TL;DR. The split between active recovery (light movement or an engaging activity) and passive recovery (rest, screens, doing nothing) comes from sports science, and even there the active option is weaker than its reputation: a 2018 review judged the active cool-down “largely ineffective” for later performance. For desk workers, the best diary evidence says both kinds work. In Sabine Sonnentag’s five-day study of 100 teachers, low-effort activities such as watching TV had the largest coefficient for bedtime well-being (0.171), physical activities came close (0.154), social activities were positive but smaller (0.069), and work done at home was negative (-0.107). A CEOtudent analysis of the 2025 American Time Use Survey shows where US full-time workers put their weekday leisure: 49.2% to TV, 19.4% to active categories, and 8.3%, about 16 minutes, to exercise. The useful question is not “active or passive?” but “which tank is empty?” CEO move: treat the evening as a scarce resource, pick the recovery that matches what the day depleted, and put it on the calendar. Student move: run a one-week experiment that alternates matched active and passive evenings, and keep only what moves next-morning energy.
This guide sits between the cluster’s recovery protocol, which sets the structure of rest from the hour to the season, and the guide to strategic napping, which handles the midday reset. If work keeps running in your head after hours, start with the shutdown ritual.
Where does the active vs. passive split come from, and does it hold up in sport?
In sports science, active recovery means low- to moderate-intensity movement after hard training, usually called an active cool-down; passive recovery means stopping and resting. Bas Van Hooren and Jonathan Peake’s 2018 review describes the common practice as 5 to 15 minutes of low- to moderate-intensity exercise within about an hour of training or competition. Their verdict: an active cool-down is “largely ineffective” at improving same-day and next-day sports performance, and most evidence shows no significant benefit for muscle soreness or measures of psychological recovery, although it “may nevertheless offer some benefits” over a passive one.
A 2018 meta-analysis of 99 studies by Olivier Dupuy and colleagues sharpens this. Active recovery reduced delayed-onset muscle soreness (standardized mean difference -0.94), but its effect on perceived fatigue was not significant (0.64, confidence interval -0.43 to 1.70).
Two lessons carry over to desk work: “active” is not automatically better, even where the term was coined, and the payoff depends on which system was taxed.
For desk workers, active recovery means engaging the body or other people: a walk, a workout, dinner with friends. Passive recovery means low-effort activity: television, a bath, light reading. Sonnentag used almost these exact labels in her 2001 diary study, calling social and physical activities “more active recovery activities” and low-effort activities “more passive activities”.
How do full-time workers actually spend their leisure time?
The American Time Use Survey (ATUS), published by the US Bureau of Labor Statistics (BLS), is the official record of how Americans spend a day. The 2025 results, released on 25 June 2026, rest on about 6,100 interviews. The survey codes one main activity at a time, so scrolling a phone while the TV is on is recorded as TV. Interviews stopped during the federal shutdown, so there are no diaries for 30 September to 11 November 2025; BLS reweighted the rest of the quarter and states that the effect cannot be quantified.
ATUS has no “knowledge worker” category. Table 1 uses full-time workers and splits weekdays from weekends, because weekday evenings are where most recovery choices get made.
Table 1. How US full-time workers spend leisure time, 2025
| ATUS leisure category | Weekday hours | Weekday minutes | Share of weekday leisure | Weekend hours | Share of weekend leisure |
|---|---|---|---|---|---|
| Watching TV | 1.55 | 93 | 49.2% | 2.78 | 46.8% |
| Playing games and computer use for leisure | 0.38 | 23 | 12.1% | 0.70 | 11.8% |
| Socializing and communicating | 0.35 | 21 | 11.1% | 0.96 | 16.2% |
| Participating in sports, exercise and recreation | 0.26 | 16 | 8.3% | 0.36 | 6.1% |
| Relaxing/thinking | 0.24 | 14 | 7.6% | 0.35 | 5.9% |
| Other leisure, including related travel | 0.22 | 13 | 7.0% | 0.57 | 9.6% |
| Reading | 0.16 | 10 | 5.1% | 0.22 | 3.7% |
| Total leisure and sports | 3.15 | 189 | – | 5.94 | – |
CEOtudent analysis of BLS American Time Use Survey 2025, Table 11B (full-time workers, hours per day as published). Shares are of the published total; weekday components add to 3.16 hours because of rounding.
Television is half of it. Full-time workers watch 1.55 hours of TV on an average weekday, 49.2% of their leisure, in line with the BLS headline for the whole population: TV took 2.6 of 5.2 leisure hours, “half of all leisure time”.
Exercise is about 16 minutes on a weekday for full-time workers, and the average hides a split. Across everyone aged 15 and over, only 25.1% did any sport, exercise or recreation on an average weekday, and those who did averaged 1.35 hours. Most people do none; a minority do a lot.
Social time is a weekend activity, and it is shrinking. Full-time workers socialize for 0.35 hours on weekdays and 0.96 at weekends. Across the population, the share of people socializing on an average day fell from 38% in 2015 to 30% in 2025, and time fell from 41 to 35 minutes, while games and leisure computer use, which includes social media, rose from 25 to 37 minutes.
Do the groups closest to knowledge work look different? Barely.
Table 2. Weekday leisure mix in three groups that overlap with knowledge work, 2025
| Measure | Full-time workers | Bachelor’s degree or higher (age 25+) | Top earnings quarter ($2,021+ a week) |
|---|---|---|---|
| Weekday leisure, hours | 3.15 | 3.97 | 2.90 |
| Watching TV, share | 49.2% | 47.6% | 50.0% |
| Exercise, share | 8.3% | 9.3% | 11.0% |
| Active (exercise plus socializing), share | 19.4% | 20.7% | 21.4% |
| Passive low-effort (TV, relaxing, reading), share | 61.9% | 61.2% | 61.4% |
| Hours of TV per hour of exercise | 6.0 | 5.1 | 4.5 |
CEOtudent analysis of BLS ATUS 2025, Table 11B, weekday columns. The bachelor’s group includes people who are not employed; the earnings quarter covers full-time wage and salary workers with one job.
In every group, about three-fifths of weekday leisure is passive and one-fifth is active. The best-paid quarter has the least weekday leisure of the three (2.90 hours) and a larger exercise share, yet still gives half of it to TV.
What does the research say about each kind of recovery?
Recovery research rarely tests TV against a run head to head; Table 3 lists the diary, panel and lab results used here, as printed.
Table 3. What the recovery studies printed
| Study and design | Activity or measure | Printed result | Reading |
|---|---|---|---|
| Sonnentag (2001): 5-day diary, 100 Dutch teachers; outcome is well-being before sleep | Low-effort (for example TV, a bath) | 0.171 (SE 0.039, t = 4.385, p < .01) | Largest of five categories |
| Same | Physical (for example sports, cycling, dancing) | 0.154 (SE 0.062, t = 2.484, p < .05) | Positive |
| Same | Social (for example meeting others, a phone chat) | 0.069 (SE 0.032, t = 2.156, p < .05) | Positive, smallest |
| Same | Household and child care | 0.049 (SE 0.043, t = 1.140) | Not significant |
| Same | Work-related activities at home | -0.107 (SE 0.031, t = -3.452, p < .01) | Negative |
| de Jonge, Shimazu and Dollard (2018): two waves two years apart, 230 health care employees | Low-effort and cognitive detachment | beta = 0.18 (p < .05) at one point; -0.02 (n.s.) over two years | Short-term only |
| Same | Physical activity and sleep quality two years later | beta = -0.16 (p < .01) | Against the authors’ hypothesis |
| Same | Work-related off-job activities and cognitive detachment | beta = -0.26 (p < .01); -0.24 (p < .001) over two years | The only stable finding |
| Chang, Labban, Gapin and Etnier (2012): meta-analysis, 79 studies, 1,034 effect sizes, 2,072 subjects | One bout of exercise and cognitive performance | g = 0.097 | Positive, small |
| Chang and colleagues (2025): meta-review of 30 meta-analyses, 383 studies, 18,347 participants (abstract only) | One bout of exercise and cognitive function | Mean SMD = 0.33 (95% CI 0.24 to 0.42); attention 0.37 | Small to medium |
| Kang and Kurtzberg (2019): lab experiment, 414 students | Same break task on a phone vs. paper or computer | 6.38 vs. 8.13 anagrams solved afterwards; 5.32 with no break | Phone break restored less |
Figures as printed. Sonnentag coefficients are from Table 2, Model 3, checked against the scanned page image.
Both kinds of evening worked in the diary data. With end-of-day mood, demographics and job conditions controlled, Sonnentag found that low-effort, social and physical activities each predicted better bedtime well-being, and work done at home predicted worse. Her conclusion: “both types of activities have beneficial effects.” Evenings spread across more activity categories were linked with higher well-being, and active activities did not amplify the passive ones; the benefits simply sat side by side. The limits: one profession, broad categories, self-report, data now 25 years old.
Next-morning vigor follows the same pattern. In Lieke ten Brummelhuis and Arnold Bakker’s diary study of 74 employees (356 data points; abstract only), social, low-effort and physical activities raised next-morning vigor through more detachment and relaxation, while work and household tasks lowered it. Feuerhahn, Sonnentag and Woll’s study of 126 workers (abstract only) linked exercise after work to more positive evening affect, but not to less negative affect.
Over two years, most of it washes out. In the de Jonge panel, low-effort activities went with better cognitive detachment at one point but not two years later; only off-job work held up, as a negative. More physical activity went with lower sleep quality two years on, contrary to the authors’ hypotheses, but the survey asked about average hours after a shift, not time of day.
Exercise has the best experimental evidence for thinking, and timing matters. Yu Kai Chang and colleagues’ 2012 meta-analysis found a small positive effect of one bout of exercise on cognitive performance (g = 0.097). Tests taken 0 to 10 minutes after exercise showed negative effects, the largest benefits appeared after an 11 to 20 minute delay, sessions longer than 11 minutes produced positive effects, and immediately after exercise only very light, light or moderate intensity helped. A 2025 meta-review by the same group (abstract only) puts the average effect at 0.33, but reports that intensity, type and duration did not moderate it, so treat the 2012 timing details as sensible defaults, not laws.
Screens split in two. Television behaved like any low-effort activity. Interactive screens are less clear. In Sanghoon Kang and Terri Kurtzberg’s experiment, students who did a shopping-list break task on a phone then solved 6.38 anagrams, against 8.13 after the same task on paper or a computer, about 21.5% fewer, though more than the 5.32 solved with no break. It is one lab study with students. On the other side, survey studies summarized by Leonard Reinecke and Diana Rieger link entertaining video games to all four recovery experiences.
Guilt can cancel the benefit of passive recovery. The same review summarizes Reinecke, Hartmann and Eden’s 2014 “guilty couch potato” studies: people with depleted self-control were more likely to see their media use as procrastination, felt more guilt, and benefited less from media-induced recovery, though they needed it more.
Nature adds a modest attention benefit. Matthew Stevenson, Theresa Schilhab and Peter Bentsen’s 2018 review (abstract only) found that working memory, cognitive flexibility and, less reliably, attentional control improved after exposure to natural environments, with low to moderate effect sizes.
The label matters less than the experience it produces. Andrew Bennett, Arnold Bakker and James Field’s meta-analysis (299 effect sizes, 54 samples, N = 26,592; abstract only) found detachment more strongly linked to lower fatigue than relaxation or control, and control experiences more strongly linked to vigor than detachment or relaxation. Laurens Steed and colleagues (198 samples; abstract only) reported that effects “differed markedly” depending on whether recovery was measured as activities, experiences or states. An activity restores you to the extent that it produces detachment, relaxation, mastery or control, the four experiences covered in the recovery protocol guide linked above.
Where does leisure time go, compared with where the evidence points?
Table 4 joins the two datasets: the ATUS share of weekday leisure for full-time workers, and what the opened studies say about the closest research category.
Table 4. Leisure time against recovery evidence
| ATUS category | Weekday share | Sports-science label | Direction of evidence | Confidence |
|---|---|---|---|---|
| Watching TV | 49.2% | Passive | Positive for bedtime well-being and next-morning vigor; short-term link with detachment; weaker with guilt | Moderate (diary, panel; self-report) |
| Games and computer use, incl. social media | 12.1% | Mixed | Games linked with recovery experiences in surveys; phone breaks restored less in one lab study | Weak, conflicting |
| Socializing and communicating | 11.1% | Active, social | Positive but smallest diary coefficient; next-morning vigor; null over two years | Low to moderate |
| Sports, exercise and recreation | 8.3% | Active, physical | Positive for evening mood and vigor; small to medium cognitive gain; one panel links it with lower later sleep quality | Moderate; experimental for cognition |
| Relaxing/thinking | 7.6% | Passive | Helps when it is relaxation; thinking about work works against detachment | Indirect |
| Other leisure, incl. travel | 7.0% | Unclassified | Not assessed | None |
| Reading | 5.1% | Passive body, engaged mind | Grouped with TV as low-effort by de Jonge and colleagues; no separate estimate | Indirect |
CEOtudent analysis of BLS ATUS 2025 (Table 11B) joined with the studies in Table 3, ten Brummelhuis and Bakker (2012), Feuerhahn, Sonnentag and Woll (2014), Reinecke and Rieger (preprint) and Stevenson, Schilhab and Bentsen (2018). The confidence grade is an editorial judgment.
The biggest block is not a failure. The diary evidence does not support guilt about TV; guilt is part of what blunts its benefit. The leverage is quality: a chosen programme with an end point, not a default stream with a laptop open.
The smallest blocks carry the most specific benefits. Exercise is the only ATUS category here backed by meta-analyses of experiments showing a cognitive benefit, and it gets about 16 minutes on a weekday. As an illustrative assumption, moving 20 minutes a day from TV to a walk would multiply weekday movement time by 2.3, raise the active share from 19.4% to 29.9%, and still leave TV at 38.6% of leisure.
The fastest-growing block has the weakest case. Games and leisure computer use grew 48% across the population between 2015 and 2025, and the one lab result on phone breaks points the wrong way.
Why is passive recovery not the enemy?
Sonnentag wrote that her low-effort finding “questions the assumption about the negative impact” of passive leisure, and sports science says the same from the other side. The real enemies are elsewhere. The first is evening work: negative in Sonnentag’s diaries and the only stable predictor of poor detachment in the de Jonge panel. The second is unchosen screen drift. The third is the workload itself: time pressure at work predicted lower bedtime well-being (-0.308, t = -3.208) even after the evening’s activities were accounted for. If every evening fails, read the guide to burnout as a systems failure before redesigning your leisure again.
The CEOtudent Recovery Match: which recovery for which depletion?
Recovery is specific: what helps soreness may not help fatigue. Desk work drains at least four capacities, plus one failure mode that no activity fixes. Name the empty tank before choosing the evening.
Table 5. The CEOtudent Recovery Match
| What is depleted | How it shows up at 6 p.m. | First-choice recovery | Mode | Evidence anchor | Watch out for |
|---|---|---|---|---|---|
| Attention | Rereading the same line, avoiding small decisions | An easy to moderate walk of more than 11 minutes, outdoors if possible; or quiet rest without a screen | Active-light | Exercise bouts help attention (Chang 2012, 2025); nature helps working memory (Stevenson 2018) | Phone breaks; hard intensity right before thinking work |
| Body | Stiff back, restlessness after a day of sitting | Movement you enjoy: walk, cycle, gym, dancing | Active-physical | Physical activity predicted better bedtime well-being and positive affect (Sonnentag 2001; Feuerhahn 2014) | If sleep worsens, move the session earlier |
| People, over-exposed | Drained after calls, conflict or client work | Low-effort solitude chosen in advance: a series, a bath, a novel | Passive | Largest diary coefficient (Sonnentag 2001) | Guilt and second screens |
| People, isolated | Flat after a solo day of focused work | One real conversation or shared activity | Active-social | Social activity predicted well-being and vigor (Sonnentag 2001; ten Brummelhuis and Bakker 2012) | Feeds standing in for contact |
| Drive | Boredom, a sense that the day’s work did not matter | A mastery or control activity: a skill hobby, a moderately hard game, a sport with a goal | Active-engaging | Control experiences were more strongly linked with vigor than detachment or relaxation (Bennett and colleagues 2018) | More passive hours, which do not target vigor |
| Work still running | Replaying meetings, checking email again | Close the workday first, then choose a tank | A boundary | Off-job work was negative in both Sonnentag and de Jonge | Calling any leisure recovery while work stays open |
CEOtudent editorial framework. The anchors are associations and lab effects; the matching logic is an editorial inference, not a tested intervention.
The CEO reading is resource allocation: about 3.15 weekday leisure hours, spent by diagnosis rather than by default, and protected like a client meeting. For attention, the cognitive load budget shows how to stop overspending before the evening starts.
What does a practical break and evening menu look like?
For where to place breaks in the workday, see ultradian rhythms; the micro-break meta-analysis is in the energy audit guide.
Table 6. Recovery menu by depleted tank and time available
| Depleted | 5-minute break | 15 to 20-minute break | Evening block (60 to 90 minutes) |
|---|---|---|---|
| Attention | Look out of a window, phone face down | Easy walk outside; start the next hard task 11 to 20 minutes after you stop moving | An early walk or light workout, then low-effort time |
| Body | Stairs, a stretch, a lap of the building | Brisk walk or mobility routine | Training, sport, cycling or dancing |
| People, over-exposed | Sit alone with the door closed | A solo walk with no calls | A chosen episode, bath or novel, stop time set in advance |
| People, isolated | Call a colleague instead of messaging | Coffee or lunch with someone | Dinner, a class or a team sport |
| Drive | Two minutes of a non-work skill | A puzzle or game you are improving at | A hobby with visible progress |
CEOtudent editorial framework. Durations are editorial suggestions; the 11-minute and 11 to 20 minute figures come from Chang and colleagues (2012).
How do you find out what restores you? A one-week experiment
The studies describe averages, so test the Match on yourself: each day, rate energy at bedtime, vigor the next morning and sleep quality, each from 1 to 5.
Table 7. The one-week recovery experiment
| Day | Evening assignment | What to log |
|---|---|---|
| Monday | Baseline: your usual evening | Lowest tank at the end of work; the three ratings |
| Tuesday | Baseline again | The three ratings |
| Wednesday | Matched active recovery from Table 5, at least 30 minutes | Ratings, activity, start time |
| Thursday | Matched passive recovery, chosen in advance, with a stop time and no second screen | Ratings, and whether you felt guilty |
| Friday | Repeat whichever of Wednesday or Thursday scored higher on next-morning vigor | Ratings |
| Saturday | A longer active block, outdoors or with people | Ratings |
| Sunday | A deliberate, guilt-free low-effort block | Ratings, then review the week |
CEOtudent editorial framework. The scales and rules are editorial conventions, not validated instruments.
Four rules keep it honest:
- Judge by next-morning vigor, not bedtime mood, which flatters whatever you just did.
- Keep a change only if it beats both baseline days by at least one point on two or more mornings. One good morning is noise.
- If sleep quality drops after active evenings, move the activity earlier rather than dropping it.
- If nothing moves the numbers, the problem is load, not leisure. If you use a wearable, check which wearable metrics actually mean anything before trusting a readiness score over your own ratings.
The CEO move at the end of the week is to book the winning evening as a recurring calendar block. The Student move is to write the next hypothesis down before testing it, for example “on attention-drained days, a walk beats TV on next-morning vigor”, and run the week again in a month.
What this does not mean
- More passive time is not always better. The diary studies looked at ordinary evenings, not at how much is too much.
- Exercise is not compulsory recovery. Effects are small to medium, measured by self-report for mood and lab tasks for cognition.
- Cause is not established. People may choose activities based on how they already feel; Sonnentag controlled for end-of-day well-being, which helps but does not settle it.
- ATUS does not describe knowledge workers precisely. Tables 1 and 2 use proxies, count primary activities only, cover the United States, and miss six weeks of 2025.
- Sports science does not transfer directly. Muscle soreness is not mental fatigue; the active vs. passive split is borrowed as a frame, not as evidence.
- The samples are narrow: 100 teachers in 2001, 230 health care employees, 414 students.
This article summarizes research findings for general information. It is not medical advice, and anyone whose health limits exercise or affects sleep should follow a clinician’s guidance.
Frequently asked questions
Is watching TV after work bad for recovery?
Not according to the diary evidence. In Sonnentag’s study, low-effort activities such as TV had the largest positive coefficient for bedtime well-being. The benefit appears smaller when viewing brings guilt.
Is active recovery better than passive recovery?
Neither wins overall. Both predicted better well-being in diary studies, and even in sport an active cool-down was judged “largely ineffective” for later performance. Match the mode to what is depleted.
How long should a walk be to help focus?
In Chang and colleagues’ 2012 meta-analysis, sessions longer than 11 minutes produced positive effects on later cognitive tests, the largest benefits appeared 11 to 20 minutes after exercise ended, and tests in the first 10 minutes showed negative effects.
Does scrolling a phone count as a break?
It counts, but in one lab experiment it restored less: students solved 6.38 anagrams after a phone break, against 8.13 after the same break on paper or a computer.
Should evening exercise stop if sleep suffers?
One two-year panel linked more off-job physical activity with lower later sleep quality, but did not record time of day. Log sleep and move sessions earlier before dropping them.
How much leisure time do full-time workers actually have?
In the 2025 American Time Use Survey, 3.15 hours on weekdays and 5.94 hours on weekend days and holidays, roughly half of it spent watching TV.
Sources
- US Bureau of Labor Statistics (2026). American Time Use Survey: 2025 Results. News release USDL-26-1022, 25 June 2026, with Tables 1, 2, 11A and 11B and the Technical Note.
- Sonnentag, S. (2001). Work, recovery activities, and individual well-being: A diary study. Journal of Occupational Health Psychology, 6(3), 196-210. Scanned author copy, University of Konstanz repository.
- de Jonge, J., Shimazu, A., and Dollard, M. (2018). Short-term and long-term effects of off-job activities on recovery and sleep: A two-wave panel study among health care employees. International Journal of Environmental Research and Public Health, 15(9), 2044.
- ten Brummelhuis, L. L., and Bakker, A. B. (2012). Staying engaged during the week: The effect of off-job activities on next day work engagement. Journal of Occupational Health Psychology, 17(4), 445-455 (abstract only).
- Feuerhahn, N., Sonnentag, S., and Woll, A. (2014). Exercise after work, psychological mediators, and affect: A day-level study. European Journal of Work and Organizational Psychology, 23(1), 62-79 (abstract only).
- Bennett, A. A., Bakker, A. B., and Field, J. G. (2018). Recovery from work-related effort: A meta-analysis. Journal of Organizational Behavior, 39(3), 262-275 (abstract only).
- Steed, L. B., Swider, B. W., Keem, S., and Liu, J. T. (2019). Leaving work at work: A meta-analysis on employee recovery from work. Journal of Management (abstract only).
- Chang, Y. K., Labban, J. D., Gapin, J. I., and Etnier, J. L. (2012). The effects of acute exercise on cognitive performance: A meta-analysis. Brain Research, 1453, 87-101.
- Chang, Y. K., Ren, F. F., Li, R. H., Ai, J. Y., Kao, S. C., and Etnier, J. L. (2025). Effects of acute exercise on cognitive function: A meta-review of 30 systematic reviews with meta-analyses. Psychological Bulletin, 151(2), 240-259 (abstract only).
- Kang, S., and Kurtzberg, T. R. (2019). Reach for your cell phone at your own risk: The cognitive costs of media choice for breaks. Journal of Behavioral Addictions, 8(3), 395-403.
- Reinecke, L., and Rieger, D. Media entertainment as a self-regulatory resource: The Recovery and Resilience in Entertaining Media Use (R2EM) model. Preprint (2020) of a chapter accepted for The Oxford Handbook of Entertainment Theory. Used for its summary of Reinecke, Hartmann and Eden (2014) and of survey studies on video games.
- Stevenson, M. P., Schilhab, T., and Bentsen, P. (2018). Attention Restoration Theory II: A systematic review to clarify attention processes affected by exposure to natural environments. Journal of Toxicology and Environmental Health, Part B, 21(4) (abstract only).
- Dupuy, O., Douzi, W., Theurot, D., Bosquet, L., and Dugué, B. (2018). An evidence-based approach for choosing post-exercise recovery techniques to reduce markers of muscle damage, soreness, fatigue, and inflammation: A systematic review with meta-analysis. Frontiers in Physiology, 9, 403.
- Van Hooren, B., and Peake, J. M. (2018). Do we need a cool-down after exercise? A narrative review of the psychophysiological effects and the effects on performance, injuries and the long-term adaptive response. Sports Medicine, 48(7), 1575-1595.
Tables 1, 2 and 4 are CEOtudent analyses of the BLS American Time Use Survey 2025 (Table 11B), with Table 4 joined to the studies listed above; Tables 5, 6 and 7 are CEOtudent editorial frameworks; Table 3 reports figures as printed. The 20-minute TV-to-walk swap is an illustrative assumption. Some summaries describe Chang and colleagues’ 2012 meta-analysis as covering 1,034 participants; the paper reports 1,034 effect sizes from 2,072 subjects. Pooled effect sizes from Steed and colleagues and from Stevenson and colleagues were not used because only their abstracts were accessible, and a widely cited lunchtime park-walk field study was left out because no open copy could be retrieved.
This content was compiled with the support of AI following in-depth research, then written and prepared for publication by the CEOtudent editorial team.
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