PLoS ONE plos plosone PLOS ONE 1932-6203 Public Library of Science San Francisco, CA USA 10.1371/journal.pone.0272460 PONE-D-22-07400 Research Article Research and analysis methodsMathematical and statistical techniquesStatistical methodsMetaanalysis Physical sciencesMathematicsStatisticsStatistical methodsMetaanalysis Medicine and health sciencesClinical medicineSigns and symptomsFatigue Biology and life sciencesNeuroscienceCognitive scienceCognitive psychologyAttention Biology and life sciencesPsychologyCognitive psychologyAttention Social sciencesPsychologyCognitive psychologyAttention Biology and life sciencesPsychologyEmotions Social sciencesPsychologyEmotions Biology and life sciencesPsychologyRelaxation (psychology) Social sciencesPsychologyRelaxation (psychology) Social sciencesEconomicsLabor economicsEmployment Science policyResearch integrityPublication ethics Research and analysis methodsDatabase and informatics methodsDatabase searching "Give me a break!" A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance Efficacy of micro-breaks https://orcid.org/0000-0003-4949-7292 Albulescu Patricia Conceptualization Methodology Writing – original draft Writing – review & editing https://orcid.org/0000-0002-9878-8136 Macsinga Irina Resources Visualization Writing – review & editing * Rusu Andrei Data curation Formal analysis Methodology Resources Software Supervision Writing – review & editing Sulea Coralia Conceptualization Resources Supervision Visualization Writing – review & editing Bodnaru Alexandra Data curation Formal analysis Methodology Visualization Writing – review & editing https://orcid.org/0000-0001-8101-1753 Tulbure Bogdan Tudor Project administration Resources Supervision Visualization Writing – review & editing Department of Psychology, West University of Timișoara, Timișoara, Romania Steinborn Michael B. Editor Julius-Maximilians-Universität Würzburg, GERMANY

The authors have declared that no competing interests exist.

 * E-mail: irina.macsinga@e-uvt.ro 31 8 2022 2022 17 8 e0272460 12 3 2022 19 7 2022 2022 Albulescu et al This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Recovery activities during short breaks taken between work tasks are solutions for preventing the impairing effects of accumulated strain. No wonder then that a growing body of scientific literature from various perspectives emerged on this topic. The present meta-analysis is aimed at estimating the efficacy of micro-breaks in enhancing well-being (vigor and fatigue) and performance, as well as in which conditions and for whom are the micro-breaks most effective. We searched the existent literature on this topic and aggregated the existing data from experimental and quasi-experimental studies. The systematic search revealed 19 records, which resulted in 22 independent study samples (N = 2335). Random-effects meta-analyses shown statistically significant but small effects of micro-breaks in boosting vigor (d = .36, p < .001; k = 9, n = 913), reducing fatigue (d = .35, p < .001; k = 9, n = 803), and a non-significant effect on increasing overall performance (d = .16, p = .116; k = 15, n = 1132). Sub-groups analyses on performance types revealed significant effects only for tasks with less cognitive demands. A meta-regression showed that the longer the break, the greater the boost was on performance. Overall, the data support the role of micro-breaks for well-being, while for performance, recovering from highly depleting tasks may need more than 10-minute breaks. Therefore, future studies should focus on this issue.

 Romanian Ministry of Education and Research PN-III-P1-1.1-TE-2019-2032 Rusu Andrei The work of A. R. was supported by a grant of the Romanian Ministry of Education and Research, CNCS - UEFISCDI, project number PN-III-P1-1.1-TE-2019-2032, within PNCDI III. Data Availability All relevant data are within the article and its Supporting Information files. Introduction

In an "always-on" culture encouraged by the Fourth Industrial Revolution [1], it is essential to find a balance between being effective at work and having optimal well-being. Recent reports highlight the "human energy crisis" many employees face today [2, 3]. Heavy workloads and long hours impede their capacity and energy renewal [4]. Accordingly, scholars from different areas, from organizational psychology or ergonomics to experimental psychology, have been paying attention to mechanisms related to recovery from effort in both employees and students [5]. Therefore, a growing body of literature focuses on momentary recovery and energy management strategies during working time [6, 7].

Energy, as well as effort, is required in achieving work-related tasks and objectives. Work demands can deplete psychological resources [8], having a strong correlation with exhaustion [9] and fatigue [10]. After expending energy over a while, a process of recovery or replenishment is needed [11]. Individuals have several possibilities to recover and build new resources, and during more extended periods of free time, such as evenings [12], weekends [13], or vacations and sabbaticals [14]. Importantly, recovery happens also at shorter intervals during formal working hours, such as lunch breaks [15], scheduled breaks [16], or micro-breaks [17].

The concept of micro-breaks originates in the ergonomics literature, defined as scheduled rests that individuals take to prevent the onset or progression of physical symptoms, such as musculoskeletal pain or discomfort [18]. In the organizational literature, this concept was introduced as a brief resource-replenishing strategy, taken informally between work tasks [19, 20]. Besides micro-breaks [21], several other terms are widely used to refer to short internal recovery, such as work breaks [22], rest breaks [16], energy management strategies [5], recovery behaviors [23], restorative activities [24], and mini-breaks [25]. Micro-breaks are beneficial for the worker’s well-being and job performance [19, 26], even if the total work time is reduced because of the breaks [16]. For the purpose of this paper, we adopted a general definition of micro-breaks as short discontinuities in one’s tasks of no longer than 10 minutes [17, 27]. Although a consensus was not reached on the optimal duration of a micro-break, or even on how short a short break is, thus creating a fairly high variability in time-on-break between studies, we rely both on the categorization of recovery time by Sluiter et al. [27], and the qualitative exploration of Bennett et al. [17]. Specifically, Sluiter et al. [27] used the term "microrecovery" to define what happens in the first minutes after a period of effort exertion, considering short pauses between tasks. Because the next category of recovery time includes a period between 10 minutes and about 1 hour after engaging in work-related tasks, we identified the 10-minutes limit as the maximum amount of time allocated for micro-breaks. Moreover, Bennett et al. [17] coming across the same issue related to micro-break duration, conducted a series of semi-structured interviews supporting the time-cap of 10 minutes for such breaks. Thus, we selected the term micro-breaks as it best defines the duration (micro; 10 minutes or shorter) and the action (break).

A growing body of literature focused on the recovery after the work-related energies have been exhausted [28–30]. However, the process of recovery that happens during the workday or between work tasks is still insufficiently analyzed, and conclusions on their effects are still not clear. The present meta-analysis addresses these limitations, focusing on the recovery process by including experimental studies investigating the momentary impact of micro-breaks between work tasks on well-being and performance.

Theoretical underpinnings and outcomes of micro-breaks

We can rely on multiple explanatory theories to understand how micro-breaks act on individual outcomes. From a fundamental standpoint, the cognitive load theory states that the mental capacity in working memory is limited, and if a task requires too much ability, learning will be hindered [31–33]. Individuals have limited cognitive resources; when allocating resources to one task, their availability becomes limited for other jobs [34]. In this explanatory context, micro-breaks can be seen as natural reactions of the cognitive system to a possible cognitive overload that could affect performance.

Narrowing down towards the applied workplace context, the Conservation of Resources theory (COR) [35] and the Effort Recovery Model (ERM) [8] provide the theoretical foundation for the role of recovery in the relationship between work demands, resources, and stress. The general assumption is that employees have a particular supply of personal resources, such as directed attention or mental resilience instrumental for achieving work goals [36]. Recovery is thus necessary, achievable when no demands similar to those related to the task at hand are put on the person [8], or when new resources are built up (e.g., energy, feelings control) [35]. Individuals lacking recovery experiences tend to endure fatigue and to feel negative affect [37], whereas recovered individuals feel more vigorous and engage in helping behaviors [38]. Moreover, the restoration theories such as Attention Restoration Theory (ART) [39] and The Stress Recovery Theory (SRT) [40] are traditionally used to explain the mechanisms through which exposure to nature can improve mental well-being and performance by reducing the impact of stress, mental fatigue, and negative affect [41–43].

In terms of specific outcomes, there are (at least) two individual-level components of well-being relevant for recovery: vigor (a pleasant activation) and fatigue (unpleasant deactivation) [28, 44]. Moreover, in COR theory, energy is an intrinsic resource (i.e., vigor) that must be replenished when exhausted [45]. Vigor contributes to the willingness to invest effort into the tasks at hand and persist when difficulties arise [46]. For instance, in one study many of employees reported break activities were negatively associated with increased energy (i.e., vitality) but positively related to fatigue [5]. Such results suggest that "employees seek out these strategies when they are already fatigued" [5, p. 34]. The results of a diary approach suggest that break activities positively predict vigor but negatively predict fatigue [21].

Performance represents another key outcome on which micro-breaks are considered to have an impact. It is well known that cognitive (i.e., declarative knowledge, procedural knowledge, and skills) and motivational factors (i.e., effort investment and persistence) are the main determinants of work performance [47]. Breaks from work can improve task performance through beneficial resource-strain, cognitive, affective, and motivational mechanisms [16]. Breaks are essential for performance on sustained attention tasks, suggesting that the vigilance sensitivity decrement is influenced by the frequent use of cognitive resources [48].

However, the current knowledge on micro-breaks relies considerably on experimental data testing their effects, such as improved self-control capacity, mood, or work engagement [49–51]. Specific answers are still needed to understand the effects of micro-breaks on well-being and performance, to explore whether they have an optimal duration and how vital the contextual factors are. To our knowledge, these important questions have no clear answers to date.

Based on the theoretical and empirical rationale described above, we explored two main questions in this meta-analysis. The first refers to the efficacy of micro-breaks (as defined earlier) on participants’ well-being. In other words, we would like to see if we could collect enough meta-analytical evidence to support the assumption that micro-breaks increase individuals’ vigor and decrease their fatigue levels. The second research question refers to the efficacy of micro-breaks in enhancing participants’ performance. In this respect, we would like to see whether we could find sufficient meta-analytic support for the idea that, despite slightly reducing the time allocated to the task, could micro-breaks actually augment one’s performance? In addition to these central questions, we wanted to refine our finding by exploring the impact of several moderator variables.

 Potential moderators for the effectiveness of micro-breaks Break activity and duration

Breaks lead to recovery when individuals engage in activities that reduce the demands put on their resources [5, 52]. During work hours, recovery activities can be related to task objectives (e.g., helping a colleague; setting up a new work-related goal) [5, 53, 54], or can be unrelated to the job (e.g., attending to physiological needs; engaging in social interactions; cognitive; relaxing; directing attention to natural elements) [5, 21].

Overall, work-related micro-break activities were associated with decreased well-being, decreased sleep quality, and increased negative mood [55]. Physical activities such as stretching and exercise were associated with increased positive emotions and decreased fatigue [56, 57]. Relational activities (e.g., checking in with friends and family members) were associated with increased feelings of vitality [21]. The use of personal social media and games was associated with less conflict between work and private life [58], whereas watching a short movie clip was associated with increased recovery and performance [59].

Regarding the duration of micro-breaks and their impact on well-being and performance, some studies suggested that recovery effects could be elicited after a very short time (i.e., 27.4 seconds) [60]. Another study showed that 40-s micro-breaks are sufficient to improve attention and task performance [61]. Finally, other scholars were more generous with the time needed to recover during micro-breaks, from a few seconds to several minutes, implying the possibility that micro-breaks may have an "optimal duration" [20]. However, there is still no established standard regarding the length of such short breaks, as well as no explicit consideration on how much time is sufficient for recovery to occur [17].

Considering the significant difference in the proposed duration of micro-breaks and the fact that there is "little hard evidence concerning the optimum length of rest breaks" [62, p. 123], we would also like to address the following question: Does the efficacy of micro-breaks differ as a function of break activity and break duration?

 Study design, setting, sample characteristics, and contextual factors

Because resource expenditure and recovery can be affected by several contextual and personal factors [63, 64], we consider several additional moderators.

In relation to the type of task from which the participants are recovering, research in neuroscience and cognitive science highlights the relationship between mental effort, complex cognitive tasks, and working memory capacity [65–68]. The more complex a task is, the more mental effort is required. This effort increases neural activity and the metabolic demands on the brain [69]. As a result, fatigue sets in quickly, working memory becomes overloaded, and the recovery effort will be more significant [31]. Therefore, the type of cognitive task the individual is involved in before the break becomes relevant in studying the efficacy of micro-breaks on well-being and performance.

The study setting for the experiment (e.g., laboratory vs. field) is also of interest as a moderating factor, because usually there are no direct personal consequences of one’s behavior in the case of participants in a laboratory experiment, where controlled breaks are taken as instructed. In contrast, participants within the working schedule may experience perceived pressure from colleagues or superiors to keep working to avoid looking "lazy" or uninvolved with the organizational objectives.

When researchers test the effect of micro-breaks on individual outcomes, they tend to use convenience samples of students [17]. Hence, the category of participants (i.e., students vs. employees) may also translate into different effects of the experimental manipulations since the populations may differ in their fundamental motivation to participate in such studies.

Another aspect that could moderate the effect of the break on the cognitive resources’ restoration is the type of break taken by the control group (i.e., no break vs. some form of task interruption) that is generally used in experimental studies. Therefore, in experimental designs where the control group had no breaks, we expect the effect of breaks for the intervention group to be more substantial simply because the participants in the control group did not interrupt their work and had no time for energy recovery [8].

Finally, the measurement and conceptualization issues are primarily relevant for the performance outcome because performance can mean different things in different environments [70]. For some work positions, performance could mean having a prompt reaction time, for others could mean displaying correct responses, while for others could mean generating a new and divergent set of ideas. Moreover, self-reported performance represents a subjective perception that is susceptible to distortions. When the effect of breaks on performance is experimentally tested, it is typically anchored in an active sustained attention research approach (measured by means of highly demanding speed tests) or in a more passive sustained attention approach (measured by means of detection tasks), only recently being used a simpler, sustained-attention, reaction-timed task, requiring speed responses to simple targets (measured with psychomotor vigilance test) [70]. Therefore, our final question investigates the effect of such methodological factors. As far as the data allowed us, we wanted to delineate the impact of a) the task performed before taking the break (e.g., cognitive or creative activities); b) the setting of the study (e.g., workplace vs. laboratory); c) the professional category of participants (e.g., employees vs. students); d) the type of control group (e.g., also in break vs. no break), and e) the operationalization of the performance outcome. Consequently, we explored to what degree the efficacy of micro-breaks differs between various contextual factors (i.e., the design characteristics detailed above).

 Method

We used the PRISMA 2020 framework to conduct and report the systematic review and meta-analysis [71]. The protocol was registered on the PROSPERO platform (ID: CRD42021242961).

Eligibility criteria

Based on the PICOS approach, the included studies had to meet the following criteria: the studied population to be represented by healthy individuals, either employees or students involved in depleting work or comparable work-related tasks (to be able to generalize the findings to the workplace context) (P); to be embedded in micro-breaks literature or focused on short break activities during tasks of 10 minutes maximum (I); a control group to be included as a comparison (C); among the monitored outcomes to be at least one of interest, such as vigor, fatigue, or performance (O); and to have a between-groups experimental or quasi-experimental design (S). Also, the studies had to be published in the last 30 years, written in English (language), and available in full text (availability). The 30 years for this search was used according to Scholz et al.’s [22] argument on the changes in the workplace due to the inclusion of computers and subsequent changes following the reliance on technology.

Moreover, the studies were eligible if they included all the necessary data in computing effect sizes. If these details were not reported, the corresponding author was contacted to provide them.

 Information sources and search strategy

The systematic search strategy was based on enquiring exclusively online databases (SCOPUS, MEDLINE, and PsycINFO) for research published between January 1990 and April 2021. Searches were performed using Boolean operators. Details about how the search was conducted for each database can be found in S1 Table.

 Selection process and data management

We used a two-step approach in study selection: (1) titles and abstracts screening and (2) full-text screening of the remaining records. In the first step, we enquired if the studies investigated internal rest breaks and the outcomes of interest, such as well-being and performance, the design of the studies, and details about the population tested. The next step in the study selection process consisted of screening the full texts of records selected in the previous step and applying the eligibility mentioned above criteria. Cited references were also checked, and eligibility criteria were also applied to these records.

Two independent reviewers (PA and AB) did the screening of both titles and abstracts, and full-text records was done by two independent reviewers (PA and AB). Any disagreement between them over the eligibility of particular studies was resolved through discussions with a third reviewer (AR).

 Data items and collection process

For each eligible study, we proceeded to extract the following information: general bibliographical information (i.e., authors and year of publication); sample characteristics such as country, professional category (i.e., employees or students), age, and gender (P); recovery activity duration (expressed in minutes), type (i.e., work vs. non-work-related; and cognitive, physical, relational, relaxing, or nature-related), and setting (i.e., organization vs. laboratory) (I); type of control group (i.e., also break vs. no break) (C); type of outcome (i.e., vigor, fatigue, performance) and the operationalization (O); research design (i.e., randomized vs. non-randomized) (S). Moreover, we included antecedents of recovery as the type of work task (i.e., clerical, cognitive, creative, or emotional work), the relevance of the task for the workplace (relevant or irrelevant), as well as task duration (i.e., time on the task before the break, expressed in minutes).

We recorded effect sizes for measures of vigor, fatigue, and performance (objective and subjective). Objective performance is expressed as a measure of accuracy representing the amount of work performed in a specific time (e.g., mean correct responses, number of words remembered, errors reported during the completion of tasks, etc.), response speed (reaction time), as well as ideas generated (e.g., where the task require generating new ideas on a topic). Subjective performance variables were measures of self-reported levels of work productivity. Vigor and fatigue represent scores on subjective, self-report instruments.

The data collection and coding process were performed by two reviewers working independently (PA and AB). Differences or inconsistencies were re-examined with a third reviewer (AR) until an agreement was reached. To evaluate the degree of agreement between the reviewers, we computed Cohen’s kappa coefficient. The results suggest a moderate average agreement between the assessors (72.56%; average k = 0.45).

 Risk of bias

The internal validity of the studies was performed based on the Cochrane risk of bias tool [72] by taking into consideration six domains: sequence generation and allocation concealment (selection bias), blinding of outcome assessor (detection bias), incomplete outcome data (attrition bias), selective outcome reporting (reporting bias), and other potential threats to internal validity.

Each criterion was evaluated for each study by assigning it a "low risk," "high risk," or "unclear risk" of bias rating. At the low risk of bias were labelled the studies which reported a clear description of how that specific internal validity criterion was handled. The more criteria with a low risk of bias a study meets, the higher the study’s internal validity can be concluded.

The same two assessors performed the risk of bias assessment. The same third expert discussed any incongruence between them and consensually settled. Inter-rater agreement was consistent across domains, ranging from fair (k = 0.27 for blinding of outcome assessor and participants) to substantial (k = 0.67 for incomplete outcome data).

 Summary measures and synthesis of results

The main research questions were addressed using random-effects meta-analyses based on Borenstein et al.’s [73] framework. We used effect size estimates based on the between-groups standardized mean difference (Cohen’s d) [74], with 95% confidence intervals and two-sided p-values. Positive estimates represent effects in the hypothesized direction (i.e., increased vigor and performance; decreased fatigue), while negative values indicate opposed ones.

Because only two studies collected and analyzed follow-up data [75, 76], we decided to include only the post-manipulation data in our analysis.

To ensure that all effect sizes are computed on independent groups, in cases where studies assessed the effect of different micro-break interventions against the same control group, we combined those intervention groups into one by using standardized or pooled data [17, 49, 59, 75, 77–80]. For the study conducted by Rees et al. [81] several steps were taken, namely: (1) for each of the five post-interruption blocks for each outcome variable tested (i.e., correct responses, reaction times, response bias, sensitivity), the average was calculated; (2) from every five experimental groups (i.e., free break, music, music with video, choosing between listening to music or watching a music video, no activity break), because they were tested against the same control group, we created a single intervention group by calculating their weighted mean and pooled standard deviation; and (3) because three outcome measures fell into our accuracy operationalization of performance, we aggregated them into a single accuracy indicator.

In three other studies, we estimated the effect size based on the result of the analysis of variance with one degree of freedom at between-group level [82, 83] or based on the p-value of a χ2 test and sample size [57].

Besides the weighted average effect size for each outcome, we computed the between-studies heterogeneity. Following the recommendations made by Borenstein et al. [84], we reported the Q, I2, and τ2 indices. A statistically significant Q reflects if the true effect sizes vary across studies, whereas τ2 estimates the between-studies variance. Based on the standard deviation of true effects (τ), a prediction interval for the true effects can be estimated, informing how widely the effects vary. Moreover, the I2 statistic quantifies the dispersion observed due to true variations in effect sizes.

 Additional analyses Detecting extreme effect sizes

A single sample may heavily influence the results and conclusion of a meta-analysis if it is abnormally large, affecting the validity and robustness of the meta-analysis [85, 86]. We followed the approach proposed by Viechtbauer and Cheung [86] and defined a study as an outlier when its effect size estimate is so extreme that the study cannot be part of the "population" of effect sizes we pool in our meta-analysis, differing significantly from the overall effect. We examined outliers in each meta-analytic distribution as follows: (1) identifying outliers based on the study’s confidence interval (i.e., if there are studies for which the confidence interval does not overlap with the confidence interval of the pooled effects), (2) we proceeded to analyze the data with and without the studies identified as being extreme, and (3) if one such extreme value had a substantial impact on the results (e.g., shifts the heterogeneity from non-significant to significant), we proceeded to remove it from the subsequent (main) analysis.

 Moderator analyses

The hypothesized categorial moderators were tested using subgroup analyses based on a mixed-effects model (i.e., employing a random-effects model within each subgroup, while between-subgroup differences were tested for significance based on a fixed-effect model). We used meta-regression under a random-effects model for numerical moderators.

 Publication bias

For this purpose, we corroborated information from multiple sources. After visually inspecting the forest plot to see the relationship between sample size and effects we also used Egger’s test, which yields a p-value [87], as well as Duval and Tweedie’s [88] trim and fill procedure to estimate the effect sizes after taking into account publication bias (i.e., imputed studies).

All meta-analytical analyses and publication bias were conducted with the aid of Comprehensive Meta-Analysis Version 3 software [89]. The prediction intervals were calculated with the spreadsheet provided by Borenstein et al. [84].

 Results Selection and inclusion of studies

The systematic search yielded 4868 unique records (after removing the duplicates) (see Fig 1). These were first reviewed based on title and abstract, removing another 4825 entries. In the next step, we analyzed the full text for 43 articles, two of which were included after screening the reference lists for potentially relevant studies. Out of these records, 25 were excluded for the following reasons: (1) 6 for not using a control group, (2) 9 employed a within-subjects design, and (3) 10 had incomplete data for computing effect sizes. The corresponding authors were contacted for this latter category, making available data from only one more study [81]. Hence, the final sample included 22 independent study samples that resulted from 19 publications (see Fig 1 for the complete flow of the literature search).

10.1371/journal.pone.0272460.g001 The PRISMA flow diagram of the literature search and selection process. Description of the included studies

A systematic overview of the studies’ characteristics (e.g., participants, design) is displayed in Table 1. A summary of attributes of experimental manipulations (e.g., breaks, tasks before breaks) and outcomes are shown in Table 2. Moreover, a detailed narrative overview is provided in S1 File.

10.1371/journal.pone.0272460.t001 Summary of studies included in the meta-analysis and their description.
Publication Study no. Country Sample Mean age % Women Randomization Control Setting Risk of bias
Low Unclear High
Bennett et al. (2020) [17] USA Students 24.2 55.2 Yes No break Laboratory 3 3 0
Beute & de Kort (2014) [49] Study 1 Netherlands Students 22.2 53.3 No Break Laboratory 1 3 2
Blake et al. (2019) [90] China Employees 32.5 47.5 Yes Break Organization 4 0 2
Blasche et al. (2013) [75] Austria Employees 40.1 60.2 Yes Break Organization 2 2 2
Clauss et al. (2018) [76] Germany Employees 42.3 71.1 No Break Organization 1 3 2
Conlin et al. (2020) [77] USA Students 20 33.1 No No break Laboratory 2 4 0
Ellwood et al. (2009) [78] Australia Students 22 72.2 No No break Laboratory 2 3 1
Finstad et al. (2006) [91] Study 1 USA Students - - Yes Break Laboratory 2 4 0
Study 2 USA Students - - Yes No break Laboratory 2 4 0
Study 3 USA Students - - Yes No break Laboratory 2 4 0
Janicke et al. (2018) [79] USA Employees 36.2 47 Yes Break Organization 4 2 0
Kennedy & Ball (2007) [82] Australia Employees 29.9 57.3 No Break Organization 2 1 3
Lacaze et al. (2010) [57] Brazil Employees 30 73.4 No Break Organization 2 3 1
Michishita et al. (2017) [50] Japan Employees 45 23.8 Yes Break Organization 1 3 2
Michishita et al. (2017) [51] Japan Employees 40.9 32.2 Yes Break Organization 1 4 1
Paulus et al. (2006) [80] Study 2 USA Students Yes No break Laboratory 1 5 0
Study 3 USA Students Yes No break Laboratory 1 5 0
Rees et al. (2017) [81] Australia Students 20.5 33.3 Yes No break Laboratory 2 4 0
Rieger et al. (2017) [59] Germany Students 25.5 72.7 Yes Break Laboratory 3 3 0
Steidle et al. (2017) [92] Germany Employees 36.9 43.9 Yes Break Organization 2 3 1
Steinborn & Huestegge, (2016) [83] Germany Unknown 21.7 85 No No break Laboratory 1 4 1
Wollseiffen et al. (2016) [93] Germany Employees 41 46 Yes No break Laboratory 1 5 0
10.1371/journal.pone.0272460.t002 Characteristics of the interventions and outcomes.
Identification Study Intervention type Characteristics of the task preceding the break Characteristics of micro-breaks Outcome
Type of task Workplace relevance Activity performed Time on task (minutes) Break activity Break duration (minutes)
Bennett et al. (2020) [17] Work & Non work Clerical Relevant Attention Network Test (Fan, McCandliss, Sommer, Raz, & Posner, 2002) 10 Cognitive & relaxation 5 Fatigue
Vigor
Beute & de Kort (2014) [49] Study 1 Non work Clerical Relevant Typing task – Cognitive & nature 3 Performance
Fatigue
Vigor
Blake et al. (2019) [90] Non work Clerical Relevant Office tasks – Physical 10 Performance
Blasche et al. (2013) [75] Non work Clerical Relevant Office tasks – Physical 8 Fatigue
Clauss et al. (2018) [76] Work Emotional Relevant Nursing tasks 210 Cognitive 10 Fatigue
Conlin et al. (2020) [77] Non work Clerical Relevant Clerical editing task 10 Cognitive & nature 0.66 Performance
Ellwood et al. (2009) [78] Work & non work Creative Irrelevant Idea generation test 2 Cognitive 5 Performance
Finstad et al. (2006) [91] Study 1 Non work Cognitive Irrelevant Prospective memory test (Thorndike & Lorge, 1944) 30 RelaxationCognitive 0.133 Performance
Study 2 Non work Cognitive Irrelevant Prospective memory test (Thorndike & Lorge, 1944) 30 Relaxation 0.166 Performance
Study 3 Non work Cognitive Irrelevant Prospective memory test (Thorndike & Lorge, 1944) 30 Relaxation 0.166 Performance
Janicke et al. (2018) [79] Non work Relevant – 240 Cognitive 4 Vigor
Kennedy & Ball, (2007) [82] Non work Emotional Relevant Call center tasks – Relaxation 10 Fatigue
Vigor
Lacaze et al. (2010) [57] Non work Emotional Relevant Call center tasks 180 Physical 10 Fatigue
Performance
Michishita et al. (2017) [50] Non work Clerical Relevant – – Physical 10 Fatigue
Vigor
Michishita et al. (2017) [51] Non work Clerical Relevant – – Physical 10 Fatigue
Vigor
Paulus et al. (2006) [80] Study 2 Non work Creative Irrelevant Brainstorming 16 Relaxation 4.5 Performance
Study 3 Non work Creative Irrelevant Brainstorming 16 Relaxation 4.5 Performance
Rees et al. (2017) [81] Non work Cognitive Relevant Simulated rail control task 20 Cognitive 5 Performance
Rieger et al. (2017) [59] Non work Cognitive Irrelevant Reading-span task (Daneman & Carpenter, 1980) and Operation-span task (Turner & Engle, 1989) – Cognitive 2 Vigor
Performance
Steidle et al. (2017) [92] Non work Clerical Relevant Office tasks – Nature & physical 10 Fatigue
Vigor
Steinborn & Huestegge, (2016) [83] Non work Cognitive Irrelevant Mental-addition and verification tasks (Zbrodoff & Logan, 1990) – Cognitive & physical 3 Performance
Wollseiffen et al. (2016) [93] Non work Cognitive Irrelevant Memory matrix (Dorval & Pepin, 1986; Schaefer & Thomas, 1998), and Chalkboard challenge d2-R test (R Brickenkamp, 2002; Rolf Brickenkamp, Schmidt-atzert, & Liepmann, 2010) 120 Physical 3 Fatigue
Vigor

Eleven studies used samples of students, whereas the other ten studies tested their hypotheses on samples of employees. One study used "normal volunteers" to characterize its sample without further clarifications. The total number of participants in these studies was 2335, with a mean age of 31.2 years old.

Most of the studies employed an experimental design, where participants were randomly allocated to different interventions (n = 15), whereas fewer used non-random allocation but with equivalent groups (n = 7). Most of the studies took place in a laboratory (n = 13); a smaller number was in an organizational/workplace setting (n = 9). In most studies, participants in the control group were engaged in some break or free time between work tasks (n = 12). In contrast, in a slightly smaller number of studies, these participants continued working without respite (n = 10).

To study the resource replenishing effects of breaks, participants had to complete a series of tasks before taking a respite. These tasks were either relevant to organizational life, such as work simulations and actual work-related tasks (n = 13), or irrelevant, such as various cognitive tests (n = 9). Participants were exposed to different type of demands, such as cognitive (n = 7), emotional (n = 3), or clerical (n = 8). Studies in which participants had to generate new ideas were considered as having creative demands (n = 3). Time on task is one of the most widely studied contributors to the depletion of resources. In our sample, this information was specified only for 13 studies, with participants spending between a minimum of 2 minutes and a maximum of 4 hours on resource-demanding tasks before getting a break.

In almost all of the studies, the break was a non-work one (n = 19), whereas only one study included a work-related break. Two studies were incorporated into a category with work and non-work micro-breaks because they shared the same control group, and their results were pooled in single indicators. Thus, the low variability on this factor also impedes treating it as a moderator (despite our initial intention). Regarding what participants did during the micro-breaks, five studies used a combination of two activities. For three of these studies, the combination of multiple types of activities was a result of using the same control group to compare different interventions. Five studies included a cognitive micro-break, where participants were involved in activities such as watching movie clips. Six studies offered a physical break between work bouts, whereas the other six activities during breaks were relaxing. Hence, the heterogeneous and mixed nature of the micro-breaks employed in the included studies impedes us from exploring this aspect as a potential moderator. Break duration varied significantly between studies, ranging between 8 seconds and 10 minutes.

Considering the outcomes’ operationalizations, vigor and fatigue were exclusively assessed with self-report scales. The measures varied from multi-factor well-established instruments (e.g., Activation-Deactivation-Checklist [94]; Utrecht Work Engagement Scale [95]; Profile of Mood States, [96]), to one-item ones [e.g., 92] The reporting of reliability estimates was inconsistent across studies (and not possible for single-item measures), but when mentioned, generally exceeded α = .80 or even α = .90 [e.g., 17, 79, 92]. As for performance, there were studies using both objective and subjective measures of performance, as well as measures of creativity. We grouped accuracy (e.g., mean correct responses, number of words remembered, errors reported during the completion of tasks, etc.) and reaction speed in cognitive tasks into a category of objective measures (n = 8), self-perceived performance was considered as a subjective measure (n = 4), and idea generation was considered as creative performance (n = 3). A more fine-grained categorization (especially for the objective measures) was hard to impose because of the limited number of studies. In terms of reliability, with two exceptions (Studies 2 and 3 from Paulus et al. [80]), there were no such estimates reported. While the mentioned cases focused on creative performance with interrater reliabilities of > .90, for all the other operationalizations it was not possible to make any accurate inference from this perspective. However, as also previously discussed [70], the objective measures typically imply the employment of arbitrary tasks and/or unaudited performance measures or paradigms with reduced numbers of trials. Hence, it is less likely to expect such approaches as being psychometrically precise. Unfortunately, in the absence of reliability estimates, such measurement artefacts cannot be taken into account meta-analytically.

 Quality of the included studies

The risk of bias assessment results for each threat to the internal validity are shown in Table 1 (for each study) and Fig 2 (as a visual summary).

10.1371/journal.pone.0272460.g002 Risk of internal bias summary.

The results following the selection bias assessment show an unclear risk for both domains (i.e., sequence generation and allocation concealment), as thirteen of the twenty-two studies did not make explicit the randomization method. Detection bias follows the trend, with most studies in the unclear risk of bias category (72% of included studies). Most studies were at low risk for attrition bias (n = 20). Twenty-one studies were assessed with unclear risk regarding reporting bias. For other potential threats to validity, fifteen studies out of twenty-two have been evaluated as having low risk.

Overall, only four out of twenty-two studies were assessed with a low risk of bias, whereas one presented a high risk for at least half of the criteria. Thus, we are inclined to consider the risk of bias in our overall sample as being somewhat unclear.

 Preliminary analyses

To detect potential outliers, we analyzed the studies for which the confidence intervals failed to overlap with the confidence interval of the pooled effects. We found only two potential outliers. One of them was in the sample of effects regarding the role of micro-breaks on fatigue [49], with an effect size of d = 13.43, and a 95%CI which stretched between 11.11, and 15.75, being completely non-overlapped with the overall one [0.29, 1.52]. The other one was in the sample of effects of micro-breaks on performance outcomes [77], with an effect size of d = 3.85, 95%CI of [3.38, 4.33], as compared to the meta-analytical one laying between [-0.14, 0.86]. The decision to exclude them was proven legitimate, as the results differed greatly, with improvements in heterogeneity. Specifically, for the effect on fatigue; before exclusion the heterogeneity was statistically significant (Q(9) = 127.55, p < .001), while after excluding the outlier became non-significant (Q(8) = 6.24, p = .619), result also reflected into the I2 value (before exclusion: I2 = 92.94%; and after: I2 = 0.00%). In the case of performance, heterogeneity with the outlier was also higher (Q(15) = 242.57, p < .001; I2 = 93.82%), as without it (Q(14) = 34.52, p = .002; I2 = 59.45%). The detailed analyses including the outliers can be found in S2 Table.

 Effectiveness of micro-breaks

The main meta-analytical results are presented in Table 3 and displayed in Fig 3. These revealed a statistically significant but small effect of micro-breaks on vigor, d = 0.36, p < .001, 95% CI [.16, .55], and fatigue d = 0.35, p < .001, 95% CI [.19, .50], while the effect on performance was not statistically significant, d = 0.16, p = .17, 95% CI [-0.04, .37].

10.1371/journal.pone.0272460.g003 <p>Standardized effect sizes and forest plot for the sample of studies regarding (a) Vigor, (b) Fatigue, and (c) Performance.</p> </caption> <graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0272460.g003" xlink:type="simple"/> </fig> <table-wrap id="pone.0272460.t003" position="float"> <object-id pub-id-type="doi">10.1371/journal.pone.0272460.t003</object-id> <label>Table 3</label> <caption><title>Effectiveness of micro-breaks on vigor, fatigue, and performance.
Outcome k n1 n2 d SE 95% CI p Q τ2 I2 95% prediction interval
Vigor 9 614 299 .36 0.10 [.16, .55] < .001 13.61 0.04 41.21 [-.15, .86]
Fatigue 9 528 275 .35 0.08 [.19, .50] < .001 6.25 0.00 0.00 [.16, .53]
Performance 15 711 421 .16 0.10 [-.04, .37] .116 34.52** 0.09 59.45 [-.53, .86]

k = number of studies included in the analysis; n1 = number of participants included in the intervention groups, n2 = number of participants included in the control groups; d = weighted average effect size; SE = standard error of the average effect size; 95% CI = 95% confidence interval; Q = statistical test for the estimation of heterogeneity; τ2 = between-study variance; I2 = proportion of variation in the observed that is due to true effects variation (%).

*p < .05

**p < .01

Heterogeneity analyses suggested that the effects on vigor (Q(8) = 13.61, p = .093; I2 = 41.21%; τ2 = .04; 95% prediction interval: [-.15, .86]) and especially on fatigue (Q(8) = 6.25, p = .619; I2 = 0.00%; τ2 = .00; 95% prediction interval: [.16, .53]) were quite homogenous. However, there was significant unexplained variance in the true effect sizes for performance (Q(14) = 34.52, p = .002; 95% prediction interval: [-.53, .86]). A big proportion of the observed variance being due to real variations of the effects (I2 = 59.45%, τ2 = 0.09).

 Moderator analyses

Even though the effects on vigor and fatigue were relatively homogeneous, and only those on performance revealed significant between-studies variations, we continued with the moderator analyses on all three outcomes (especially since we still had rational/theoretical arguments in this regard). The results of the moderator analyses for all outcomes of interest can be seen in Table 4. Because of the modest number of studies on each category and the low variability in many cases, we only had the methodological possibility to test a low number of moderators (i.e., break duration, the task before break, type of participants, study setting, or control group activity).

10.1371/journal.pone.0272460.t004 Test of significance for each presumed moderator.
Moderator Vigor Fatigue Performance
k Q p k Q p k Q p
Break duration (minutes) 9 0.01 .909 9 0.61 .436 15 7.50 .006
Antecedent task (cognitive vs. clerical vs. emotional vs. creative) 8 2.28 .094 8 0.43 .514 14 6.53 .011
Professional category (employees vs. students) 9 0.02 .899 9 0.37 .542 14 2.66 .103
Study setting (laboratory vs. workplace) 9 0.02 .902 9 0.55 .459 15 2.73 .099
Type of control (break vs. no break) 9 0.08 .777 9 0.55 .459 15 2.66 .103
Performance operationalization (objective, subjective, creative) – – – – – – 15 4.31 .116

The effect of break duration was tested with meta-regression while the other moderators were tested with subgroup analysis.

For vigor and fatigue, the results show that none of the considered moderators impacted the efficacy of micro-breaks (all ps > .050). For overall performance, however, two moderators were found. Break duration was revealed to be one of the significant results (b = .07, p = .006, R2 = .34). Indicating that the longer the break, the more micro-break leads to a performance increase. The second significant effect was the type of task performed before the break (Q(2) = 6.53, p = .011). More specifically, when the task was cognitive, the micro-breaks had a very small effect on performance (d = -.09, 95%CI [-.39, .30], p = .541), which was non-significant and still heterogeneous. When the tasks were creative, micro-breaks had a small, significant effect (d = .38, 95%CI [.11, .64], p = .006), and for clerical tasks the effect of micro-breaks was medium and significant (d = .56, 95%CI [0.01, 1.12], p = .047). It is important to mention that the latter effect is based only on two studies; hence, it has to be cautiously interpreted. To have a broader picture of the role of task antecedent to the break, in Table 5, we also report the sub-group results for vigor and fatigue (not only for performance). It may be worth noticing that the effect on vigor when the micro-break is taken from a cognitive task is also minimal and non-significant (important to bear in mind that the sub-groups differences are not statistically significant).

10.1371/journal.pone.0272460.t005 Meta-analytical findings at each level of the antecedent task moderator.
Outcome Moderator levels k d SE 95%CI p Q τ2 I2
Antecedent task (activity preceding the break)
Vigor Cognitive 2 .07 .19 [-.31, .45] .728 9.14 .04 45.29%
Clerical 6 .45 .12 [.21, .68] < .001 0.54 .00 0.00%
Fatigue Clerical 5 .31 .10 [.11, .50] .002 1.21 .00 0.00%
Emotional 3 .46 .21 [.05, .86] .027 4.28 .07 53.26%
Performance Cognitive 9 -.09 .15 [-.39, .20] .541 18.71* .11 57.25%
Clerical 2 .56 .28 [.01, 1.12] .047 3.05 .12 67.23%
Creative 3 .38 .14 [.11, .64] .006 0.47 .00 0.00%

Note: The analysis on vigor was done without the effect from Kennedy and Ball [81] being a single study with emotional labor task; the analysis on fatigue was performed without the effect from Wollseiffen et al. [93], being the only study with cognitive task; the analysis on performance was conducted without Lacaze et al. [57], because we could not accurately classify the type of task.

*p < .05

Finally, we tested if study quality (i.e., total criteria with low risk of bias for internal validity–see Table 1) was associated with the efficacy of the interventions. The results of the meta-regression suggest that for neither of the outcomes the amount of criteria with low risk of bias had a significant impact on efficacy (effect on vigor: b = -.05, p = .642, R2 = .00; effect on fatigue: b = -.01, p = .905, R2 = .00; effect on performance: b = -.13, p = .329, R2 = .00).

 Publication bias

For the effect size estimates on vigor, Egger’s test was not statistically significant (intercept = 0.21, p = .915), while the trim and fill procedure imputed two studies to the right of the mean. The adjusted effect was d = 0.45, being similar in magnitude to the observed value (d = 0.35). In the case of fatigue, the statistically non-significant results on Egger’s test (intercept = -0.46, p = .769) indicated a lack of publication bias, but the trim and fill procedure imputed two studies to the right of the mean. The adjusted effect was d = 0.40, being also like the observed one d = 0.34. Finally, for performance, Egger’s test was statistically significant (intercept = -2.63, p = .048), indicating possible publication bias. The trim and fill procedure imputed two studies to the right of the mean, where the adjusted value suggests a significant small effect (d = 0.22, 95% CI [0.02, 0.43]) as compared to the observed one (d = 0.14, 95% CI [-0.07, 0.36]). Even though statistically significant, it still is similar in magnitude. Overall, whereas some evidence for the presence of publication bias exists, it does not seem to be an impactful threat to the observed effects.

 Discussion

The main objective of the present meta-analysis was to examine the efficacy of micro-breaks (less than 10 min pauses from tasks) on individual outcomes such as well-being (i.e., increased vigor and decreased fatigue) and performance. Moreover, we also considered the influence of work demands and several contextual factors, such as professional category or study setting, on the role of micro-breaks for focus outcomes.

Our results revealed that micro-breaks are efficient in preserving high levels of vigor and alleviating fatigue. It seems that the effects are univocal and generalizable for the well-being outcomes. These were relatively homogeneous, and none of the included moderators were significant. Hence, the data suggest that micro-breaks may be a panacea for fostering well-being during worktime.

When it comes to performance, the data revealed some nuances. The break duration was a significant covariate of the effect of micro-breaks: the longer the break, the better the performance. Moreover, the type of task from which participants were taking the break also emerged as a significant moderator. Micro-breaks could significantly increase performance for clerical work or creative exercises and not for a cognitively demanding task. These results have both theoretical and practical implications.

Firstly, our results support a central assumption of the recovery literature, which states that engaging in recovery activities (what an individual does) leads to a recovered system (more energy, less fatigue, and better performance on some tasks). When no further demands are put on the individual, recovery is possible through a short break from the work tasks [8].

Secondly, break duration was essential in recovery and micro-breaks literature [8, 17]. A break is taken in order to replenish energy to achieve goals and performance. The link between goals and performance is ensured by attention [97], a key concept in cognitive psychology studies. The difference between micro-breaks, short breaks, and long breaks, can be related from this perspective to the functioning of the three attention networks: alerting, guidance, and executive control [98]. Studies show that if the first two fluctuate on a momentary basis, executive control benefits from greater stability [99] and it allows individuals to monitor their attention focus having an impact on behavioral self-regulation [100]. However, at the same time, break duration is largely missing from previous recovery research, considering time either as a boundary condition or not discussing time at all [54]. This lack of focus on break duration resulted in high variability between studies regarding the length of such breaks. Moreover, as a result, practical answers tested empirically to attest whether micro-break duration matters for well-being or performance are missing. Thus, even if micro-breaks are understood as short breaks under 10 minutes in duration [27], the specific time of these micro-breaks was not yet established [17, 27]. When considering only performance as outcome, other scholars also noticed the difficulty of giving a universal answer to the question of how long a break should be in order to be effective [70]. The present study contributes to this body of literature, supporting the assumption that short breaks of close to ten minutes efficiently alleviate fatigue, increase energy, and boost (subjective / perceived) performance. These results offer, therefore, some clarity related to a duration standard.

Thirdly, regarding the effects of micro-breaks on performance as a function of the task participants were engaged in, the results show that especially for clerical (routine tasks) or creative (where divergent thinking is needed) tasks, taking short breaks helps individuals in performing better at subsequent tasks. These results are in line with another meta-analysis showing that when attempting creative problems requiring a wider search of knowledge, individuals benefit from a period of time in which the problem is set aside prior to further attempts to solve it [101]. The effect of breaks also tends to be better reflected in subjective evaluations of performance and actual creative outputs. Therefore, micro-breaks make individuals feel more vigorous and less fatigued and stimulate them to feel more productive after the break.

Routine tasks refer to sequences of actions that are performed with a high level of automaticity, with high speed and low variability [102, 103]. They release cognitive resources to think about other aspects of the work or simply for the mind to wander, increasing the probability of making mistakes [104]. The break can decrease this risk, interrupt spontaneous ideas that cross to mind rapidly and unconsciously [105] and refocus the attention on the next task, facilitating performance.

Referring to creative tasks, they essentially demand creative cognition and divergent thinking [106]. Creative cognition supposes the ability to strategically search memory for task-relevant information and to suppress interference with other information that comes to mind during divergent thinking [107]. It is also connected with associative processes [108]. According to the dual-process model of creativity, there are two pathways to creative performance: flexibility and persistence. The flexibility pathway stimulates creativity by flexible switching between approaches and sets [109]. Thus, task switching strengthens flexibility and can further improve creative performance. If we look at the break as a switching task, this is a possible explanation for improving creative performance after the break by strengthening flexibility.

However, when it comes to cognitively demanding tasks, taking short breaks does not seem to affect subsequent performance. Based on recent experimental research showing that the break duration is an essential factor in understanding the recovery processes [17], a possible explanation for the result of our study is that the pause with a duration of less than 10 minutes can replenish vigor, but not fully restore the resources needed to perform in a demanding cognitive task. At the same time, our data also showed that when categorizing performance in subtypes, only the effects for cognitive performance still remain heterogeneous (variation for which we did not have sufficient data to further disentangle). As also Schumann et al. [70] pointed out in their review, there are multiple methodological factors (e.g., employment of arbitrary tasks and/or unreliable or unaudited performance measures; insufficient number of trials) which could result in artefactual variance. Moreover, even if taking into account their purpose, all these measures can be grouped under the umbrella term of performance, the many conceptual and operational differences between them could also make one rightfully argue against their aggregation. Hence, these particular results should be taken with increased caution. As cognitive demands are prevalent in the workplace and also the educational settings, future studies might test the conditions under which respites positively affect subsequent performance by applying more standardized experimental paradigms and increasing consensus on methodological approaches.

Indeed, the effect of recovery during micro-breaks on subsequent performance seems to be more entangled compared to the effect it has on well-being, thus deserving a closer look. As a detailed inspection of aspects such as break length and the type of task from which the break is taken offered valuable insights but no definitive answers regarding this effect, having an overview also of the excluded studies could prove fruitful. Thus, we had another look at all the articles assessed for eligibility in the present meta-analysis, and specifically at those focused on performance outcomes. Whereas some laboratory studies found no effect of taking short breaks between various resource-depleting tasks on subsequent performance [e.g., 110–112], others found significant improvements in performance after taking a break [e.g., 57, 78, 83].

Studies in which various work tasks or environments were simulated also found either no significant impact of breaks on performance [113–115], or either positive effects [81]. For example, breaks were found to improve performance in a simulated rail control task in comparison to the control condition [81], whereas other studies simulating night shifts [113, 114] or simulating nighttime flights for piloting crew [115] found no such positive, significant effects. When considering experimental studies conducted only in real-life work settings, the patterns of results are similar. For example, a study introduced brief Qigong exercise breaks as interventions in two sites of a major organization in China for twelve consecutive weeks, finding no improvement in self-reported work performance for the office workers [90]. However, another study found positive effects of breaks on worker productivity for a similar population, namely computer operators of a large insurance company [56]. Moreover, two other studies found that intra-operative micro-breaks during which surgeons executed mild stretching exercises positively impacted their performance without affecting the operative duration [116, 117]. Importantly, no study found significantly decreased performance when a break was introduced between tasks, adding to the argument that even when less time is spent on the task at hand due to the time allocated for the break [19, 26], performance does not worsen compared to individuals who continued working [90, 112, 118]. In other words, even if we dismiss all the studies finding a positive impact of breaks on task efficiency and consider micro-breaks as not improving performance, taking a break at least does not harm it. Also, the boost in performance may be occupation or task specific (e.g., computer operators [56], or even surgeons [116, 117]), an avenue of research that further deserves scholarly focus.

From a practical perspective, these results offer strong support that taking short breaks during working hours is beneficial for individuals’ health and productivity. Sedentary activities requiring constant monitoring and attention resulting from accelerated automation and the COVID-19 pandemic (e.g., online education, shift to remote working) might remain problematic. Taking short breaks can become more necessary to protect individual well-being and performance [119]. Therefore, organizations must reconsider the usefulness of an "always-on" culture for personal and organizational outcomes.

Managers can support employees’ well-being by encouraging them to take micro-breaks. Such leadership engagement is relevant, considering that many employees still might feel that taking breaks might be perceived as counterproductive behavior [120]. Moreover, organizations could also benefit from training to build personal resources and organizational capacities, learning how and when to engage in efficient energy management and recovery strategies. We agree with the proposition of Bennett et al. [28] that further exploration of organizational policies conducive for employee recovery would be very interesting for research and practice alike.

As mentioned before, about half of the studies were conducted on students. This aspect has several implications. Students are considered similar to employees in terms of their engagement in structured and constraining activities to a certain measure and directed towards specific goals, such as completing assignments and attending classes [121, 122]. Also, their experience with various demands and associated distress emphasizes the need to understand how detrimental effects, such as fatigue, can be prevented, and positive outcomes, such as vitality and performance, can be enhanced. Therefore, how micro-breaks are structured and experienced can significantly influence students’ well-being and performance outcomes.

Moreover, our results can also have implications for an educational perspective. Lectures can become more successful when delivering information alternate with learning pauses [123, 124]. In this context, restorative breaks, especially in online learning, where students need to look away from their computers may help reestablish their energy and focus. In this way, it is possible to have a deep learning process right in the educational setting and an enhanced chance to sustain performance in the longer term. Teaching students the benefits of short breaks during individual study for optimal learning can be one of the goals of educational policies that increase students’ motivation and achievements. However, one should bear in mind that these observations are only presumed implications for the academic environment, being based on activities more specific to the workplace environment. As previously mentioned [125], even though academic classwork, as also office work, is a source of fatigue, the two environments bear differences that make the generalization between them cautionary.

Limitations, future research directions, and conclusions

Although this meta-analysis sheds some light on the effect of micro-breaks on individual outcomes, it is not without any limitations, thus prompting the reader to interpret these results with caution.

Firstly, the number of studies was modest for each outcome, which limited the moderator analyses. Specifically, essential moderators that could have helped us better understand the heterogeneity presented for the performance effect were impossible to analyze. Some examples are break type (work or non-work), specific activity performed during the break (physical, relational, cognitive, relaxation, nature-related, etc.), or time working on the task before taking a break. In the recent literature review on the effect of breaks on performance, the aspect of testing moderator variables was also discussed, concluding that underdeveloped methodological approaches for tasks and measures, and extremely heterogeneous perspectives concerning contexts, and designs, make it hard to conduct such differential analyses in the field of rest-break research [70]. Thus, we could not address one of the most important questions for practice about which specific activity is most efficient for recovering lost resources during work: "What to do in these breaks to feel and perform better?". However, while we still need a clear explanation for the performance outcome, at least for well-being, the answer seems to be "any type of decoupling activity".

Secondly, besides the increased heterogeneity in measurement approaches (especially when considering performance), another important cautionary aspect may be their reliability. The fact that we have inconsistent reporting for the well-being self-reports and no information for the other measures makes it impossible to scrutinize the potential bias induced by measurement error. When possible, future studies should not overlook reporting reliability estimates. This way updated meta-analyses on this topic may address the artefactual variance accountable by measurement error [126, 127].

Furthermore, because all the studies considered in the present meta-analysis used self-reports of well-being outcomes, our results could be exposed to response biases [128]. Although this is a well-known risk when using self-reports, the energetic activation (e.g., vigor) and deactivation (e.g., fatigue) of the well-being components considered in this meta-analysis represent a subjective component of a "bio-behavioral system of activation" [129, 130 p. 827], experienced as feelings, emotions, or dispositions [7]. Thus, one’s evaluation of their subjective experience can be more suitable than other individuals’ reports or assessments. However, future studies could also benefit from a combination of self-reports of well-being with objective measures of the bio-behavioral systems involved (e.g., endocrinological indicators) [130].

Lastly, we considered only two aspects of well-being, a pleasant activation (e.g., vigor) and unpleasant deactivation (e.g., fatigue), leaving aside other concepts studied in recovery research such as anxiety or tension [131]. Moreover, the present meta-analysis is based on studies from the pre-pandemic literature. The new Covid-19 pandemic brought forward new challenges at home, at school, and at work, changing the way people work in fundamental ways [132]. Thus, future studies could benefit from including this new challenge related to the pandemic in their designs.

The current meta-analysis was performed on twenty-two experimental studies published in the past thirty years that tested the effects of micro-breaks on vigor, fatigue, and performance. Specifically, it showed that micro-breaks positively impact well-being by enhancing vigor and lowering fatigue, regardless of the contextual factors. Importantly, micro-breaks do not seem to influence performance generally. However, when the break is more extended, the performance tends to improve, especially when individuals are engaged in creative or clerical tasks, and less when performing activities of a cognitively demanding nature.

 Supporting information PRISMA 2020 checklist.

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 Details regarding the search string for each database.

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 Overall effect on fatigue and performance with the outliers included.

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 Detailed description of the included studies.

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 References Schwab K. The Fourth Industrial Revolution. 2016 (Geneva: World Economic Forum). Energx. The first annual energx womens energy intelligence report. Why Are Women So Tired? Australia’s female energy crisis. 2019 [cited 7 February 2022]. Available from: https://docs.wixstatic.com/ugd/92f44e_fa4a3a6b428d40139a65ddfb19c82f79.pdf?index=true Young S, Duff S, Stanney K. How Nurse Leaders Can Reduce Burnout: Focus on Mental Energy!. Nurse Lead. 2016 Apr 1;14(2):139–41. doi: 10.1016/j.mnl.2015.07.011 Schwartz T. We’re in a new energy crisis. This one is personal. Harvard Business Review. 2011. Available from: https://hbr.org/2011/03/were-in-a-new-energy-crisis-th.html Fritz C, Lam CF, Spreitzer GM. It’s the little things that matter: An examination of knowledge workers’ energy management. Acad Manag Perspect. 2011 Aug;25(3):28–39. doi: 10.5465/AMP.2011.63886528 Kim S, Cho S, Park Y. Daily microbreaks in a self-regulatory resources lens: Perceived health climate as a contextual moderator via microbreak autonomy. J Appl Psychol. 2022 Jan;107(1):60. doi: 10.1037/apl0000891 33646798 Quinn RW, Spreitzer GM, Lam CF. Building a sustainable model of human energy in organizations: Exploring the critical role of resources. Acad Manag Ann. 2012 Jun 1;6(1):337–96. doi: 10.1080/19416520.2012.676762 Meijman TF, Mulder G. Psychological Aspects of Workload. W: Drenth PJD, Thierry H.(red.), Handbook of Work and Organizational Psychology; 1998 (s. 5–33). Lee RT, Ashforth BE. A meta-analytic examination of the correlates of the three dimensions of job burnout. J Appl Psychol. 1996 Apr;81(2):123. doi: 10.1037/0021-9010.81.2.123 8603909 Lu L, Chou CY. Protecting job performance and well‐being in the demanding work context: The moderating effect of psychological detachment for Chinese employees. Appl Psychol. 2020 Sep;69(4):1199–214. doi: 10.1111/apps.12216 Zijlstra FR, Sonnentag S. After work is done: Psychological perspectives on recovery from work. Eur J Work Organ Psychol. 2006 Jun 1;15(2):129–38. doi: 10.1080/13594320500513855 Rook JW, Zijlstra FR. The contribution of various types of activities to recovery. Eur J Work Organ Psychol. 2006 Jun 1;15(2):218–40. doi: 10.1080/13594320500513962 Fritz C, Sonnentag S. Recovery, health, and job performance: effects of weekend experiences. J Occup Health Psychol. 2005 Jul;10(3):187. doi: 10.1037/1076-8998.10.3.187 16060723 De Bloom J, Kompier M, Geurts S, De Weerth C, Taris T, Sonnentag S. Do we recover from vacation? Meta-analysis of vacation effects on health and well-being. J Occup Health. 2008:0812090045-. doi: 10.1539/joh.k8004 19096200 Sianoja M, Syrek CJ, de Bloom J, Korpela K, Kinnunen U. Enhancing daily well-being at work through lunchtime park walks and relaxation exercises: Recovery experiences as mediators. J Occup Health Psychol. 2018 Jul;23(3):428. doi: 10.1037/ocp0000083 28358570 Wendsche J, Lohmann-Haislah A, Wegge J. The impact of supplementary short rest breaks on task performance: A meta-analysis. Sozialpolitik. ch. 2016;2(2):2–3. doi: 10.18753/2297-8224-75 Bennett AA, Gabriel AS, Calderwood C. Examining the interplay of micro-break durations and activities for employee recovery: A mixed-methods investigation. J Occup Health Psychol. 2020 Apr;25(2):126. doi: 10.1037/ocp0000168 31464460 McLean L, Tingley M, Scott RN, Rickards J. Computer terminal work and the benefit of microbreaks. Appl Ergon. 2001 Jun 1;32(3):225–37. doi: 10.1016/s0003-6870(00)00071-5 11394463 Kim S, Park Y, Niu Q. Micro‐break activities at work to recover from daily work demands. J Organ Behav. 2017 Jan;38(1):28–44. doi: 10.1002/job.2109 Kim S, Park Y, Headrick L. Daily micro-breaks and job performance: General work engagement as a cross-level moderator. J Appl Psychol. 2018 Jul;103(7):772. doi: 10.1037/apl0000308 29595289 Zacher H, Brailsford HA, Parker SL. Micro-breaks matter: A diary study on the effects of energy management strategies on occupational well-being. J Vocat Behav. 2014 Dec 1;85(3):287–97. doi: 10.1016/j.jvb.2014.08.005 Scholz A, Wendsche J, Ghadiri A, Singh U, Peters T, Schneider S. Methods in Experimental work break research: a scoping review. Int J Environ Res Public Health. 2019 Jan;16(20):3844. doi: 10.3390/ijerph16203844 31614598 Almén N, Lisspers J, Öst LG, Sundin Ö. Behavioral stress recovery management intervention for people with high levels of perceived stress: A randomized controlled trial. Int J Stress Manag. 2020 May;27(2):183. doi: 10.1037/str0000140 Beute F, Kaiser FG, Haans A, de Kort Y. Striving for mental vigor through restorative activities: Application of the Campbell Paradigm to construct the Attitude toward Mental Vigor scale. Ment Health Prev. 2017 Dec 1;8:20–6. doi: 10.1016/j.mhp.2017.09.001 Geurts SA, Sonnentag S. Recovery as an explanatory mechanism in the relation between acute stress reactions and chronic health impairment. Scand J Work Environ Health. 2006 Dec 1:482–92. doi: 10.5271/sjweh.1053 17173204 Zhu Z, Kuykendall L, Zhang X. The impact of within‐day work breaks on daily recovery processes: An event‐based pre‐/post‐experience sampling study. J Occup Organ Psychol. 2019 Mar;92(1):191–211. doi: 10.1111/joop.12246 Sluiter JK, Frings-Dresen MH, Meijman TF, Van Der Beek AJ. Reactivity and recovery from different types of work measured by catecholamines and cortisol: a systematic literature overview. Occup Environ Med. 2000 May 1;57(5):298–315. doi: 10.1136/oem.57.5.298 10769296 Bennett AA, Bakker AB, Field JG. Recovery from work‐related effort: A meta‐analysis. J Organ Behav. 2018 Mar;39(3):262–75. doi: 10.1002/job.2217 Blanco-Encomienda FJ, García-Cantero R, Latorre-Medina MJ. Association between work-related rumination, work environment and employee well-being: A meta-analytic study of main and moderator effects. Soc Indic Res. 2020 Aug;150(3):887–910. doi: 10.1007/s11205-020-02356-1 Steed LB, Swider BW, Keem S, Liu JT. Leaving work at work: A meta-analysis on employee recovery from work. J Manag. 2021 Apr;47(4):867–97. doi: 10.1177/0149206319864153 Sweller J. Cognitive load theory. Psychol Learn Motiv 2011 Jan 1. doi: 10.1016/B978-0-12-387691-1.00002–8 De Jong T. Cognitive load theory, educational research, and instructional design: Some food for thought. Instr Sci. 2010 Mar;38(2):105–34. doi: 10.1007/s11251-009-9110-0 Kirschner PA. Cognitive load theory: Implications of cognitive load theory on the design of learning. Learn Instr. 2002 Feb 1;12(1):1–0. doi: 10.1016/S0959-4752(01)00014-7 Paas F, Van Gog T, Sweller J. Cognitive load theory: New conceptualizations, specifications, and integrated research perspectives. Educational psychology review. 2010 Jun;22(2):115–21. doi: 10.1007/s10648-010-9133-8 Hobfoll SE. Conservation of resources: a new attempt at conceptualizing stress. Am Psychol. 1989 Mar;44(3):513. doi: 10.1037//0003-066x.44.3.513 2648906 Hobfoll SE. Social and psychological resources and adaptation. Rev Gen Psychol. 2002 Dec;6(4):307–24. doi: 10.1037/1089-2680.6 Kirkegaard Thomsen D. The association between rumination and negative affect: A review. Cogn Emot. 2006 Dec 1;20(8):1216–35. doi: 10.1080/02699930500473533 Kühnel J, Sonnentag S, Westman M. Does work engagement increase after a short respite? The role of job involvement as a double‐edged sword. J Occup Organ Psychol. 2009 Sep;82(3):575–94. doi: 10.1348/096317908X349362 Kaplan S. The restorative benefits of nature: Toward an integrative framework. J Environ Psychol. 1995 Sep 1;15(3):169–82. doi: 10.1016/0272-4944(95)90001-2 Ulrich RS. Aesthetic and affective response to natural environment. In Altman I, Wohlwill JF, editors. Behavior and the natural environment. Boston: Springer; 1983. pp. 85–125. Bowler DE, Buyung-Ali LM, Knight TM, Pullin AS. A systematic review of evidence for the added benefits to health of exposure to natural environments. BMC Public Health. 2010 Dec;10(1):1–0. doi: 10.1186/1471-2458-10-456 20684754 Korpela KM, Ylén M, Tyrväinen L, Silvennoinen H. Favorite green, waterside and urban environments, restorative experiences and perceived health in Finland. Health Promot Int. 2010 Jun 1;25(2):200–9. doi: 10.1093/heapro/daq007 20176589 Rydstedt LW, Johnsen SÅ. Towards an integration of recovery and restoration theories. Heliyon. 2019 Jul 1;5(7): e02023. doi: 10.1016/j.heliyon.2019.e02023 31372527 van Hooff ML, Geurts SA. Need satisfaction and employees’ recovery state at work: A daily diary study. J Occup Health Psychol. 2015 Jul;20(3):377. doi: 10.1037/a0038761 25705912 Hobfoll S, Shirom A. Conservation of resources theory: Applications to stress and management in the workplace. Public Policy Adm. 2001;87:57–80 Schaufeli WB, Bakker AB. Job demands, job resources, and their relationship with burnout and engagement: A multi‐sample study. J Organ Behav. 2004 May;25(3):293–315. doi: 10.1002/job.248 Campbell JP, McCloy RA, Oppler SH, Sager CE. A theory of performance. Personnel selection in organizations. 1993;3570:35–70. Helton WS, Russell PN. Rest is still best: The role of the qualitative and quantitative load of interruptions on vigilance. Hum Factors. 2017 Feb;59(1):91–100. doi: 10.1177/0018720816683509 28146674 Beute F, De Kort YA. Natural resistance: Exposure to nature and self-regulation, mood, and physiology after ego-depletion. J Environ Psychol. 2014 Dec 1;40:167–78. doi: 10.1016/j.jenvp.2014.06.004 Michishita R, Jiang Y, Ariyoshi D, Yoshida M, Moriyama H, Obata Y, et al. The introduction of an active rest program by workplace units improved the workplace vigor and presenteeism among workers. J Occup Environ Med. 2017 Dec 1;59(12):1140–7. doi: 10.1097/JOM.0000000000001121 28816734 Michishita R, Jiang Y, Ariyoshi D, Yoshida M, Moriyama H, Yamato H. The practice of active rest by workplace units improves personal relationships, mental health, and physical activity among workers. J Occup Health. 2017:16–0182. doi: 10.1539/joh.16-0182-OA 27980249 Trougakos JP, Hideg I. Momentary work recovery: The role of within-day work breaks. In Sonnentag S, Perrewé PL, Ganster DC, editors. Current perspectives on job-stress recovery. Emerald Group Publishing Limited; 2009. pp. 37–84. doi: 10.1108/S1479-3555(2009)0000007005 De Bloom J, Kinnunen U, Korpela K. Recovery processes during and after work. J Occup Environ Med. 2015 Jul 1;57(7):732–42. doi: 10.1097/JOM.0000000000000475 26147541 Bosch C, Sonnentag S, Pinck AS. What makes for a good break? A diary study on recovery experiences during lunch break. J Occup Organ Psychol. 2018 Mar;91(1):134–57. doi: 10.1111/joop.12195 Fritz C, Ellis AM, Demsky CA, Lin BC, Guros F. Embracing work breaks. Organ Dyn. 2013 Jan 1;42(4):274–80. doi: 10.1016/j.orgdyn.2013.07.005 Henning RA, Jacques P, Kissel GV, Sullivan AB, Alteras-Webb SM. Frequent short rest breaks from computer work: effects on productivity and well-being at two field sites. Ergonomics. 1997 Jan 1;40(1):78–91. doi: 10.1080/001401397188396 8995049 Lacaze DH, Sacco ID, Rocha LE, Pereira CA, Casarotto RA. Stretching and joint mobilization exercises reduce call-center operators’ musculoskeletal discomfort and fatigue. Clinics. 2010;65(7):657–62. doi: 10.1590/S1807-59322010000700003 20668622 Kühnel J, Vahle-Hinz T, de Bloom J, Syrek CJ. Staying in touch while at work: Relationships between personal social media use at work and work-nonwork balance and creativity. Int J Hum Resour Man. 2020 May 30;31(10):1235–61. doi: 10.1080/09585192.2017.1396551 Rieger D, Reinecke L, Bente G. Media-induced recovery: The effects of positive versus negative media stimuli on recovery experience, cognitive performance, and energetic arousal. Psychol Pop Media Cult. 2017 Apr;6(2):174. doi: 10.1037/ppm0000075 Henning RA, Sauter SL, Salvendy G, Krieg EF Jr. Microbreak length, performance, and stress in a data entry task. Ergonomics. 1989 Jul 1;32(7):855–64. doi: 10.1080/00140138908966848 2806221 Lee KE, Williams KJ, Sargent LD, Williams NS, Johnson KA. 40-second green roof views sustain attention: The role of micro-breaks in attention restoration. J Environ Psychol. 2015 Jun 1;42:182–9. doi: 10.1016/j.jenvp.2015.04.003 Tucker P. The impact of rest breaks upon accident risk, fatigue and performance: a review. Work Stress. 2003 Apr 1;17(2):123–37. doi: 10.1080/0267837031000155949 Bakker AB, Demerouti E, Oerlemans W, Sonnentag S. Workaholism and daily recovery: A day reconstruction study of leisure activities. J Organ Behav. 2013 Jan;34(1):87–107. doi: 10.1002/job.1796 Claessens BJ, Van Eerde W, Rutte CG, Roe RA. Things to do today. . .: A daily diary study on task completion at work. Appl Psychol. 2010 Apr;59(2):273–95. doi: 10.1111/j.1464-0597.2009.00390.x Clark RC, Nguyen F, Sweller J. Efficiency in learning: Evidence-based guidelines to manage cognitive load. John Wiley & Sons; 2011 Mayer RE, Moreno R. Nine ways to reduce cognitive load in multimedia learning. Educ Psychol. 2003 Mar 1;38(1):43–52. doi: 10.1207/S15326985EP3801_6 Newell A, Simon HA. Human problem solving. Englewood Cliffs, NJ: Prentice-hall; 1972 Jun 1. Paas F, Sweller J. An evolutionary upgrade of cognitive load theory: Using the human motor system and collaboration to support the learning of complex cognitive tasks. Educ Psychol Rev. 2012 Mar;24(1):27–45. doi: 10.1007/s10648-011-9179-2 Curtin A, Tong S, Sun J, Wang J, Onaral B, Ayaz H. A systematic review of integrated functional near-infrared spectroscopy (fNIRS) and transcranial magnetic stimulation (TMS) studies. Front Neurosci. 2019 Feb 28;13:84. doi: 10.3389/fnins.2019.00084 30872985 Schumann F, Steinborn MB, Kürten J, Cao L, Händel BF, Huestegge L. Restoration of Attention by Rest in a Multitasking World: Theory, Methodology, and Empirical Evidence. Front. Psychol. 2022;13:867978. doi: 10.3389/fpsyg.2022.867978 35432083 Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021 Apr 1;88:105906. doi: 10.1136/bmj.n71 33782057 Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al, editors. Cochrane handbook for systematic reviews of interventions. John Wiley & Sons; 2011. Available at: https://handbook-5-1.cochrane.org/ Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to Meta-Analysis. John Wiley and Sons, 2009. 421 p. https://doi.org/10.1002/9780470743386 Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. New York: Routledge; 1988. doi: 10.4324/9780203771587 Blasche G, Pfeffer M, Thaler H, Gollner E. Work-site health promotion of frequent computer users: comparing selected interventions. Work. 2013 Jan 1;46(3):233–41. doi: 10.3233/WOR-121520 23324690 Clauss E, Hoppe A, O’Shea D, González Morales MG, Steidle A, Michel A. Promoting personal resources and reducing exhaustion through positive work reflection among caregivers. J Occup Health Psychol. 2018 Jan;23(1):127. doi: 10.1037/ocp0000063 27936830 Conlin A, Hu X, Barber LK. Comparing relaxation versus mastery microbreak activity: a within-task recovery perspective. Psychol Rep. 2021 Feb;124(1):248–65. doi: 10.1177/0033294119900347 31918612 Ellwood S, Pallier G, Snyder A, Gallate J. The incubation effect: hatching a solution?. Creat Res J. 2009 Feb 9;21(1):6–14. doi: 10.1080/10400410802633368 Janicke SH, Rieger D, Reinecke L, Connor W. Watching online videos at work: The role of positive and meaningful affect for recovery experiences and well-being at the workplace. Mass Commun Soc. 2018 May 4;21(3):345–67. doi: 10.1080/15205436.2017.1381264 Paulus PB, Nakui T, Putman VL, Brown VR. Effects of task instructions and brief breaks on brainstorming. Group Dyn. 2006 Sep;10(3):206. doi: 10.1037/1089-2699.10.3.206 Rees A, Wiggins MW, Helton WS, Loveday T, O’Hare D. The impact of breaks on sustained attention in a simulated, semi‐automated train control task. Appl Cogn Psychol. 2017 May;31(3):351–9. doi: 10.1002/acp.3334 Kennedy GA, Ball H. Power break: A brief hypnorelaxation program to reduce work-related fatigue and improve work satisfaction, productivity, and well-being. Aust J Clin Exp Hypn. 2007 Nov 1;35(2):169–93. Steinborn MB, Huestegge L. A walk down the lane gives wings to your brain. Restorative benefits of rest breaks on cognition and self‐control. Appl Cogn Psychol. 2016 Sep;30(5):795–805. doi: 10.1002/acp.3255 Borenstein M, Higgins JP, Hedges LV, Rothstein HR. Basics of meta‐analysis: I2 is not an absolute measure of heterogeneity. Res Synth Methods. 2017 Mar;8(1):5–18. doi: 10.1002/jrsm.1230 28058794 Kepes S, McDaniel MA, Brannick MT, Banks GC. Meta-analytic reviews in the organizational sciences: Two meta-analytic schools on the way to MARS (the Meta-Analytic Reporting Standards). J Bus Psychol. 2013 Jun;28(2):123–43. doi: 10.1007/s10869-013-9300-2 Viechtbauer W, Cheung MW. Outlier and influence diagnostics for meta‐analysis. Res Synth Methods. 2010 Apr;1(2):112–25. doi: 10.1002/jrsm.11 26061377 Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997 Sep 13;315(7109):629–34. doi: 10.1136/bmj.315.7109.629 9310563 Duval S, Tweedie R. Trim and fill: a simple funnel‐plot–based method of testing and adjusting for publication bias in meta‐analysis. Biometrics. 2000 Jun;56(2):455–63. doi: 10.1111/j.0006-341x.2000.00455.x 10877304 Borenstein M, Hedges L, Higgins J, Rothstein H. Comprehensive meta-analysis version 3 [software] Biostat. Englewood, NJ. 2013. Blake H, Lai B, Coman E, Houdmont J, Griffiths A. Move-It: a cluster-randomised digital worksite exercise intervention in China: outcome and process evaluation. Int J Environ Res Public Health. 2019 Jan;16(18):3451. doi: 10.3390/ijerph16183451 31533292 Finstad K, Bink M, McDaniel M, Einstein GO. Breaks and task switches in prospective memory. Appl Cogn Psychol. 2006 Jul;20(5):705–12. doi: 10.1002/acp.1223 Steidle A, Gonzalez-Morales MG, Hoppe A, Michel A, O’shea D. Energizing respites from work: a randomized controlled study on respite interventions. Eur J Work Organ Psychol. 2017 Sep 3;26(5):650–62. doi: 10.1080/1359432x.2017.1348348 Wollseiffen P, Ghadiri A, Scholz A, Strüder HK, Herpers R, Peters T, et al. Short bouts of intensive exercise during the workday have a positive effect on neuro‐cognitive performance. Stress Health. 2016 Dec;32(5):514–23. doi: 10.1002/smi.2654 26449710 Thayer RE. Activation-deactivation adjective check list: Current overview and structural analysis. Psychol Rep. 1986 Apr;58(2):607–14. doi: 10.2466/pr0.1986.58.2.607 Schaufeli WB, Bakker AB, Salanova. Utrecht work engagement scale-9. Educ Psychol Meas. 2003. doi: 10.1037/t05561-000 McNair DM, Lorr M, Droppleman LF. Manual profile of mood states. San Diego, CA: Educational and Industrial Testing Services; 1971. Dijksterhuis A, Aarts H. Goals, Attention, And (Un)Consciousness. Annu Rev Psychol. 2010; 61(1):467–490. doi: 10.1146/annurev.psych.093008.100445 19566422 Posner MI, Rothbart MK. Research on attention networks as a model for the integration of psychological science. Annu Rev Psychol. 2007 Jan; 58: 1–23. doi: 10.1146/annurev.psych.58.110405.085516 17029565 Fan J, Wu Y, Fossella JA, Posner MI. Assessing the heritability of attentional networks. BMC Neurosci. 2001 Sep 14; 2(1): 1–7. doi: 10.1186/1471-2202-2-14 11580865 Hofmann W, Gschwendner T, Friese M, Wiers RW, Schmitt M. Working memory capacity and self-regulatory behavior: Toward an individual differences perspective on behavior determination by automatic versus controlled processes. Pers Processes Ind Differ. 2008; 95(4): 962–977. doi: 10.1037/a0012705 18808271 Sio UN, Ormerod TC. Does incubation enhance problem solving? A meta-analytic review. Psychol Bull. 2009 Jan;135(1):94–120. doi: 10.1037/a0014212 19210055 Ohly S, Sonnentag S, Pluntke F. Routinization, work characteristics and their relationships with creative and proactive behaviors. J Organ Behav. 2006 May;27(3):257–79. doi: 10.1002/job.376 Desrochers TM, Amemori KI, Graybiel AM. Habit learning by naive macaques is marked by response sharpening of striatal neurons representing the cost and outcome of acquired action sequences. Neuron. 2015 Aug 19;87(4):853–68. doi: 10.1016/j.neuron.2015.07.019 26291166 Weichbrodt J, Grote G. Rules and Routines in Organizations: a review and extension. In Fourth International Conference on Organizational Routines. Nice/France 2010 Jun 11 (pp. 1–35). Khalil R, Godde B, Karim AA. The link between creativity, cognition, and creative drives and underlying neural mechanisms. Front Neural Circuits. 2019 Mar 22;13:18. doi: 10.3389/fncir.2019.00018 30967763 Gilhooly KJ, Fioratou E, Anthony SH, Wynn V. Divergent thinking: Strategies and executive involvement in generating novel uses for familiar objects. Br J Psychol. 2007 Nov;98(4):611–25. doi: 10.1111/j.2044-8295.2007.tb00467.x 17535464 Beaty RE, Seli P, Schacter DL. Network neuroscience of creative cognition: mapping cognitive mechanisms and individual differences in the creative brain. Curr Opin Behav Sci. 2019 Jun 1;27:22–30. doi: 10.1016/j.cobeha.2018.08.013 30906824 Benedek M, Könen T, Neubauer AC. Associative abilities underlying creativity. Psychol Aesthet Creat Arts. 2012 Aug;6(3):273. doi: 10.1037/a0027059 Nijstad BA, De Dreu CK, Rietzschel EF, Baas M. The dual pathway to creativity model: Creative ideation as a function of flexibility and persistence. Eur Rev Soc Psychol. 2010 Mar 1;21(1):34–77. doi: 10.1080/10463281003765323 Lim J, Quevenco FC, Kwok K. EEG alpha activity is associated with individual differences in post-break improvement. Neuroimage. 2013 Aug;76(1):81–9. doi: 10.1016/j.neuroimage.2013.03.018 23523810 Scholz A, Ghadiri A, Singh U, Wendsche J, Peters T, Schneider S. Functional work breaks in a high-demanding work environment: an experimental field study. Ergonomics. 2018;61(2):255–64. doi: 10.1080/00140139.2017.1349938 28679350 Sun Y, Lim J, Dai Z, Wong K, Taya F, Chen Y, et al. The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study. Neuroimage. 2017 May 15; 152:19–30. doi: 10.1016/j.neuroimage.2017.02.084 28257928 Centofanti SA, Hilditch CJ, Dorrian J, Banks S. The impact of short night-time naps on performance, sleepiness and mood during a simulated night shift. Chronobiol Int. 2016;33(6):706–15. doi: 10.3109/07420528.2016.1167722 27077524 Centofanti SA, Dorrian J, Hilditch CJ, Banks S. Do night naps impact driving performance and daytime recovery sleep?. Accid Anal Prev. 2017 Febr; 99:416–21. doi: 10.1016/j.aap.2015.11.009 26616017 Neri DF, Oyung RL, Colletti LM, Mallis MM, Tam PY, Dinges DF. Controlled breaks as a fatigue countermeasure on the flight deck. Aviat Space Environ Med. 2002;73(7): 654–64. 12137101 Hallbeck MS, Lowndes BR, Bingener J, Abdelrahman AM, Yu D, Bartley A, et al. The impact of intraoperative microbreaks with exercises on surgeons: A multi-center cohort study. Appl Ergon. 2017 Apr; 60:334–41. doi: 10.1016/j.apergo.2016.12.006 28166893 Park AE, Zahiri HR, Hallbeck MS, Augenstein V, Sutton E, Yu D et al. Intraoperative “Micro Breaks” With Targeted Stretching Enhance Surgeon Physical Function and Mental Focus. Ann Surg. 2017 Febr; 265(2):340–46. doi: 10.1097/SLA.0000000000001665 28059962 Nakphet N, Chaikumarn M, Janwantanakul P. Effect of Different Types of Rest-Break Interventions on Neck and Shoulder Muscle Activity, Perceived Discomfort and Productivity in Symptomatic VDU Operators: A Randomized Controlled Trial. Int J Occup Saf Ergon. 2014;20(2): 339–53. doi: 10.1080/10803548.2014.11077048 24934429 Ding L, Molina JS. ‘Forced Automation’by COVID-19? Early Trends from Current Population Survey Data. Federal Reserve Bank of Philadelphia September 2020. 2020 Sep 14. Sidle SD. Counterproductive Work Behavior: Can It Sometimes Be Good to Be Bad?. Acad Manag Perspect. 2010 Aug;24(3):101–3. doi: 10.5465/amp.24.3.101 Ouweneel E, Le Blanc PM, Schaufeli WB. Flourishing students: A longitudinal study on positive emotions, personal resources, and study engagement. J Posit Psychol. 2011 Mar 1;6(2):142–53. doi: 10.1080/17439760.2011.558847 Salanova M, Schaufeli W, Martínez I, Bresó E. How obstacles and facilitators predict academic performance: The mediating role of study burnout and engagement. Anxiety Stress Coping. 2010 Jan 1;23(1):53–70. doi: 10.1080/10615800802609965 19326271 Berkeley Center for Teaching and Learning. Considerations for Large Lecture Classes. 2022 [cited 7 February 2022]. Available from: https://teaching.berkeley.edu/considerations-large-lecture-classes LSA Technology Services University of Michigan. Limiting Zoom Fatigue and Implementing Breaks. 2020 Sep 9 [cited 7 February 2022]. Available from: https://lsa.umich.edu/technology-services/news-events/all-news/teaching-tip-of-the-week/limiting-zoom-fatigue-and-implementing-breaks.html Blasche G, Szabo B, Wagner‐Menghin M, Ekmekcioglu C, Gollner E. Comparison of rest‐break interventions during a mentally demanding task. Stress Health. 2018; 34(5):629–38. doi: 10.1002/smi.2830 30113771 Hunter JE, Schmidt FL. Methods of Meta-analysis: Correcting Error and Bias in Research Findings (2nd ed.). Newbury Park, CA: Sage Publications; 2004. Wiernik BM, Dahlke JA. Obtaining unbiased results in meta-analysis: The importance of correcting for statistical artifacts. Adv Methods Pract Psychol Sci. 2020;3(1), 94–123. doi: 10.1177/2515245919885611 Donaldson SI, Grant-Vallone EJ. Understanding self-report bias in organizational behavior research. J Bus Psychol. 2002 Dec;17(2):245–60. doi: 10.1023/A:1019637632584 Thayer RE. The biopsychology of mood and arousal. Oxford University Press; 1990 Sep 27. Watson D, Wiese D, Vaidya J, Tellegen A. The two general activation systems of affect: Structural findings, evolutionary considerations, and psychobiological evidence. J Pers Soc Psychol. 1999 May;76(5):820. doi: 10.1037/0022-3514.76.5.820 Lee K, Sargent LD, Williams K, Williams N, Johnson K. Green micro-breaks: Viewing workplace nature improves mood and performance. In Academy of Management Proceedings 2017 (Vol. 2017, No. 1, p. 11996). Briarcliff Manor, NY 10510: Academy of Management. doi: 10.5465/ambpp.2017.247 Rudolph CW, Allan B, Clark M, Hertel G, Hirschi A, Kunze F, et al. Pandemics: Implications for research and practice in industrial and organizational psychology. Ind Organ Psychol. 2021 Jun;14(1–2):1–35. doi: 10.31234/osf.io/k8us2 10.1371/journal.pone.0272460.r001 Decision Letter 0 Steinborn Michael B. Section Editor 2022 Michael B. 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2 May 2022

PONE-D-22-07400Let's take a break! A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performancePLOS ONE

Dear Dr. Macsinga,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Editorial comment: Two expert reviewers commented on your manuscript. As you can see, both referees seem to consider you work important overall, while at the same time provided a whole number of additional points that might be useful to consider during the revision of the manuscript. To name the most important points, both referees raised the methodical points of how to best quantify study results, and when to consider a qualitative evaluation of aspects of the studies. Here, both refer to findings on the connection between experience and performance (which sometimes go together, othertimes not), and, to the reliability of the underlying tests and performance measures. My personal suggestion is to also consider that there are different options to compute rest break effects and to take this into account (if necessary, in a more qualitative way by discussing it). Overall, this work is very useful contribution of the field, and I would invite you preparing a revision of your work that addresses all points together with a cover letter that provides point-by-point replies. 

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: N/A

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: Dear colleagues,

this is a very thorough meta-analysis on a very important topic from work and organizational research:

the effects of short rest breaks on strain, motivation and perfromance.

I really liked to read the paper and the quality, so far, is very impressive.

However, I have some further suggestions for improvement before a publication is warranted.

1) When reporting I2 please use superscript for '2' => I²

2) p.2, l.34: "Sub-groups analyses on performance types revealed significant effects only for tasks with less cognitive demands".

3) Overall, the data support the role of micro-breaks for well-being, while for performance, recovering from highly depleting tasks may need more than 10-minute breaks. Therefore, future studies should focus on this issue.

[Or what do you mean specifcally with 'process'?)

4) p. 5, l. 120: Please revise the sentence and refer to the study: for example

"For instance, in one study many of emplyoees reported break activities were negatively associated with increased energy (i.e., vitality) but positively related to fatigue [5]."

5) p.13., l. 303: "The main research questions were addressed using random-effects meta-analyses

based on Borenstein et al.'s [72] framework."

6) 13, l. 306: "two-sided p-values".

7) p.14. l329-330: τ² (Suberscript)

8) p.16: 365-376: The numbers do not fully match with the data in the flow diagramm: please check this

9) I missed a number of studies that might have matched with your inclusion criteria. Did you found them during search?

Singh, U., Ghadiri, A., Weimar, D., & Prinz, J. (2020). “Let’s have a break”: An experimental comparison of work-break interventions and their impact on performance. Journal of Business Research, 112, 128-135.

Blasche, G., Szabo, B., Wagner‐Menghin, M., Ekmekcioglu, C., & Gollner, E. (2018). Comparison of rest‐break interventions during a mentally demanding task. Stress and Health, 34(5), 629-638.

10.) p.21, l.385+386 should be deleted

11) p.33, l.665 "However, at least for well-being, the answer seems to be "any type of decoupling activity" (delete comma)

12) p.30: l.581: you write voluntary but to my impression the breaks were forced (involuntary)

13) p.30, l.587 fits with that meta-analysis

Sio, U. N., & Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin, 135(1), 94.

14) p.33: Another option would be adjusting for reliabilty of measure within the meta-analysis (see Schmidt-Hunter-Approach)

Reviewer #2: The authors present an manuscript that deals with an important topic, the influence of rest breaks on feelings and performance, which is well written overall and personally interesting to me as a reader. Being a professor in personnel psychology and statistics, I will judge the manuscript with a focus on concept and methodology. See below for detailed comments.

## the abstract need revision. the abstract should include the research question, the methods and the results but in a comprehensible way. statistics or other details or specifics should not be referred to in the abstract.

## The writing is good, and the manuscript is generally interesting to read. It is also theoretically well argued, and to the point. There are some points to consider. The first concerns the instruments to measures effects of breaks, it can be a rating scale or a performance output but the effect size is difficult to compare directly, even between performance outputs of different tasks, not to speak of between feelings and performance. It depends on how good the psychometric quality of the measure is. For example, 30 min of a vigilance task deliver only a few measurement units while 10 min of a self-paced task provide a huge amount of trials to obtain reliable measures, and statistics crucially depend on it. (suggested reference: Schumann et al. (2022). Restoration of attention by rest in a multitasking world: Theory, methodology, and empirical evidence. Frontiers in Psychology, 13, 867978. doi:10.3389/fpsyg.2022.867978

## definitions of micro breaks fit with the meaning used in work psychology. I have no problem with this definition because the authors explain everything well in the manuscript, so there is no ambivalence. On the other hand, researcher with a more cognitive experimental focus often differ in the use of what is a micro break versus a short break versus long breaks. This might be discussed.

## glucose and depletion of resources. in the manuscript, the authors often refer to how task deplete mental resource in a way that gives the impression of a strong underlying basis of biology and physiology. On one occasion, for example, glucose is referred to as a causal factor determining resources. This is a difficult question, I would suggest reconsidering this point, it is in my opinion not clear.

## tables. If possible, the tables should be presented in APA norm and maybe in a more economic way, The tables are huge and exceed a page. If the authors find ways to organise this more economically, good, otherwise, it is also okay, I would be fine with the present version.

**********

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Reviewer #1: Yes: Johannes Wendsche

Reviewer #2: No

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 10.1371/journal.pone.0272460.r002 Author response to Decision Letter 0 Submission Version 1

14 Jun 2022

Ref: PONE-D-22-07400

Title: Let's take a break! A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance

Authors: Patricia Albulescu, Irina Macsinga, Andrei Rusu, Coralia Sulea, Alexandra Bodnaru, Bogdan Tudor Tulbure

RESPONSE LETTER

Dear dr. Steinborn,

Thank you for granting us the opportunity to revise and resubmit our manuscript and thank you for the feedback and extremely valuable comments for improving the quality of the paper. In the following, we will answer each and every suggestion in a point-by-point manner.

But first of all, we want to mention that when we decided on the title for the manuscript, unfortunately, we did not pay enough attention to notice that there are other published articles (even in our search results) using a similar syntagm, such we used (i.e., "Let’s have a break"), in their title (e.g., Singh, U., Ghadiri, A., Weimar, D., & Prinz, J. (2020). “Let’s take a break”: An experimental comparison of work-break interventions and their impact on performance. Journal of Business Research, 112, 128-135.).

Thus, we suggest a slight modification to the tile, by using a syntagm that seems not to be found in other article titles (at least based on a google scholar search).

Initial title: Let's take a break! A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance

New title: "Give me a break!" A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance

Responses to the section editor’s observations

The main point and overall impression:

As you can see, both referees seem to consider you work important overall, while at the same time provided a whole number of additional points that might be useful to consider during the revision of the manuscript. To name the most important points, both referees raised the methodical points of how to best quantify study results, and when to consider a qualitative evaluation of aspects of the studies. Here, both refer to findings on the connection between experience and performance (which sometimes go together, other times not), and, to the reliability of the underlying tests and performance measures. My personal suggestion is to also consider that there are different options to compute rest break effects and to take this into account (if necessary, in a more qualitative way by discussing it).

Overall, this work is very useful contribution of the field, and I would invite you preparing a revision of your work that addresses all points together with a cover letter that provides point-by-point replies.

<Response> Thank you for your positive feedback and the chance to revise the manuscript! As we also developed in the responses to each reviewer, the possibility to control for psychometric artefacts (reliability estimates) based on Hunter and Schmidt’s approach was limited by inconsistencies in reporting such estimates for vigor and fatigue, and with an almost total lack of reporting for the performance outcomes (with two exceptions). Hence the decision to entirely apply Borenstein et al.’s framework for the meta-analysis. But we agree that this may be an important aspect, and as you rightfully suggested, we developed and inserted in the manuscript a detailed discussion of this limitation and its implications. We also discussed and accentuated the cautionary note regarding the diversity and lack of consistency when it comes to approaches for performance and the consequential potential sources of bias. These aspects were developed (1) at the end of the Introduction (by adding new details to the already existing mentions on measurement and conceptualization issues), (2) in the Description of the included studies subsection from Results (we developed on the operationalizations being used in the included studies by critically uprising their reliability, threats to reliability and the general inconsistencies in approaches), (3) in the Discussion when presenting the results on the performance outcome as also in the Limitations subsection. This way the reader will get a stronger critical appraisal of this body of literature.

Additional requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

<Response> The elements related to style requirements were checked again against PlosOne’s specifications.

2. We note that you have provided funding information. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement.

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

<Response> The “Financial Disclosure Statement” was removed from the manuscript. The information related to funding can be found in the “Funding Statement” document. No update is required on this funding statement.

3. We note that this manuscript is a systematic review or meta-analysis; our author guidelines therefore require that you use PRISMA guidance to help improve reporting quality of this type of study. Please upload copies of the completed PRISMA checklist as Supporting Information with a file name “PRISMA checklist”.

<Response> The filled-in PRISMA checklist was uploaded as Supporting Information the following journal guidelines (i.e., Supporting Information files should be saved as “S1_Fig.tif”, “S1_File.pdf”, etc.) as “S4_Table”. After revision, the file name was changed from “S4_Table” to “S4_Table. PRISMA Checklist”.

Responses to the first reviewer’s comments

Overall impression:

This is a very thorough meta-analysis on a very important topic from work and organizational research: the effects of short rest breaks on strain, motivation and perfromance. I really liked to read the paper and the quality, so far, is very impressive. However, I have some further suggestions for improvement before a publication is warranted.

<Response> Thank you for your positive feedback and appreciation!

Comments #1 to #7:

(1) When reporting I2 please use superscript for '2' => I²;

(2) p.2, l.34: "Sub-groups analyses on performance types revealed significant effects only for tasks with less cognitive demands".

(3) Overall, the data support the role of micro-breaks for well-being, while for performance, recovering from highly depleting tasks may need more than 10-minute breaks. Therefore, future studies should focus on this issue. [Or what do you mean specifcally with 'process'?)

(4) p. 5, l. 120: Please revise the sentence and refer to the study: for example

"For instance, in one study many of emplyoees reported break activities were negatively associated with increased energy (i.e., vitality) but positively related to fatigue [5]."

(5) p.13., l. 303: "The main research questions were addressed using random-effects meta-analyses based on Borenstein et al.'s [72] framework."

(6) 13, l. 306: "two-sided p-values".

(7) p.14. l329-330: τ² (Suberscript)

<Response> Thank you for the detailed observations! All these suggestions were considered and can be found modified (with track changes) in the revised manuscript.

Comment #8: p.16: 365-376: The numbers do not fully match with the data in the flow diagram: please check this.

<Response> Thank you for noticing this! We checked the information and the results of the search process. By mistake, in the text were reported 15 records instead of 25 excluded with reason (as correctly reported on the flow chart). The correction was made accordingly.

Comment #9: I missed a number of studies that might have matched with your inclusion criteria. Did you find them during search?

Singh, U., Ghadiri, A., Weimar, D., & Prinz, J. (2020). “Let’s have a break”: An experimental comparison of work-break interventions and their impact on performance. Journal of Business Research, 112, 128-135.

Blasche, G., Szabo, B., Wagner‐Menghin, M., Ekmekcioglu, C., & Gollner, E. (2018). Comparison of rest‐break interventions during a mentally demanding task. Stress and Health, 34(5), 629-638.

<Response> We found one of the suggested studies. The first study, conducted by Singh et al. (2020), was found during the systematic search but was excluded from further analysis (records excluded with reason) as it was deemed not eligible because it tested three parallel interventions with no control group to serve as a comparison (see the Comparator criterion from the PICOS – ‘Eligibility criteria’ section of the manuscript). The second study done by Blasche et al. (2018) did not appear in the initial systematic literature search. Analyzing it and applying our inclusion/exclusion criteria, we found it also not eligible as the task in which participants were engaged (from which the micro-break was taken) does not have a correspondence in the occupational setting. Moreover, as the authors conclude, “Though an academic class imposes demands also found in other kinds of mental work, and both academic classwork and office work lead to fatigue, office work and work in an academic class are obviously not identical. This warrants caution in generalizing the current findings to other contexts of mental work (p. 636)”. All other papers included in this meta-analysis used tasks with some degree of similarity with those specific to the job environment.

However, after reading again our manuscript, we noticed that the exclusion of the non-work-related studies was not made clear enough, thus in the revised version, we made this explicit mention for the eligibility criteria. Moreover, based on Blasche et al.’s (2018) suggestion we also lowered our tone on a cautionary note in the discussion of the implications of our meta-analysis for the educational setting.

Comments #10 to #12:

(10) p.21, l.385+386 should be deleted

(11) p.33, l.665 "However, at least for well-being, the answer seems to be "any type of decoupling activity" (delete comma)

(12) p.30: l.581: you write voluntary but to my impression the breaks were forced (involuntary)

<Response> All suggestions were included in the new version of the manuscript.

Comment #13: p.30, l.587 fits with that meta-analysis

Sio, U. N., & Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin, 135(1), 94.

<Response> We checked the suggested reference and thank you for pointing it out. Indeed, it fits with the drawn conclusion, and we included a mention based on it in the new version of the manuscript. Accordingly, the References section was also updated.

Comment #14: p.33: Another option would be adjusting for reliabilty of measure within the meta-analysis (see Schmidt-Hunter-Approach)

<Response> When we started planning the meta-analysis, we also discussed the possibility to control for psychometric artefacts based on Hunter and Schmidt’s approach. However, while screening the full-text articles and prior to beginning the coding process, we realized that there were large inconsistencies in reporting the reliabilities of the outcomes of interests. Only for some of the vigor and fatigue measures, the authors reported reliabilities (some were also one-item instruments). Moreover, for what we referred to as 'objective measures' of performance (e.g., error rates, reaction times, etc.), there was no such information. Hence, we decided to entirely apply Borenstein et al.’s framework for the meta-analysis. But we agree that this may be an important aspect, and as also per the Editor’s suggestion, we inserted in the manuscript a description and a discussion of this limitation and its implications.

Responses to the second reviewer’s comments

Overall impression:

The authors present an manuscript that deals with an important topic, the influence of rest breaks on feelings and performance, which is well written overall and personally interesting to me as a reader. Being a professor in personnel psychology and statistics, I will judge the manuscript with a focus on concept and methodology. See below for detailed comments.

<Response> Thank you for your positive feedback and appreciation!

Comment #1: the abstract needs revision. the abstract should include the research question, the methods and the results but in a comprehensible way. statistics or other details or specifics should not be referred to in the abstract.

<Response> The statistical details were removed from the abstract. We also reformulated the aims and methods details from the abstract in a more comprehensive way.

Comment #2: The writing is good, and the manuscript is generally interesting to read. It is also theoretically well argued, and to the point. There are some points to consider. The first concerns the instruments to measures effects of breaks, it can be a rating scale or a performance output but the effect size is difficult to compare directly, even between performance outputs of different tasks, not to speak of between feelings and performance. It depends on how good the psychometric quality of the measure is. For example, 30 min of a vigilance task deliver only a few measurement units while 10 min of a self-paced task provide a huge amount of trials to obtain reliable measures, and statistics crucially depend on it. (suggested reference: Schumann et al. (2022). Restoration of attention by rest in a multitasking world: Theory, methodology, and empirical evidence. Frontiers in Psychology, 13, 867978. doi:10.3389/fpsyg.2022.867978

<Response> Thank you for stressing this aspect! Indeed, it represents an important limitation of the current literature. As also the Editor suggested, we discussed it in several points of our manuscript. Moreover, thanks to the suggested review (Schumann et al., 2022), we also referred to some of their valuable critical insights. Precisely, (1) we began by further developing the measurement and conceptualization issues already mentioned towards the end of the Introduction, (2) continued by describing the state of the reliabilities of the used measures in the description of the sample of studies from the Results section, and (3) finally, we also addressed this issue in the Discussion by stressing out, among others, that "there are multiple methodological factors (e.g., employment of arbitrary tasks and/or unreliable or unaudited performance measures; insufficient number of trials) which could result in artefactual variance", and "even if taking into account their purpose, all these measures can be grouped under the umbrella term of performance, the many conceptual and operational differences between them could also make one rightfully argue against their aggregation. Hence, these particular results should be taken with increased caution.", as we also suggest " future studies might test the conditions under which respites positively affect subsequent performance by applying more standardized experimental paradigms and increasing consensus on methodological approaches." (These are just some examples of new mentions that we added to the manuscript.)

Comment #3: definitions of micro breaks fit with the meaning used in work psychology. I have no problem with this definition because the authors explain everything well in the manuscript, so there is no ambivalence. On the other hand, researcher with a more cognitive experimental focus often differ in the use of what is a micro break versus a short break versus long breaks. This might be discussed.

<Response> We searched in the cognitive-focused literature, and we didn’t find a clear differentiation between micro-breaks, short-breaks, and long breaks. We have cited several studies in cognitive psychology that emphasize the importance of refocusing attention after the break and we have highlighted a link between the three attention networks and breaks. We have inserted the new paragraph in the text.

Comment #4: glucose and depletion of resources. in the manuscript, the authors often refer to how task deplete mental resource in a way that gives the impression of a strong underlying basis of biology and physiology. On one occasion, for example, glucose is referred to as a causal factor determining resources. This is a difficult question, I would suggest reconsidering this point, it is in my opinion not clear.

<Response> In order to not create confusion related to the biological underlying mechanism, we deleted the entire phrase and the references.

Comment #5: tables. If possible, the tables should be presented in APA norm and maybe in a more economic way, The tables are huge and exceed a page. If the authors find ways to organise this more economically, good, otherwise, it is also okay, I would be fine with the present version.

<Response> All the included tables meet PlosOne’s style formatting requirements, which do not follow APA norms. Unfortunately, we did not find a more economical way to organize the information.

Submitted filename: Response to Reviewers.docx

 10.1371/journal.pone.0272460.r003 Decision Letter 1 Steinborn Michael B. Section Editor 2022 Michael B. Steinborn This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 1

27 Jun 2022

PONE-D-22-07400R1"Give me a break!" A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performancePLOS ONE

Dear Dr. Macsinga,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Editor comment. The manuscript seem now ready for publication. I would accept your manuscript for publication after considering some minor points provided by reviewer 1. There will be no further rounds, which means the manuscript will officially be accepted after resubmission and editorial check of the final version. Please submit your revised manuscript by Aug 11 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Michael B. Steinborn, PhD

Section Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

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Reviewer #1: I would like to thank the authors for revising the manuscript in line with my earlier comments.

I have some few (minor) recommendation for further improvement before a publication is warranted.

1) Abstract

Please inlcude specific information on the final sample size (number of studies, number of participants; i.e., data from 19 publications with 22 independent study samples, N = ...; data from p. 16) and in addition the

average effect size estimates of microbreaks. This information will be helfpul for readers to get the most important results

from your review in a quick way. I do agree with reviewer 2 that not all statistical information (95%CIs, p values, I²) is necessary in the abstract. But d-values and corresponding ks are 'must-haves' from my perspective.

2) p.16, l.380: do you mean 22 independent study samples from 19 publications?

3) Figure with PRIMSA scheme: Eligibility

Full text assessed = 43 articles

then you exclude 24

=> difference is 19

but you report 22 articles for the qualitative analysis ???

In addition, number of publications shlould be marked with k (n is usally used for participant sample size).

In the final step please report:

Included: k=19 publications with 22 independent study samples

(correct?)

4) p. 30, l. 575: Our results reveal that micro-break...

5) p.24, l.469: A d = 13.43 is extreme from my experience of this literature.

Have you checked effect coding and effect calculations from this specific study,

maybe by different coders?

6) According to your registered study protocol only control-group design studies could be included.

However, during your literature search you find that there are many studies using

no control group /within-subject designs.

I agree that that this design might affect the valdity of results.

On the other hand, even the design and measures of the included studies are largely heterogenous.

So at least for the small effects sizes for performance outcomes it might be interesting to integrate and discuss some of the

relevant excluded study results in the discussion. Do these studies found some performance effects?

For instance, consider tthi studies:

Engelmann, C., Schneider, M., Kirschbaum, C., Grote, G., Dingemann, J., Schoof, S., & Ure, B. M. (2011). Effects of intraoperative breaks on mental and somatic operator fatigue: a randomized clinical trial. Surgical endoscopy, 25(4), 1245–1250. https://doi.org/10.1007/s00464-010-1350-1

Engelmann, C., Schneider, M., Grote, G., Kirschbaum, C., Dingemann, J., Osthaus, A., & Ure, B. (2012). Work breaks during minimally invasive surgery in children: patient benefits and surgeon's perceptions. European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie, 22(6), 439–444. https://doi.org/10.1055/s-0032-1322542

Park, A. E., Zahiri, H. R., Hallbeck, M. S., Augenstein, V., Sutton, E., Yu, D., Lowndes, B. R., & Bingener, J. (2017). Intraoperative "Micro Breaks" With Targeted Stretching Enhance Surgeon Physical Function and Mental Focus: A Multicenter Cohort Study. Annals of surgery, 265(2), 340–346. https://doi.org/10.1097/SLA.0000000000001665

It is hard to conduct real intervention-control-group designs in such work settings. For instance, consider the Engelmann studies that showed real performance effects in a way that breaks improved patient outcomes (not only the concentration of the surgeons).

However, such studies found positive effects of breaks on performance which bolster the argument that breaks might even improve perfomance. Another argument is also that in many rest break studies the intervention group with additional rest breaks has actually a shorter total time on task (or work duration). Thus, significant increases in work performance (if this is assessed) are not really to be expected, it will be fine if this might be similar to the control group which has a longer time on task.

In sum, I will prefer if you could add some additional insights relating to performance effects from the excluded study types into the discussion.

Reviewer #2: The manuscript has improved greatly, and I would recommend this work for publication. I have no further comments.

**********

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Reviewer #1: No

Reviewer #2: No

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 10.1371/journal.pone.0272460.r004 Author response to Decision Letter 1 Submission Version 2

19 Jul 2022

Responses to the first reviewer’s comments

Reviewer #1: I would like to thank the authors for revising the manuscript in line with my earlier comments. I have some few (minor) recommendation for further improvement before a publication is warranted.

<Response> Thank you for your feedback and suggestions for improvement of our manuscript. We approached every comment carefully and integrated the suggestions in the new manuscript. In the following, we also responded to each and every comment.

1) Abstract

Please inlcude specific information on the final sample size (number of studies, number of participants; i.e., data from 19 publications with 22 independent study samples, N = ...; data from p. 16) and in addition the average effect size estimates of microbreaks. This information will be helfpul for readers to get the most important results from your review in a quick way. I do agree with reviewer 2 that not all statistical information (95%CIs, p values, I²) is necessary in the abstract. But d-values and corresponding ks are 'must-haves' from my perspective.

<Response> Thank you for this suggestion. We included in the abstract a phrase summarizing the retrieved number of studies, as well as the effect sizes for each of the outcomes of interest.

2) p.16, l.380: do you mean 22 independent study samples from 19 publications?

<Response> Thank you for pointing this mistake out. The observation is correct, and we made a change here, at line 382 using the phrase “22 independent study samples” instead of the initial one, reading “22 studies”, as this, we hope, will be a clearer message.

3) Figure with PRIMSA scheme: Eligibility

Full text assessed = 43 articles

then you exclude 24

=> difference is 19

but you report 22 articles for the qualitative analysis ???

In addition, number of publications shlould be marked with k (n is usally used for participant sample size).

In the final step please report:

Included: k=19 publications with 22 independent study samples

(correct?)

<Response> Thank you for pointing this out! The changes in the Figure 1 were processed as follows:

1. Changed n with k in the entire PRISMA flow diagram

2. Articles included in the qualitative synthesis (k = 19)

3. Studies included in quantitative synthesis (meta-analysis) (k = 19 publications with 22 independent study samples)

4) p. 30, l. 575: Our results reveal that micro-break...

<Response> Thank you. We implemented the suggestion which can be found at line 577, page 30.

5) p.24, l.469: A d = 13.43 is extreme from my experience of this literature.

Have you checked effect coding and effect calculations from this specific study, maybe by different coders?

<Response> For all coding we used two independent raters. Also, all the calculations were automatically done by the software we used (Comprehensive Meta-Analysis v 3.0), based on means, standard deviations, and sample sizes as input data. However, this particular effect also puzzled us and made us check it meticulously (since human error may hay have slipped in extracting the descriptive results from the manuscript). After inspecting the data against the effect size formula, we realized that the standard deviations of each mean are very low, hence the very large d value (after the standardization of the mean difference). Bellow, we will illustrate the calculus:

Experimental group data: Mean = 2.14, Std. Dev. = 0.12, Sample size = 51

Control group data: Mean = 3.72, Std. Dev. = 0.11, Sample size = 17

d = |(M experimental – M control)| / Pooled SD

d = |(2.14 – 3.72)| / 0.118

d = 1.58 / 0.118

d = 13.39

Some observations: (1) the obtained result varies slightly from the one outputted by Comprehensive Meta-Analysis (we do not know the exact formulas behind the software, maybe include the correction for sample size or something similar); (2) the difference in means is computed in module since a lower score on fatigue (as is the case for the experimental condition compared to the control one) is the expected result; (3) the actual design of the study included 4 groups (2 experimental, the difference being the theme of the micro-break, nature exposure <n =26=""> or urban exposure <n =="" 25="">, and 2 control, one with the same depleting task but without micro-break <n =="" 17="">, and another one without any manipulation <n =="" 19="">); since the later control fell outside our purpose (because we aimed at comparing groups who passed a similar depleting treatment, the only difference being the micro-break manipulation, as to draw conclusions on the effect of micro-breaks in working conditions), we pulled the data of the two experimental groups into one (n = 51; also these groups had similar results, i.e., means of 2.2 and 2.1) and compared it against the eligible control (n = 17). In their study, Beute and de Kort (2014), reported only the omnibus comparison between the four conditions (ANOVA analysis), without finding a significant overall effect (possible because of the small samples from each condition and the low and homogeneous variances), thus, they did not report further analyses on these data. Moreover, even for the significant differences, they reported only the overall effect size (partial etta squared) and no pairwise effects (hence the reason no similar effect size was reported in the manuscript).

6) According to your registered study protocol only control-group design studies could be included.

However, during your literature search you find that there are many studies using no control group /within-subject designs.

I agree that that this design might affect the valdity of results.

On the other hand, even the design and measures of the included studies are largely heterogenous.

So at least for the small effects sizes for performance outcomes it might be interesting to integrate and discuss some of the relevant excluded study results in the discussion. Do these studies found some performance effects?

For instance, consider tthi studies:

Engelmann, C., Schneider, M., Kirschbaum, C., Grote, G., Dingemann, J., Schoof, S., & Ure, B. M. (2011). Effects of intraoperative breaks on mental and somatic operator fatigue: a randomized clinical trial. Surgical endoscopy, 25(4), 1245–1250. https://doi.org/10.1007/s00464-010-1350-1

Engelmann, C., Schneider, M., Grote, G., Kirschbaum, C., Dingemann, J., Osthaus, A., & Ure, B. (2012). Work breaks during minimally invasive surgery in children: patient benefits and surgeon's perceptions. European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie, 22(6), 439–444. https://doi.org/10.1055/s-0032-1322542

Park, A. E., Zahiri, H. R., Hallbeck, M. S., Augenstein, V., Sutton, E., Yu, D., Lowndes, B. R., & Bingener, J. (2017). Intraoperative "Micro Breaks" With Targeted Stretching Enhance Surgeon Physical Function and Mental Focus: A Multicenter Cohort Study. Annals of surgery, 265(2), 340–346. https://doi.org/10.1097/SLA.0000000000001665

It is hard to conduct real intervention-control-group designs in such work settings. For instance, consider the Engelmann studies that showed real performance effects in a way that breaks improved patient outcomes (not only the concentration of the surgeons).

However, such studies found positive effects of breaks on performance which bolster the argument that breaks might even improve perfomance. Another argument is also that in many rest break studies the intervention group with additional rest breaks has actually a shorter total time on task (or work duration). Thus, significant increases in work performance (if this is assessed) are not really to be expected, it will be fine if this might be similar to the control group which has a longer time on task.

In sum, I will prefer if you could add some additional insights relating to performance effects from the excluded study types into the discussion.

<Response> Thank you for this suggestion! We further developed the discussion, looking at all the studies on performance from the 43 papers included in the eligibility assessing phase (including the ones that you suggested). Hence, we added a more extensive overview on the effect of breaks on performance (see Pages 33-34, lines 662-694). Because we included papers not cited previously throughout the manuscript, the in-text citations and reference list were also updated.

Responses to the second reviewer’s comments

Reviewer #2: The manuscript has improved greatly, and I would recommend this work for publication. I have no further comments.

<Response> Thank you for all the suggestions made during the first round of feedback, which made it possible to have this new and improved version of the manuscript. Also, thank you for your kind support during this review process.

Submitted filename: Response to Reviewers.docx

 10.1371/journal.pone.0272460.r005 Decision Letter 2 Steinborn Michael B. Section Editor 2022 Michael B. Steinborn This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 2

20 Jul 2022

"Give me a break!" A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance

PONE-D-22-07400R2

Dear Dr. Macsinga,

the manuscript has even further improved and is ready for publication now. We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Additional Editor Comments (optional):

Reviewers' comments:

 10.1371/journal.pone.0272460.r006 Acceptance letter Steinborn Michael B. Section Editor 2022 Michael B. Steinborn This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

4 Aug 2022

PONE-D-22-07400R2

"Give me a break!" A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance

Dear Dr. Macsinga:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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