT would generalize to other environmental settings (Koegel & Koegel, 2005, 2012). PRT strategies are a core component of an early intervention approach called the Early Start Denver Model, which we discuss below.

The UCLA/Lovaas and the Early Start Denver Model (ESDM) are specific manualized sets of interventions that have gained some popularity and have research supporting their effectiveness (Rogers & Dawson, 2009a,b,c; Rogers, Dawson, & Vismara, 2012). Specific interventions emphasize social skills and include such interventions as social stories, imitation, joint attention training, peer training, and play therapy.

Interventions tend to be intense, comprehensive, and involve many different helping professionals. Some may be delivered in specialized programs or centers, while others are home, agency, or school-based.

Attention Deficit/Hyperactivity Disorder (ADHD)

Most children will have times when they fidget, have trouble paying attention, or just can’t seem to sit still and focus on a task. For children suffering from ADHD, these behaviors can seem constant and out of control. Inattentiveness and hyperactivity interfere with their day-to-day functioning and can have a severe impact on the child’s ability to function and thrive in a school environment.

As part of the diagnostic criteria, ADHD begins in childhood. The disorder is most often diagnosed during the early years of schooling, but in some cases is not diagnosed until adolescence or adulthood even though, in retrospect, symptoms began much earlier. It is important to note that research shows that between 30 and 70% of children with ADHD continue to have symptoms of the disorder when they become adults (Kessler et al., 2006). Counselors may have adult clients who have been struggling with ADHD for much of their lives, and may not have received any treatment until adulthood; often the lifelong struggle has a negative effect on self-esteem as individuals may be repeatedly told that they are “stupid” or “lazy.”

ADHD is usually diagnosed before the age of 12 and surveys suggest it affects roughly 5% of children (APA, 2013). Many parents or caregivers first observe the hyperactivity, although it may be hard to distinguish this from normative behaviors of children at a young age. The DSM-5 diagnostic criteria are split into two main areas: the first criterion is marked by persistent patterns of inattentiveness, and the second focuses on hyperactivity and impulsivity.

Inattentiveness and distractibility can manifest in many ways. The child may often make careless mistakes, or may have difficulty readily organizing or accomplishing even simple tasks. Children may have trouble following directions and may not seem to be listening, even when they are spoken to directly. They are often forgetful, lack the ability to follow through on things, such as daily chores and homework, and lose or misplace things easily. All of these issues can combine to make the child reluctant to engage in school fully, especially when asked to perform complicated or time-consuming tasks (which become more prevalent as the child moves up in grades).

The other set of criteria focuses on impulsive behaviors and hyperactivity. Children may often fidget or seem unable to control their bodily movement, sometimes finding things to drum on or making other repetitive movements that may be loud and distracting to other students in the classroom. They tend to interrupt the teacher or other students, and have great difficulty waiting for their turn. They may leave their seat or place in line for no apparent reason, or climb or run in situations where that behavior is not appropriate. Many children with ADHD talk inappropriately in class, again because they are unable to control their impulsivity. Teachers or parents may describe them as “always on the go,” “high energy,” or “out of control.”

The Case of Gabby

Gabby is an 8-year-old third grader who is struggling at school. Although she seemed to do fine in school until now, third grade is turning out to be a struggle for her. She misplaces her homework or forgets to complete it at home. She frequently fails to complete her tasks fully or read all of her reading assignments. Gabby’s teacher has noticed her inability to focus, difficulty with working in a group, and lack of attention to details. Although she can sometimes work on her own and in small time frames, Gabby gets easily distracted when working with peers; she tends to ramble when she talks and often will go off on tangents when asked a question.

Gabby’s teacher reached out to her parents to express her concern over Gabby’s behaviors and lack of attention. Her parents first noticed there was an issue in first grade. She seemed disorganized and wasn’t able to tell them her homework assignments. They felt as if they had to repeat instructions to her and many times she did not seem to be listening. She never seemed to finish reading any of her books, always moving on to something else before she even got halfway through. Gabby has two older brothers and one younger sister. One of the older brothers has a diagnosis of ADHD.

Gabby says that she likes school and tries very hard, but just can’t seem to follow directions or “get it.” She likes more active classes, such as gym, art, and music, but struggles with math and English. She has several close friends and loves to talk and play games. She loves dance and is on a traveling soccer team.

Comorbidity

Roughly 60% of children diagnosed with ADHD fit the criteria for another mental health disorder (Pliszka, 2011). The most common comorbid diagnoses are mood disorders, such as anxiety and depression, conduct disorder, and language and communication disorders. It is important to note that differential diagnosis is key with ADHD, as its symptoms can present as similar to certain anxiety and mood disorders, such as Generalized Anxiety Disorder (GAD) or Bipolar disorder. Prior to the DSM-5, the diagnosis of ADHD was not made for individuals diagnosed with a disorder on the autistic spectrum. DSM-5 now allows for both disorders to be diagnosed if criteria for both are met.

Cultural Considerations and Population Factors

A greater percentage of children from higher socioeconomic levels appear to receive a diagnosis of ADHD. Research found that parents of minority children were less likely to seek treatment and felt that there were substantial issues that prevented their children from being properly diagnosed or receiving effective treatment (Livingston, 1999; Taylor & Leitman, 2003). These barriers included fear of labeling, lack of knowledge regarding mental health issues, fear of misdiagnosis, and language issues (Hervey-Jumper, Douyo, Falcone, & Franco, 2008).

There are also many theories as to why there is a significant discrepancy in diagnosis levels with regard to gender. Girls with ADHD frequently do not exhibit the observable behavior problems that boys do, such as violent outbursts or aggressive behaviors. Instead, girls often exhibit symptoms associated with inattentiveness, and busy teachers may easily miss these more subtle cues (Hinshaw, 2002).

Etiology and Risk Factors

As with all of the disorders in this chapter, the specific causes of ADHD are not fully known. However, it is clear that there is a strong genetic component and that ADHD appears to be highly heritable; studies show that parents with ADHD have a greater than 50% chance of having a child with the same diagnosis (APA, 2013). Studies also show that children and adults with ADHD tend to have abnormal levels of certain neurotransmitters like dopamine as well as irregular nerve pathways that regulate behavior (APA, 2013). Neurotransmitter levels have been linked to issues, such as attention, learning, movement, sleep, and mood. In many cases, however, there is no hereditary linkage.

There also appear to be common environmental factors that contribute to the likelihood of an ADHD diagnosis. These include smoking, taking drugs, or drinking during pregnancy, premature birth or low birth weight, and birth or early brain injury related medical issues. Additionally, there is some evidence that environmental toxins, such as lead or PCBs, may also be linked to higher risk of developing ADHD.

Treatment Interventions

Counseling interventions employed for ADHD typically include behavioral, cognitive behavioral, family-based, and relaxation techniques (National Institute of Health, 2008). Most research suggests that medications like stimulants are most effective in treating the primary symptoms of ADHD. Although behavioral techniques when used alone seem to have limited impact on symptomology, they can decrease disruptive behaviors and improve social skills and parent-child relationships (Brown et al., 2005). Those interventions that include multiple approaches, such as medication, family, school-based, and behavioral techniques appear to have a greater impact than any one intervention alone (Brown et al., 2005). It is important to note that CBT interventions are more often used with adult populations, and appear to be less effective with younger populations (Roman, 2010).

Behavioral Therapy

Behaviorally based treatments focus on training parents, teachers, or other caregivers to implement contingency management programs and reinforcement schedules. Parents generally attend parent training programs where they are given assigned readings and instruction in standard behavioral techniques. Some research shows behavioral interventions to be effective in the treatment of ADHD (Fabiano et al., 2009; Daley et al., 2014). Interventions typically include creating everyday routines, organizational interventions, and behavioral reinforcement. Environmental interventions can include limiting choices, reducing distractions, chunking of assignments, and changing parent and teacher interactional strategies. Typical behavioral interventions revolve around goals and reinforcements, as well as discipline when necessary.

Counselors and school counselors often work with teachers in a consultation model to teach behavioral strategies for application in the classroom. The use of a daily report card system where the child receives tokens or points for certain target behaviors in the classroom is a popular example of a behavioral program for children with ADHD.

Cognitive-Behavioral Interventions

CBT interventions focus on emotional regulation, self-talk and self-instruction, self-monitoring, and problem-solving strategies. As with CBT interventions discussed in previous chapters, the goal of these interventions revolves around teaching self-control, decatastrophizing, and self-reinforcement. Counselors typically try to accomplish these goals through modeling, role playing, and practicing cognitive strategies (cognitive restructuring, thought stopping and thought replacement, scaling, and contingency management) (Szigethy, Weisz, & Findling, 2012). For example, a child may be taught to stop a thought of “I am out of control and everyone is looking at me” and replace it with a more effective emotion-regulating thought like “I can get back on track and I only missed a little of what the teacher said.”

The premise is that individuals with ADHD tend to lack internal cues that keep then on task or the ability to take in cues from the environment. It is important to note that cognitive behavioral interventions were prevalent in the 1980s and 1990s for ADHD, but the use of CBT with younger populations has waned in the absence of strong research to support its efficacy.

Medication

For those individuals with ADHD, stimulant medications such as Adderall or Ritalin are the best known and most widely used treatments (Greenhill & Ford, 2002). Typically, these stimulant medications are paired with behavioral or cognitive behavioral interventions. Contrary to popular belief, it is important to note that not all children with this diagnosis are given a prescription for stimulants; however, between 70% to 80% of children with ADHD respond positively to these medications, which may help with concentration. But, there is mixed evidence of significant long-term effects on school achievement or behavioral management (Prasad et al., 2013).

Oppositional Defiant Disorder (ODD)

Every child can have a bad day, a day where they totally lose control or throw a tantrum in a supermarket because their mom would not buy them their favorite sugary cereal. For some, however, an irritable mood and frequent outbursts are more the rule than the exception. Oppositional defiant disorder (ODD) is characterized by irritability and negativity in almost every setting and evidenced by frequent outbursts and verbal tirades. Often, these outbursts are directed at those individuals in authority, such as teachers, caregivers, and parents. At other times, behaviors may be purposeful attempts to annoy peers. Children with ODD are easily offended and described by peers as jealous, vengeful, blaming, unstable, and difficult to be around (Essau, 2014).

It is clear from the above list of symptoms that these children can cause significant distress to family, friends, and school systems. Consequently, children with ODD have difficulty making friends or functioning successfully in a school system, resulting in significant distress for the child as well.

ODD is a comparatively common childhood disorder with prevalence estimated in the National Comorbidity Survey Replication at between 6% to 10% (APA, 2013; Nock, Kazdin, Hiripi, & Kessler, 2007). ODD is diagnosed more often in boys than in girls, and diagnosed more often in younger children, perhaps to avoid mislabeling what is thought to be normative teenage behavior (Essau, 2014).

To fit the DSM-5 diagnosis for ODD, the child must regularly exhibit four of the following behaviors: arguing with adults, losing temper, actively defying or refusing to comply with rules or requests from authority figures, intentionally behaving in a way that annoys another person, being angry or resentful, being easily annoyed by others, being vengeful or spiteful, and blaming others for their own misbehavior or mistakes. Negativity and defiance are often expressed through obstinacy, resistance to direction, and unwillingness to share or compromise. Examples of defiance may also include constant testing of limits and boundaries, arguing, ignoring, and failing to accept blame or consequences.

The aggression may manifest itself in verbal or physical hostility, though this is usually without the more severe aggression and physicality seen in Conduct Disorder, which is described in the next section. These behaviors need to last at least six months to fit the diagnosis and symptoms must cause significant impairment in social, academic, and occupational functioning. Keep in mind that in almost all cases, the child does not see themselves as out of control or in the wrong, but views their behaviors as appropriate in response to the unreasonable demands that the authority figures put on them.

The Case of Drew

Drew, a 7-year-old first grader, has been sent to the school counselor and principal on numerous occasions. The most recent incident involved an incident of elopement. Drew walked away from the playground and refused to come in after recess was over. After the incident, while in the school counselor’s office, Drew refused to talk or even acknowledge that the counselor was present. Drew’s teachers have expressed high levels of frustration and feel as though the interventions they have tried so far have had little impact. Drew refuses to be placed in “time-out,” and when disciplined makes comments like “I don’t care if I can’t eat lunch with my friends, I don’t like them anyway.” His teachers believe that his outbursts and disruptive behaviors are negatively impacting the other children’s ability to learn.

Drew argues almost constantly with peers, and is obsessed with catching other students who are not following the rules. He talks almost nonstop while in school, and in less structured environments, such as the bus or recess, his talking increases. He repeatedly ignores the rules his teachers set and the directions they give in class. He does not accept responsibility for anything, and often accuses other students of doing the same thing that earned him a reprimand from the teacher.

Drew’s parents were divorced when he was four, and he now lives with his mother and two older brothers. Drew’s mom describes him as “out of control” with “no respect for me or his father.” When she tries to punish or reprimand him at home, Drew says he does not care about losing TV or computer privileges. His mother says that he is always going into his older brothers’ rooms and taking things from them without asking. He hardly ever comes when called and sometimes “runs away” for hours at a time to other houses in the neighbourhood or to the neighborhood playground. He also tries to play one parent against the other with comments like “Dad lets me stay up till nine when I’m at his house, that’s why I like him more.”

When Drew finally opens up to his school counselor, he quickly becomes loud and overemotional. He says that no one understands him and he does not care about school or getting good grades. He describes his older brothers as bullies and his mother as overbearing and domineering. He says that none of the trouble he gets into at school is his fault, and no one likes him. When asked if there is anything he would like to do differently or change, he replies “Why should I change, it’s not my fault!”

Comorbidity

Studies suggest that roughly 15 to 20% of those diagnosed with ODD also fit the criteria for ADHD. Anxiety (14%) and depressive disorders (9%) are also highly correlated with ODD (Angold, Costello, & Erkanli, 1999). Most children with Conduct Disorder (CD) begin with ODD-like behaviors. Studies indicate that the majority of children with ODD do not develop CD, but ODD is usually present as a forerunner to childhood-onset CD (APA, 2013).

Cultural Considerations and Population Factors

Although present at all economic levels, ODD appears to be overrepresented in lower socioeconomic groups (Loeber, Burke, Lahey, Winters, & Zera, 2000). This may be due to limited access to medical and psychiatric services in younger years, as well as an increased exposure to the risk factors examined below.

In addition, research suggests that children from minority populations who have anxiety or depressive disorders may be misdiagnosed with ODD or CD instead, in part because of stereotypes and biased attributions for behavior. For example, children with affective and anxiety disorders may also exhibit irritability and may refuse to take part in situations perceived as dangerous; as a result, this may be misinterpreted as oppositional behavior (Lau et al., 2004).

Etiology and Risk Factors

Like most of the disorders discussed in this chapter, research has not found any specific environmental trigger or underlying cause of ODD. Most experts believe that there are many contributing environmental and biological risk factors, including the child’s temperament, developmental delays in cognition or communication, lack of or inconsistent parental support and supervision, previous abuse or neglect, and possible brain chemical imbalances. Environmental stressors affecting a child’s sense of consistency and security may also play a role in increasing disruptive behaviors. Examples include parental divorce, financial issues, frequent moves or school changes, and child care changes.

ODD may be best understood in the context of a biopsychosocial model, which considers biological risk factors and harmful aspects of the child’s environment. Some experts believe that children with ODD seem to lack the cognitive or emotional skills required for executive functions (i.e., problem solving, working memory, task completion) to comply with the requests from authority figures. These deficits undercut the child’s capacity to regulate emotion; thus, the child loses his or her temper as well as the ability to cope or problem solve (McKinney & Renk, 2007).

Treatment Interventions

Counseling treatment usually involves behavioral, cognitive behavioral, or family approaches. Individual counseling interventions usually focus on emotional regulation, healthy expression of feelings, and cognitive restructuring, which helps the child to look at events more realistically.

Behavioral-based intervention emphasizes extinguishing inappropriate behaviors and learning more appropriate and adaptive behaviors. Caregivers and parents are taught reinforcement techniques, and when appropriate, punishment techniques. The hope is that appropriate behaviors eventually become habitual and naturally reinforced by the child’s everyday environment.

Family-based interventions focus on parent training, communication, family roles, and behavioral interventions. Parents are taught to implement behavioral contracts, as well as methods for extinguishing unwanted behaviors and reinforcing positive ones. Counselors stress to caregivers the need to be consistent in the use of secondary gain (appropriate rewards) and the importance of the child eventually getting primary gains (naturally occurring rewards from the environment). Again, the hope is that these new appropriate behaviors become more habitual as they get reinforced. For example, if a child is able to stay on task longer in class they may answer a teacher’s question correctly. The teacher then gives verbal praise which increases the likelihood of that appropriate behavior continuing.

One specific family intervention, parent-child interaction therapy (PCIT) focuses on parent-child interaction patterns and on improving the parent-child relationship. PCIT is divided into two stages: parent-child relationship development and discipline training. The goals of the first stage are to develop a loving and nurturing parent-child bond through interactive play. The goals of the second stage mainly focus on skill development and behavioral reinforcement. Sessions consist of the therapist coaching parents in behavioral techniques, usually with the help of a one-way mirror and a headset audio device (Bodiford McNeil, Hembree-Kigin, & Anhalt, 2011).

Although medications are not normally used in the treatment of ODD, children with co-occurring disorders, such as ADHD or Generalized Anxiety Disorder (GAD), may be taking some form of medication.

Conduct Disorder (CD)

Any counseling professional will tell you that it is not uncommon for adolescents to test boundaries, break rules, and get in trouble. However, there are some children and adolescents who show consistent patterns of violating others’ rights and displaying behaviors that fly in the face of established social norms and the law. Conduct disorder is exemplified by prolonged periods of antisocial behaviors, the breaking of established rules and social norms, and violations of the law. Most often, professionals view conduct disorder as similar, but much more serious than ODD and a possible precursor to antisocial personality disorder (Murphy, Cowan, & Sederer, 2001).

Because of the behaviors associated with this diagnosis, individuals with CD are frequently viewed by peers, adults, and agencies as delinquent, “bad,” or “the criminal type.” Symptoms vary depending on the severity of the disorder and the age of the child, but fall into four distinct behavioral clusters: destructive, deceitful, aggressive, and violating established rules. Examples of destructive behaviors include arson and vandalism. Aggressive behaviors include bullying, cruelty to animals, physical altercations, and forcing sexual activity. Deceitful behaviors involve lying, cheating, shoplifting, and other criminal activity. Rule breaking examples include skipping school, running away, or engaging in activities not suitable for that age group.

Children with CD have more difficulty in terms of academic struggles, interpersonal relationships, and drug and alcohol use. The legal system is more often involved as well, putting youth at risk for a downward spiral if intervention does not happen (Boesky, 2002).

The lifetime prevalence of CD is estimated to be around 10%. Similar to ODD, more males than females receive the diagnosis (12.0% among males and 7.1% among females). Based on specific research, it is interesting to note, however, that there is a great deal of variance in the presence of specific behavioral criteria from 33% reporting repeatedly staying out at night without parental permission to 0.3% reporting that they forced some kind of sexual activity (Nock, Kazdin, Hiripi, & Kessler, 2006).

The Case of Ryan

Ryan is a 15-year-old sophomore in high school who has had many “run-ins with the law.” The most recent incident involved stealing his mother’s credit cards and going on a shopping spree with his friends. His mother called the police and Ryan spent six months in a juvenile detention center and currently has a parole officer. His presenting problems in counseling include issues with probationary restrictions, violent outbursts, alcohol and other drug use/abuse, and feelings of overall anxiety and depression.

As a child, Ryan moved from town to town and school to school. Ryan has four siblings and two stepsiblings. His parents divorced when he was six, and he lives with his mother and three of his siblings. Ryan states that his father is an “angry drunk” and used to hit him when he was younger. His mother was also an alcoholic and drug addict, but seems to be abstaining at this point. Ryan’s mom has also been diagnosed with Bipolar Disorder and is taking medication. He was very close to his paternal grandfather, who was killed in a car accident when Ryan was twelve.

Ryan has been suspended from school several times and removed from his most recent school for bullying, marijuana possession, and several fights with fellow classmates. His school record indicates that he has a history of skipping school, failing classes, and having altercations with teachers. He has been arrested on several occasions, once for arson, and twice for disorderly conduct.

Ryan’s mom reports that he continually lies about where he is going or what he is doing. After this most recent incident, she no longer wants Ryan living with her and his other siblings. She says that Ryan “has always gotten into things he shouldn’t have way earlier then he should have.” He started smoking and drinking at a very early age. Mom remembers the first time he got in trouble with the law was when he was ten and stole candy and playing cards from the local grocery store.

Comorbidity

Those diagnosed with CD are at a significantly higher risk of meeting the criteria for at least one other disorder, especially substance abuse and impulse control disorders (APA, 2013). Some research suggests that the correlation with ADHD may be as high as 50% (Nock, Kazdin, Hiripi, & Kessler, 2006). Approximately 30 to 40% of those persons diagnosed with CD will have a co-occurring mood disorder. Most will have academic issues and co-occurring learning disabilities. Because at least 60% will have an additional mental health or learning disability, it is important to have a multidisciplinary approach to treatment, including incorporating medical, educational, community, and mental health services (Essau, 2014).

Cultural Considerations and Population Factors

CD is more commonly diagnosed in neighborhoods characterized by social disorganization and high crime rates (Loeber et. al., 2000). The symptoms of the disorder revolve around breaking rules, violating others’ rights, and violating social norms. This leaves open the question of who decides which norms and rules are appropriate, how to judge when these norms and rules have been broken, as well as the impact that the environment and poverty play.

As with ODD, children from minority cultures who have anxiety or depressive disorders may be misdiagnosed with CD if their behavior is misattributed to oppositional reasons (Lau et al., 2004).

Etiology and Risk Factors

Conduct disorder involves an interaction of genetic/biological, environmental, and social influences; there is no single cause of CD. Research suggests genetic and biological influences, since behavioral disorders tend to cluster in families. Some research found that individuals with CD may inherit a lower baseline autonomic nervous system, and may need greater levels of stimulation to feel normal or “alive.” This genetic predisposition may account for the higher level of sensation seeking activity associated with this disorder (Davidge et al., 2004; Lahey, Hart, Pliszka, Applegate, & McBurnett, 1993). Children with CD have a low resting heart rate (Mawson, 2009); this underarousal may result in sensation seeking and engaging in disruptive behaviors in order to get to an optimal arousal state, or it may reduce a sense of guilt or anxiety that inhibits such behaviors in other children (van Goozen, Snoek, Matthys, Rossum, & Engeland, 2004).

Environmental factors include parental mental health issues and substance abuse, chaotic family situations, and childhood abuse and neglect (APA, 2013). Another risk factor appears to be inconsistent parenting styles where the child does not learn the relationship between behaviors and consequences, or is reinforced for tantrums and noncompliance by overwhelmed or uninformed parents. Early childhood temperament patterns, such as irritability and inconsolability, are risk factors as well. Finally, social risk factors include lack of structure, community violence, lack of parental supervision, and dysfunctional family environments.

Treatment Interventions

Treatment of children with conduct disorder is complex and challenging; depending on the severity of the behaviors, treatment can be provided in a variety of different settings. Adding to the challenge of treatment are the child’s uncooperative attitude, and sometimes fear and distrust on the part of the adults. In developing a comprehensive treatment plan, a child and adolescent psychiatrist may use information from the child, family, teachers, community (including the legal system), and other medical specialties to understand the causes of the disorder.

As we’ve emphasized throughout this book, every client and every situation is different. Individualized treatment plans should be developed to address the particular problems and severity of each child and family situation.

Counseling Interventions

Behavior interventions and counseling are frequently employed to assist the child in appropriately expressing and controlling anger and aggression. Parents are often trained in behavioral management and educational programs as well as ways to cope with the chaos that this disorder can bring to the family structure. Because of the high comorbidity rates, interventions may also include medication as well as typical treatments for the co-occurring disorders. Because of the severity of the symptoms involved, the course of treatment is seldom brief and may include a multidisciplinary approach.

Eyberg, Nelson, and Boggs (2008) identified sixteen evidence-based treatments for disruptive behavior disorders that all include a focus on increasing reinforcement of more prosocial and compliant behaviors, utilizing appropriate punishment for disruptive behaviors, and training parents to be consistent and predictable in their application of reinforcement and punishment. Other factors which impacted the success of these interventions were the parents’ willingness to make changes to their own behavior, such as discontinuing substance abuse.

Family-Based Interventions

One popular approach is Parent Management Training (PMT) (Feldman & Kazdin, 1995; Kazdin, 2005). In this highly researched and evidence-based approach, parents are trained in ways to assist their children in problem solving, emotional regulation, and impulse control. PMT interventions focus on maladaptive parent-child interactions mainly involving discipline practices, and rely heavily on principles of operant conditioning. The counselor starts by providing an overview of underlying concepts and instructional sessions that involve social learning principles and behavioral techniques, modeling behaviors for parents, and coaching in implementation of specific conditioning techniques.

Multisystemic Therapy (Henggeler & Lee, 2003) is another evidence-based, integrative, family-based treatment designed to improve psychosocial functioning for children and their families.

Behavioral Family Therapy is another evidence-based approach that has been used for many years with children diagnosed with ODD and CD (Eyberg, Nelson, & Boggs, 2008). Techniques in Behavioral Family Therapy include shaping, reinforcement, behavioral contingencies, and behavioral contracts. The counseling process involves several steps, including establishing rapport, identifying problematic behaviors, developing goals, choosing rewards/punishments, and finally creating the behavioral contracts. In behavioral family therapy, the family environment, the child’s temperament, unproductive behaviors, and negative reinforcement are all addressed in an attempt to modify the family system as well.

Other Treatment Approaches

Group assertiveness training has also been used effectively in school-based groups for middle schoolers (Huey & Rank, 1984).

When CD is severe and persistent, or when the family is unable or unwilling to commit to treatment, children may need an alternative placement to keep either the child or the family safe. As always, the least restrictive setting should be used for the briefest time possible. Therapeutic foster care or respite care may also be an option.

Studies show that multifocused psychosocial interventions that are delivered early in development to at-risk children show the most effectiveness. The importance of prevention and early intervention cannot be overstated (Connor et al., 2006).

The use of medication for CD and ODD has not been well studied, and current research suggests that medication should be used only when evidence-based psychosocial treatments have not worked, and that medication should not be the sole treatment for these disorders (Connor, 2002: Connor et al., 2006). On the other hand, medication may help treat comorbid disorders so that the child can benefit from the psychosocial interventions for CD/ODD.

Case Conceptualization Considerations Using the T/C Model

The disorders described in this chapter are diverse in terms of etiology and treatment. Keep in mind that environmental stressors may play a substantial role in the development of disruptive behavior disorders, such as parental conflict, divorce, poverty, and unsafe neighborhoods. Additionally, deficits in problem solving, emotion regulation, and coping skills may play a role. Temperament is also a factor; therefore, assessing both environmental, cognitive, and behavioral influences is critical.

Of course, whenever you work with children and adolescents, the role of the family is significant. A thorough assessment of family norms, values, discipline styles, and interaction patterns is a necessary component of the case conceptualization process.

Now that we examined the research and diagnostic categories for the various childhood onset disorders, let’s turn to another case example and case conceptualization.

The Case of Phillip

Example of T/C Case Conceptualization Model Outline

(*designates issues to further explore)

Presenting Problem: difficulty following directions, inattention, distraction, academic problems

Internal Personality Constructs and Behavior:

Self-Efficacy: low

Self-Esteem: low*

Attitudes/Values/Beliefs: low valuing of education

Attachment Style: Parents are involved and concerned*

Biology/Physiology/Heredity: male, 12 years old, siblings also have attention problems, father has ADHD as well, currently prescribed stimulant medication

Affect: distracted, irritable, possible depression

Cognition: Belief that he should be left alone

Hot Thoughts: “Just leave me alone.”

Behavior: loses things, disorganized, “spacy,” wanders around aimlessly, unable to sit still, isolated

Symptomology: irritable, distractible, social isolation

Coping Skills and Strengths: few coping skills, supportive parents

Readiness for Change: precontemplation

Life Roles: student, sibling, son

The Case of Phillip

Phillip is a 12-year-old boy who was recently diagnosed by his family physician with ADHD and prescribed medication. His mother and father came to you for help with Phillip’s behaviors at home and school. Phillip’s father discloses that he also has a diagnosis of ADHD, and reveals that he sees many of his traits in Phillip. Phillip is very messy and unorganized both at school and at home. Phillip’s mom describes him as a “wild child” who does not follow directions. Phillip also has two younger siblings, and his mom describes them all as unable to listen or sit still for more than a few minutes. Mom describes the home environment as “chaotic, where one child just feeds off the other two. We can’t sit down to a family meal or watch a movie or have quiet time to read.” Dad describes Phillip as “spacy” and “in his own little world.”

Phillip’s teachers report that he often appears unaware of what is taking place around him. He consistently daydreams, and doesn’t respond to peers or to the teachers. When the teacher asks what he is thinking about, he responds “I don’t know.” Phillip especially has trouble with self-motivation and written tasks. Phillip is extremely unorganized and spends a great deal of time looking for lost homework, pencils, or his lunch. He makes careless mistakes and seems not to be listening when given instructions. When asked to complete any activity that lasts longer than five minutes, he becomes distracted, often distracting others in the process.

Phillip frequently misplaces things, such as his coat or his lunchbox, and has trouble following even simple directions on where to go or what to do. He does not seem to have any close friends, and usually wanders around aimlessly or daydreams during recess or lunch breaks. He has trouble completing assignments on time or according to the directions, and often forgets to bring the right books to school. Phillip is resentful of the extra attention he gets and would like the teachers and aides to just leave him alone.

Phillip prefers to sit in the back of the classroom, and if allowed, would spend as much time as he could doodling in his notebook or staring out the window. While in the counselor’s office, Phillip spends most of the initial session swiveling and rolling around in the office chair. The counselor habitually has to repeat questions several times, and mom and dad have to continually prompt Phillip to stay on task.

Environment:

Relationships: conflicted relationship with parents, few friends

Culture:*

Family Norms and Values: family values organization and quiet

Societal Influences: school and societal value on organization, quiet

Timeline:

Past Influences: past school experience*

Present Influences: depressed mood, difficulty concentrating, conflicted relationship with parents, siblings*

Future Goals: increased concentration in school and at home, academic success, closer friendships, higher self-efficacy, improved relationships with family

Counseling Keystones

Autism spectrum disorder (ASD), generally referred to as autism, encompasses a group of complex and varying neurodevelopmental disorders that can severely impact a child’s ability to understand and interact with others and their environment.

ASD is characterized by deficits in communications skills and reciprocal communication, repetitive patterns of behavior, and neurological and developmental delays.

The number of cases of ASD has increased drastically over the past few decades, with the most current studies reporting that approximately one child in every 88 could potentially fit the diagnosis.

Although there may be differences in communication styles and early childhood developmental expectations from culture to culture, those with ASD would be considered out of the norm in any context.

Given the wide variance in symptoms and severity of ASD, there is most likely a complex picture of etiology that includes genetics, brain development, and environmental factors.

Research on ASD has shown that early intervention is key and usually involves several educational, compensatory (helping the child use areas of strength to address areas of need), and behavioral interventions.

Attention deficit/hyperactivity disorder (ADHD) is usually diagnosed before the age of 12 and affects roughly 5% of children.

Diagnostic criteria for ADHD are split into two main areas; the first set of criteria are marked by persistent patterns of inattentiveness, and the second focuses on hyperactivity and impulsivity.

Roughly 60% of children diagnosed with ADHD fit the criteria for another mental health disorder, including mood disorders, such as anxiety and depression, conduct disorder, and language and communication disorders.

Research shows that there is a strong genetic component and that ADHD appears to be highly heritable.

Counseling interventions employed for ADHD typically include behavioral, cognitive behavioral, family-based, and relaxation techniques.

Oppositional defiant disorder (ODD) is characterized by irritability and negativity in almost every setting and evidenced by frequent outbursts and verbal tirades.

To fit the DSM-5 diagnosis for ODD, the child must have regularly exhibited four of the following behaviors: arguing with adults, losing temper, actively defying or refusing to comply with rules or request from authority figures, intentionally behaving in a way that annoys another person, being angry or resentful, being easily annoyed by others, being vengeful or spiteful, and blaming others for their own misbehavior or mistakes.

Studies suggest that roughly 15% to 20% of those diagnosed with ODD also fit the criteria for ADHD.

Most experts believe that there are many contributing environmental and biological risk factors to an ODD diagnosis, including the child’s temperament, developmental delays in cognition or communication, lack of or inconsistent parental support and supervision, previous abuse or neglect, and possible brain chemical imbalances.

Conduct disorder (CD) is exemplified by prolonged periods of anti-social behaviors, the breaking of established rules and social norms, and violations of the law.

Those diagnosed with CD are at a significantly higher risk of meeting the criteria for at least one other disorder, especially substance abuse and impulse-control disorders.

Counseling interventions employed with ODD and CD are usually behaviorally based and focus on appropriately expressing and controlling anger and aggression.

Exercises

EXERCISE 12.1 Making Certain That Language and Communication Styles Are Developmentally Appropriate

CLASS EXERCISE: Small group work followed by large group discussion.

Question 1: Would you change your counseling focus toward certain constructs (i.e. focus more on behavior) when working with children and adolescents? Why or why not?

Question 2: Are there words or phrases that you would typically use with adults that you would not use while working with younger children? Which ones? (Identify 5 to 10)

Question 3: Would you change your nonverbal communication style when working with children? Adolescents? If so, how?

EXERCISE 12.2 Working with Parents, Caregivers, and Home Environments

CLASS EXERCISE: Small group discussion followed by large group discussion.

Question 1: How does working with children change your approach to your role as counselor?

Question 2: How would you work with parents/caregivers? What could be the potential benefits? Potential drawbacks?

Question 3: How is consultation with parents different/similar to the counseling process?

EXERCISE 12.3 Counseling Interventions with Children and Adolescents

CLASS EXERCISE: Individual work followed by large group discussion.

Question 1: In your opinion, what types of interventions might work better with younger children? With adolescents?

Question 2: Using the T/C Case Conceptualization Model, what constructs might you focus on more with children, and which might you emphasize with adolescents? Environment? Cognition? Behaviors? Why or why not?

Question 3: What areas of strength can you focus on when working with children?

The Case of Bill

EXERCISE 12.4 Case Conceptualization Practice Using the T/C Model

See The Case of Bill, above.

CLASS EXERCISE: Small group discussion followed by large group discussion.

Question 1: What is your case conceptualization of this case?

Question 2: What else would you want to know?

Question 3: What would be three possible goals for Bill in counseling?

Go Further

Treatment of Autism Spectrum Disorders: Evidence-Based Intervention Strategies for Communication and Social Interactions edited by Patricia Prelock and Rebecca McCauley (2012) Brookes

Autism Spectrum Disorders: From Theory to Practice by Laura Hall (2012) Pearson

The SAGE Handbook of Emotional and Behavioral Difficulties edited by Philip Garner, James Kauffman, and Julian Elliot (2014) SAGE

Driven to Distraction: Recognizing and Coping with Attention Deficit Disorder by Edward M. Hallowell and John J. Ratey (2011) Anchor

The ADHD Workbook for Kids: Helping Children Gain Self-Confidence, Social Skills, and Self-Control by Lawrence Shapiro (2010) Instant Help

Parenting Children with ADHD: 10 Lessons That Medicine Cannot Teach (APA Lifetools) by Vincent J. Monastra (2005) American Psychological Association

Mastering Your Adult ADHD: A Cognitive-Behavioral Treatment Program Therapist Guide (Treatments That Work) by Steven Safren, Carol Perlman, Susan Sprich, and Michael Otto (2005) Oxford University Press

Oppositional Defiant Disorder and Conduct Disorder in Children by Walter Matthys and John Lochman (2011) Wiley

Conduct and Oppositional Defiant Disorders: Epidemiology, Risk Factors, and Treatment edited by Cecilia A. Essau (2014) Routledge

Emerging Approaches to the Conceptualization and Treatment of Personality Disorder

John F. Clarkin Weill Cornell Medical College

Kevin B. Meehan Long Island University

Mark F. Lenzenweger State University of New York at Binghamton

and Weill Cornell Medical College

Personality disorders are both prevalent and debilitating, but controversies abound concerning the definition, assessment and treatment of these conditions. This review examines major approaches to conceptualizing the personality disorders, as recently emerging in DSM–5, Section III, and the research domain criteria initiative of the National Institute of Mental Health. Three prominent models for understanding these disorders (neural functioning, interpersonal model, and the cognitive–affective processing system model) are considered with their relevant empirical foundations. The implications for future psychopathology and treatment research and practice are detailed.

Keywords: personality, personality disorder, assessment and treatment

Personality disorders (PD) are prevalent in the general popula- tion (10.56% median prevalence across studies; see Lenzenweger, 2008). They are highly debilitating, exerting a powerful impact on work functioning as well as interpersonal and intimate relations. However, there are many impediments to the assessment and treatment of patients with a personality disorder, not the least of which are the controversies in defining personality disorder, the range of severity across the disorders, the difficulties in identifying the key dimensions of personality dysfunction, the striking heter- ogeneity amongst patients that carry the same personality disorder diagnosis, and the paucity of treatment research on the majority of the personality disorder types.

In this overview, which is necessarily selective and nonexhaus- tive, we explore a number of empirical developments in person- ality pathology research, with a particularly focus on the potential impact of these developments on conceptualization, assessment and treatment. While there is substantial agreement about the limitations of the PD nosology articulated in the Diagnostic and Statistical Manual for Mental Disorders, now in its fifth edition (DSM–5; APA, 2013), there is less agreement about how to ad- vance our conceptualization. The alternative DSM–5 model for personality disorders, retained in Section 3 of the DSM–5, pro-

poses a radical restructuring of PD diagnosis. At the same time, the National Institute of Mental Health (NIMH) is moving away from DSM diagnoses and instead favoring dimensional evaluations of domains of psychopathology, called research domain criteria (RDoC; Insel & Gogtay, 2014). Each of these approaches will be discussed, including their advantages and limitations, as well as a number of assumptions about the nature of personality pathology that need to be evaluated. Further, a number of promising models of personality psychopathology that have received less visibility thus far will be discussed, which stand to make important contri- butions to advancing our conceptualization of PDs.

We also attempt to use this review to sketch the outlines of near future research and clinical developments in furthering our under- standing the etiology and pathogenesis of PD. A central issue for the field remains the identification of the constituent domains of dysfunction related to PD and the psychological and neural mech- anisms underlying these domains that contribute to self and inter- personal disruptions. We highlight research techniques that have refined our fine-grain understanding of the functioning of these disorders. Future empirical diagnostic and treatment efforts will focus on the interaction of organization at the brain, in the mind, and in behavior. Within this brain-mind-behavior matrix, we view PD as an emergent phenomenon, such that the resulting diagnos- able PD represents a rich interactive product of this matrix in relation, of course, with the environment. PD, as an emergent product, cannot be reduced to single explanatory dimensions (e.g., disagreeableness or neuroticism).

Historical Influences on Conception of Personality and Its Disorders

The history of the investigation of personality disorders has been conceptualized as occurring in three phases (Livesley, 2001). Dating from the 19th century, the first phase involved the work of

This article was published Online First March 23, 2015. John F. Clarkin, Department of Psychiatry, Weill Cornell Medical Col-

lege; Kevin B. Meehan, Department of Psychology, Long Island Univer- sity; and Mark F. Lenzenweger, Department of Psychology, State Univer- sity of New York at Binghamton, and Department of Psychiatry, Weill Cornell Medical College.

Correspondence concerning this article should be addressed to John F. Clarkin, Weill Cornell Medical College, NY Presbyterian Hospital— Westchester Division, 21 Bloomingdale Road, White Plains, NY 10605. E-mail: [email protected]

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pioneers in clinical psychiatry and psychopathology in formulating conceptions of character and its related pathology. In the second phase, empirical investigation of personality pathology began in the 1960s and 70s. The second phase was furthered with the introduction of the multi-axial system in the DSM–III in 1980, which provided an explicit locus for the assignment of a person- ality disorder diagnosis. This official recognition of the personality disorders with explicit diagnostic criteria necessarily fostered a focus on PD diagnosis and the development of semi-structured interviews for PD. These interviews provided a methodology for the reliable definition of PD constructs, which set the stage for investigations directed at the validity of the PDs. Such validity oriented investigations have taken many forms, ranging from ef- forts to investigate underlying neurobehavioral systems to re- sponses to highly detailed, manualized treatments.

In the third, post DSM–III (APA, 1980) phase, the problems and shortcoming of the original DSM-based PD classification systems have become clear. Most notable, the DSM personality disorder categories tend to be quite heterogeneous. For example, Clarkin (1998) and colleagues (2004) have argued that because of the polythetic nature of the criteria for borderline personality disorder (BPD), patients may have distinct symptom profiles with pertinent prognostic implications (i.e., suicidality), and yet each meets cri- teria for the disorder. There is considerable comorbidity both among the personality disorders and between Axis I and II disor- ders (Lenzenweger et al., 2007). Further, problems with differen- tial diagnosis as well as concerns about stigma may lead clinicians to diagnose Axis I but not personality disorders (Paris, 2007). The recognition of these shortcomings have resulted in a third phase in which a proliferation of attempts to develop new classification schemes for both research and clinical purposes.

Major Clinical and Research Approaches Under Consideration

In response to the aforementioned limitations of the DSM–IV classification of personality disorders, the Personality and Person- ality Disorders Workgroup (PPDWG) introduced a novel diagnos- tic system in Section III’s “Alternative DSM–5 Model for Person- ality Disorders” (APA, 2013); though ultimately not adopted, it represents an intriguing hybrid model that combines dimensional assessments of personality functioning with personality traits. In the latter aspect of the model, traits are argued to better capture both the individuality of the patient, and provide a basis to under- stand similarities among groups of patients with different person- ality disorders (i.e., traits cut across different disorders and bring a clearer understanding of important organizing underlying similar- ities). Those who favor the trait approach to description of the personality pathology cite the advantages of coverage of the com- plex domain of personality functioning, and tout the advantages of dimensional measurement over categorization, which is seen as losing too much information (Widiger, Simonsen, Sirovatka, & Regier, 2006). The dimensional approach, in the PD context, has been centered on the issue of personality traits for the most part; however, a dimensional methodological approach is generally highly valuable for tapping into meaningful individual differences in any measured construct.

Proponents of trait theory emphasize the continuity of traits between “normal” personality and “abnormal” personality disor-

der, as well as the ability of dimensional measurement to better characterize the well-known heterogeneity of personality distur- bance (Trull, 2006). In this conceptualization, personality pathol- ogy is understood as an extreme of position on a normal trait dimension (e.g., extreme neuroticism or negative affectivity (dis- agreeableness) would be evident in many PDs). Traits describe individuals in terms of their stable patterns across different envi- ronmental situations, but do not address how or why the behaviors occur. In the main, traits are largely descriptive, lacking causal force. This is not necessarily because traits cannot exert causal force, but rather they simply have not been typically studied in a manner to allow for the investigation of causal effects. Even the well-known dimensions in the popular five factor model of per- sonality assessment are fundamentally descriptive at their core (e.g., those tapped by the NEO–PI–R and related instruments; Costa & McCrae, 1992). It is well known that the five factors did not come from a model of personality or personality processes; rather they were distilled, in large part, from the natural language (English) of people used to describe themselves and others.

As shall be discussed in greater detail, it is important to emphasize that personality is the product of a complex interaction of underlying genetic, epigenetic, and trait dimensions that are contextualized by individuals’ personal histories (Depue & Lenzenweger, 2005; Lenzenweger & Depue, in press). While trait dimensions, reflecting the activity of underlying neurobehavioral systems, can be studied and understood, this interactive process has given rise to a more complex phenotype that is not merely the sum of its constituent parts. We think, along with others, that personality processes can help us to understand how and why the personality traits have their impact on social rela- tions and occupational functioning (Hampson, 2012). With the com- bination of personality traits and personality processes (Caspi et al., 2005; Cervone, 2005; Mischel & Shoda, 2008;), one can achieve a fuller picture of personality functioning.

Last, although many investigators and clinicians have seen the value in the general trait approach to PD, its utility in the clinical situation has been questioned (particularly by seasoned clinicians) for a number of reasons. First, clinicians tend to focus less on traits as the point of intervention and more on the active interchange between the patients’ personality and environment form the nexus of the treatment foci. Second, the role of the clinician in the assessment of the key traits is complicated by the absence of a clinician-based method for standardized data gathering. Addition- ally, in a hybrid model it was not clear how clinicians would reliably rate (in common practice) self-and-other functioning. At its conclusion, the hybrid model depended on a self-report inven- tory (PID–5, Krueger, 2013) for the assessment of personality traits deemed central to PD; a necessary next step for the model would be the development of a clinician-based assessment system as self-report may be inadequate for valid assessment.

Research Domain Criteria

Though not specific to personality disorders, the recently pro- posed research initiative of the NIMH might have a major role in guiding future empirical PD research efforts. The RDoCs initiative emerged, in large part, out of a concern about the rampant comor- bidity amongst disorders on the two Axes of DSM–IV. The senti- ment related to this comorbidity was that it exemplified a muddy phenomenological and classification picture that was hampered in

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its ability to guide research. The RDoCs approach seeks to en- courage investigators to abandon the DSM diagnostic system as a guide research and adopt, rather, a dimensional approach that seeks to map underlying systems thought to be reflective in normal and abnormal behavior (Sanislow, Pine, Quinn, et al., 2010). It is interesting to note that dimensional measurement and the study of basic processes underlying psychopathology constructs has long history in clinical psychology and experimental psychopathology, whereas traditional psychiatry had remained a largely categorical/ diagnosis related enterprise. This initiative will focus research on neurobiological systems such as positive affect, negative affect, cognition, regulatory processes, and social processes as well as other features. These systems are intended to be evaluated at varying levels of analysis, from underlying genetic factors to manifest behaviors. Rather than focus on specific disorders, broad domains of psychopathology (i.e., fear responsivity) will be eval- uated along dimensions of severity and across units of analysis.

The methodological perspective of RDoCs shares many charac- teristics with a neural systems approach (Depue & Lenzenweger, 2001, 2005; Lenzenweger & Depue, in press), which shall be discussed in more detail, in that it seeks to elucidate underlying substrates of psychopathology. Such an approach holds enormous promise for later guiding treatment interventions at the level of systems from which psychopathology arises, rather than treatments targeting manifest disorders. However, to date the gaps in our understanding of how these systems relate to the emergent pro- cesses upon which therapists intervene is vast, and therefore the immediate expectation of NIMH that proposed treatments should target domains and not disorders impresses as premature. Our emerging understanding of these neurobiological systems are much more coherent at the lower biological units of analysis; the less clear sketches of an organizing framework at higher behav- ioral units clearly call for more research (and yet is not where funding priorities seem to lie). It will be essential to flesh out these higher units of analysis that include behavior, cognition, motiva- tion, and relatedness, because at these levels the implications for psychosocial treatments will be most evident. To promote the development of treatments targeting systems that have only begun to be fully understood seems to place the cart before the horse.

However, over time one interesting implication of the RDoCs initiative will be the manner in which it will encourage a focus on personality systems that can be evaluated at multiple levels of analysis. It is conceivable, if properly designed, that RDoCs in- spired studies will capitalize on attention to the moment-to- moment functioning of patients at various levels of the organism (e.g., neurotransmitters, neurocognitive functioning, psychological functioning). With the introduction of the RDoC initiative, there may indeed be a shift from examining personality pathology from a cross-sectional, categorical perspective to using a dimensional domains of dysfunction perspective, tapped at different levels (e.g., neural, psychological, and behavioral) of the organism with measurement in real-time and in ecologically valid contexts.

Assumptions in Perspectives on Personality Pathology

One fascinating aspect of the struggle over the reformulation of personality disorder diagnosis in DSM–5 was that the methodolog- ical approaches at the heart of the debate were not new to clinical psychology or psychiatry by any measure. As noted above, clinical

psychological science has long embraced the dimensional method of assessment, whereby constructs are measured in a continuous fashion and variation is a matter of degree. On the other hand, the adherence to classification represented the 100 year-old tradition of psychiatry, whereby psychiatric conditions were akin to medical ailments that could be discerned clearly with pathological states being relatively crisply demarcated from nonpathological states. Though the debates are not new, at this point we now have accumu- lating data that should lead us to call into question a number of assumptions about personality pathology.

Caseness

Traditionally, in the diagnosis of personality disorders using the DSM-based approach, a diagnosis for a specific PD or PD–Not Otherwise Specified (PD–NOS) was given— one either had the diagnosis, or one did not. Having the diagnosis defined the pres- ence. Most models of personality disorder that have their roots in a model of normal personality functioning have posited that per- sonality disorders represent either extremes of commonly occur- ring “normal” personality dimensions (i.e., very low or very high values on a measured personality dimension).

The boundary between normal personality functioning and func- tioning that constitutes a personality disorder is hypothetical in nature, and defies exact definition. At the extremes (no problems in love and work vs. severe difficulties in these areas) there is a clear differentiation between personality disorder and its absence. However, there is considerable terrain in between such extremes, ranging from essential normality through subclinical deviations of little clinical significance to subclinical expressions clearly worthy of treatment. From a clinical point of view, the exact boundary between personality difficulties and personality disorder is not the only consideration related to the decision to intervene. In short, many individuals who seek therapeutic assistance in interpersonal difficulties, but who do not meet the level of dysfunction of a personality disorder may still need and, potentially, benefit from clinical assistance.

Stability Over Time

The assumption of total personality stability at least among the personality disorders is no longer seen as tenable (Lenzenweger et al., in press). Recent longitudinal studies have revealed that per- sonality disorder, as defined and identified by the DSM criteria, tends to decline categorically and dimensionally over time, both in community and clinical samples (see Lenzenweger et al., in press for an extensive review; see also Morey & Hopwood, 2013). The literature on the stability and change features in relation to PD is now massive and will not be reviewed here. Consider as but two examples, the Collaborative Longitudinal Personality Disorders Study (CLPS) found a significant decrease in personality disorder diagnoses over a two year time period (Shea et al., 2002) among patients with Axis II diagnoses residing in the community, and a similar decline was found in a sample of university students followed for 4 years (Lenzenweger et al., 2004). The picture of change in PD over time is consistent across the four major longi- tudinal studies of PD (Lenzenweger et al., in press; Morey & Hopwood, 2013).

The general finding of decrease in personality disorder criteria over time has resulted in speculation about what precisely is

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changing over time and what remains relatively stable, an issue that has been of central concern in personality theory. There is also considerable interest in the underlying mechanism or mechanisms for such change over time (which is clearly not explained simply by treatment effects). One explanation is that among borderline patients, the remission of acute symptoms such as suicidal behav- ior has a different time course than more stable temperamental features such as chronic anger (Zanarini et al., 2003). Likewise, Clark (2007) suggests that basic temperamental dimensions are responsible for the enduring aspects of the personality disorders.

A unique effort to understand change in personality disorder is the Longitudinal Study of Personality Disorders (Lenzenweger, 2006), which sought to examine whether change in personality disorder features would be related to change in personality dimensions reflec- tive of underlying neurobiological systems (Lenzenweger, 2006). Over a 4-year period, elevated initial levels of the agentic positive emotion system predicted more rapid decline in Cluster B person- ality disorder features over time. The authors suggested that indi- viduals with personality disorder features, but nonetheless able to engage with the world and to use rewards and incentives for self-regulation, find themselves less susceptible to continuing per- sonality dysfunction over time. Consistent with this hypothesis is the results of a prospective follow-up study over a 16-year period of BPD patients treated at McLean Hospital (Zanarini, Frankenburg, Reich et al., 2012). Whereas BPD patients were slower than the comparison patients to achieve symptomatic reductions, both groups had achieved high rates of remission at the 16-year follow-up. However, only 40% of the patients with BPD attained symptom recovery of 8 years or longer, as compared to 75% of the comparison patients with other personality disorders. The authors indicated that vocational impair- ment was related to the BPD patients’ failure to attain or maintain both symptom remission and good social and vocational functioning.

Emerging Models of Psychopathology

In contrast to the understanding of normal personality function- ing, the field of personality disorders is dominated by partial models of personality pathology that need amplification with the- oretical understanding and empirical advances (Lenzenweger & Clarkin, 2005). Conceptualizations of personality pathology must include multiple levels of analysis, including biological systems (e.g., RDOCs), behavioral traits (e.g., DSM–5 Section III), emer- gent processes (mental representations), and the interpersonal en- vironment. It is essential not only to understand the mechanisms underlying personality pathology at each of these levels, but also models are needed for articulating the dynamic interactions be- tween levels. We will discuss a number of such models that, while not actively part of the discussion about how to move PD diagnosis forward, have enormous promise in that regard.

Neural Systems Model

Over the past 20 years, we have seen an increased focus on the process/systems approach to understanding the causes of psycho- pathology. Kagan (Schwartz, Snidman, & Kagan, 1999) described anxiety psychopathology emanating from deviations in the fear system. Recall the core assessments of the children in Kagan’s landmark studies were done in the laboratory when the children were 4 months old, thus tapping early indicators of behavioral

inhibition. Davidson (1998) described affective disorder, particu- larly depression, in terms of the approach (positive emotion) and the withdrawal (negative emotion) systems. This work was done largely in the context of psychophysiological assessments. Depue and Lenzenweger (2001, 2005) proposed a model that describes personality disorders as emergent products of the agentic ap- proach, affiliation, anxiety, fear, and constraint systems. Predic- tions from this model are currently being tested in the laboratory using both psychological and pharmacological probes. This gen- eral line of thinking, where deviations in basic processes are thought to underlie the development of signs and symptoms of psychopathology, has long been a methodological and theoretical mainstay in both experimental and developmental psychopathol- ogy.

For a full appreciation of personality pathology, one must con- sider at least six relevant levels of the organism: (1) observable behavior (signs), (2) subjective experience, (3) neurocognitive functioning (e.g., working memory), (4) neurobehavioral systems and related individual variation in these systems (e.g., affiliation), (5) genetic and epigenetic inputs, and 6) environmental inputs (e.g., severe childhood trauma). Continuing advances in genetics and epigenetics research methods as well as neurocognitive labou- ratory methods (particularly with the incorporation of emotion/ affect) have enabled the PD research field to investigate these influences on the development and functioning of personality pathology.

Of particular importance is the endophenotype approach (Gottesman & Gould, 2003; see also Lenzenweger, 2013), which has gained considerable traction in psychopathology research in the past decade, and makes considerable use of models that speak to genetic underpinnings for some aspects of liability that can turn into personality disorder as well as the rigorous methods of mea- surement and testing found in the experimental psychology labo- ratory. The endophenotype approach seeks to identify genetically influenced indicators of psychopathology liability that may be closer to the genetic end of the gene to behavior pathway, which may provide a cleaner window on those processes related to the development of psychopathology (Gottesman & Gould, 2003).

As noted above, we view PD as an emergent end product of interacting processes, processes involving neurobehavioral sys- tems underpinning the psychological organization, epigenetic fac- tors, and environmental inputs (Lenzenweger & Depue, in press; Lenzenweger, 2010). In an emergent view of PD, the resulting configured personality disorder phenotypes are not reducible in a straightforward manner to the underlying individual component systems or influences. Moreover, the match between emergent phenotypes and existing descriptions of the personality disorders remains to be explored fully. Departing from trait models, which tend to focus on the extremity of a given trait, a neural systems model places emphases on trait levels and the interaction of traits (reflective of neural system interaction) as well as emphasis on thresholds for eliciting activation of the systems underlying those traits at various levels of excitation. The contribution of stress and environmental conditions on phenotypic presentation will be mag- nified or mitigated by underlying neurobiological systems, which over time will tend to bias attention in perception in ways that will come to be reliable and recognizable behavioral expressions. How- ever, manifestations of underlying systems are not stable over time, but rather vary greatly according to the affective and inter-

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personal context. The notion of thresholds by which the context evidences its effect is a key notion shared by the CAPS model, which shall be discussed shortly.

A neural systems model also departs from trait models in its conceptualization of the interaction of extreme trait dimensions. The same stressor may be differentially affecting underlying sys- tems due to their differential thresholds, and with perturbations in one system potentially cascading into others. Put differently, trait neuroticism differs greatly at conditions of high versus low trait agreeableness not simply by type, but by virtue of the interaction of perturbations to anxiety and affiliative systems under varying conditions of arousal. As can be seen, with the inclusion of other neural systems and ranges of stressors on those systems the com- plexity and nuance of emergent configurations is enormous, and therefore the manifest personality configuration is not readily reducible to its constituent parts.

Interpersonal Model

A key component of the DSM–5 Section III hybrid model was the focus on disordered self-functioning as it relates to interactions with others. This focus is in line with a growing consensus in the field that self-and-other functioning is at the centre of personality and personality disorder (Bender & Skodol, 2007; Gunderson & Lyons-Ruth, 2008; Hengartner et al., 2013; Horowitz, 2004; Krueger, 2013; Livesley, 2001; Pincus, 2005; Meyer & Pilkonis, 2005). This is a view that has long been espoused, for many decades, in object relations theory (Kernberg, 1984), and it is central to the followers of Sullivan and the interpersonal approach (Hopwood, Wright, Ansell, & Pincus, 2013). The centrality of self and interpersonal functioning has many implications.

In the DSM–5 Section III hybrid model each of the six person- ality disorder configurations specified has a unique and distinctive combination of faulty self-and-other functioning. As an example, antisocial personality disorder is characterized by an absence of prosocial internal standards, mirrored by interpersonal relations lacking concern for others and an incapacity for intimate relations. In contrast, avoidant personality disorder is marked by low self- esteem and marked impairments in developing close relations. When the DSM categories are examined at the individual criterion level, one can recognize the following interpersonal difficulties: pervasive distrust of others; detachment from social relations; reduced capacity for close relationships; instability in interpersonal relations; excessive attention seeking, avoidance, submissive and clinging behavior, preoccupation with interpersonal control, con- flict, aggression; defective or relative absence of moral functioning (dishonesty, stealing, physical violence, disregard for the rights of others). The emphasis on interpersonal behavior (with elements of self-and-other embedded within it) and its dysfunction strikes us as potentially rich (still largely untapped) as an avenue for future exploration in the study of PD’s. As such it represents an oppor- tunity to pursue with vigor the seminal insights regarding the importance of the interpersonal (self-and-other) dimensions artic- ulated by early workers such as Leary (interpersonal) and Kern- berg (object relations).

A contemporary interpersonal model of personality pathology (Hopwood et al., 2013; Pincus & Hopwood, 2012) differs in its emphasis from trait models by noting that a given trait will not express itself in every interpersonal context. Rather, this approach

conceptualizes personality dysfunction as arising from psychopa- thology operating within a complex relational matrix. Interper- sonal situations are organized along the axes of agency (from dominance to submission) and communion (from warmth/ap- proach to cold/avoidance). On one level basic aspects of person- ality pathology may be understood in terms of extremity of prob- lem interpersonal behaviors, which shares many features with pathological trait descriptions. A central aspect of an interpersonal model is also the focus on the rigidity of interpersonal styles; perhaps more important than our manifest style is our ability to flexibly step out of our characteristic ways of being in order to respond to the needs of others and situational demands. For ex- ample, an individual’s predilection for taking a more dominant role in interpersonal contexts is not in and of itself a problem, unless it is expressed in extreme ways and accompanied by an inability flexible shift into a more submissive role according to situational demands (i.e., needing to ask for help). At times of distress, such difficulty with agentic complementarity is likely to exacerbate distress rather than afford an opportunity for the relationship to provide a regulatory function.

An interpersonal model does not simply conceptualize the per- sonality disorders as extreme and rigid forms of interpersonal problem types. Rather, psychopathology is thought to powerfully interact with interpersonal dispositions in a pathoplastic relation- ship. This model shares the phenotypic emphasis of a neural systems model, in that interpersonal and personality dysfunction are understood to mutually shape each’s manifest expression, but importantly one cannot be easily reduced to the other (i.e., per- sonality pathology is not simply and outgrowth of interpersonal dysfunction; interpersonal dysfunction is not simply an outgrowth of personality pathology). Also consistent with a neural systems model, phenotypic personality dysfunction is conceptualised as emergent mental representations of self-interacting with others that subsequently shape interpersonal behaviors and motives (Pincus, 2005). This model has important implications for conceptualizing the heterogeneity of many personality disorders, with interpersonal subtypes having been empirically identified within both personal- ity (Wright et al., 2012) and symptom disorders (Cain et al., 2010, 2012).

Disturbed and disturbing interpersonal behavior is the final common pathway of a number of dysfunctional processes in indi- viduals with personality disorder. From a neural system’s perspec- tive, the human affiliation system is so basic to our fundamental nature as social animals and is so clearly rooted in genetic influ- ences, related neurobehavioral systems, and environmental inputs (see Lenzenweger & Depue, in press; Depue & Lenzenweger, 2005) that a fuller understanding of this rich matrix is not only essential for the illumination of normal psychological functioning, but clearly for pathological functioning as well.

Cognitive–Affective Processing System Model

Central to any theory of personality and personality disorder, its development, and intervention, is the question of what about the personality is relatively stable and what changes with time (see Lenzenweger, Hallquist, & Wright, in press). One cannot coher- ently address the issue of personality stability and change without a model of personality and its dysfunction. With the central issue of personality stability and change in mind, we consider the

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cognitive–affective processing system model (CAPS) (Mischel & Shoda, 2008). The CAPS model is based on empirical data de- scribing individual behavior within and across situations (Mischel & Shoda, 2008). This is a process model that conceives of per- sonality in terms of distinct internalized cognitive–affective units that capture an individual’s encoding and interpretation of situa- tions, beliefs about the world, affective tendencies, goals and values, and self-regulatory competencies. These cognitive– affective units are seen as existing in a structured network and mediate between the environmental situation and the individual’s behavioral response. This theoretical model is able to capture both intra-individual, interindividual, and group differences in person- ality, making it a compelling model for personality dysfunction (Eaton et al., 2009). This model of personality functioning has considerable empirical support, and has been articulated in an effort to understand both the consistency of personality and the creativity of the individual in the specific situation.

This meta-theory emphasizes five levels of experience: (1) an organized pattern of activation of internal cognitive–affective units (CAUs; e.g., conceptions of self-and-others, expectancies and be- liefs, affects, goals and values, self-regulatory plans); (2) behav- ioral expressions of this internal processing system; (3) self-and- other perception of these behaviors over time; (4) construction of one’s typical environment; and (5) the predispositions at the bio- logical and genetic levels of existence. This framework suggests that personality dysfunction can occur at multiple levels, and the assessment of these crucial areas could guide targets for interven- tion.

Consistent with a CAPS model, multiple theories of personality disorder use similar concepts to understand mental representations: consider for example, schemas (Pretzer & Beck, 2005), internal working models (Bretherton & Munholland, 2008), or internalized object relations (Kernberg & Caligor, 2005). The level of differ- entiation and integration of CAUs strongly influences our capacity to access, retrieve and adaptively use pertinent mental representa- tions (Mischel, 2004; see also Blatt, 1995). The more quickly and flexibly that representations can be retrieved and utilized to make fine-grained distinctions between contexts, the better able one is to regulate emotions and maintain a coherent sense of self. In con- trast, when CAUs are limited in breadth and rigidly applied re- gardless of context, individuals are likely to struggle to regulate emotions, to feel unmoored by novel contexts and respond to them as if they are old ones.

The CAPS model differs from trait models in its emphasis on the stability of personality features within a given context that would not be expected between contexts (i.e., intra-individual variability; Mischel, 2004). This distinction has significant impli- cations for how pathological aspects of personality are assessed. Rather than a conceptualization of personality pathology as ex- treme dispositional attributes, such as excessively low or high agreeableness, a CAPS model would emphasize the stability of the behavioral signature within which the attribute is observed. For example, from an interpersonal perspective a behavioral signature might be observed in which the individual is agreeable (agentic) only when also in the dominant role (behavior covariation) or when experiencing the other person in the submissive role (per- ception covariation) (Roche et al., 2013; see also Roche et al., 2014 for clinical applications). In this model emergent phenotypes may be understood as those with common organizing interconnec-

tions of CAUs in response to like contexts, thus sharing charac- teristic if-then signatures.

Key Cognitive–Affective Processes in Personality Pathology

Empirical developments in a number of core cognitive–affective processes stand to elucidate central processes in personality pa- thology. Though by no means an exhaustive list, we discuss rejection sensitivity and empathy because they have been fruitfully evaluated at multiple levels of analysis, including biological, be- havioral, and interpersonal features.

Rejection Sensitivity

Rejection sensitivity is a specific form of cognitive–affective unit (Mischel & Shoda, 2008), object relation dyad, and self-other perception that influences social reactions and behavior. As a construct, it is intimately related to interpersonal function and dysfunction. Rejection sensitivity is ‘the processing disposition to anxiously expect, readily perceive and intensively (negatively) react to rejection cues’ (Downey & Feldman, 1996). Individuals with high degree of rejection sensitivity focus extensively on anxious expectations of rejection. This can result in the perception of rejection even in the ambiguous and/or innocuous behavior of others. There is a tendency to automatically interpret any social situation as confirming their rejection fears. Such an ‘automatic’ ascription of negative dispositions to others accounts for increas- ing interpersonal conflicts by eliciting a self-fulfilling prophecy of rejection.

In nonclinical individuals, social rejection and threats to accep- tance signal the need to increase cognitive control in order to help interpret rejection-related stimuli in ways that minimise personal distress and promote one’s adjustment by responding to the im- mediate moment with emotional balance (Eisenberger et al., 2003). This mechanism can explain why the deployment of effortful attentional strategies accounts for a successful adjustment follow- ing interpersonal conflicts (Hooker et al., 2010).

Again, for the purposes of illustration, let us consider rejection sensitivity in relation to a particular PD, namely borderline PD. Rejection sensitivity is central to interpersonal difficulties of BPD (Ayduk et al., 2008; Staebler et al., 2011a; Stanley & Siever, 2010), and can account for the association between BPD features and the increased tendency to interpret neutral social faces as untrustworthy (Miano et al., 2013). Borderline patients react in a defensive manner and feel rejected regardless of actual interper- sonal acceptance or rejection.

However, an effortful attention deployment function (or an efficiently acting function) as noted above seems to be lost or missing in BPD. It is important to note that low executive control abilities increase the risk of developing borderline features in individuals high in RS (Ayduk et al., 2008), indicating that the capacity to effortfully control rejection cues may play a major role in the pathogenesis and maintenance of the disorder. Effortful cognitive abilities are required for inhibiting one’s own self- experience (e.g., perceived distress or rejection) in order to foster an unbiased consideration of another’s state of mind (e.g., neutral intention, context-dependent evaluation rather than hostile attribu- tions) (Lieberman, 2007). BPD patients show a ‘reflexive’ hyper-

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sensitivity to negative social cues (Koenigsberg et al., 2009b) as well as reduced perspective taking and increased personal distress (Dziòbek et al., 2011).

Empathy

The process of empathy or empathic linkages between self-and- others, rightly highlighted in DSM–5 (Section III), is a multifac- eted process central to smooth, flexible, and enjoyable interper- sonal relations. This complex process involves components of affective arousal, emotional understanding, and emotion regulation (Decety, 2010). Empathy is described as an affective response arising from the understanding of the other’s emotional state or condition (Eisenberg et al., 1991; Decety, 2010). Empathy, the ability to recognize the emotions and feelings of others, is distin- guished from sympathy, which is an other-oriented emotion that involves the added emotional response of concern for the welfare of others.

Mature empathic sensitivity and sympathy depend upon the integration of affective arousal, emotional understanding, and emotion regulation, all in the service of goal-directed, social be- havior (Decety, 2010). Affective arousal is active and evident in infants, prior to the development of language. Discrete signs of emotional experience are evident in the facial expressions of infants, and infants quickly derive information about the caregiv- ers’ emotional states of pleasure or displeasure.

Gradually, the cognitive understanding of the emotional states of others develops, progressing from situation-bound, behavioral explanations to broader, more mentalistic understandings (Harris et al., 1981). This evolution of a developing cognitive empathy allows the individual to utilize perspective-taking to image what the other is experiencing. This process has been discussed not only in terms of cognitive empathy, but also theory of mind, and executive function and self-regulation. Affective resonance be- tween two individuals is deepened by the growing representations of the feelings of another as an intentional agent (Decety et al., 2008). By four years of age, children can understand that the emotion that another feels about a given event depends upon that person’s perception of the event, and this emotion recognition is related to social cognition performance into late adolescence.

Finally, the third key element in empathic linkages to others is emotion regulation. Smooth, satisfying interpersonal relations in- volve both the joyful experience of spontaneous cognitive- emotional experience, but also in the ability to regulate emotions appropriately, especially negative emotions. The development of emotion regulation is closely linked to the parallel development of executive functions and metacognition. Regions of the prefrontal cortex and the dorsal anterior cinculate cortex (ACC) are inti- mately involved in these modulation processes (Ochsner, Bunge, Gross, & Gabrieli, 2002). There is a growing understanding of the developmental course of these functions well into adolescence (Casey, Tottenham, Liston, & Durston, 2005).

Contemporary models of cognitive emotion regulation are built on that background by use of fMRI studies of appraisal and reappraisal (Ochsner & Gross, 2008). Emotions arise from brain systems that appraise the significance of stimuli given the goals and needs of the individual, and reappraisal is an effort to recon- sider the stimuli and modulate the affective and behavioral re- sponse. Reappraisal depends upon interactions between prefrontal

and cingulated regions implicated in control, and the amygdala and insula that are implicated in emotional responding.

In normal individuals affect regulation by reappraisal in contrast to suppression is associated with greater positive emotion, reduced negative emotion and better interpersonal functioning (Gross & John, 2003). However, continuing with our BPD illustrations, those with BPD have difficulty processing negative affect effi- ciently and effectively (Silbersweig et al., 2007). Borderline pa- tients rely on reflexive, automatically responding networks, whereas healthy controls make more use of networks with access to higher level conscious cortical processing (Koenigsberg et al., 2009a). Most importantly, borderline patients are deficient in their ability to reduce negative affect by reappraisal (Koenigsberg et al., 2009a).

Effortful control has been described as the ability to inhibit a dominant response in order to perform a subdominant response (Posner & Rothbart, 2000). Impulsivity in behavior is inversely related to the capacity for effortful control, a self-regulation di- mension of temperament (Ellis, Rothbart, & Posner, 2004). The individual with effortful control is able to voluntarily inhibit, activate or change attention, and thus, potentially modify and modulate subsequent affect. The development of effortful control in infants and toddlers is central in the regulation of affect, and the development of mature social relations and conscience (Eisenberg, Hofer, Sulik, & Liew, 2014).

There is preliminary information on how the empathic process can go array in those with personality disorders. Those with antisocial personality disorder, more specifically psychopathy, are proficient in perceiving others’ intentions, but are deficient in recognition of negative emotional facial expressions (Decety & Moriguchi, 2007). There are deficits in the perception of fear and sadness, and this has been associated with blunted amygdala responses (Blair, 2010) with reduction in the functional connec- tivity between the amygdala and prefrontal cortex, resulting in the lack of integration of emotions and cognition. Those with narcis- sistic personality disorder manifest deficits in affective empathy (Ritter et al., 2011).

Implications

The models and methods discussed have a number of implica- tions for near future research, assessment, and clinical develop- ments that will be essential in furthering our understanding of personality pathology.

Implications for Conceptualizing PD Pathology

First, as has been now made clear, we deem it essential to conceptualise PD pathology as emergent phenotypes based on underlying biological and behavioral trait systems, in interaction with relational experiences, that result in unique self-other config- urations. It should be noted that the focus on self-and-other is not an end in and of itself. The self-versus-other distinction, and the manner in which pathology can manifest itself, will impact other areas of personality/psychological functioning. What is the rela- tionship between self- and interpersonal dysfunction, and symp- toms mentioned in the personality disorder criteria such as suicidal behavior (BPD), antisocial and immoral behavior (antisocial per- sonality disorder), anxiety and depression? Emergent representa-

161CONCEPTUALIZATION AND TREATMENT OF PERSONALITY DISORDER

tions of self-affectively relating to others not only arise from underlying biological and behavioral trait systems, but also sub- sequently shape the experience and expression of those systems, biasing subsequent traits expression and interpersonal behaviors over time (Lenzenweger & Depue, in press; Pincus, 2005).

Second, personality pathology must be conceptualised as unsta- ble. It is important to note that the aforementioned process by which emergent phenotypes both arise from and influence the subsequent expression of underlying systems over time may lead to either a “hardening” or “softening” of the phenotypic features over time. For example, whereas low agentic positive emotion may manifest as avoidant behaviors that calcify future relational avoid- ance, high agentic positive emotion may manifest as approach behaviors that, even if dysfunctionally executed much of the time, may create opportunities for social reward and comfort that may mitigate future dysfunction (Lenzenweger & Depue, in press).

Third, personality pathology must be conceptualised as contex- tual. Pathological processes that bias perception and attention are evidenced under stimulus contexts that may not be elicited in other contexts, and may not be shared to the same extent by those without such pathology. For example, borderline symptoms often occur in the context of social threat; interpersonal hypersensitivity contributes to affectivity, impulsivity, aggression, suicidality and social dysfunction (Gunderson & Lyons-Ruth, 2008). Rejection sensitivity leads to aggressive responses in the context of rejection (Romero-Canyas et al., 2010), but the capacity for effortful control is protective (Ayduk, Zayas, Downey et al., 2008). Further, while some personality pathologies are characterized by are character- ized by dramatic fluctuations in functioning between contexts (e.g., borderline pathology), other pathologies are characterized by a rigid inability to fluctuate and adapt in the presence of changing contexts (e.g., narcissistic and obsessive– compulsive pathologies).

Implications for Research in PD Pathology

Each of the above observations helps us to understand the significant heterogeneity of personality pathology. Future research will need strategies to address the significant heterogeneity in personality pathology. In this regard, methodological approaches such a mixture modelling show significant promise (Lenzenweger, Clarkin, Yeomans, Kernberg, & Levy, 2008; Wright et al., 2013). One of the major limitations of commonly used statistical ap- proaches to cluster or factor personality pathology is that they seek to identify latent structures without an a priori model based in clinical and empirical knowledge of the psychopathology. Rather, dimensions that reflect like constructs, or subjects that have like features, are organized in imprecise ways and often involve a significant amount of the researcher’s discretion in drawing lines between components or groups, leading to failures to replicate findings across studies. In contrast, finite multivariate mixture modelling makes no a priori assumptions regarding the data struc- ture (e.g., common metrics, standardization) and it allows for underlying components of different size, shape, and orientation (unlike ad hoc procedures such as k-means clustering, e.g.). More- over, finite mixture modelling provides a statistically well princi- pled basis for testing the number of components harbored within the data (i.e., model selection), and thus affords advantages in identifying latent structures in heterogeneous psychopathology indicators/datasets (Lenzenweger et al., 2008).

Future PD research will also need to increasingly focus on real-time assessments of self- and interpersonal functioning in ecologically meaningful contexts. For example, from interpersonal model, problems in agentic complementarity (i.e., flexibly meeting another’s dominance with submissiveness and vice versa accord- ing to situational demands; see Pincus & Hopwood, 2012) is not easy captured cross-sectionally, as the appropriateness of the in- dividual’s behavioral is dependent on the role of the interactant at that given moment. Therefore, research tools are needed that may capture the contextual nature of dysfunctional processes in per- sonality disordered individuals. For example, real-time coding of interpersonal patterns between interactants has been fruitfully evaluated using Sadler’s joystick method (Sadler et al., 2009; Thomas et al., 2014), which observers record real-time fluctuations in agency and communion in among interactants (i.e., patient and therapist, romantic couples). The identification of dysfunctional interpersonal patterns that may powerfully interact with the emer- gence of personality pathology would be essential not only to conceptualizing its phenotypic presentation, but also have impor- tant treatment implications in terms of identifying potentially countertherapeutic behavioral transactions (Hopwood et al., 2013).

Ecological momentary assessment (EMA) is another exciting methodological tool that stands to contribute to understanding the contextual nature of dysfunctional processes in personality disor- dered individuals. Experience sampling methods and ecological momentary assessment are advances over self-report methods that are susceptible to memory bias, in that participants are asked to provide brief but immediate ratings following specific events or random prompts at specified intervals. Such methods allow re- searchers to move away from aggregate ratings of a given behav- ioral or emotional experience to evaluate intra-individual variabil- ity. Consider for the purposes of illustration some recent research on borderline PD. With an event-contingent ecological momentary assessment procedure, while borderline patients were found to evi- dence higher overall mean levels of negative affect as compared to controls, greater affective variability was observed with regard to positive affect (Russell, Moskowitz, Zuroff et al., 2007). Further, while on average BPD patients were more submissive and quarrel- some in their interpersonal behavior than were controls, significant variability was reported with regard to agreeableness. The aggregate findings are not surprising and consistent with past research suggest- ing that borderline patients struggle with assertion and aggression. What is surprising and more powerful is the intrainidvidual variability within borderline pathology; it is clinically resonant to consider the inconsistency with which positive relatedness is experiencing and subsequently elicited, and the potentially destabilizing ebb and flow of a good feeling for borderline patients.

Experience sampling methods are perhaps most useful for eval- uating hypotheses consistent with a CAPS model Mischel & Shoda, 2008), in which behaviors are most meaningful when understood in the context of characteristic situation-behavior re- sponse patterns, rather than aggregated across unrelated situations (as is often the case in cross-sectional designs). For example, by electronically sampling a range of affective experiences at five random times a day for 21 days, Berenson and colleagues (2011) demonstrated a relationship between momentary feelings of rage in the context of perceptions of rejection in participants high in borderline personality features that was not observed in those with low borderline features. Sadikaj and colleagues (2013) found that,

162 CLARKIN, MEEHAN, AND LENZENWEGER

relative to controls, patients with BPD were more quarrelsome and experienced greater negative affect in the context of perceptions of others as quarrelsome. A trait-level assessment of rage and other experiences of anger (or low agreeableness) would obscure the more specific “if-then” signature characterized by precipitating perceptions of rejection and hostility in others.

To give another example of fruitful research in this regard, utilizing the CAPS framework (Mischel & Shoda, 2008), multi- level models were applied to event-contingent social interaction data to examine the influence of narcissistic grandiosity and nar- cissistic vulnerability (Roche et al., 2013). Participants in this 7-day diary study rated their own and others’ behavior on dimen- sions of agency and communion. Whereas trait-level research has indicated that grandiose narcissistic pathology tends to be associ- ated with dominant and domineering behaviors, a more specific and surprising contextual association was found in which agency was not complemented (e.g., matching dominance with domi- nance) in the context of perceiving the interactant as more friendly. It might have been expected that those high on grandiose narcis- sism would seek to control those perceived as more quarrelsome, but Roche and colleagues (2013) note that concern about failing to enhance the self and dominate a quarrelsome other, and its subse- quent loss of status, may lead to avoidance and submissiveness unless the potential for self-enhancement is assured (i.e., with a friendly interactant). Taken together, such methodological ap- proaches have significant implications for not only conceptualiz- ing but also treating the contingent nature of affective and inter- personal dysfunction in borderline and narcissistic pathologies.

Implications for Evaluating PD Treatments

Subsequent to the articulation of explicit diagnostic criteria for the personality disorders in 1980 (DSM–III), there has been an explosion of research on personality pathology and treatment of the PDs. This effort has not been proportionate across the various PDs, but focused mainly on the severe end of the PD spectrum, especially involving the borderline and antisocial personality dis- orders. Using the empirical investigation of psychotherapy for borderline patients as illustrative, it seems clear that structured treatments can reduce harmful symptoms, such as suicidal behav- ior. However, the question still remains if psychotherapy can change the enduring aspects of the personality, such as the auto- matic and reflective representations of self-and-other which guide the processes of interpersonal interaction that we have detailed above. Centrality of self-and-other functioning may naturally lead to the ability of treatment to change self-and-other interpersonal functioning. Treatment research to date has focused on symptoms, with less attention to self-and-other functioning.

Kazdin (2007) accurately points out that discussion and theory about why psychotherapy changes people is plentiful, but evidence for the change is quite rare. The mechanisms or processes that are responsible for the changes are still elusive. Despite the centrality of interpersonal behavior in the personality disorders, which is now considerably emphasised in DSM–5’s Section III (APA, 2013), the fine grained study of change in the interpersonal domain remains an area ripe for investigation in the PDs. There will be considerable challenges in the study of change in interpersonal functioning in the PDs within the context of treatment. Improve- ment in interpersonal functioning will not translate simply to

increased scores on extraversion or sociability in a personality trait scheme. Rather, interpersonal behavior in the real-world must be dissected carefully, particularly in relation to contexts where it is manifested in its various forms (love, work, schooling, family functioning, and so on). Future treatment research should seek to evaluate how interpersonal patterns in the treatment (i.e., interper- sonal joystick) should mirror interpersonal patterns in daily life (i.e., EMA), and changes over time in the contingent nature of personality dysfunction should then be reflected in changes in manifest symptom (self-report) and brain (fMRI) functioning. De- spite the emphasis in treatment research of change in manifest symptom functioning, there would be clear benefit to evaluating clinical response at these multiple levels.

Personality disorders are marked by heterogeneity both within a given disorder and with comorbidity across the personality disor- ders. The various constellations that personality disorder assumes make it difficult to articulate a treatment that fits all of these individuals even within one personality disorder category. Treat- ment research may be more illuminative were it to focus on domains of PD dysfunction, not disorders. Given the issues de- scribed above with the assessment and treatment of PD, it seems logical to consider the specific client in terms of salient interper- sonal difficulties and how these difficulties are manifested in that individual’s unique environment. Domains of dysfunction and severity of these dysfunctions become as important in the clinical workup as the identification of the PD category itself.

An integrated modular approach (Clarkin, Cain, & Livesley, in press) is an invitation to drop categorisation of strategies and techniques related to therapy school (e.g., cognitive– behavioral, psychodynamic), and instead focus on patient domains of dysfunc- tion and a variety of ways to approach them with effective treat- ment modules. The central difficulty in those with personality disorder is an observable dysfunction in interpersonal relations, with a more covert difficulty in the mental representations of self-and-others (Pincus, 2005; Kernberg, 1984). Individuals scor- ing high on any personality disorder dimension have considerable interpersonal difficulties characterized by a solitary lifestyle, con- flicted and distressed social relations, and lack of social support (Hengartner, Muller, Rodgers, Rossler, & Ajdacic-Gross, 2013).

One way to tailor the treatment to the individual is to assess for domains of dysfunction, and match treatment modules to these domains. One can identify treatment modules which target specific domains of dysfunction embedded in larger intervention packages that have been empirically investigated (e.g., Bateman & Fonagy, 2006; Clarkin et al., 2006; Linehan, 1993), or treatment modules devised by clinical researchers with experience intervening with specific target areas (e.g., Safran & Muran, 2000). There are two overarching modules of treatment for those suffering from PD: 1) general treatment modules that are used to structure treatment, enhance motivation for change, and manage the relationship be- tween patient and therapist, and 2) specific treatment modules for specific domains of dysfunction.

Conclusion

The traditional concept of personality rests on the notion of consistency of behavior across situations and time. Modern models of personality—incorporating social, cognitive, and affective com- ponents— have transcended this classic conceptualization. For ex-

163CONCEPTUALIZATION AND TREATMENT OF PERSONALITY DISORDER

ample, the CAPS model we have described is one of situational consistency and cross-situational novelty. Social neurocognitive science is exploding with information about the processes involved in the individual’s self-functioning as one relates to others. We have focused here on a few of those processes, best captured by the concepts of rejection sensitivity and empathy. Moreover, modern personality neuroscience emphasizes the integration of neurobe- havioral systems with the major phenotypic behavioral systems we think of as constituting the basic foundation of personality (e.g., approach, affiliation, fear, anxiety, constraint, and so on; see Lenzenweger & Depue, in press; Depue & Lenzenweger, 2005).

As social animals, we are dependent on others from birth, and negotiating the environment with other individuals is a key process in productive living. Personality dysfunction or personality disor- der is a disruption in this process of negotiating our needs and desires with others. DSM–5 section III has emphasized the disrup- tion in self-and-other functioning that is central across all the personality disorders or types. Thus, understanding the manner in which our genetically influenced, neurobiologically mediated, psy- chologically experienced, and socially shaped personalities inter- act with and are influenced by the environment is indeed the research task ahead of us. Being able to influence this complex matrix to move dysfunctional states in the direction of health and adaptation is the clinical task ahead of us.

Résumé

Les troubles de la personnalité sont courants et leur effet est débilitant, mais il existe des dissensions au sujet de la définition, de l’évaluation et du traitement de ces conditions. Cette revue examine les principales démarches de conceptualisation des trou- bles de la personnalité, aussi récentes que celle qui figure dans la section III du DSM–5 et que l’initiative des critères de volets de recherche du National Institute of Mental Health. Trois modèles connus pour expliquer ces troubles (fonctionnement neural, modèle interpersonnel et modèle du système de traitement cognitif-affectif) sont examinés selon leurs fondements empiriques pertinents. Les répercussions pour la recherche future en psycho- pathologie, sur les traitements et la pratique sont présentées.

Mots-clés : personnalité, trouble de la personnalité, évaluation et traitement.

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Received September 8, 2014 Revision received December 11, 2014

Accepted December 19, 2014 !

167CONCEPTUALIZATION AND TREATMENT OF PERSONALITY DISORDER

T/C Case Conceptualization Model Outline

(* Areas that the counselor believes require more information)

Client: First Name:

Client Demographics:

Age

Gender

Relationship Status:

Spiritual/Religious Affiliation

Other

Presenting Problem: [No diagnostic nomenclature. No DSM-5 diagnosis. Provide a briefly stated presenting problem based on information conveyed by the client in the case study.]

Internal Personality Constructs and Behavior

Self-efficacy:

Self-esteem:

Attitudes/Values/Beliefs:

Attachment Style:

Biology/Physiology/Heredity:

Affect:

Cognition:

Hot Thoughts:

Behavior:

Symptomology:

Coping Skills and Strengths:

Readiness for Change:

Life Roles:

Environment

Relationships:

Culture:

Family Norms and Values:

Societal Influences:

Timeline

Past Influences:

Present Influences:

Future Goals:

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