Stronger Together? Impact of daily energy management strategies profiles on telecommuters’ performance

Stronger Together? 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Impact of daily energy management strategies profiles on telecommuters’ performance Chen Sun, Xiangping Zhan, Danli Wang, Ying Tian, Yitong Huang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7006998/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract With the rapid advancements in telecommunication technology, telecommuting as a new form of work increasingly found their way into the workplace. In this context, employees inevitably faced work time ambiguous, which might impede their energy recovery process. This study aimed to investigate the categories of energy management strategies of telecommuter and how they were related to performance. The study was conducted by electronic questionnaire across five consecutive workdays among telecommuters. Latent profile analysis identified three patterns of energy management strategies and respectively named energy management strategies double-low type (A), energy management strategies double-high type (B), Low micro break—High work related strategies (C). Moreover, group C showed to have significantly higher task performance as well as organizational citizenship behavior compared to group A, which also showed significant lower task performance and organizational citizenship behavior compared to group B. As such, the current research represented a new perspective on how telecommuters could effectively maintain, sustain and restore energy to improve their performance. energy management strategies performance vitality telecommuting latent profile analysis Figures Figure 1 Background With the rapid advancements in telecommunication technology, telecommuting as a new form of work increasingly found their way into the workplace (Bakaç et al., 2021). Telecommuting provided great benefits for employees, such as flexible work hours and daily commute expenses saving. In spite of these potential benefits, concerned remain that telecommuting could harm task performance of employee (Golden, 2012 ; Swisher, 2013 ). For example, Jackie Reses, head of human resources at Yahoo, thought that when we worked from home, speed and quality are often sacrificed (Swisher, 2013 ). In addition to concern about task performance, the other significant problems of telecommuters were susceptible to feelings of isolation, because of the lacked of social interaction and cooperation (Luckerson, 2012 ; Spilker, 2014 ). As a result, the contextual performance of telecommuters could be suffered (Luckerson, 2012 ; Spilker, 2014 ). Human energy was viewed as a resource that helped people focus attention and motivate their behavior (Fritz et al., 2011 ). Energizers were more productive, creative and they also had a positive impact on organization and outside it (Cross et al., 2003 ; Fritz et al., 2011 ; Schippers & Hogenes, 2011 ). Previous studies had shown that energetic employees were essential to the success of an organization (Cross et al., 2003 ; Fritz et al., 2011 ; Schippers & Hogenes, 2011 ). When the organization was energized internally, everything seemed to happen more easily (Parker et al., 2021 ). However, this energetic resource was limited and could be depleted over the course of the day (Fritz et al., 2011 ). In particular, telecommuters might be vulnerable to energy depletion and exhaustion, because they lacked the physical separation and associated cognitive reprieve offered by more separated work and family domains (Golden, 2012 ). It meant that employees should use strategies to maintain or replenish energy throughout the workday (Taylor, 2020 ). In this context, the current research putted attention on the energy management strategies as the most appropriate way to maintain energy for telecommuters. Energy management strategies referred to activities that individuals deliberately used throughout the workday to sustain their energy levels (Parker et al., 2017 ). Based on studies of specific and short respite activities, Fritz et al. ( 2011 ) distinguished two distinct categories of energy management strategies. The first class of energy management strategies, taking micro break strategies, were characterized by short, informal respite activities that were voluntarily taken between tasks (Kim et al., 2018 ). There were four prototypical micro-break activities: relaxation, nutrition-intake, socialization, and cognitive activities (Kim et al., 2018 ; Sianoja et al., 2018 ). The second class of energy management strategies were work related strategies, which included three types of strategies, namely meaning-making, prosocial and organizing strategies (Parker et al., 2017 ). Previous studies had testified to the benefits of energy management strategies at work and further indicated the relationship between energy management strategies and positive outcomes (e.g., work performance) for employees (Cross et al., 2003 ; Fritz et al., 2011 ; Kim et al., 2018 ; Parker et al., 2017 ; Schippers & Hogenes, 2011 ; Taylor, 2020 ). For example, Kim et al. ( 2018 ) found that micro-break strategies were associated with increased positive affect of employee at work which, in turn, predicted their greater sales performance. Review of previous studies, numerous researches had pointed to the benefits of external recovery, but the internal recovery—energy management strategies had received much less attention (Kinnunen et al., 2015 ). Op den Kamp et al. ( 2020 ) who considered energy management strategies as a specific form of goal-oriented, called on researchers to focus on it. Besides this, researchers of energy management strategies had mostly adopted a variable-centered approach (Kim et al., 2018 ; Parker et al., 2017 ; Taylor, 2020 ), examining the separate, unique effects of each strategy in isolation, ignoring the possibility that employees simultaneously used multiple strategies to sustain energy, especially for telecommuters. The focus on employees well-being and task performance had been dominant in research about energy management strategies. However, little is known about how energy management strategies affected their ability to go above and beyond their work roles (e.g., contextual performance). Therefore, our first aim was to identify distinct latent profiles of energy management strategies from a person-oriented view, that was, to identify subgroups of telecommuters using similar energy management strategies during the working days. The second aim was to investigate the distinctive relationship of this subgroups identified with task performance and contextual performance for telecommuters. Theoretical Foundations and Research question Next, we briefly introduced the Conservation of Resources Theory (COR; Hobfoll, 1989 ) that could explain how our conceptual model of energy management strategies sat within the theoretical framework. COR theory was primarily guided by two key principles: resource conservation and resource acquisition (Hobfoll, 1989 ; Hobfoll et al., 2018 ). Resource conservation referred to the withdrawal of individuals from situations or behaviors considered to threaten their resources, which aimed to avoid resource loss or potential future threats. Resource acquisition indicated that individuals actively interacted with their surrounding environment to increase their resource reserves. In line with the principle of resource conservation, energy was considered a limited resource that individuals tried to avoid losing (Fritz et al., 2011 ; Taylor, 2020 ). For instance, employees are required to complete a range of tasks and manage complex work demands throughout the workday (Schilbach et al., 2021 ). Therefore, their energetic resource could be depleted over the course of a workday. The perspective of resource conservation asserted that employees could not continue to work indefinitely throughout the workday, but they needed to recover depleted energy (Kim et al., 2018 ). From this point of view, employees could take micro-break activities (e.g., taking a short nap or walk, snacking or drinking at work) to restore their depleted energetic resources (Kim et al., 2018 ). According to the principle of resource acquisition, in order to gain resources, individuals needed to invest resources (Hobfoll, 1989 ; Hobfoll et al., 2018 ). In this sense, employees might invest available resources (i.e., by implementing work related energy management strategies) to obtain additional resources (i.e., increases in energy) and ensure adequate resources for the future (Taylor, 2020 ). Each of the types of work related energy management strategies (i.e., meaning-related strategy, organizing strategy, prosocial strategy) had the potential to enhance energy of employees, either objectively or subjectively (Schippers & Hogenes, 2011 ). To be specific, the use of meaning-related strategy might guide employees to rethink the importance of their work, thereby gaining the motivation to re-engage with it in a positive way (Schippers & Hogenes, 2011 ). This process could inject new energy into the employees. Use of organizing strategies could conducive employees to better manage their time, thereby freeing up resources for investment towards other goals (Trougakos & Hideg, 2009 ). Moreover, energy of employees could be replenished through social interactions with others by using prosocial strategy (Parker et al., 2017 ). Importantly, COR theory also suggested that the gain of resources became increasingly valuable, when the loss of resources was very prominent (Hobfoll et al., 2018 ). As a result, it might become increasingly important to use energy management strategies when employees were faced with higher work demands during the workday (Parker et al., 2017 ). Person-centered approaches were able to identify the unique profile of the variables, which allowed researchers to find different unobserved subpopulations in the sample (Chawla et al., 2020 ; Gabriel et al., 2018 ). Therefore, we adopted latent profile analysis (LPA) to investigate the extent of joint use of energy management strategies by telecommuters. Energy management strategies included micro-break strategies (nutrition-intake activities, relaxation activities, cognitive activities, social micro-break activities) and work related strategies (meaning-related strategy, prosocial strategy, organizing strategy). Based on the above seven profile indicators, a multitude of profile combinations could occur when taking account of low, moderate, and high levels of each construct. Consistent with previous studies about LPA (Chawla et al., 2020 ; Parker et al., 2021 ), we did not pose any hypothesis about specific profiles, given the inductive nature of this approach (Bennett et al., 2016 ). However, in the current context, certain profiles that seemed theoretically plausible. For example, some employees might favor work-related energy management strategies at the expense of other kinds of strategies. Some employees fairly seldom use both work related and micro-break strategies (Kinnunen et al., 2015 ). Moreover, some employees were used to engaging in social activities during lunch breaks (Trougakos et al., 2014 ). Considering the large number of possible profiles that we might identify in our analysis, yielding our first research question. Research Question 1: Do distinct profiles of energy management strategies exist that differ in quantity (level) and quality (shape)? Perhaps successful energy management was the result of a certain combination of these strategies (Kinnunen et al., 2015 ). For example, Sonnentag and Zijlstra ( 2006 ) found that actively engaged in work related strategies during workdays (e.g., reflecting on the meaning of their work) appeared to be associated with good well-being of employees. Fritz et al. ( 2011 ) indicated that strategies related to learning, to the meaning of work and to positive workplace relationships were most strongly linked to high energy level of employees. Thus, in order to understand whether certain combinations of daily energy management strategies were more beneficial, we examined the relationship between different profiles of energy management strategies and employee performance (e.g., task performance and contextual performance). The second research question of this study was as follows. Research Question 2: Do profiles of energy management strategies differentially relate to task performance and contextual performance? Methods Participants and Procedure Between May and August 2021, we disseminated an advertisement for this study on personal social media platforms to recruit participants. The inclusion criteria for participants were as follows: 1) full-time employees who telecommute via the Internet (working 30 or more hours per week), and 2) individuals who work at least five days per week while working from home. This study received approval from the Ethics Committee of Central China Normal University (ID: CCNU-IRB-202306003a). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. Before beginning the daily assessments, participants completed a baseline questionnaire via Question Star, an online survey platform, where they provided demographic information. One week later, participants took part in an online diary study over five consecutive workdays (Monday through Friday). Specifically, researchers distributed questionnaires to participants in the afternoon, at the end of each workday (typically completed around 6:00 p.m.). The afternoon survey assessed participants’ energy management strategies, vitality, task performance, and contextual performance. Our final sample consisted of 102 participants who provided assessments of their energy management strategies for at least three workdays (e.g., Chawla et al., 2020 ; Mühlenmeier et al., 2022 ). The response rate of the questionnaire was 86.7%. The average age of participants was 33.10 (SD = 8.29) and average tenure in their job was 12.71 years (SD = 10.31). Of the participants, 59.80% were women and 40.20% were men, and 70.59% were married. The majority of the participants had a higher education qualification (77.45%) and the majority of participants (60.78%) did not hold a supervisory position. Daily Survey Measures Daily Energy Management Strategies Energy management strategies consisted of two dimensions: micro-break strategies and work-related strategies. Daily micro-break strategies were measured using the 9 items developed by Kim et al. ( 2018 ). The scale contains four categories of micro break: cognitive micro-break (e.g., Since arriving at work today, I have voluntarily read nonwork-related books, newspapers, and magazines), nutrition-intake micro-break (Since arriving at work today, I have voluntarily drank coffee, black tea, green tea, or other caffeinated beverages), social micro-break (Since arriving at work today, I have chatted with coworkers on nonwork-related topics), and relaxation micro-break (Since arriving at work today, I have voluntarily engaged in exercise activities, such as walking or stretching in the office). Participants indicated how frequently they had made use of each strategy on a 5-point scale, ranging from 1 (never) to 5 (very often). In this study, the Cronbach’s alphas of the scale was 0.89. Daily work-related strategies were assessed using the 9 items developed by Parker et al. ( 2017 ). The scale contains three dimensions: prosocial (e.g., Today, I expressed my gratitude to my colleagues), organizing (Today, I checked and updated my work plan), and meaning-related strategies (Today, I reflected on the meaning of work). Participants rated how often they engaged in these work-related strategies during the workday on a 5-point scale (1 = never to 5 = very frequently). Cronbach’s alphas of the scale was 0.91. Vitality Vitality was measured with a 5-item scale developed by McNair et al. ( 1971 ). An example item was as follows “At present, I feel energetic”. Participants were made on a five-point Likert-type scale ranging from 1 strongly disagree to 5 strongly agree. In this study, the Cronbach’s alphas of the scale were 0.81 and 0.80. Task performance We measured task performance using seven items adapted from Williams and Anderson ( 1991 ). Sample items included “Fulfilled my responsibilities as specified in my job description”. Participants responded with “Yes” or “No” based on their agreement with statements regarding their task performance. In this study, the Cronbach’s alphas of the scale was 0.86. Contextual performance Contextual performance was measured using the eight-item scale developed by Dalal et al. ( 2009 ). An example item is: “Today, I genuinely expressed concern for others in the workplace”. Participants also responded “Yes” or “No” depending on whether they agreed with the statements concerning their contextual performance. In this study, the Cronbach’s alphas of the scale was 0.87. Analytic Approach Considering the non-independence of the data (i.e., days nested within people), we conducted multilevel latent profile analysis (MLPA) (e.g., Chawla et al., 2020 ). We firstly ran null models using Mplus 7.4, which could decompose between- and within-person variance in each variable. As shown in Table 1 , 34.07% and 60.42% of the variance in our constructs was within-person, supporting our use of MLPA. MLPA was an inductive method, which indicated that the number of profiles was unknown. Therefore, we specified a two-profile solution and increased the number of profiles extracted until model fit did not improve further (Nylund et al., 2007 ). To determine the appropriate number of latent profile groups, we evaluated each solution by using seven fit statistics: log likelihood (LL), Akaike information criterion (AIC), Bayesian information criterion (BIC), Sample-size-adjusted BIC (SSA-BIC), Lo-Mendell-Rubin likelihood ratio test (LMR), Bootstrap likelihood ratio test (BLRT), and entropy (Chawla et al., 2020 ; Nylund et al., 2007 ). Specifically, the ideal profile solution should have smaller AIC, BIC, and SSA-BIC statistics compared with other solutions, significant LMR and BLRT statistics. In addition to this, researchers were also encouraged to comprehensive consideration of the rationality and interpretability of the group solutions (Kinnunen et al., 2015 ). After identifying the best-fitting profile solution, we used the manual stepwise Bolck–Croon–Hagenaar (BCH) approach to explore the relationships between the profiles of energy management strategies identified and performance. This approach had the ability to describe whether one profile was significantly different from other profiles on each outcome. Table 1 Variance Decomposition for Variables Variable Within-person variance (σ 2 ) Between-person variance (τ 00 ) Percentage of within-person variance Micro-break 0.278 0.372 42.77% Work related strategy 0.201 0.389 34.07% Vitality 0.261 0.171 60.42% Task performance 0.562 0.579 49.26% Contextual performance 0.785 0.869 47.46% Results Preliminary Analyses Descriptive statistics and correlations of study variables were shown in Table 2. The results indicated that micro-break strategies were positively correlated with vitality ( r = 0.193, p < 0.01), task performance ( r = 0.097, p < 0.05) and contextual performance ( r = 0.112, p < 0.05). Work related strategies were also positively associated with vitality ( r = 0.333, p < 0.01), task performance ( r = 0.452, p < 0.01) and contextual performance ( r = 0.527, p < 0.01). Additionally, Vitality (After working) was significantly related to task performance ( r = 0.515, p < 0.01) and contextual performance ( r = 0.495, p < 0.01), respectively. Table 2 Means, Standard Deviations, and Correlations of Study Variables Variables M SD 1 2 3 4 5 6 7 8 1.Gender 1.590 0.491 1 2.Age 33.180 8.268 -0.056 1 3.Education 3.960 0.873 -0.052 -0.361 ** 1 4.Micro-break strategies 2.717 0.808 -0.067 0.081 -0.116 ** 1 5.Work related strategies 3.330 0.768 -0.131 ** 0.195 ** -0.101 * 0.171 ** 1 6.Vitality 3.473 0.659 -0.121 ** 0.105 * -0.039 0.193 ** 0.333 ** 1 7.Task performance 5.410 1.071 0.013 0.145 ** -0.097 * 0.097 * 0.452 ** 0.515 ** 1 8.Contextual performance 5.220 1.292 -0.061 0.210 ** -0.105 * 0.112 * 0.527 ** 0.495 ** 0.629 ** 1 Note. * p < 0.05. ** p < 0.01. Profiles of energy management strategies Table 3 indicated the results of our profile enumeration. The three-profile solution had the best statistical fit (i.e., highest Entropy and a significant LMR statistic) compared to two-, four-, five- and six-profile solutions. Furthermore, each profile contains more than 1% of our study sample (Nylund et al., 2007). Descriptive information related to each energy management strategies profile could be found in Table 4 and Figure 1 clarified the quantitatively and qualitatively different profiles. The profile with the largest membership (41.53%) reflected that individuals taken the highest levels of nutrition-intake micro-break activities ( M = 3.056), relaxation activities ( M = 3.652), cognitive activities ( M = 3.528), and social micro-break activities ( M = 3.620), as well as fairly higher levels of meaning-related strategies ( M = 3.379), prosocial strategies ( M = 3.650) and organizing strategies ( M = 3.369). We labeled this profile energy management strategies double-high type . The second largest profile (30.04%) represented home-based telecommuters who were taken low levels of micro-break and high work related strategies . These individuals taken the more moderate levels of nutrition-intake micro-break activities ( M = 2.197), relaxation activities ( M = 2.808), and lowest cognitive activities ( M = 1.738), social micro-break activities ( M = 2.008) and the highest levels of meaning-related strategies ( M = 3.683), prosocial strategies ( M = 3.993), organizing strategies ( M = 3.867). Our final profile (28.43%) included telecommuters who taken the lowest levels of nutrition-intake micro-break activities ( M = 2.019), relaxation activities ( M = 2.397), and the more moderate cognitive activities ( M = 2.029), social micro-break activities ( M = 2.375) and the lowest of meaning-related strategy ( M = 2.409), prosocial strategy ( M = 2.718) and organizing strategy ( M = 2.599). We labeled this profile energy management strategies double-low type . In combination, these profiles yield important insights into the existence of profiles of energy management strategies, as expressed in Research Question 1. Table 3 Latent Profile Enumeration Fit Statistics Number of profiles LL FP AIC BIC SSA-BIC Entropy LMR ( p ) BLRT 2 -5280.895 28 10617.790 10735.574 10646.701 0.904 0.000 0.000 3 -5000.845 38 10077.690 10237.540 10116.927 0.929 0.000 0.000 4 -4718.737 48 9533.474 9735.390 9583.036 0.898 0.143 0.000 5 -4543.127 58 9202.254 9446.235 9262.142 0.916 0.073 0.000 6 -4426.799 68 8989.598 9275.645 9059.811 0.909 0.174 0.000 Note. LL= log-likelihood; FP = Free parameters; AIC = Akaike information criteria; BIC = Bayesian information criteria; SSA-BIC = Sample-size adjusted BIC; LMR = Lo, Mendell, and Rubin (2001) test; BLRT = Bootstrapped likelihood ratio test. Table 4 Descriptive Information for Within-Person Latent energy management strategies Profiles Profile Variable Energy management strategies double-low type Energy management strategies double-high type Low micro break-High work related strategy M p M p M p MBN 2.019 0.000 3.056 0.000 2.197 0.000 MBR 2.397 0.000 3.652 0.000 2.808 0.000 MBC 2.029 0.000 3.528 0.000 1.738 0.000 MBS 2.375 0.000 3.620 0.000 2.008 0.000 WRR 2.409 0.000 3.379 0.000 3.683 0.000 WRS 2.718 0.000 3.650 0.000 3.993 0.000 WRO 2.599 0.000 3.369 0.000 3.867 0.000 Percentage of each profile 28.43% 41.53% 30.04% Note. MBN = Nutrition-intake micro-break activities; MBR = Relaxation activities; MBC = Cognitive activities; MBS = Social micro-break activities; WRR = Meaning-related strategy; WRS = Prosocial strategy; WRO = Organizing strategy. Mean differences of profiles classes on task performance and contextual performance To explore whether our profiles exhibited differential relationships with task performance and contextual performance, we performed a BCH analysis. As shown in Table 5, the three patterns differed significantly in task performance and contextual performance. To be specific, home based telecommuters in low micro break-high work related strategies profile had significantly highest task performance and contextual performance compared with other profiles. In addition to this, on days when home based telecommuters belonged to the energy management strategies double-low type profile, they reported significantly lowest task performance and contextual performance compared with other profiles. Table 5 Three-Step Results for Distal Outcomes (BCH) Energy management strategies double-low type (A) Energy management strategies double-high type (B) Energy management type based on work-related strategies (C) Chi-square (χ 2 ) Task performance 4.578 B,C 5.727 A,C 6.153 A,B 211.566 *** Organizational citizenship behavior 4.215 B,C 5.659 A,C 6.068 A,B 221.873 *** Note. *** p < 0.001. Discussion We explored the distinct profiles of energy management strategies by using MLPA, and then compared these with each other regarding task performance and contextual performance. The results of the study revealed three profiles: energy management strategies double-high type, energy management strategies double-low type, low levels of micro-break and high work related strategies . BCH results indicated that the profiles differed in task performance and contextual performance. It could be said that home-based telecommuters in low levels of micro-break and high work related strategies profile had significantly highest task performance and contextual performance compared with other profiles. And on days when home-based telecommuters belonged to the energy management strategies double-low type profile, they reported significantly lowest task performance and contextual performance compared with other profiles. In conclusion, our study showed that low levels of micro-break and high work related strategies seemed to be the most conducive to internal recovery of home-based telecommuters. The reason could be explained by self-determination theory. This theory suggested that the satisfaction of three basic psychological demands of individuals, namely relationship, competence, and autonomy, contributed to increase their vitality and well-being (Deci & Ryan, 2008 ). Especially for home-based telecommuters, emotions were the dominant factor affecting their telecommuting experience and performance (Wang et al., 2022 ). When home-based telecommuters proactively used work-related strategies to reflect on their work plan and built good relationships with colleagues, their three basic demands were met. Therefore, they gained a positive emotional experience from telecommuting, which could further promote their task performance and contextual performance. Moreover, from the results of the study, it appeared that micro-breaks did not help much in the internal recovery of home-based telecommuters. This might be because home-based telecommuters’ work and home roles shared the same physical space, the additional physical reminders of conflict and lack of role demarcation enabled permeability between work and home domains (Ashforth et al., 2000 ; Delanoeije et al., 2019 ). Thus, home-based telecommuters who worked from home generally involved frequent transitions between work and family roles when taking micro-break strategies at work (Ashforth et al., 2000 ; Wang et al., 2022 ). Previous research had found that the ease of role transition could be influenced by the context (Delanoeije et al., 2019 ; Wang et al., 2022 ). When working from home, the physical and psychological transition from home to work role for telecommuters required more effort after taking micro-break strategies (Ashforth et al., 2000 ). In short, the energy gained by home-based telecommuters taking micro-break strategies was not enough to replenish the energy consumed by the role transformation. Practical Implications Identifying profiles of daily energy management strategies has significant implications for both home-based telecommuters and organizations. Home-based telecommuters should understand the advantages of engaging in combinations of work-related strategies during working hours. In other words, they should avoid focusing solely on one type of work-related strategies. Instead, our findings indicate that the greatest advantages—both for task performance and organizational citizenship behavior—are achieved when home-based telecommuters consistently report adopting low levels of micro-break and high work related strategies. Therefore, we suggest that home-based telecommuters should be encouraged to prioritize work-related energy management strategies. It is important to note that employees should exercise caution when utilizing micro-break strategies, aiming to minimize frequent transitions between work and family roles to reduce energy depletion. Organizations should actively encourage and train employees to integrate work-related energy management strategies. This can be facilitated through targeted training programs or by providing resources that enable employees to apply these strategies more effectively. For instance, training on time management, task reflection, and teamwork skills could be implemented to improve both task performance and organizational citizenship behavior. Given the role confusion experienced by employees working from home when using micro-breaks, organizations should provide clear guidelines to help employees effectively incorporate micro-breaks as needed. Furthermore, organizations should encourage employees to establish boundaries between work and family responsibilities during work hours to alleviate the stress associated with role transitions. Finally, organizations can foster a supportive organizational culture by facilitating connections among colleagues through online social activities or by setting clear and achievable work goals to enhance employees’ sense of accomplishment. These practices can, in turn, promote home-based telecommuters’ emotional well-being and improve their work performance. Limitations and Future Research Directions Firstly, data collection for this study relied on self-reports, which may introduce the potential for common method variance. Self-reported data may also heighten the likelihood of socially desirable or respondents’ tendencies to either exaggerate or downplay their behaviors or attitudes. Future studies can mitigate this limitation by incorporating objective measures or multi-source feedback (e.g., supervisors or colleagues performance rating). Secondly, the study is based on daily assessments conducted over a five-day period, resulting in cross-sectional data collection within a limited time frame. While this approach facilitates the examination of daily fluctuations, it does not capture long-term changes in energy management strategies. Energy management strategies dynamics may fluctuate over time, particularly for telecommuters who encounter varying work demands or personal challenges. Future research can employ longitudinal designs to examine how energy management strategies and their impact on performance evolve over extended periods, such as weeks, months, or even years. Thirdly, the study does not consider individual differences in personality, work habits, or other psychological traits that may influence the relationship between the profiles of energy management strategies and work outcomes. Moreover, future research can investigate interventions aimed at enhancing energy management strategies among telecommuters. For instance, training programs focused on mindfulness, stress management, or time management can improve their ability of energy management. Conclusions In the current study, we adopted an intra-individual, person-centered approach, illustrating the profiles of daily energy management strategies, and the impact of these profiles on job performance/contextual performance of home-based teleworkers. Latent profile analysis identified three patterns of energy management strategies and respectively named energy management strategies double-low type (A), energy management strategies double-high type (B), Low micro break—High work related strategies (C). Moreover, group C showed to have significantly higher task performance as well as organizational citizenship behavior compared to group A, which also showed significant lower task performance and organizational citizenship behavior compared to group B. Our findings suggested that home-based telecommuters should be encouraged to primarily use work-related energy management strategies, supplemented by micro break strategies. Overall, our study provided a scientific theoretical basis for how home-based telecommuters can effectively manage energy to improve their performance. Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board (Approval Number: [ID: CCNU-IRB-202306003a]). All procedures performed in this study involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all participants prior to data collection. Consent for publication All participants were informed that the results of the study may be published in academic outlets. They provided their consent for the anonymized data to be used for publication purposes. Availability of data and material The data which supports the findings of this study is available from corresponding author on request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions Chen Sun and Xiangping Zhan contributed equally to the conceptualization, study design, and data collection. Danli Wang assisted in the literature review and data analysis. Qing Sun provided critical revisions and contributed to the theoretical framework. Yitong Huang supported manuscript drafting and formatting. Hongyu Ma supervised the entire project and provided guidance throughout the research process. All authors read and approved the final manuscript. Acknowledgements I would like to express my heartfelt gratitude to my six-and-a-half-month-old baby, whose presence has been a constant source of joy and inspiration throughout this journey. Thank you for bringing light and motivation to my work in ways words cannot fully capture. 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J Occup Health Psychol. 2022;27(3):286–98. https://doi.org/10.1037/ocp0000306 Nylund KL, Asparoutiov T, Muthen BO. Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Struct Equation Modeling-a Multidisciplinary J. 2007;14(4):535–69. https://doi.org/10.1080/10705510701575396 Op den Kamp EM, Bakker AB, Tims M, Demerouti E. Proactive vitality management and creative work performance: The role of self-insight and social support. J Creative Behav. 2020;54(2):323–36. https://doi.org/10.1002/jocb.368 . Parker SL, Dawson N, Van den Broeck A, Sonnentag S, Neal A. Employee motivation profiles, energy levels, and approaches to sustaining energy: A two-wave latent-profile analysis. J Vocat Behav. 2021;131:103659. https://doi.org/10.1016/j.jvb.2021.103659 . Parker SL, Zacher H, de Bloom J, Verton TM, Lentink CR. Daily use of energy management strategies and occupational well-being: The moderating role of job demands. Front Psychol. 2017;8:1477. https://doi.org/10.3389/fpsyg.2017.01477 . Schilbach M, Baethge A, Rigotti T. Do challenge and hindrance job demands prepare employees to demonstrate resilience? J Occup Health Psychol. 2021;26(3):155–74. https://doi.org/10.1037/ocp0000282 . Schippers MC, Hogenes R. Energy management of people in organizations: A review and research agenda. J Bus Psychol. 2011;26(2):193–203. https://doi.org/10.1007/s10869-011-9217-6 . 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;23(3):428–42. https://doi.org/10.1037/ocp0000083 . Sonnentag S, Zijlstra FRH. Job characteristics and off-job activities as predictors of need for recovery, well-being, and fatigue. J Appl Psychol. 2006;91(2):330–50. https://doi.org/10.1037/0021-9010.91.2.330 . Spilker MAA. Making telework work: The effect of telecommuting intensity on employee work outcomes. University of Missouri-Saint Louis; 2014. Swisher K. Physically together: Here’s the internal Yahoo nowork-from-home memo for remote workers and maybe more . Here's the Internal Yahoo No-Work-From-Home Memo - Kara Swisher - News - AllThingsD; 2013. Taylor MR. (2020). Human energy in the workplace: An investigation of daily energy management strategies, job stressors and employee outcomes. Dissertations and Theses . https://doi.org/10.15760/etd.7497 Trougakos JP, Hideg I. (2009). Momentary work recovery: The role of within-day work breaks. In Current perspectives on job-stress recovery (pp. 37–84). JAI Press/Emerald Group Publishing. https://doi.org/10.1108/S1479-3555(2009)0000007005 Trougakos JP, Hideg I, Cheng BH, Beal DJ. Lunch breaks unpacked: The role of autonomy as a moderator of recovery during lunch. Acad Manag J. 2014;57(2):405–21. https://doi.org/10.5465/amj.2011.1072 . Wang W, Wei T, Yu S, Chen J, Yang X. A telecommuting experience service design decision model based on BP neural network. Psychol Res Behav Manage. 2022;15:3147–66. https://doi.org/10.2147/PRBM.S386089 . Williams LJ, Anderson SE. Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. J Manag. 1991;17(3):601–17. https://doi.org/10.1177/014920639101700305 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7006998","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495407138,"identity":"99a7b28b-9c34-4049-928a-af185474d4fc","order_by":0,"name":"Chen Sun","email":"","orcid":"","institution":"Central China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Sun","suffix":""},{"id":495407139,"identity":"864b111e-5503-4513-91c3-8c3db8beec7f","order_by":1,"name":"Xiangping Zhan","email":"","orcid":"","institution":"Central China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Xiangping","middleName":"","lastName":"Zhan","suffix":""},{"id":495407140,"identity":"37f20202-2efc-44df-a115-0908858c66e1","order_by":2,"name":"Danli Wang","email":"","orcid":"","institution":"Central China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Danli","middleName":"","lastName":"Wang","suffix":""},{"id":495407141,"identity":"8eaaa702-979f-4211-97a8-293c637a9677","order_by":3,"name":"Ying Tian","email":"","orcid":"","institution":"Central China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Tian","suffix":""},{"id":495407142,"identity":"5214266d-a63c-42ef-8c14-f8f2e78d9a20","order_by":4,"name":"Yitong Huang","email":"","orcid":"","institution":"Central China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yitong","middleName":"","lastName":"Huang","suffix":""},{"id":495407143,"identity":"fdee8f6a-fdbd-474d-9455-63800ad5f56c","order_by":5,"name":"Hongyu Ma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYFACHgaGD0CSDy5wgAgtjDOAJBtJWpiBFjEQr0W3/ewxadscOxk2BuaHnwvbGOT4biQwfi7Ao8XsTF6adO62ZKDD2IylZ7YxGEveSGCWnoFPy4EcM6AWZqAWHjZm3jaGxA03EtjATsWp5fwbM2nLbfVwLfWEtdwA2sK47TBcS4IBYS1vjC17tx0Hqgf6heechOHMMw+bpfE7LMfwxs9t1fb87M0PP/OU2cjzHU8++BmfFiBgkQBTzGASxGZswK8BqPYDIRWjYBSMglEwwgEAnCM81TvmF5gAAAAASUVORK5CYII=","orcid":"","institution":"Central China Normal University","correspondingAuthor":true,"prefix":"","firstName":"Hongyu","middleName":"","lastName":"Ma","suffix":""}],"badges":[],"createdAt":"2025-06-30 06:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7006998/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7006998/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88466849,"identity":"1406c9e7-07dc-4074-a150-68d624a98e6c","added_by":"auto","created_at":"2025-08-06 17:42:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34105,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLatent profiles of daily energy management strategies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eMBN =\u003cem\u003e \u003c/em\u003eNutrition-intake micro-break activities; MBR = Relaxation activities; MBC = Cognitive activities; MBS = Social micro-break activities; WRR = Meaning-related strategy; WRS = Prosocial strategy; WRO = Organizing strategy. The \u003cem\u003ey\u003c/em\u003e axis refers to participants’ level of each of the energy management strategies. (1 = never; 5 = always).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7006998/v1/ef83e44193af9ddcf269e0c4.png"},{"id":88468197,"identity":"3d9d12ad-7842-441e-bf97-50b8182ab315","added_by":"auto","created_at":"2025-08-06 18:06:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":980815,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7006998/v1/71cf988b-a284-4523-b188-864679b2ead1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stronger Together? Impact of daily energy management strategies profiles on telecommuters’ performance","fulltext":[{"header":"Background","content":"\u003cp\u003eWith the rapid advancements in telecommunication technology, telecommuting as a new form of work increasingly found their way into the workplace (Baka\u0026ccedil; et al., 2021). Telecommuting provided great benefits for employees, such as flexible work hours and daily commute expenses saving. In spite of these potential benefits, concerned remain that telecommuting could harm task performance of employee (Golden, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Swisher, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). For example, Jackie Reses, head of human resources at Yahoo, thought that when we worked from home, speed and quality are often sacrificed (Swisher, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In addition to concern about task performance, the other significant problems of telecommuters were susceptible to feelings of isolation, because of the lacked of social interaction and cooperation (Luckerson, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Spilker, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). As a result, the contextual performance of telecommuters could be suffered (Luckerson, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Spilker, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHuman energy was viewed as a resource that helped people focus attention and motivate their behavior (Fritz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Energizers were more productive, creative and they also had a positive impact on organization and outside it (Cross et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Fritz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Schippers \u0026amp; Hogenes, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Previous studies had shown that energetic employees were essential to the success of an organization (Cross et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Fritz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Schippers \u0026amp; Hogenes, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). When the organization was energized internally, everything seemed to happen more easily (Parker et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, this energetic resource was limited and could be depleted over the course of the day (Fritz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In particular, telecommuters might be vulnerable to energy depletion and exhaustion, because they lacked the physical separation and associated cognitive reprieve offered by more separated work and family domains (Golden, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It meant that employees should use strategies to maintain or replenish energy throughout the workday (Taylor, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this context, the current research putted attention on the energy management strategies as the most appropriate way to maintain energy for telecommuters.\u003c/p\u003e\u003cp\u003eEnergy management strategies referred to activities that individuals deliberately used throughout the workday to sustain their energy levels (Parker et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Based on studies of specific and short respite activities, Fritz et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) distinguished two distinct categories of energy management strategies. The first class of energy management strategies, taking micro break strategies, were characterized by short, informal respite activities that were voluntarily taken between tasks (Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). There were four prototypical micro-break activities: relaxation, nutrition-intake, socialization, and cognitive activities (Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sianoja et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The second class of energy management strategies were work related strategies, which included three types of strategies, namely meaning-making, prosocial and organizing strategies (Parker et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Previous studies had testified to the benefits of energy management strategies at work and further indicated the relationship between energy management strategies and positive outcomes (e.g., work performance) for employees (Cross et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Fritz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Parker et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Schippers \u0026amp; Hogenes, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Taylor, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For example, Kim et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that micro-break strategies were associated with increased positive affect of employee at work which, in turn, predicted their greater sales performance.\u003c/p\u003e\u003cp\u003eReview of previous studies, numerous researches had pointed to the benefits of external recovery, but the internal recovery\u0026mdash;energy management strategies had received much less attention (Kinnunen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Op den Kamp et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) who considered energy management strategies as a specific form of goal-oriented, called on researchers to focus on it. Besides this, researchers of energy management strategies had mostly adopted a variable-centered approach (Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Parker et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Taylor, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), examining the separate, unique effects of each strategy in isolation, ignoring the possibility that employees simultaneously used multiple strategies to sustain energy, especially for telecommuters. The focus on employees well-being and task performance had been dominant in research about energy management strategies. However, little is known about how energy management strategies affected their ability to go above and beyond their work roles (e.g., contextual performance). Therefore, our first aim was to identify distinct latent profiles of energy management strategies from a person-oriented view, that was, to identify subgroups of telecommuters using similar energy management strategies during the working days. The second aim was to investigate the distinctive relationship of this subgroups identified with task performance and contextual performance for telecommuters.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTheoretical Foundations and Research question\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNext, we briefly introduced the Conservation of Resources Theory (COR; Hobfoll, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) that could explain how our conceptual model of energy management strategies sat within the theoretical framework. COR theory was primarily guided by two key principles: resource conservation and resource acquisition (Hobfoll, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Hobfoll et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Resource conservation referred to the withdrawal of individuals from situations or behaviors considered to threaten their resources, which aimed to avoid resource loss or potential future threats. Resource acquisition indicated that individuals actively interacted with their surrounding environment to increase their resource reserves. In line with the principle of resource conservation, energy was considered a limited resource that individuals tried to avoid losing (Fritz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Taylor, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For instance, employees are required to complete a range of tasks and manage complex work demands throughout the workday (Schilbach et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, their energetic resource could be depleted over the course of a workday. The perspective of resource conservation asserted that employees could not continue to work indefinitely throughout the workday, but they needed to recover depleted energy (Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). From this point of view, employees could take micro-break activities (e.g., taking a short nap or walk, snacking or drinking at work) to restore their depleted energetic resources (Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). According to the principle of resource acquisition, in order to gain resources, individuals needed to invest resources (Hobfoll, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Hobfoll et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this sense, employees might invest available resources (i.e., by implementing work related energy management strategies) to obtain additional resources (i.e., increases in energy) and ensure adequate resources for the future (Taylor, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Each of the types of work related energy management strategies (i.e., meaning-related strategy, organizing strategy, prosocial strategy) had the potential to enhance energy of employees, either objectively or subjectively (Schippers \u0026amp; Hogenes, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). To be specific, the use of meaning-related strategy might guide employees to rethink the importance of their work, thereby gaining the motivation to re-engage with it in a positive way (Schippers \u0026amp; Hogenes, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This process could inject new energy into the employees. Use of organizing strategies could conducive employees to better manage their time, thereby freeing up resources for investment towards other goals (Trougakos \u0026amp; Hideg, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Moreover, energy of employees could be replenished through social interactions with others by using prosocial strategy (Parker et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Importantly, COR theory also suggested that the gain of resources became increasingly valuable, when the loss of resources was very prominent (Hobfoll et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a result, it might become increasingly important to use energy management strategies when employees were faced with higher work demands during the workday (Parker et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePerson-centered approaches were able to identify the unique profile of the variables, which allowed researchers to find different unobserved subpopulations in the sample (Chawla et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gabriel et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, we adopted latent profile analysis (LPA) to investigate the extent of joint use of energy management strategies by telecommuters. Energy management strategies included micro-break strategies (nutrition-intake activities, relaxation activities, cognitive activities, social micro-break activities) and work related strategies (meaning-related strategy, prosocial strategy, organizing strategy). Based on the above seven profile indicators, a multitude of profile combinations could occur when taking account of low, moderate, and high levels of each construct. Consistent with previous studies about LPA (Chawla et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Parker et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we did not pose any hypothesis about specific profiles, given the inductive nature of this approach (Bennett et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, in the current context, certain profiles that seemed theoretically plausible. For example, some employees might favor work-related energy management strategies at the expense of other kinds of strategies. Some employees fairly seldom use both work related and micro-break strategies (Kinnunen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, some employees were used to engaging in social activities during lunch breaks (Trougakos et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Considering the large number of possible profiles that we might identify in our analysis, yielding our first research question.\u003c/p\u003e\u003cp\u003eResearch Question 1: Do distinct profiles of energy management strategies exist that differ in quantity (level) and quality (shape)?\u003c/p\u003e\u003cp\u003ePerhaps successful energy management was the result of a certain combination of these strategies (Kinnunen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). For example, Sonnentag and Zijlstra (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) found that actively engaged in work related strategies during workdays (e.g., reflecting on the meaning of their work) appeared to be associated with good well-being of employees. Fritz et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) indicated that strategies related to learning, to the meaning of work and to positive workplace relationships were most strongly linked to high energy level of employees. Thus, in order to understand whether certain combinations of daily energy management strategies were more beneficial, we examined the relationship between different profiles of energy management strategies and employee performance (e.g., task performance and contextual performance). The second research question of this study was as follows.\u003c/p\u003e\u003cp\u003eResearch Question 2: Do profiles of energy management strategies differentially relate to task performance and contextual performance?\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eParticipants and Procedure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBetween May and August 2021, we disseminated an advertisement for this study on personal social media platforms to recruit participants. The inclusion criteria for participants were as follows: 1) full-time employees who telecommute via the Internet (working 30 or more hours per week), and 2) individuals who work at least five days per week while working from home. This study received approval from the Ethics Committee of Central China Normal University (ID: CCNU-IRB-202306003a). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. Before beginning the daily assessments, participants completed a baseline questionnaire via Question Star, an online survey platform, where they provided demographic information. One week later, participants took part in an online diary study over five consecutive workdays (Monday through Friday). Specifically, researchers distributed questionnaires to participants in the afternoon, at the end of each workday (typically completed around 6:00 p.m.). The afternoon survey assessed participants\u0026rsquo; energy management strategies, vitality, task performance, and contextual performance. Our final sample consisted of 102 participants who provided assessments of their energy management strategies for at least three workdays (e.g., Chawla et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; M\u0026uuml;hlenmeier et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The response rate of the questionnaire was 86.7%. The average age of participants was 33.10 (SD\u0026thinsp;=\u0026thinsp;8.29) and average tenure in their job was 12.71 years (SD\u0026thinsp;=\u0026thinsp;10.31). Of the participants, 59.80% were women and 40.20% were men, and 70.59% were married. The majority of the participants had a higher education qualification (77.45%) and the majority of participants (60.78%) did not hold a supervisory position.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDaily Survey Measures\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eDaily Energy Management Strategies\u003c/em\u003e\u003c/p\u003e\u003cp\u003eEnergy management strategies consisted of two dimensions: micro-break strategies and work-related strategies. Daily micro-break strategies were measured using the 9 items developed by Kim et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The scale contains four categories of micro break: cognitive micro-break (e.g., Since arriving at work today, I have voluntarily read nonwork-related books, newspapers, and magazines), nutrition-intake micro-break (Since arriving at work today, I have voluntarily drank coffee, black tea, green tea, or other caffeinated beverages), social micro-break (Since arriving at work today, I have chatted with coworkers on nonwork-related topics), and relaxation micro-break (Since arriving at work today, I have voluntarily engaged in exercise activities, such as walking or stretching in the office). Participants indicated how frequently they had made use of each strategy on a 5-point scale, ranging from 1 (never) to 5 (very often). In this study, the Cronbach\u0026rsquo;s alphas of the scale was 0.89.\u003c/p\u003e\u003cp\u003eDaily work-related strategies were assessed using the 9 items developed by Parker et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The scale contains three dimensions: prosocial (e.g., Today, I expressed my gratitude to my colleagues), organizing (Today, I checked and updated my work plan), and meaning-related strategies (Today, I reflected on the meaning of work). Participants rated how often they engaged in these work-related strategies during the workday on a 5-point scale (1\u0026thinsp;=\u0026thinsp;never to 5\u0026thinsp;=\u0026thinsp;very frequently). Cronbach\u0026rsquo;s alphas of the scale was 0.91.\u003c/p\u003e\u003cp\u003e\u003cem\u003eVitality\u003c/em\u003e\u003c/p\u003e\u003cp\u003eVitality was measured with a 5-item scale developed by McNair et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). An example item was as follows \u0026ldquo;At present, I feel energetic\u0026rdquo;. Participants were made on a five-point Likert-type scale ranging from 1 strongly disagree to 5 strongly agree. In this study, the Cronbach\u0026rsquo;s alphas of the scale were 0.81 and 0.80.\u003c/p\u003e\u003cp\u003e\u003cem\u003eTask performance\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe measured task performance using seven items adapted from Williams and Anderson (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Sample items included \u0026ldquo;Fulfilled my responsibilities as specified in my job description\u0026rdquo;. Participants responded with \u0026ldquo;Yes\u0026rdquo; or \u0026ldquo;No\u0026rdquo; based on their agreement with statements regarding their task performance. In this study, the Cronbach\u0026rsquo;s alphas of the scale was 0.86.\u003c/p\u003e\u003cp\u003e\u003cem\u003eContextual performance\u003c/em\u003e\u003c/p\u003e\u003cp\u003eContextual performance was measured using the eight-item scale developed by Dalal et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). An example item is: \u0026ldquo;Today, I genuinely expressed concern for others in the workplace\u0026rdquo;. Participants also responded \u0026ldquo;Yes\u0026rdquo; or \u0026ldquo;No\u0026rdquo; depending on whether they agreed with the statements concerning their contextual performance. In this study, the Cronbach\u0026rsquo;s alphas of the scale was 0.87.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalytic Approach\u003c/b\u003e\u003c/p\u003e\u003cp\u003eConsidering the non-independence of the data (i.e., days nested within people), we conducted multilevel latent profile analysis (MLPA) (e.g., Chawla et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). We firstly ran null models using Mplus 7.4, which could decompose between- and within-person variance in each variable. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 34.07% and 60.42% of the variance in our constructs was within-person, supporting our use of MLPA. MLPA was an inductive method, which indicated that the number of profiles was unknown. Therefore, we specified a two-profile solution and increased the number of profiles extracted until model fit did not improve further (Nylund et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). To determine the appropriate number of latent profile groups, we evaluated each solution by using seven fit statistics: log likelihood (LL), Akaike information criterion (AIC), Bayesian information criterion (BIC), Sample-size-adjusted BIC (SSA-BIC), Lo-Mendell-Rubin likelihood ratio test (LMR), Bootstrap likelihood ratio test (BLRT), and entropy (Chawla et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Nylund et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Specifically, the ideal profile solution should have smaller AIC, BIC, and SSA-BIC statistics compared with other solutions, significant LMR and BLRT statistics. In addition to this, researchers were also encouraged to comprehensive consideration of the rationality and interpretability of the group solutions (Kinnunen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). After identifying the best-fitting profile solution, we used the manual stepwise Bolck\u0026ndash;Croon\u0026ndash;Hagenaar (BCH) approach to explore the relationships between the profiles of energy management strategies identified and performance. This approach had the ability to describe whether one profile was significantly different from other profiles on each outcome.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariance Decomposition for Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWithin-person variance (σ\u003csup\u003e2\u003c/sup\u003e )\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBetween-person variance (τ\u003csub\u003e00\u003c/sub\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage of within-person variance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMicro-break\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42.77%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork related strategy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.389\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.07%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVitality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e60.42%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTask performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49.26%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContextual performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47.46%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePreliminary Analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics and correlations of study variables were shown in Table 2. The results indicated that micro-break strategies were positively correlated with vitality (\u003cem\u003er\u003c/em\u003e = 0.193, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), task performance (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.097, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and contextual performance (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.112, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Work related strategies were also positively associated with vitality (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.333, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), task performance (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.452, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) and contextual performance (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.527, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). Additionally, Vitality\u003csub\u003e(After working)\u0026nbsp;\u003c/sub\u003ewas\u0026nbsp;significantly related to task performance (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.515, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) and contextual performance (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.495, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Means, Standard Deviations, and Correlations of Study Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"740\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1.Gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e2.Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e33.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e8.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e3.Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e-0.361\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e4.Micro-break strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.116\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e5.Work related strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.131\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.195\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.101\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.171\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e6.Vitality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.121\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.105\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.193\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.333\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e7.Task performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e1.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.145\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.097\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.097\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.452\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.515\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e8.Contextual performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e1.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.210\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.105\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.112\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.527\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.495\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.629\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eProfiles of energy management\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003estrategies\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 indicated the results of our profile enumeration. The three-profile solution had the best statistical fit (i.e., highest Entropy and a significant LMR statistic) compared to two-, four-, five- and six-profile solutions.\u0026nbsp;Furthermore, each profile contains more than 1% of our study sample\u0026nbsp;(Nylund et al., 2007). Descriptive information related to each energy management strategies profile could be found in Table 4 and Figure 1 clarified the quantitatively and qualitatively different profiles. The profile with the largest membership (41.53%) reflected that individuals taken the highest levels of nutrition-intake micro-break activities (\u003cem\u003eM\u003c/em\u003e = 3.056), relaxation activities (\u003cem\u003eM\u003c/em\u003e = 3.652), cognitive activities (\u003cem\u003eM\u003c/em\u003e = 3.528), and social micro-break activities (\u003cem\u003eM\u003c/em\u003e = 3.620), as well as fairly higher levels of meaning-related strategies (\u003cem\u003eM\u003c/em\u003e = 3.379), prosocial strategies (\u003cem\u003eM\u003c/em\u003e = 3.650) and organizing strategies (\u003cem\u003eM\u003c/em\u003e = 3.369). We labeled this profile \u003cem\u003eenergy management strategies double-high type\u003c/em\u003e. The second largest profile (30.04%) represented home-based telecommuters who were taken \u003cem\u003elow levels of micro-break and high work related strategies\u003c/em\u003e. These individuals taken the more moderate levels of nutrition-intake micro-break activities (\u003cem\u003eM\u003c/em\u003e = 2.197), relaxation activities (\u003cem\u003eM\u003c/em\u003e = 2.808), and lowest cognitive activities (\u003cem\u003eM\u003c/em\u003e = 1.738), social micro-break activities (\u003cem\u003eM\u003c/em\u003e = 2.008) and the highest levels of meaning-related strategies (\u003cem\u003eM\u003c/em\u003e = 3.683), prosocial strategies (\u003cem\u003eM\u003c/em\u003e = 3.993), organizing strategies (\u003cem\u003eM\u003c/em\u003e = 3.867). Our final profile (28.43%) included telecommuters who taken the lowest levels of nutrition-intake micro-break activities (\u003cem\u003eM\u003c/em\u003e = 2.019), relaxation activities (\u003cem\u003eM\u003c/em\u003e = 2.397), and the more moderate cognitive activities (\u003cem\u003eM\u003c/em\u003e = 2.029), social micro-break activities (\u003cem\u003eM\u003c/em\u003e = 2.375) and the lowest of meaning-related strategy (\u003cem\u003eM\u003c/em\u003e = 2.409), prosocial strategy (\u003cem\u003eM\u003c/em\u003e = 2.718) and organizing strategy (\u003cem\u003eM\u003c/em\u003e = 2.599). We labeled this profile \u003cem\u003eenergy management strategies double-low type\u003c/em\u003e. In combination, these profiles yield important insights into the existence of profiles of energy management strategies, as expressed in Research Question 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Latent Profile Enumeration Fit Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"693\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eNumber of profiles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eLL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eSSA-BIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eEntropy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLMR\u003csub\u003e\u0026nbsp;(\u003cem\u003ep\u003c/em\u003e)\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eBLRT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e-5280.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e10617.790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10735.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10646.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e-5000.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e10077.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10237.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10116.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e-4718.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e9533.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9735.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9583.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e-4543.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e9202.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9446.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9262.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e-4426.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e8989.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9275.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9059.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eLL= log-likelihood; FP = Free parameters; AIC = Akaike information criteria; BIC = Bayesian information criteria; SSA-BIC = Sample-size adjusted BIC; LMR = Lo, Mendell, and Rubin (2001) test; BLRT = Bootstrapped likelihood ratio test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Descriptive Information for Within-Person Latent\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eenergy management strategies\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eProfiles\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"686\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 115px;\"\u003e\n \u003cp\u003eProfile\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 203px;\"\u003e\n \u003cp\u003eEnergy management strategies double-low type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 195px;\"\u003e\n \u003cp\u003eEnergy management strategies double-high type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 174px;\"\u003e\n \u003cp\u003eLow micro break-High work related strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eMBN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e2.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eMBR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e2.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eMBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eMBS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e2.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eWRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e3.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eWRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e3.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eWRO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e3.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e3.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003ePercentage of each profile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 203px;\"\u003e\n \u003cp\u003e28.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 195px;\"\u003e\n \u003cp\u003e41.53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 174px;\"\u003e\n \u003cp\u003e30.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003eMBN =\u003cem\u003e\u0026nbsp;\u003c/em\u003eNutrition-intake micro-break activities; MBR = Relaxation activities; MBC = Cognitive activities; MBS = Social micro-break activities; WRR = Meaning-related strategy; WRS = Prosocial strategy; WRO = Organizing strategy. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMean differences of profiles classes on task performance and contextual performance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore whether our profiles exhibited differential relationships with task performance and contextual performance, we performed a BCH analysis. As shown in Table 5, the three patterns differed significantly in task performance and contextual performance. To be specific, home based telecommuters in \u003cem\u003elow micro break-high work related strategies\u003c/em\u003e profile had significantly highest task performance and contextual performance compared with other profiles. In addition to this, on days when home based telecommuters belonged to the \u003cem\u003eenergy management strategies double-low type\u003c/em\u003e profile, they reported significantly lowest task performance and contextual performance compared with other profiles.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 Three-Step Results for Distal Outcomes (BCH)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eEnergy management strategies double-low type (A)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eEnergy management strategies double-high type (B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eEnergy management type based on work-related strategies (C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eChi-square (\u0026chi;\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eTask performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e4.578\u003csup\u003eB,C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e5.727\u003csup\u003eA,C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e6.153\u003csup\u003eA,B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e211.566\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eOrganizational citizenship behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e4.215\u003csup\u003eB,C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e5.659\u003csup\u003eA,C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e6.068\u003csup\u003eA,B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e221.873\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003e\u003csup\u003e***\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe explored the distinct profiles of energy management strategies by using MLPA, and then compared these with each other regarding task performance and contextual performance. The results of the study revealed three profiles: \u003cem\u003eenergy management strategies double-high type, energy management strategies double-low type, low levels of micro-break and high work related strategies\u003c/em\u003e. BCH results indicated that the profiles differed in task performance and contextual performance. It could be said that home-based telecommuters in \u003cem\u003elow levels of micro-break and high work related strategies\u003c/em\u003e profile had significantly highest task performance and contextual performance compared with other profiles. And on days when home-based telecommuters belonged to the \u003cem\u003eenergy management strategies double-low type\u003c/em\u003e profile, they reported significantly lowest task performance and contextual performance compared with other profiles. In conclusion, our study showed that \u003cem\u003elow levels of micro-break and high work related strategies\u003c/em\u003e seemed to be the most conducive to internal recovery of home-based telecommuters. The reason could be explained by self-determination theory. This theory suggested that the satisfaction of three basic psychological demands of individuals, namely relationship, competence, and autonomy, contributed to increase their vitality and well-being (Deci \u0026amp; Ryan, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Especially for home-based telecommuters, emotions were the dominant factor affecting their telecommuting experience and performance (Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). When home-based telecommuters proactively used work-related strategies to reflect on their work plan and built good relationships with colleagues, their three basic demands were met. Therefore, they gained a positive emotional experience from telecommuting, which could further promote their task performance and contextual performance. Moreover, from the results of the study, it appeared that micro-breaks did not help much in the internal recovery of home-based telecommuters. This might be because home-based telecommuters\u0026rsquo; work and home roles shared the same physical space, the additional physical reminders of conflict and lack of role demarcation enabled permeability between work and home domains (Ashforth et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Delanoeije et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus, home-based telecommuters who worked from home generally involved frequent transitions between work and family roles when taking micro-break strategies at work (Ashforth et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Previous research had found that the ease of role transition could be influenced by the context (Delanoeije et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). When working from home, the physical and psychological transition from home to work role for telecommuters required more effort after taking micro-break strategies (Ashforth et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In short, the energy gained by home-based telecommuters taking micro-break strategies was not enough to replenish the energy consumed by the role transformation.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePractical Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIdentifying profiles of daily energy management strategies has significant implications for both home-based telecommuters and organizations. Home-based telecommuters should understand the advantages of engaging in combinations of work-related strategies during working hours. In other words, they should avoid focusing solely on one type of work-related strategies. Instead, our findings indicate that the greatest advantages\u0026mdash;both for task performance and organizational citizenship behavior\u0026mdash;are achieved when home-based telecommuters consistently report adopting low levels of micro-break and high work related strategies. Therefore, we suggest that home-based telecommuters should be encouraged to prioritize work-related energy management strategies. It is important to note that employees should exercise caution when utilizing micro-break strategies, aiming to minimize frequent transitions between work and family roles to reduce energy depletion. Organizations should actively encourage and train employees to integrate work-related energy management strategies. This can be facilitated through targeted training programs or by providing resources that enable employees to apply these strategies more effectively. For instance, training on time management, task reflection, and teamwork skills could be implemented to improve both task performance and organizational citizenship behavior. Given the role confusion experienced by employees working from home when using micro-breaks, organizations should provide clear guidelines to help employees effectively incorporate micro-breaks as needed. Furthermore, organizations should encourage employees to establish boundaries between work and family responsibilities during work hours to alleviate the stress associated with role transitions. Finally, organizations can foster a supportive organizational culture by facilitating connections among colleagues through online social activities or by setting clear and achievable work goals to enhance employees\u0026rsquo; sense of accomplishment. These practices can, in turn, promote home-based telecommuters\u0026rsquo; emotional well-being and improve their work performance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and Future Research Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFirstly, data collection for this study relied on self-reports, which may introduce the potential for common method variance. Self-reported data may also heighten the likelihood of socially desirable or respondents\u0026rsquo; tendencies to either exaggerate or downplay their behaviors or attitudes. Future studies can mitigate this limitation by incorporating objective measures or multi-source feedback (e.g., supervisors or colleagues performance rating). Secondly, the study is based on daily assessments conducted over a five-day period, resulting in cross-sectional data collection within a limited time frame. While this approach facilitates the examination of daily fluctuations, it does not capture long-term changes in energy management strategies. Energy management strategies dynamics may fluctuate over time, particularly for telecommuters who encounter varying work demands or personal challenges. Future research can employ longitudinal designs to examine how energy management strategies and their impact on performance evolve over extended periods, such as weeks, months, or even years. Thirdly, the study does not consider individual differences in personality, work habits, or other psychological traits that may influence the relationship between the profiles of energy management strategies and work outcomes. Moreover, future research can investigate interventions aimed at enhancing energy management strategies among telecommuters. For instance, training programs focused on mindfulness, stress management, or time management can improve their ability of energy management.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn the current study, we adopted an intra-individual, person-centered approach, illustrating the profiles of daily energy management strategies, and the impact of these profiles on job performance/contextual performance of home-based teleworkers. Latent profile analysis identified three patterns of energy management strategies and respectively named energy management strategies double-low type (A), energy management strategies double-high type (B), Low micro break\u0026mdash;High work related strategies (C). Moreover, group C showed to have significantly higher task performance as well as organizational citizenship behavior compared to group A, which also showed significant lower task performance and organizational citizenship behavior compared to group B. Our findings suggested that home-based telecommuters should be encouraged to primarily use work-related energy management strategies, supplemented by micro break strategies. Overall, our study provided a scientific theoretical basis for how home-based telecommuters can effectively manage energy to improve their performance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board (Approval Number: [ID: CCNU-IRB-202306003a]). All procedures performed in this study involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all participants prior to data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants were informed that the results of the study may be published in academic outlets. They provided their consent for the anonymized data to be used for publication purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data which supports the findings of this study is available from corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChen Sun and Xiangping Zhan contributed equally to the conceptualization, study design, and data collection. Danli Wang assisted in the literature review and data analysis. Qing Sun provided critical revisions and contributed to the theoretical framework. Yitong Huang supported manuscript drafting and formatting. Hongyu Ma supervised the entire project and provided guidance throughout the research process. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI would like to express my heartfelt gratitude to my six-and-a-half-month-old baby, whose presence has been a constant source of joy and inspiration throughout this journey. Thank you for bringing light and motivation to my work in ways words cannot fully capture.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAshforth BE, Kreiner GE, Fugate M. 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J Manag. 1991;17(3):601\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/014920639101700305\u003c/span\u003e\u003cspan address=\"10.1177/014920639101700305\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"energy management strategies, performance, vitality, telecommuting, latent profile analysis","lastPublishedDoi":"10.21203/rs.3.rs-7006998/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7006998/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith the rapid advancements in telecommunication technology, telecommuting as a new form of work increasingly found their way into the workplace. In this context, employees inevitably faced work time ambiguous, which might impede their energy recovery process. This study aimed to investigate the categories of energy management strategies of telecommuter and how they were related to performance. The study was conducted by electronic questionnaire across five consecutive workdays among telecommuters. Latent profile analysis identified three patterns of energy management strategies and respectively named energy management strategies double-low type (A), energy management strategies double-high type (B), Low micro break\u0026mdash;High work related strategies (C). Moreover, group C showed to have significantly higher task performance as well as organizational citizenship behavior compared to group A, which also showed significant lower task performance and organizational citizenship behavior compared to group B. As such, the current research represented a new perspective on how telecommuters could effectively maintain, sustain and restore energy to improve their performance.\u003c/p\u003e","manuscriptTitle":"Stronger Together? Impact of daily energy management strategies profiles on telecommuters’ performance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-06 17:42:36","doi":"10.21203/rs.3.rs-7006998/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-26T11:27:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107063795957896401732307198122457365324","date":"2026-05-22T17:48:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T11:48:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48488996692281662065954812898035519967","date":"2025-08-06T08:12:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-04T04:07:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-07T13:43:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-04T00:25:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-04T00:25:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-06-30T06:23:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e0b6ac06-faa2-4117-9aa3-656965c339ad","owner":[],"postedDate":"August 6th, 2025","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-26T11:27:23+00:00","index":95,"fulltext":""},{"type":"reviewerAgreed","content":"107063795957896401732307198122457365324","date":"2026-05-22T17:48:50+00:00","index":91,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-06T17:42:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-06 17:42:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7006998","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7006998","identity":"rs-7006998","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}