EFTA01113830.pdf

BASIC AND APPLIED SOCIAL PSYCHOLOGY. 28(1). 1-16 Copyright 0 2006. Lawrence Erlbaum Associates. Inc. Improved Self-Control: The Benefits of a Regular Program of Academic Study Megan Oaten and Ken Cheng Macquarie University, Sydney Academic examination stress impairs regulatory behavior by consuming self-control strength (Oaten & Chang, 2005). In this study, we tested whether a study intervention program. a form of repeated practice of self-control, could improve regulatory strength and dampen the debili- tating effects of exam stress. We assessed 2 cohorts at baseline and again at the commencement of exams. Without any intervention, we replicated our previous findings of deteriorations in regulatory behaviors at exam time. Students receiving the study program, however, showed sig- nificant improvement in self-regulatory capacity as shown by an enhanced performance on a visual tracking task following a thought-suppression task. During examinations, these partici- pants also reported significant decreases in smoking, alcohol. and caffeine consumption and an increase in healthy eating, emotional control. maintenance of household chores, attendance to commitments, monitoring of spending, and an improvement in study habits. Hence, the study program not only overcame deficits caused by exam stress but actually led to improvements in self-control even during exam time. Self-regulation or self-control (terms used interchangeably Heatherton, & Tice, 1994; Muraven, Tice, & Baumeister, here) can be defined as the capacity to enact control over 1998). The resource model considers self-control to operate one's behavior. Self-control is needed to override dominant like a muscle. Any act of self-control tires this muscle, leav- behaviors that may be self-destructive, irrational, or undesir- ing less available strength for subsequent self-control tasks. able in the long term. Examples of typical self-control prob- This muscle is considered to fatigue easily, as all acts of lems include not exercising enough, engaging in unsafe sex- self-control have been argued to draw on a common resource ual practices, abusing drugs and alcohol, overspending, and or regulatory strength that is of limited capacity and is there- not sticking to study schedules. fore readily depleted. This aspect of the model is well estab- Our goals in this study were to (a) replicate the finding lished, with evidence to suggest that in the short term, peo- that real world stress, specifically academic examinations, ple's capacity for self-control diminishes following exertion consume self-control strength and consequently produce im- much like muscular action. For example, when individuals pairments in a number of unrelated regulatory behaviors were asked to engage in tasks involving self-regulation, the (Oaten & Cheng, 2005a), and (b) test whether the repeated ability to self-regulate in subsequent activities significantly practice of self-control (a study intervention program) could declined (Muraven et al., 1998; Vohs & Heatherton, 2000; improve regulatory strength and make students less vulnera- Vohs & Schmeichel, 2003). This effect of depletion has been ble to the debilitating effects of periods of high academic reported across a variety of tasks in physical, intellectual, and demand. emotional domains. RESOURCE MODEL OF SELF-CONTROL ACADEMIC STRESS AND SELF-CONTROL FAILURE A recent model suggests a lack of self-regulatory resources as one reason why self-regulation might fail (Baumeister, Failures of self-control may be related to experienced stress. A disturbing trend in student health is the reported increase in Correspondence should be addressed to Megan Oaten. Department of student stress internationally (Sax, 1997; Cotton, Dollard, & Psychology. Macquarie University. Sydney. New South Wales. Austra- de Jonge, 2002). Students report experiencing academic lia 2109. E-mail: stress at predictable times each semester, with the greatest EFTA01113830 2 OATEN AND CHENG sources of academic stress resulting from studying for and cost"ofcontrollingstress such that this cost is reflected in are- taking exams, grade competition, and the large amount of duced capacity to regulate task performance following an course content to master in a small amount of time (Archer & external stressor (unpleasant electric shock or unpredictable Lamnin, 1985; Britton & Tesser, 1991; Kohen & Fraser, noise). Glass et al.'s (1969) findings that performance is im- 1986). Examination periods have been used to investigate a paired followingstressors have beenreplicatedmany times us- number of stress responses. A finding that surfaces in these ing measures of frustration tolerance (Glass & Singer, 1972), studies is that many forms of self-regulation break down proofreading (Gardner, 1978; Glass & Singer, 1972), and the when people are managing stress. For example, West and Stroop Task (Glass & Singer, 1972). These tasks all required Lennox (1992) reported that smoking level among students the individual to override a dominant response, thus requiring was higher immediately preceding exams than at a more neu- self-control (Muraven & Baumeister, 2000). It seems that the tral period. Cartwright et al. (2003) revealed that greater aca- work required to control stress leaves the individual less able to demic stress was associated with more fatty food intake, less regulate behavior successfully. Poorer self-control is a conse- fruit and vegetable intake, more snacking, and a reduced like- quence of previous attempts to regulate stress. lihood of daily breakfast consumption. Recent longitudinal research has found that academic examination stress was as- SELF-REGULATORY IMPROVEMENT sociated with increases in cigarette smoking and decreases in physical activity (Steptoe, Wardle, Pollard, Canaan, & Thus, artificial laboratory tasks of self-regulation and having Davies, 19%). to deal with the stress of examination both lead to poorer In a previous study (Oaten & Cheng, 2005a), we tested self-control. These findings support one important aspect of whether at stressful times (during examination periods) peo- the resource model: depletion. In addition, the resource ple fail at self-regulation in domains in which control has pre- model makes a second prediction: Self-control should also viously been successful (e.g., diet). We found that students at become stronger with repeated practice, and such strengthen- exam time reported breakdowns in regulatory behavior that ing may provide a strategy to counter regulatory failure. were not found in a control group. We found this effect inboth a Previous research has found that the repeated practice of laboratory task (Stroop Test; Stroop, 1935) and on a range of self-control was followed by increments in self-control per- self-reported day-to-day behaviors. Performance on the formance (Muraven, Baumeister, & Tice, 1999; Oaten & Stroop Test deteriorated following thought suppression, a Cheng, 2005b; Oaten, Cheng, & Baumeister, 2003). In the form of regulatory activity, during the examination period. study with the longest duration, the uptake and maintenance Outside of the examination period, no such effect due to of an exercise program over a 2-month period produced sig- thought suppression was evident. Exam time also proved det- nificant improvements in a wide range of regulatory behav- rimental to a number of other self-control operations. During iors (Oaten & Cheng, 2005b). Improvements were found in a the examination period, students reported an increase in smok- laboratory task (visual tracking under distraction, which is ing and caffeine consumption; a decrease in healthy dietary used in this study as well) and on many self-reported every- habits, emotional control, frequency and duration of physical day behaviors. The laboratory measure and the self-reported activity, maintenance of household chores and self-care hab- behaviors bore no resemblance to the exercise program other its, attendance to commitments, and monitoring of spending; than that they all involved self-regulation. In particular, indi- and deterioration of sleep patterns and study habits. viduals who participated in the exercise program demon- In light of the resource model of self-control, our interpre- strated better self-regulation in other spheres: related (e.g., tation of the link between exam stress and self-control failure they engaged in more healthy behaviors), unrelated (e.g., is that managing stress requires self-regulation and thus de- missed fewer appointments), and laboratory based (visual pletes limited regulatory resources. An important part of the tracking task WM. body's defenses for coping with stress is the "fight-or-flight" There are two ways in which self-control strength could response. The fight-or-flight response prepares people for be improved. These are consistent with the ways in which physical, emotional, and mental action and is considered es- muscular strength can be increased: power (an increase in the sential for survival (Selye, 1956). These fight-or-flight re- simple baseline capacity) and stamina (a reduction in vulner- sponses, however, can be counterproductive when dealing ability to fatigue). Muraven et al. (1999), Oaten et al. (2003), with the stresses of modem life such as academic examina- and Oaten and Cheng (2005b) found evidence for increased tions (Zillman, 1983).People therefore require self-regulation stamina. The self-regulatory training appears to make people to override these natural responses to substitute other, quite less vulnerable to the effects of resource depletion. unnatural responses (such as studying harder) in their place. Stress regulation may also involve processes that demand inhibition, such as ignoring sensations, overriding negative THIS RESEARCH thoughts, and suppressing emotions (Wegner & Pennebaker, 1993) as well as regulating attention (Hockey, 1984). Glass, In this study, we examined how students fared in the exami- Singer, and Friedman (1%9) found that there is a "psychic nation period after they had been partaking in a regular study EFTA01113831  IMPROVED SELF-CONTROL 3 TABLE 1 Timeline for Study Program Semester I Semester Break Semester 2 Thu Baseline Exams Control Baseline Control Follow-up Baseline Exams Cohort SP SP Cohort 2 WL WL C C SP SP Note. SP = intervention phase (study program): WL = no-intervention phase (waiting list control): C = control phase (non-stressful testing sessions. program. In the experimental design, two cohorts partici- ing tasks that required some form of regulatory exertion— pated in the study intervention program (Table () at different in particular, a thought-regulation task (Oaten & Cheng, times of the academic year. Cohort 1 entered the study inter- 2005b) or emotion regulation (Oaten, Chau, & Cheng, vention program directly; they were tested twice across Se- 2005)—but was unaffected when following tasks that did mester 1 (baseline, exams). Cohort 2 was tested across a time not require self-control (watching humorous videos; Oaten span that included parallel testing sessions to Cohort I during et al., 2005). Thus, this task is sensitive to depletion manip- Semester 1 (waiting-list control). Cohort 2 then entered a ulations but not to nondepleting intervening tasks. In this control phase that included two assessments of self-regula- study, we administered the VTT twice at each session, and tory behavior (baseline, follow-up) during the semester in between V11' testings, participants were told to control break, which provided a neutral period of academic demand. their thoughts by not thinking about a white bear. This is a The control phase tests whether any obtained findings were standard manipulation of regulatory depletion used in past the result of repeated testing and provides measures of retest research (Muraven et al., 1998). Our (Oaten & Cheng, reliability. Finally, Cohort 2 entered the study intervention 2005b) previous research has found that performance on program in Semester 2. the VTT is highly sensitive to an intervening thought-sup- Cigarette smoking, alcohol consumption, and caffeine pression task, performance being worse after 5 min of consumption are some of the behaviors included in this thought suppression. A program of regular physical exer- study. Cigarettes, alcohol, and caffeine are the most widely cise, however, alleviated the adverse effect of the used psychoactive substances in the world (Nehlig, 1999). thought-suppression task on the VTT. We were therefore Despite differing levels of social acceptability, these behav- interested in finding out whether a study intervention pro- iors are all considered addictive (Stepney, 1996) and there- gram would have similar effects. We predicted similar per- fore require some level of regulatory management formance on the VTT before thought suppression in all (Mumford, Neill, & Holtzman, 1988). The other regulatory conditions. After thought suppression, however, perfor- behaviors of interest are diet, physical activity, self-care hab- mance on the V11' should be most impaired in participants its such as household chores, emotional control, study habits, tested at exam time without intervention (waiting-list con- spending habits, and time management. If managing the trol), next most impaired in participants tested during stress of examinations does deplete regulatory resources, and nonstressful times (control), and least impaired in partici- the repeated practice of self-control does improve regulatory pants who had partaken the study intervention program capacity, then we would expect (a) maintenance or even im- (study program). provement in regulatory behavior at exam time for those peo- ple participating in the intervention phase (study program), (b) impairment in regulatory behavior for those people in the METHOD no-intervention phase (waiting-list control) during exam time, and (c) no change in regulatory behavior across the Participants control phase (nonstressful testing sessions). We were also interested in finding out whether academic A total of 45 Macquarie University undergraduates (7 men stress affects self-control performance on a standard labora- and 38 women) recruited from introductory psychology tory task. We used visual tracking under distraction, which courses participated in return for partial fulfillment of a requires participants to perform a computerized VTT while course requirement. The age of participants ranged from 18 a distracter video is played simultaneously at a loud vol- to 51 years, with a mean age of 23 years. ume. The VTT requires participants to track the movement We randomly assigned participants to one of two cohorts of multiple independent targets displayed on a computer (Cohorts 1 and 2). Cohort 1 = 28; 4 men and 24 women) monitor (Pylyshyn & Storm, 1988; Scholl, Pylyshyn, & entered the study intervention phase directly and was indi- Feldman, 2001). The participant must ignore the distracter vidually tested in 2- to 30-min sessions separated by 8-week video content and attend only to the VIT. In a recent set of interim periods. Cohort 2 = 17; 3 men and 14 women) first studies, VTT performance deteriorated only when follow- entered the no-intervention phase (wait-list control) and then EFTA01113832 4 OATEN AND CHENG provided general controls (control phase) before proceeding making participants aware of their own concrete progress, to the study intervention phase and were individually tested which was required to maintain their long-term engagement in 6- to 30-min sessions separated by 8-week interim periods. with the program (Schunk, 1995; Zimmerman, 1989). Study schedule. The study schedule provided a tem- Design poral plan for studying in the lead up to examinations. The Table 1 shows the schedule of testing for the two cohorts. Co- study schedule specified all of the available dates and times hort 1 entered the intervention phase (study program) di- during that specific semester (taking into consideration uni- rectly. We obtained baseline measures for Cohort I in Week 5 versity contact hours and any specified work commitments), of Semester 1, the commencement of the study program, and along with a "suggested" study task designated to a specific then again during the exam period for that semester. Cohort 2 date(s). We administered the study schedule so as to enable entered the no-intervention phase (waiting-list control) in Se- participants to detect and react to any discrepancies resulting mester I with no study program. Parallel to Cohort 1, we ob- from the comparison of their current level of study and final tained baseline measures for Cohort 2 in Week 5 and then study goal state over the course of the semester. Students again during the exam period. Cohort 2 entered the interven- were expected to (a) gradually increase awareness to these tion phase (study program) in Semester 2. We again obtained suggested versus enacted discrepancies and (b) learn to mod- baseline measures in Week 5, at the commencement of the ify their behaviors so as to reduce incongruities, thus enhanc- study program, and then during the exam period. Cohort 2 ing self-regulation and improving performance. also provided general controls by participating in two testing sessions (baseline, follow-up) occurring during nonstressful Study register and study diary. These tools provided times. This served as within-subjects and between-subject opportunities for students to monitor themselves and to gen- control for the effects of the study program. All testing ses- erate the feedback necessary for self-regulation. Self-moni- sions were uniform. Experimental sessions were separated toring refers to the activities involved in observing and re- by 8-week periods. cording one's own behavior (Mace, Belfiore, & Shea, 1989). We tailored study programs to suit each participant's stu- Feedback is generated by a perceived discrepancy between dent workload and included the provision of a study register the outcome state (in this case, the study goal) and the current (log of hours spent studying, which was submitted to us in state regarding the task. This feedback fosters attempts to re- testing sessions), study diary (which was also submitted in duce any disparity by changing plans, tactics, or strategies; experimental sessions), artificial early deadlines, and a study modifying aspects of their goals; or even abandoning the task schedule for the examination period. We give more details (Ruder & Winne, 1995). Participants' utilization of these following. tools was expected to reveal their planning process and their We analyzed each experimental phase (intervention, awareness of various cues while monitoring. no-intervention, and control) separately using a more conser- vative alpha value of .01 for all statistical tests due to re- Manipulation Checks peated analysis of the same participants. We employed the study register and study diaries as manipu- lation checks to ensure that participants were adhering to the Study Program study program. Participants were instructed to bring both their student time- table (i.e., a schedule of class contact hours) and assessment Study register. Average study time was assessed by timetable (due dates for coursework assessments) to the ini- having participants complete a study register (a log of the tial testing session. We discussed with the participants any time spent studying) throughout the no-intervention (wait- work commitments that needed to be incorporated into the ing-list control) and intervention (study program) phases. For study program. analyses, study time was defined as the total number of hours, on average, that participants studied per week. Artificial early deadlines. Self-imposed deadlines are a popular strategy used by many in attempts to curb procrasti- Study diaries. To assess ease of uptake and mainte- nation (Tice & Baumeister, 1997). In fact, recent research nance of the study program, we employed the use of study di- suggested that external deadlines are more effective than aries. As part of their diary logs, participants were asked the self-imposed deadlines in boosting task performance (Ariely following questions: "What level of difficulty, if any, have & Wertenbroch, 2002). We therefore imposed early artificial you experienced complying with the program?"; "Do you deadlines on participants' assessment schedules. The artifi- feel your study habits are improving with the program'?"; and cial deadlines required the breaking down of the distant goal "Do you wish to comment on the program generally?". Par- into several proximal, specific, clear, achievable goals, thus ticipants were instructed to record their progress in the dia- EFTA01113833  IMPROVED SELF-CONTROL 5 ries provided and to return them to the experimenter at each mat. We estimated current cigarette smoking as the number experimental session. of cigarettes smoked over the past 24 hr. We assessed current alcohol consumption using a 7-day recall procedure in which quantity of alcoholic beverage was recorded. We also as- Psychosocial Self-Reports sessed caffeine consumption using a 7-day recall procedure, The GeneralHealth Questionnaire (GHQ; Goldberg, with quantity being the measure of interest. 1972). We assessed emotional distress in all sessions using the 28-item version of the GHQ. This measure assesses Dietary habits. We assessed dietary habits by ques- symptoms of emotional distress in four areas: anxiety/insom- tioning participants about food choice (e.g., "In the last nia, somatic symptoms, social and cognitive dysfunction, week, how successfully did you maintain a healthy diet?") and depression. The questionnaire referred to respondents' and dietary restraint (e.g., "In the last week, how often did experiences over the past week and was coded using a you eat junk food?) over the past week. Response sets were method that assigns weights of 0, 1, 2 and 3 to each answer recorded on a 5-point scale ranging from 0 (never) to 4 (more option. The GHQ has a high degree of internal consistency, than once per day). We derived 2 measures for analysis: junk with a reported Cronbach alpha of .87, and retest reliability food and healthy eating. was reported as .88 (Goldberg, 1972). Physical activity. We measured exercise by question- Perceived Stress Scale (ASS; Cohen, Kamarck, & ing participants about the frequency and duration of physical Mermelstein, 1983). We measured perceived stress in all activity sessions over the past week. Response sets were re- sessions using the 10-item version of the PSS. We used the corded on a 5-point scale ranging from 0 (never) to 4 (more PSS to assess the degree to which situations in life are ap- than once per day). We derived 2 measures for analysis: the praised as stressful. Each item (e.g., "In the last week, how number of episodes of physical activity and the total duration often have you felt that things were going your way?") was of physical activity sessions. assessed on a 5-point scale ranging from 0 (never) to 4 (very often), with higher scores indicating greater stress. The PSS General regulatory behavior. We measured various has been shown to be very useful to assess perceived stress, everyday behaviors that involve self-control (e.g., "In the last with an overall Cronbach alpha of .87, and retest reliability week, how often did you go out with friends instead of study- was reported as .85 (Cohen et al., 1983). This measure has ing?"). We aimed to include those behaviors that do not serve also been used in studies of academic examination stress a stress-relieving function. We recorded response sets on a (Steptoe et al., 1996; Oaten & Cheng, 2005a). 5-point scale ranging from 0 (never) to 4 (more than once per day). We derived nine measures for analysis: self-care habits General Self-Efficacy Scale (GSES; Jerusalem & (laundry habits, leaving dishes in the sink), time management Schwarzer, 1992). We measured self-efficacy in all ses- (keeping appointments and procrastination), study habits sions using the 10-item version of the GSES. Each item (e.g., (spending time with friends instead of studying and watching "It is easy for me to stick to my aims and accomplish my television instead of studying), spending habits (spending goals") was assessed on a 5-point scale ranging from 0 (not at without thinking and overspending), and emotional control all tnte) to 4 (very true), with higher scores indicating higher (loss of temper). perceived self-efficacy. The scale has been used in numerous research projects in which it has typically yielded internal Visual Tracking Under Distraction consistencies between a = .76 and .91. Its stability is satisfac- tory, with retest reliability reported as .75 (Jerusalem & We gave a laboratory task of self-control twice in each test Schwarzer, 1992). session. Participants performed a VTI' while a distracter video played at the same time in the forefront of the partici- pant. We instructed the participant to ignore the distracter Behavioral Self-Reports video content and attend only to the Vff. The VTT requires We designed a questionnaire to assess cigarette smoking, al- participants to visually track the movement of multiple tar- cohol and caffeine consumption, physical activity, dietary gets displayed on a computer monitor (see Figure 1). The habits, and other regulatory behavior. We administered the distracter video included excerpts from a comedy routine by questionnaire in both sessions. The test—retest reliability of Eddie Murphy (Murphy, Tieken, & Wachs, 1983). The use of the questionnaire is reported in the Results. the VTT to assess self-regulatory capacity has been validated in previous research (Oaten and Cheng, 2005b; Oaten, et al., Chemical consumption. We assessed cigarette smok- 2005), and we selected it for that reason. ing, caffeine consumption, and alcohol consumption by the Stimuli were displayed on an I-Mac* computer equipped use of open-ended questions presented in a questionnaire for- with a 15-in. monitor set to a resolution of 800 x 600 pixels EFTA01113834 6 OATEN AND CHENG • • NI MI IN II NI • • U Step 1 Step 2 Step 3 FIGURE 1 A representation of a visual tracking task experimental sequence. Participants view items on computer monitor. In the target identification phase (Step I). six cubes appear on the screen. and three of them Hash briefly to indicate that they are the targets: then all squares move randomly (Step 2). The task of the participant is to select the three targets once they have stopped moving by placing the cursor on them andclicking with the mouse (Step 3). and a refresh rate of 95 Hz. Participants were seated 54 cm sure of self-regulatory performance by administering a sec- away from the monitor. We controlled and measured the VT1' ond VT1'. using Psyscript (Version 4; Bates & D'Oliviero, 2000). Each V11' consisted of 16 trials. At the beginning of each trial, six black squares (20 x 20 mm) were presented in a horizontal Procedure line. After 2 sec, three target items were highlighted with Testing procedure was uniform across sessions. Participants small blinking probes (disappearing and reappearing for five first signed experimental consent forms and we then admin- flashes). Then all items moved in random trajectories for S istered in order a VTT, the thought suppression task, and then sec. After all of the objects stopped moving, the participant a second VT!'. We then obtained measures of emotional dis- had to indicate the three target items using the mouse. The fi- tress, perceived stress, perceived self-efficacy, and general nal mouse click caused the display to disappear, and the par- regulatory behaviors. We conducted data collection between ticipant initiated the next trial with a key press. Tuesday and Friday of each week so that all smoking infor- Forty-eight sets of trajectories (along with target selec- mation related to a weekday. tions) were generated and stored offline. Participants com- pleted a practice trial for which the data were not collected and then completed the experimental trials in a randomized RESULTS order (different for each participant). Overall, 9 (24%) women and 2 (28%) men smoked at some point throughout the testing session; 17 (45%) women and 4 Thought Suppression Task (57%) men consumed caffeine; and 21 (55%) women and 4 (57%) men consumed alcohol. The numbers that engaged in Following the first assessment of self-regulatory perfor- regular physical activity included 32 (84%) women and 7 mance, we administered a thought suppression task to ma- (100%) men. There was no significant difference between nipulate regulatory exertion. The procedure, developed by genders in the proportions carrying out these behaviors and Wegner, Schneider, Carter, and White (1987), requires the no baseline differences between the exam-stress and control participant not to think about a white bear. This task has been groups. We restricted analyses of each behavior to those indi- used previously to manipulate self-regulatory depletion viduals who engaged in these activities rather than the entire (Muraven et al., 1999, 1998). We told participants that over sample. the course of the experiment, they would be asked to perform a cognitive task (thought suppression). We instructed partici- pants to write down all their thoughts on a piece of paper for S Manipulation Checks min, one thought per line, so that we could "see how you use words in naturally occurring sentences" (Muraven et al., Study register. The study register (log of hours spent 1998). We then administered the experimental manipulation. studying) indicated that participants did adhere to the study We instructed participants to list any thoughts that came to program. Figure 2 summarizes the mean hours spent study- mind with the caution that they should avoid thinking about a ing. Cohort 2 was the only cohort to participate in the no-in- white bear. We told participants that whenever they thought tervention phase (waiting-list control) and was therefore the of a white bear, they were to write that thought down. We em- only cohort included in the following analyses. The reported phasized that it was critical to change their thoughts immedi- average number of hours spent studying were entered into a ately and to try not to think of a white bear again. Following session (baseline, exams) repeated measures analysis of vari- the thought suppression task, we recorded a follow-up mea- ance (ANOVA). The ANOVA showed no effect of session EFTA01113835  IMPROVED SELF-CONTROL 7 Hours studying per week Study Habits Visual Tracking Task 25 40 20 35 5 30 10 - 25 20 5- 0 I IS 10 study time S 0 ■baseline: no intervention CI CXIIIIIS: no intervention baseline: no exams: no baseline: mama lIbaseline: intervention Sextons: intervention intervention intervention intervention intervention FIGURE 2 Reported average number of hours spent studying per la pre Moil& suppression epees thought inippressien week (mean ± standard error) across the testing sessions. FIGURE 3 Error rate on the visual tracking task (meant standard error) measured before and after the thought suppression task across across the no•intervention phase. Both cohorts participated sessions. in the intervention phase (study program) and we included them in the analyses. The reported average number of hours across sessions, with less depletion during the examination spent studying were entered into a session (baseline, exams) period following participation in the study program. These repeated measures ANOVA. The ANOVA found a significant impressions were confirmed by a Session (Baseline, Exams) main effect for session, F(1, 44) = 24.58, p< .001. These re- x Time (before thought suppression vs. after thought sup- sults suggest that although on average, participants' spent 11 pression) repeated measures ANOVA. With the ANOVA, we hr per week studying, study time increased to an average of found significant main effects for time, F(I, 44) = 2395.40, p 22 hr per week during the intervention phase (study pro- < .001, indicating a general tendency toward depletion fol- gram). lowing a previous self-regulatory act; a significant main ef- fect for session, F(I, 44) = 79.96,p < .001, suggesting that vi- Study diaries. All study diaries were returned to us as sual tracking performance improved across sessions; and a instructed. An inspection of the diaries indicated that all par- significant Time x Session interaction, F(1, 44) = 359.98, p< ticipants recorded progress on the study program as in- .001. The pattern of results indicates that the study program structed. Accordingly, the diary content suggested a roughly improved regulatory stamina, increasing resistance to the de- equal expenditure of effort from all participants. bilitating effects of a manipulation of regulatory depletion (a Entries from the study diaries indicate that the study pro- thought suppression task). gram required ongoing regulatory effort. For example, some participant comments include the following: "My studying is Behavioral sett-reports. Figures 4 through 10 (black improving but it is a constant struggle ... especially when ev- and striped bars) show the reported changes in regulatory be- eryone is watching TV ... I want to join them so bad"; "In or- haviors across the intervention phase (study program). Both der to stick to the program I have to get out of bed an hour cohorts participated in the intervention phase and were in- earlier so I can get the study hours in ... some mornings it is cluded in the analyses. We entered the data in Figures 4 so hard to get up ... I'd much prefer to lie in"; and "Studying through 10 into a repeated measures ANOVA, with Session at uni isn't so bad as everyone is pretty much doing the same (Baseline, Exams) as the within-subjects variable. We re- thing ... but when I get home and my flatmates are heading stricted analyses of each behavior to those individuals who out to the pub ... it is so hard not to go with them ... so far engaged in these activities rather than the entire sample. Ta- I've managed to stay strong and stick to the planned study- ble 2 summarizes the main effects of session. ing:' The comments suggest that the academic study pro- As predicted, people seemed better able to control their gram required self-control. behavior during the exam period following the intervention phase (study program). In fact, all of the behaviors showed changes in the predicted direction. Figure 4 shows a reported Study Intervention Phase decrease in chemical consumption during examinations for V77: Figure 3 summarizes (striped bars) performance those people in the study program. Smoking decreased by a on the VTT across the intervention phase (study program). mean of 7 cigarettes per day, caffeine consumption decreased Both cohorts participated in the intervention phase and were on average by 2 cups per week, and alcohol decreased on av- included in the analyses. The thought suppression task erage by 2 drinks per week. Figure 5 shows changes in di- caused deterioration in performance at baseline (depletion). etary trends across sessions. Dietary patterns improved for This effect of depletion, however, appeared to attenuate those participants in the study program, with decreased junk EFTA01113836  Consumption Patterns Self-can Habib 2 leaving dishes leafing laundry alcohol cigarettes caffeine Ohneline: no Lawn...ono° Denims! no tatelvention Obasebne: intervention intenention lebaseline no nenration Oceans no inienen000 • buekne ententotieo •e :Nis': unentonon FIGURE 7 Self-care habits across sessions (mean ± standard e