Food Quality and Preference 95 (2022) 104360

Available online 17 August 2021 0950-3293/© 2021 Elsevier Ltd. All rights reserved.

Drinking tea improves the convergent creativity performance

Yi Jiang a, b, 1, Yan Huang a, b, 1, Yuanzhi Wu c, Lei Wang a, b, d, *

a School of Psychological and Cognitive Sciences and Beijing Key Lab for Behavior and Mental Health, Peking University, China b Peking University-Taetea Consumer Research Center, Peking University, China c Academy of Certifies Tea Master, China d Gallup-Peking University Positive Psychology Center, Beijing, China

A R T I C L E I N F O

Keywords: Tea Drinking Convergent Thinking Creativity Performance Tea Consumption “Split half effect”

A B S T R A C T

Tea consumption has been extensively shown to be closely related to physical health and cognitive abilities. However, there are no definite conclusions on the relationship between tea consumption and convergent thinking. Convergent thinking requires top-down cognitive processing, which focuses on searching for an appropriate idea based on well-defined criteria. It is a necessary part of the creative process and is inextricably linked to divergent thinking that requires people to search for many different ideas with less defined criteria within a wider search span. It has been found that tea consumption is beneficial to divergent thinking in crea- tivity. Given that convergent thinking is related to divergent thinking, we hypothesized that drinking tea may also promote convergent thinking. This research was to investigate the enhancing effects of tea on convergent thinking and test its possible mediating mechanism (i.e., the role of positive emotions) and marginal conditions (e.g., the moderating roles of intelligence and tea preference). In Experiment 1, participants completed the Remote Association Test (RAT) which requires the solver to create a meaningful link (word association) that mediates three seemingly unrelated cues (e.g., Same–Tennis–Head is mediated by Match) after drinking tea or water. The results showed that the type of drinks and tea consumption habits had a significant interaction effect on RAT scores. The participants who drank tea (v.s. water) and had the habit of drinking tea performed best in the RAT. A “split half effect” was found. That is, participants’ performance in different groups was significantly different in the second half of the RAT, suggesting that drinking tea leads to persistent problem-solving convergent thinking. Experiment 2 aimed to replicate the findings in Experiment 1 using a different conver- gent thinking task, namely, riddle tasks, where participants needed to solve riddles with different levels of difficulty. The results revealed that performance in the tea group on the difficult tasks was significantly higher than that in the water group; after controlling for knowledge level and intelligence, the differences in the per- formance in the medium- and high-difficulty riddle tasks between the two groups were significant. Although no experiments found a mediating effect of positive emotions, Experiment 2 showed that the participants in the tea group were happier and more interested in the task than those in the water group. To conclude, the positive effects of tea drinking on convergent thinking was demonstrated, and the moderating effects of knowledge level, intelligence, and tea drinking habits were elaborated. The results have important practical significance for those who are engaged in creative work or those who are prone to fatigue.

1. Introduction

Tea consumption ranks second in the world, only to water con- sumption (Hodgson & Croft, 2010). Many studies have explored the functional effects of tea. It has been found that drinking tea is good for physical health (Ruxton, Phillips, & Bond, 2015; Shen & Chyu, 2016; Hayat, Iqbal, Malik, Bilal, & Mushtaq, 2015), cognition (Dietz & Dekker,

2017; Einöther & Martens, 2013; Kuriyama et al., 2006), and emotion (Einöther & Martens, 2013; Einöther, Rowson, Ramaekers, & Gies- brecht, 2016).

Recently, research on the cognitive impact of tea drinking has focused on creativity. Convergent creativity and divergent creativity involve different cognitive processes. Convergent creativity requires top-down cognitive processing, which focuses on searching for an

* Corresponding author at: School of Psychological and Cognitive Sciences, Peking University, Beijing 100871, China. E-mail address: [email protected] (L. Wang).

1 The first two authors contribute equally.

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https://doi.org/10.1016/j.foodqual.2021.104360 Received 25 December 2020; Received in revised form 10 August 2021; Accepted 12 August 2021

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appropriate idea based on well-defined criteria, while divergent crea- tivity involves less top-down processing, so people can search for many different ideas with less defined criteria within a wider search span. It has been found that tea improves divergent thinking in creative tasks, e. g., the Remote Association Test (RAT, Huang et al., 2018). However, few empirical studies have investigated the effect of tea drinking on convergent thinking (Einöther, Baas, Rowson, & Giesbrecht, 2015). Since convergent thinking is an essential human activity (Abu-Akel et al., 2020; Shettar, M, & Tewari, 2020), it is worth discovering methods that could improve convergent thinking. The current research will address this issue. We will first review the literature and describe our research proposal.

1.1. Tea and primary cognitive processing

Empirical studies on tea consumption and cognition mainly focus on tea and low-level cognitive processes, namely, attention or alertness level. To date, some studies have specifically explored the effect of black tea on attention performance (Einöther & Martens, 2013). Hindmarch, Quinlan, Moore, and Parkin (1998) compared the effects of coffee, water, and tea with and without caffeine in the critical flicker fusion (CFF) task (an objective means of measuring subjects’ ability to distin- guish discrete sensory data) and the line analog rating scale (LARS). In the CFF task, subjects are required to discriminate flicker fusion in a set of four light-emitting diodes held in foveal fixation at 1 m. With LARS, subjective ratings of treatment effects are obtained from a series of 100- mm line analog rating scales, where attention is assessed by alertness items. The results showed that caffeinated beverages improved task performance and self-reported alertness, and cognitive performance decreased more slowly over time than performance did with non- caffeinated beverages. Moreover, the study found that tea’s attention benefits could not be entirely attributed to caffeine and that other components (e.g., flavonoids, theanine) of tea could also contribute to cognitive benefits. The study showed that subjects who drank caffein- ated tea had a significantly greater CFF threshold than those who drank caffeinated water (caffeine concentrations were equal). The study pro- vided preliminary evidence for the beneficial effects of tea on attention- related performance. In their subsequent study, the main effects of 37.5 and 75 mg caffeine in the CFF and LARS tasks, respectively, were suc- cessfully replicated (Hindmarch et al., 2000).

A recent study (De Bruin, Rowson, Van Buren, Rycroft, & Owen, 2011) used double-blind placebo-controlled crossover designs and more complex attention tasks to further investigate these effects. Again, ac- curacy in the attention-switching task was improved after drinking black tea, and the participants in the tea group reported higher levels of alertness than those in the placebo group.

It can be concluded from the above studies that drinking tea can improve attention and self-reported alertness. Studies on caffeine and the combination of theanine and caffeine further support these conclu- sions (Giesbrecht, Rycroft, Rowson, & De Bruin, 2010; Kelly, Gomez- Ramirez, Montesi, & Foxe, 2008).

1.2. Tea and cognitive thinking in creativity

A few studies have investigated the relationship between tea con- sumption and creative thinking as an advanced comprehensive cognitive process. The work of Einöther et al. (2015) and Huang et al. (2018) provided preliminary evidence for the main effect of tea on divergent thinking in creative tasks. In particular, Huang et al. (2018) showed a “split half effect”; that is, the enhancing effects of tea drinking on task performance did not appear until the second half of the task. It is possible that tea also causes improvements in endurance. As the task goes on, the tea starts to take effect to resist the decrease of performance. This study showed that tea drinking can significantly help maintain and improve performance in the second half of cognitive tasks, a phenom- enon called “split-half effect”. This means that the enhancing effects of

tea on convergent creative performance lies in its ability to maintain tenacity and persistence. This may also be because the more difficult the task is, the more helpful the tea drinking is, which is consistent with previous research findings (Einöther et al., 2015).

Contrary to divergent thinking, convergent thinking focuses on producing a single, comprehensive answer to a question, which usually means the process of providing a “correct” answer to a standard question (Cropley, 2006). Convergent thinking is a necessary part of the creative process and is inextricably linked to divergent thinking. Given that tea drinking is beneficial to divergent thinking in creativity and convergent thinking is linked to divergent thinking, we hypothesized that tea may also promote convergent thinking, as assumed by Einöther et al. (2015). Einöther et al. (2015) claimed that tea consumption will improve cre- ative problem solving due to increased positive affect compared to a neutral control and to a similar extent as a positive control. Unfortu- nately, Einöther et al. (2015) did not find significant evidence to support their assumption.

We argue that there are several reasons why no empirical evidence has been found. First, there are problems in the method of measuring creativity. Previous studies have used the classic RAT to measure crea- tivity. This subjective test is very likely to be influenced by individuals’ linguistic ability and vocabulary, which were not controlled for in the former studies. In addition, convergent thinking performance is closely related to the level of participants’ knowledge and intelligence, which was not considered and controlled for in previous studies. In the current research, we will examine the effect of tea drinking on convergent thinking by addressing all the above methodological issues. Second, the tea-drinking scenes and the individuals tea-drinking habits were very different, which was not controlled for in previous studies. Huang et al. (2018) controlled for the influence of individual tea-drinking habits and tea-making scenario regarding the volume, concentration, and temper- ature of the tea by preparing the tea in the laboratory in advance, such that they found the effect of tea on divergent thinking. Therefore, we also used the same methods to exclude the influence of those factors.

Based on the above discussion, we propose the following hypothesis: H1: Drinking tea improves performance in convergent thinking

activities. We will test our research hypothesis in two experiments. In partic-

ular, we will control for the possible marginal conditions of language ability, intelligence, and tea preference and habit. Experiment 1 will test the main effect using the RAT to measure convergent thinking. Experi- ment 2 will try to replicate the findings in Experiment 1 using another type of convergent thinking task, namely, riddle tasks. In both experi- ments, we will measure possible, previously mentioned marginal con- ditions to control for their impacts on convergent thinking performance. In particular, we mainly focused on the acute effect of tea on creativity, and creativity was measured 15–20 min after tea drinking. In other words, we are mainly interested in the effects of psychological function related to creativity that may happen in a very short period of time after drinking.

Moreover, we will test the mediating role of emotion in this rela- tionship since previous studies have found that tea drinking promotes positive emotion and mood, which may benefit cognitive thinking (Desmet & Schifferstein, 2008; Isen, Labroo, & Durlach, 2004; Yoto, Motoki, Murao, & Yokogoshi, 2012). Meta-analyses of mood and crea- tivity research have shown that a positive mood leads to higher crea- tivity than a neutral mood (Baas, De Dreu, & Nijstad, 2008; Davis, 2009). De Dreu, Baas, and Nijstad (2008) explained the relationship between mood and creativity through a dual pathway model. Creativity can be achieved through either cognitive flexibility or cognitive perse- verance, both of which are mediated by mood. To, Fisher, Ashkanasy, and Rowe (2012) showed that activating a negative mood had a sig- nificant lagged effect on creative process engagement (CPE) whereas activating a positive mood did not, and that activating a positive mood had the strongest association with CPE when both proven goal orien- tation and supervisory support were high. Therefore, we will also test

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another hypothesis: H2: Positive emotions mediate the effect of drinking tea on conver-

gent thinking.

2. Experiment 1

2.1. Method

2.1.1. Participants With reference to previous classic studies (Einöther et al., 2015;

Huang et al., 2018), the sample sizes of the two studies in this paper were set at 40 and 60. A total of 40 full-time students were recruited through the Internet and WeChat for Experiment 1. In the tea group, male subjects accounted for 33.3%, and in the water group, male sub- jects accounted for 36.8%. Each participant received $6 as a reward for participating in the experiment.

2.1.2. Design This experiment included two parallel drink conditions: a cup of

black tea (Lipton, a well-known brand but anonymous to participants) and a cup of water, both of which were approximately 260 ml and were served at a drinkable temperature of 42 ◦C. Black tea was prepared in advance using a standard process: one tea bag per 150 ml water. Tea bags were steeped in boiling water for five minutes. Then, the tea and the water for the control condition were kept at a temperature of 42 ◦C in an electronic kettle. In this way, we controlled for confounding variables that existed in previous experiments, such as the brand name of the tea, the experience of preparing the tea, the tea’s concentration and tem- perature, and the utensils for drinking the tea. Under both conditions, the drinking amount (ml) of the participants was recorded. We adopted the implicit priming experimental paradigm such that participants were unaware of the independent variable manipulation (Hong, Morris, Chiu, & Benet-Martinez, 2000). Tea consumption was manipulated implicitly by serving tea or water during the greeting stage of the experiment, so the participants did not realize that drinking was the crucial part of our study. The participants were randomly assigned to one of two condi- tions. In that sense, participants are blinded to their condition.

2.1.3. Procedure In the warming-up stage, the participant arrived at room A as

scheduled to wait for the start of the experiment. A receptionist (experimenter A) poured a cup of pre-prepared hot drink (water/tea) in front of the participant. The cups provided to the participants were disposable, which were picked out from a new package in front of every participant. The purpose of this manipulation was to ensure that par- ticipants wouldn’t refuse the drink for hygienic reasons. To avoid the color, trademark and other factors of the cup affecting participants, the cup was pure white without any pattern or trademark.

Then, the receptionist returned to the seat and asked for participants’ personal information, such as the department, major, grade, student ID number, and mobile phone number not only for the payment purpose but also for extending the duration of warming-up stage. To let the participants drink as much as possible, the receptionist also poured herself a cup of the same drink. The warming-up stage lasted for three to five minutes so that the participant had enough time to finish the drink. Then, the receptionist led the participant to room B to perform the experimental task. After the participant entered room B, the receptionist measured how many milliliters the participant drank with a measuring tube and recorded it.

In room B, the experiment was conducted by experimenter B who didn’t know which drink the participant drank. The participant was asked to complete the tasks on a computer. The participant completed the Mood Inventory scale, RAT, Raven Advanced Progressive Matrices Test, Mood Inventory scale, tea consumption habits and attitudes scale, and demographic statistics questionnaire (including Chinese and math scores on the college entrance examination) in order. Experimenter B

checked whether the tasks were successfully submitted and then directed the participant to go to room A to ask the receptionist for the payment. The sessions lasted 35 min in total.

2.1.4. Measurements

2.1.4.1. Emotional state. The mood inventory (MI) scale was used to measure the participants’ emotional state during the experiment. This scale was taken from Phillips, Bull, Adams, and Fraser (2002) and Oaksford, Morris, Grainger, and Williams (1996) and used to measure the participants’ mood after drank the beverage and after they completed the convergent thinking task. In this study, the English version of Chermahini and Hommel (2012) was used for the translation into Chinese. All scale items underwent a back-translation process (Brislin, 1986) to ensure the internal validity of our translated scales. The scale has ten items: six measuring happiness (Cronbach’s alpha = 0.89), two measuring physical arousal (Cronbach’s alpha = 0.88), and two measuring anxiety (Cronbach’s alpha = 0.93).

2.1.4.2. Remote Association Test (RAT). The Chinese version of RAT compiled by Xiao, Yao, and Qiu (2016) was adopted in this study and contained 30 items. In each item there are three words (e.g., Same–Tennis–Head”), and participants are asked to make association among the three words (e.g., “please give a meaningful link by figuring out a word (word association) that mediates the three words”). The scale has good criterion validity, with a correlation coefficient of 0.34 with the Raven test and coefficients of 0.18 and 0.28 with the Torrance Test of Creativity Test (TTCT) and RCAB, respectively. In our study, the par- ticipants had 10 min to complete the test.

2.1.4.3. Level of knowledge and intelligence. Previous studies have shown that convergent thinking is related to knowledge and intelligence (Lee & Therriault, 2013; Ritter, Abbing, & Van Schie, 2018), so these factors needed to be controlled for. Xiao, Yao, and Qiu’s (2016) Chinese version of the RAT also found that the participants’ RAT scores were moderately correlated with their intelligence (Raven’s test) and signif- icantly correlated with their Chinese and math scores. Therefore, in this study, the Chinese and mathematics scores of the participants on the national standardized college entrance examination were selected as one index of the level of knowledge and intelligence of the participants, and the scores of the participants in the Raven’s Advanced Progressive Matrices (APM) were selected as another index. In consideration of the total duration, only half of the questions on the APM were used in this study (18 odd-numbered items were selected). Since the Spearman- Brown split-half reliability of the parity score on the APM in Barrow (1990) study was 0.82, we believed that it was reasonable to select half of the questions. The participants were given 10 min to complete the questions.

The participants were also asked to report their past Chinese and math scores on the national standardized college entrance examination. The two questions were as follows: “What is your past Chinese score in the college entrance examination?” and “What is your past math score in the college entrance examination?”

2.1.4.4. Tea consumption habits and attitudes scale. Due to the influence of tea drinking behavior on participants’ physical health and psycho- logical aspects, the study conducted by Einöther et al. (2015) only recruited participants who were habitual tea drinkers (those who drank more than 5 cups of tea a week). They believed that positive emotions would be generated when people who were regular tea drinkers drank their favorite drink in the lab, so we also asked the subjects whether they drank tea and used this as a control variable in this study. In addition, studies on caffeine conducted by Cook, Beaven, Kilduff, and Drawer (2012) showed that even when taking a placebo, participants could show the same stimulatory effect as when consuming actual caffeine,

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suggesting that participants’ beliefs about drinks may also affect the effects of drinks on them. Thus, we also measured one’s attitude towards the role of tea because if people believe that drinking tea makes them happier, calmer and more alert, it may also affect whether it actually works for them. We asked three questions that were rated on a 9-point Likert scale (1 = “totally disagree”, 9 = “totally disagree”): “Do you believe in tea as a pick-me-up?” “Do you believe that drinking tea makes people happier? ”, “ Do you think tea makes you calmer?”

2.2. Results

2.2.1. Statistical analysis We used SPSS 22.0 to analyze our data. ANCOVA was used to

determine the main effect of tea on performance in the RAT and the moderating effects of beverage type and tea-drinking habit.

2.2.2. Main effect Descriptive statistics showed that RAT scores were significantly

correlated with gender, and the scores of males were lower than those of females, which were also significantly correlated with age and educa- tional background (see Table 1).

Using ANCOVA controlled for gender, APM scores, education, Chi- nese and math scores on the college entrance examination, age, and drink volume, we found that, consistent with our hypothesis, the par- ticipants in the tea group had significantly higher RAT scores (M = 13.89, SD = 6.00) than those in the water group (M = 12.94, SD = 6.00) [F(1, 34) = 5.09, p = 0.035, η2p = 0.195, observed power = 0.576].

2.2.3. Moderating effects Further analysis showed that there was a marginally significant

interaction between the type of drink (drinking water/drinking tea) and whether or not the participants usually drank tea [F(1, 34) = 4.23, p = 0.052, η2p = 0.168, observed power = 0.501]. Specifically, in the tea group, 14 participants who drank tea at ordinary times had the highest convergent thinking creativity scores (M = 23.20, SD = 3.01), which was much higher than those who did not usually drink tea (M = 13.11, SD = 1.52). The difference between the tea group (M = 11.91, SD = 3.24) and the water group (M = 10.84, SD = 1.84) was relatively small for participants who did not usually drink tea (see Fig. 1).

The main effect of participants’ Raven test scores on RAT scores was significant [F(1, 34) = 6.24, p = 0.021, η2p = 0.229, observed power = 0.664]. The Pearson correlation coefficient between the participants’ Raven test scores and RAT scores was 0.300 (p = 0.060). This is similar to the results of Xiao, Yao, and Qiu’s (2016) research, showing that scores on the Chinese version of the RAT were correlated with the in- telligence levels of the participants.

After controlling for gender, drink volume, attitude towards tea, age, and educational background, MANOVA revealed no significant differ- ences between emotional states reported by the participants in the tea group and in the water group, both immediately after drinking tea and after completing the RAT and Raven tasks.

Finally, similar to previous studies (Huang et al., 2018), this study found the “split half effect”. The scores on the first half (15 questions) and the second half of the RAT were separately scored and then added to the MANOVA model. After controlling for the same variables, we found no significant differences [F(1, 34) = 3.30, p = 0.084, η2p = 0.136, observed power = 0.410] in the RAT scores from the first half between the tea group and the water group. However, with the RAT scores from the second half, the scores of participants in the tea group (M = 8.00, SD = 2.83) were significantly higher than those in the water group (M = 7.35, SD = 2.85) [F(1, 34) = 5.90, p = 0.024, η2p = 0.219, observed power = 0.639], suggesting that tea leads to persistent problem-solving conver- gent thinking. We call this phenomenon the “split half effect”.

2.3. Discussion

The results provide preliminary support for our hypothesis that drinking tea can enhance performance in convergent thinking tasks, and the effect was stronger for people who usually drink tea. This study first demonstrated the role of tea in enhancing convergent thinking. It is worth noting that in both cases, the participants did not drink much tea. Moreover, the participants did not spend much time on the task. That is, even if you drink a limited amount of tea (89.57 ml on average, which is not significantly different from 89.74 ml of water in the water group), tea may still enhance performance in convergent thinking tasks. This result indicated that the tea-drinking event itself (rather than the bio- logical components of tea) played an enhancing role. This conjecture needs to be further evaluated.

However, the results did not show that mood was the mechanism for explaining how drinking tea significantly improved convergent thinking. There are several possible explanations. First, our experiment did not include the tea preparation process that affects emotion (Dohle, Rail, & Siegrist, 2014). Second, unlike previous studies (Einöther et al., 2015, 2016), we did not purposely recruit tea drinkers as participants. We were interested in a more generalized effect of tea consumption on convergent thinking for common people. However, tea was not liked by everyone. Only a few of our participants had tea drinking habits. The four most frequently consumed beverages reported by participants were water, juice, carbonated beverages, and milk tea, all of which were sweet drinks except for water. It has been shown that emotion is related to food and beverage consumption, especially to their sensory proper- ties, e.g., sweet taste is related to happiness and surprise, while bitter taste is related to anger and disgust (Rousmans, Robin, Dittmar, & Vernet-Maury, 2000). Hence, participants who did not have tea- drinking habits and were accustomed to sweet drinks might experi- ence negative emotions caused by a bitter taste and unfamiliar beverage, which may offset any positive emotions elicited by the tea.

We attempted to determine the psychological mechanisms that mediated the performance difference shown by the two groups of par- ticipants within such a short period of time. Therefore, in Experiment 2, we explored other possible mediating mechanisms. In addition, we wanted to confirm whether the result regarding the effects of tea on

Table 1 Descriptive Statistical Results of The Main Variables (Experiment 1).

Mean SD 1 2 3 4 5 6 7 8 9

1 Gender – – 2 Education 2.43 0.50 − 0.10 3 Age 22.93 2.47 − 0.13 0.32* 4 Tea/water 0.48 0.51 − 0.04 − 0.09 0.04 5 Whether to drink tea 1.65 0.48 − 0.22 − 0.09 − 0.07 − 0.14 6 Drinking amount(ml) 89.65 53.15 − 0.26 0.16 − 0.01 0.00 − 0.25 7 RAT score 12.48 6.32 0.34* − 0.11 − 0.02 − 0.02 − 0.17 0.21 8 Raven score 12.53 3.80 − 0.09 − 0.20 0.16 0.16 0.29 − 0.18 0.30 9 Chinese score 121.86 8.52 0.08 0.17 0.23 0.23 − 0.02 0.17 0.27 − 0.07 10 Math score 133.34 11.05 − 0.13 − 0.02 0.10 0.05 0.11 0.23 0.11 0.25 0.07

Note. N = 40. * p < 0.05.

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convergent thinking task performance in Experiment 1 using the RAT to measure convergent thinking creativity could be replicated through other types of creative tasks. Hence, in Experiment 2, we used riddle tasks to measure convergent thinking. With this design, we tested whether the influence of tea on different convergent thinking tasks could be universal.

3. Experiment 2

The research intends to systematically replicate the research in Experiment 1 and determine whether tea can promote performance in other types of convergent thinking tasks. Therefore, we replaced the RAT with riddle tasks in this experiment.

Additionally, we measured participants’ motivation and involve- ment to control for the impact of these factors on convergent thinking performance.

3.1. Method

3.1.1. Participants A total of 60 (19 males) participants were recruited through the

Internet and WeChat. After controlling for the intelligence level of the participants, 59 valid data points were obtained. The participants were full-time undergraduate or graduate students at Peking University, with an average age of 21.82 (SD = 2.47). Each participant received $6 as a reward for participating in the experiment.

3.1.2. Design This experiment included two drink conditions: a cup of black tea

(the brand was Lipton, but the participant was unaware of the brand) and a cup of water, both of which were approximately 260 ml, and the temperature was 42 ◦C. Under both conditions, the amount drank (ml) by the participants was recorded. The participants were randomly assigned to one of two conditions.

3.1.3. Procedure The reception process and precautions were the same as in

Experiment 1. Then, the participants entered another designated room and were guided by another experimenter to complete the experimental task on a computer. The participants completed the emotional mood inventory (MI) scale, riddle task 1, motivation and involvement scale 1, riddle task 2, motivation and involvement scale 2, Raven Advanced Progressive Matrices Test, motivation and involvement scale 2, mood inventory (MI) scale, tea consumption habits and attitude scale, and the final demographic questionnaire (including Chinese and math scores in the college entrance examination). The session lasted 40 min in total.

3.1.4. Measurements The measurements of demographic variables, knowledge level, and

intelligence level of the participants were consistent with the materials used in Experiment 1. The remaining materials were as follows:

3.1.4.1. Chinese riddle tasks. There are two riddle tasks used in this study, taken from Li (2008) research. Riddle task 1 consisted of 10 pairs of medium difficulty riddles (average prototype heuristic rate was 0.58). Riddle task 2 consisted of 10 pairs of high difficulty riddles (average prototype heuristic rate was 0.14). In this experiment, the participants learned the prototype riddles first. The participants were presented with both the question and the answer of the prototype riddles at the same time (“有心记不住, 有眼看不见”, meaning that “you couldn’t remember with a heart and couldn’t see with eyes,” and the answer is “亡”(lost something) (see the Appendix for details). They needed to solve riddle tasks 1 and 2 based on the corresponding method they learned from the prototype riddles. The participants were given 3 min to complete each task, and two riddle tasks together took 6 min.

3.1.4.2. Tea consumption habits and attitude scale. In addition to the items used in Experiment 1, we also added a scale about the participant’s impression of the experimenter. It contained 2 additional items: “What do you think of the receptionist’s enthusiasm level?” and “What do you think of the receptionist happiness level?” (rated on a 9-point Likert scale: 1 was “the lowest” and 9 was “the highest”). We added this scale as an operational test to confirm that the way the participants were treated

Fig. 1. Moderating Effect of Drinking Habit on RAT Scores (Experiment 1).

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would not affect the experimental results.

3.1.4.3. Motivation and involvement scale. Based on Einöther et al. (2016) research, we adapted the motivation and involvement scale. Whenever a participant completed a task, we asked the participant questions about motivation and involvement. There were 5 items in total: “What is your concentration level in the past X minutes?”, “What is your involvement level with the task in the past X minutes?”, “How much happiness did you feel in the past X minutes?”, “How happy have you felt in the past X minutes?”, and “How much stress have you experienced in the past 10 min?” The ratings were scored on a 9-point Likert scale (1 was “the lowest” and 9 was “the highest”).

3.2. Results

3.2.1. Data checks The results of the operation test showed that there were no signifi-

cant differences between the impressions of the experimenters reported by the tea group participants and the water group participants. The descriptive statistics of the main variables are shown in Table 2.

3.2.2. Main effect The participants’ scores on the two riddle tasks were summed to

obtain a total score, which represented the convergent thinking score (see Fig. 2). We found that after controlling for the participants’ Chinese scores, math scores, intelligence levels and tea-drinking habits, the scores of the tea group participants on the riddle task (M = 10.94, SD = 2.86) were significantly higher than those of the water group (M = 9.00, SD = 3.01) [F(1, 58) = 6.27, p = 0.015, η2p = 0.106, observed power = 0.691].

The results (see Table 2) showed that there was a significant positive correlation between the first and second riddle tasks. The Raven scores were significantly positively related to the scores of the two riddle tasks; The type of the drinks influenced the performance of the second part of the riddle task: Participants who drank tea had higher scores in the second riddle task than those who drank water. The math scores on the college entrance examination were significantly positively related to the Raven scores and the Chinese scores on the college entrance examination.

MANOVA showed that participants in the tea group had significantly higher scores (M = 3.41, SD = 1.52) in the second riddle task than those in the water group [F (1, 58) = 5.29, p = 0.025, η2p = 0.091, observed power = 0.617]. The difference between the scores for the tea group participants (M = 7.53, SD = 2.01) and the water group participants (M = 6.59, SD = 2.31) on the medium difficulty riddle task was not sig- nificant [F(1, 58) = 2.95, p = 0.092, η2p = 0.053, observed power = 0.392].

3.2.3. Moderating effects Furthermore, the influence of participants’ level of interest and

involvement in the task was analyzed through ANCOVA. After control- ling for factors such as gender, age, education, milliliters consumed, Raven test scores, Chinese scores, and math scores, it was found that there were no significant differences in the participants’ motivation and involvement in riddle tasks 1 [F (1, 58) = 0.104, p = 0.748] and 2 [F (1, 58) = 0.003, p = 0.956] between the two groups.

Similar to Experiment 1, we did not find a main effect of drinks on emotion either before or after cognitive tasks.

3.3. Discussion

Experiment 2 replicated the results of Experiment 1, suggesting that drinking tea can significantly contribute to convergent thinking. We observed the same effect of drinking tea in two different convergent thinking tasks, including the RAT and riddle task, providing substantial evidence of the consistent positive effect of drinking tea on convergent thinking, especially convergent thinking in semantics.

The results of the research by Einöther et al. (2015) showed that the response time in the tea group was faster than that in the water group (marginally significant), while there were no significant differences in the simple and difficult RAT scores between the two groups. Our research showed that the participants’ level of knowledge and intelli- gence must be controlled for in convergent thinking tasks, and the dif- ficulty level of convergent thinking tasks must also be considered. The results of Experiment 2 showed that the performance in the tea group in the high difficulty riddle task was significantly higher than that in the water group, while in the medium difficulty task, there was only a marginally significant difference between the two groups. This may have been due to a ceiling effect, which means that both groups could do well because the task was relatively easy, and any differences are not likely to be significant. This means that the role of tea drinking was mainly reflected in improved performance in the high difficulty creative tasks. Our research showed that participants’ intelligence level and task difficulty should be taken into more consideration in the design of experiments.

4. General discussion

The purpose of our study was to test whether tea drinking improved convergent thinking and whether emotions mediated this effect. Ex- periments with two different tasks produced similar findings. Experi- ment 1 showed that drinking tea resulted in better performance on the RAT than drinking water. Experiment 2 repeated the results of Experi- ment 1 with a different convergent thinking task (solving riddles) and showed that those who drank tea performed better than those who drank water on difficult riddle tasks. Experiment 2 also found that participants’ knowledge level, intelligence level, and task difficulty had moderating effects on the impact of tea drinking on convergent thinking task performance.

Our study was the first to demonstrate a main effect of tea drinking

Table 2 Descriptive Statistical Results of The Main Variables (Experiment 2).

Mean Var 1 2 3 4 5 6 7 8 9 10

1 Gender – – 2 Education 21.82 2.47 − 0.05 3 Age 2.33 0.51 − 0.30* 0.76** 4 Tea/water 0.47 0.50 − 0.08 0.11 0.07 5 Whether to drink tea 1.62 0.49 − 0.24 − 0.16 − 0.14 0.19 6 Drinking amount(ml) 76.78 56.80 − 0.28* 0.08 0.03 0.00 0.00 7 Riddle1 score 7.07 2.19 − 0.01 − 0.25 − 0.21 − 0.23 − 0.07 − 0.21 8 Riddle2 score 2.95 1.55 0.19 − 0.17 − 0.11 − 0.32* − 0.20 0.03 0.32* 9 Raven score 12.25 2.90 − 0.13 − 0.11 − 0.04 0.02 0.04 0.02 0.34** 0.27* 10 Chinese score 120.03 10.08 0.20 − 0.21 − 0.26 − 0.13 − 0.17 0.04 0.10 0.32* 0.17 11 Math score 132.69 14.19 − 0.19 − 0.31 − 0.19 − 0.01 0.05 0.04 0.22 0.17 0.44** 0.29*

Note. N = 59. * p < 0.05. ** p < 0.01.

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on convergent thinking, which is consistent with Einöther et al. (2016) hypothesis. Although the study by Einöther et al. (2016) did not find a significant effect, the direction of their results was consistent with the hypothesis. Our results may have been due to various reasons, such as consideration of the moderating effects of intelligence level and knowledge level and controlling for variables such as beverage tem- perature and concentration. Our study used more rigorous experimental methods and procedures to demonstrate that tea enhanced convergent thinking, which could be a summary of previous research and guidance for future research.

In particular, there are some interesting and valuable findings in our study. First, we revealed the “split half effect”; that is, tea drinking can significantly help maintain and improve performance in the second half of cognitive tasks. This means that the enhancing effects of tea on convergent creative performance lies in its ability to maintain tenacity and persistence, which implies that drinking tea is beneficial for those who are engaged in creative work or easy to fatigue.

Second, the role of tea drinking was mainly reflected in improved performance in the high difficulty creative tasks. The performance in the tea group in the high difficulty riddle task was significantly better than that in the water group, while in the medium difficulty tasks, there was only a marginally significant difference between the two groups. Our finding explains that an important function of tea is to improve perfor- mance in high-level creative tasks (Canli et al., 2005; Canli et al., 2006) that require high cognitive load.

Third, it was also found that whether a participant had the habit of drinking tea moderated the main effect of tea drinking on convergent thinking, which was consistent with the hypotheses of Einöther et al. (2015) and Einöther et al. (2016). They suggested that people who like drinking tea would show improved positive moods after preparing tea or drinking tea. This result has some implications for us. The habit of drinking tea, if developed on a regular basis, is beneficial in the short

term for everyday creative activities in our daily lives. In the long run, if you are a habitual tea drinker, the next time you need to enhance your creative performance, the beneficial effect of drinking tea will be much higher than those who don’t drink tea regularly.

4.1. Limitations and implications for future research

There are still some limitations in our research. First, we did not measure the biological composition of the tea. The results of Einöther and Martens (2013) showed that two biological components, caffeine and theanine, are beneficial to attention, and attention is an essential part of cognitive function. A cup of tea (250 ml) typically contains 35–61 mg (average: 48 mg) of caffeine and 4.5–22.5 mg (average: 13.5 mg) of theanine. In most previous experiments examining tea’s effects on cognitive performance, the tea contained more than 50 mg of caffeine or 10 mg theanine (Bryan, 2008). In the present experiment, our par- ticipants absorbed relatively small amounts of tea ingredients (most of our participants drank approximately 180 ml of tea, which may contain less than the amount of caffeine and theanine consumed in a typical study.)

Second, there are limitations in our samples. On the one hand, the sample sizes in our studies were relatively small. The sample size was determined by referring to the classical research paradigm in this field. With reference to previous classic studies (Einöther et al., 2015, 2016; Huang et al., 2018), the sample sizes of the two studies in this paper were set at 40 and 60. Further study could enlarge the sample size to replicate the result. On the other hand, knowledge level and intelligence level were important control variables in our research, but our partici- pants’ knowledge level and intelligence level were high. Most partici- pants were undergraduate students at Peking University, a leading university in China, and their intelligence level and knowledge level far exceed the average level. It is worth considering whether our

Fig. 2. Main effect of drinking on the total scores of the two riddle tasks (Experiment 2).

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experimental results can be replicated if our participants had more diverse levels of intelligence and knowledge. However, we assume that the effect may be more significant for people with common levels of knowledge and intelligence because knowledgeable people may not need to drink much tea to solve difficult intellectual tasks.

Third, time between tea intake and testing is short. But after tea intake, participants had to answer some questions about their infor- mation, such as the department, major, grade, student number, and mobile number while drinking tea, which took 3–5 min. Then, the receptionist would lead the participant to room B where the Experi- menter directed the participant to perform the experimental tasks. In room B the participant would complete MI scale first and then, complete the testing of dependent variable. All of the activities will cost 15–20 min which is enough for tea to take effect (Einöther et al., 2015).

In short, drinking tea can enhance performance in creative thinking tasks. Future research should focus on specific mechanisms and clarify which variables moderate the impact of tea consumption on convergent thinking. There are several important research directions for the future.

First, the expansion of ecological validity needs to extend laboratory experiments to actual tea drinking environments as well as to different cultural environments.

The second is the exploration of mediating mechanisms. Previous research has found that people tend to associate tea drinking with a specific set of personality traits, such as smart, creative, elegant, confi- dent, and stable (Lara et al., 2011). It may be that when participants are stimulated by tea, the mental representation of a tea drinker is also activated, and they unconsciously think that they should be smarter and more creative. Another factor worth considering is the level of attention. Previous studies have shown that caffeine and theanine in tea can improve attention (e.g., Hindmarch et al., 2000) and performance in attention tasks and attention plays a very important role in other advanced cognitive processes, especially the creative process (Einöther et al., 2015; Huang et al., 2018).

The third is to explore at what stage of creativity tea takes effect. The American psychologist Runco (2004) suggested that the creative process includes six basic stages. We approximated that the effect of tea on creativity is most likely to occur in the inspiration stage when creative ideas transferred from the preconscious processing into conscious awareness (Kounios & Beeman, 2009). This is a time when ideas explode and require rich attention resources (Burton, 1999). In the future, we can explore the differential impacts of tea consumption at each stage.

Finally, we can explore the long-term and short-term effects. At present, research on tea and creativity has mainly focused on the im- mediate effects of tea. Engagement with these creativity tasks begins after a few minutes of drinking tea (Einöther et al., 2015; Huang et al., 2018). At this time, the pharmacological effects of the tea chemicals have not started to fully work, which shows that it is the psychological effects of tea that is active. Over long periods, will long-term tea drinking also improve performance in creative activities? This notion needs further verification.

5. Ethic Statement

The research was conducted in compliance with all APA Ethical Guidelines for the treatment of human participants. Neither the manu- script nor the data have been published previously, nor are they under consideration for publication elsewhere, and its publication is approved by all authors.

Author Contributions

L.W. conceived the main research idea. L.W. and Y.H. made the research design. Y.H. ran the experiments. Y.H., Y.J., and L.W. per- formed the statistics. Y.J. and L.W. were responsible for making the first English draft of the manuscript. All authors were involved in the manuscript preparation.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This work was supported in part by NSFC Grant #31971013, Beijing Well-being Foundation Grant #0020344, and Taetea Group to L.W.

Appendix:. The description of Chinese riddle task

The riddles are based on the fact that Chinese characters are hiero- glyphics. For example, in the prototype riddle, the Chinese character “忘” means “can’t remember” and “盲” means “blind”, respectively. As you can see, the top half of these two characters is the same character “亡 ”, which means “lost something”. As to the bottom halves, “心” means “heart” and “目” means “eyes”. That is, “忘” means “lost the heart so you can’t remember” while “盲” means “lost eyes so you can’t see.” So when the riddle is asking, “you couldn’t remember with a heart and couldn’t see with eyes, what character is it?” the answer is the character “亡” (“lost something”).

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