Objective: Psychological detachment facilitates recovery from work, but detachment is sometimes difficult in flexible work arrangements (FWAs). This study examined the effects of a co-created two-step workplace intervention that introduced new work strategies to facilitate psychological detachment and promote recovery in office workers with FWAs. The intervention comprised an individual-level course on digital tools and work strategies, followed by a workgroup-level workshop to develop common rules and routines in FWAs.

Methods: Office workers with FWAs in a Swedish governmental agency (intervention group, n = 97; control group, n = 70) completed a web-based questionnaire on three occasions between 2018 and 2020: at baseline 3 months before the intervention; after the individual-level course 6 months after baseline, and after the workgroup-level workshop 12 months after baseline. Effects of the intervention on need for recovery (NFR) as mediated by psychological detachment, and moderation of these effects by baseline NFR, were estimated with adjustment for covariates.

Results: At the 6- and 12-month follow-ups, we found no unmoderated statistically significant changes in NFR mediated by psychological detachment. However, the intervention appeared more beneficial for employees with high baseline NFR compared to those with low NFR, with moderated mediation by detachment at the 12-month follow-up.

Conclusions: Introducing new work strategies and common rules and routines for flexible work may be an effective intervention to facilitate detachment and reduce the need for recovery among office workers with particularly high needs.

Background: Trunk motor variability (MV) is key to understanding the development of fatigue and low back pain (LBP) in repetitive lifting, since it addresses the versatility of neuromuscular control of the multiple vertebral segments and thus the action of numerous muscles working actively together. Our goal in this scoping review was to clarify the predictive and reactive roles of trunk motor variability in occupational lifting, to inform future research and practical interventions for preventing and managing low back issues among manual workers.

Methods: We searched for full-length original articles written in English from the following three databases: MEDLINE, Scopus, and Web of Science. The search terms were structured to capture lifting, trunk, motor variability, fatigue and LBP.

Results: Sixteen studies were identified, covering both predictive associations, i.e., whether baseline differences in MV predict fatigue or pain, and reactive associations, i.e., how MV differs due to experimentally induced fatigue or the presence of pain. Most studies assessed kinematic MV (trunk angles, coordination) and a smaller subset examined kinetic variability using muscle activity measured through EMG-derived metrics. The predictive evidence, albeit from only one study, indicates that greater baseline MV is correlated with increased lifting endurance. As a reactive variable, MV increases with acute fatigue, while chronic pain tends to reduce MV or alter its complexity and structure. Diverse methods to quantify MV limited direct comparisons between several studies.

Discussion: Associations between trunk MV, fatigue, and LBP emerged, and were in accordance with results from both isometric exercise and dynamic tasks involving other body regions, such as the upper and lower extremities. However, the generalizability of the fatigue-pain-MV associations to occupational settings is questionable given the current evidence, since the reviewed studies involved small samples of individuals performing controlled lifting tasks in laboratory environments.

Background

Workers in home care have high sick leave rates, predominantly because of musculoskeletal pain. The Goldilocks Work Principle proposes that health should be promoted by a “just right” composition of work tasks. Weekly workloads differ substantially between home care workers, suggesting that certain workers may have workloads that are too high, impacting their musculoskeletal health. The aim of this study was to evaluate the effectiveness of a “GoldiCare” intervention redistributing weekly workloads to become more equal among the homecare workers. Outcomes were pain in the neck/shoulder and lower back, and the implementation of the intervention was also evaluated. 

Methods

A 16-week cluster randomized controlled trial was conducted with 125 workers from 11 home care units, divided into six intervention units and five control units. The operation coordinators of each intervention unit were educated in the Goldilocks Work Principle and provided with a planning tool to facilitate an even distribution of high care need clients. The control group continued their usual work. Primary outcomes were pain intensity in the neck/shoulder and lower back (0 to 10). Secondary outcomes included fatigue (0 to 10), composition of physical behaviors and postures (accelerometers), adherence to the intervention (weekly usage rates of the planning tool), and performance of the intervention (percentage of workers with an even distribution of workload). 

Results

The analysis showed no difference between the intervention and control groups in change in lower back pain (0.07, 95%CI[-0.29;0.43]), neck/shoulder pain (-0.06, 95%CI[-0.49;0.36]) or fatigue (0.04, 95%CI[-0.52;0.61]. No significant changes were observed in the composition of physical behaviors (p=0.067) or postures (p=0.080-0.131) between the two groups. The intervention was succesfully implemented in three units of the six, with adherence ranging from 82-100% across the intervention period. The remaining three units had an adherence of 0-47%. No improvement in performance was observed.

Conclusion

No significant intervention effects were observed on musculoskeletal pain, fatigue, or the composition of physical behaviors and postures. The findings suggest that the intervention was not adequately implemented within the organization. Consequently, we cannot discern whether the lack of positive results were due to poor implementation or an ineffective intervention. Results thus highlight the need for a more comprehensive understanding of organizational structures within home care to facilitate more effective implementations. The hypothetical effectiveness of a fully implemented intervention remains unknown.

Background

Eldercare work is physically demanding, which may contribute to high rates of sickness absence. Understanding the temporal patterns of time on feet and sitting, the latter assumed to represent recovery, and how they depend on organizational and individual factors is key to a better work organization that can effectively promote health, but this has not been studied before.

Aim

To describe temporal patterns of time on feet and sitting among homecare and nursing home workers and examine their associations with setting, job demands and resources, job title, and age.

Methods

Swedish homecare (n = 101) and nursing home (n = 73) workers wore accelerometers for 7 consecutive days to assess physical behaviors. Short (≤5 min), moderate (>5 to ≤30 min), and long (>30 min) bouts of time on feet and sitting were identified, with their relative distribution expressed in 5 ratios and analyzed using compositional data analysis procedures. Workers also completed a questionnaire on job organizational factors (job demands and resources) and individual factors (job title and age). MAN(C)OVA models were used to analyze differences in behaviors between eldercare settings, with organizational and individual factors being added in 2 consecutive models. Univariate analyses followed the multivariate models.

Results

Homecare and nursing home workers spent most of the workday on their feet (51.9% and 56.9%, respectively). The only statistically significant difference between settings was that homecare workers spent 30.1% less time sitting in long bouts relative to moderate and short compared to nursing home workers (P = 0.011), and this difference remained after adding covariates. Higher age was associated with more time on feet relative to sitting (P = 0.002, η2 = 0.06) and more time on feet in long bouts relative to moderate and short bouts (P = 0.001, η2 = 0.06) with medium effect sizes, as well as to more time on feet in moderate bouts relative short bouts (P = 0.011, η2 = 0.04), and less sitting in long bouts relative to moderate and short bouts (P = 0.019, η2 = 0.03) with small effect sizes.

Conclusions

Temporal patterns varied by setting and age, with homecare workers sitting less in long bouts than nursing home workers, and older workers spending more time on feet than younger workers. These findings suggest that work setting and worker characteristics are associated with temporal patterns of physical behavior, although most effects were small-to-moderate and their practical relevance remain uncertain and warrants further study.

Introduction. Eldercare organizations face high sickness absence rates and staff turnover and rely heavily on temporary workers to fill staffing gaps. Temporary workers may experience differences in job demands and resources compared to permanent workers, but this has been largely understudied.

Aim. To compare perceived job demands and resources between permanent and temporary Swedish eldercare workers.

Methods. Permanent and temporary eldercare workers in a Swedish municipality were invited to answer a digital survey on work environment conditions. Differences between permanent and temporary workers in job demands and resources were analyzed using multivariate analysis of variance adjusted for age, sex, place of birth, and percent of full-time work and univariate analyses were conducted to consider differences in specific factors.

Results. 1076 permanent and 675 temporary workers received the survey and the final study sample included 451 permanent and 151 temporary workers. Multivariate analyses revealed that temporary workers reported statistically significant lower job demands compared to permanent workers, but no statistically significant differences in resources were found between the groups. Univariate analyses showed that temporary workers reported lower quantitative demands, perceived exertion, and time spent bending forward, than permanent workers. These data suggest comparable support across groups, but a higher workload among permanent workers.

Conclusion. Our findings indicate that temporary workers experienced lower job demands than permanent workers, but that no notable difference was found in resources. Interventions aimed at distributing job demands more evenly among eldercare workers with different employment forms may be necessary.

Background: Flexible work arrangements (FWA) allow for work demands to extend into non-work hours, challenging employees' detachment from work. The extent of detachment may influence sleep and physical activity. However, organizational initiatives to influence detachment, and thus likely the 24-hour compositions of physical behaviors, among workers with FWA are sparse.

Aim: To examine the effects of a workplace intervention on the 24-hour composition of physical behaviors among office workers with flexible work.

Methods: The intervention introduced work strategies to promote detachment through an individual-level course on how to use digital tools and a workgroup-level workshop to develop common rules and routines in flexible work. Accelerometer and diary data were collected at baseline in an intervention group (eventually received both intervention activities, n=27) and a control group (no intervention, n=21), and again at a 12-month follow-up after the intervention to document sleep, physical activity, and inactivity.  Using compositional data analysis, we calculated two log-transformed ratios (ILR): 1) sleep relative to time awake and 2) physical activity relative to inactivity within time awake. Intervention effects were analyzed using Repeated Measures ANOVA.

Results: In the intervention group, sleep increased from 26% at baseline to 29% at follow-up, while time being active remained at 6% and inactivity decreased from 68% to 65%. In the control group, sleep decreased from 29% to 27%, time being active increased from 5% to 6%, and inactivity increased from 66% to 67%. Intervention effects on sleep were significant, while no significant difference in physical activity was observed between the groups.

Conclusions: The intervention was effective in increasing sleep in the intervention group compared to the control group but did not affect physical activity relative to inactivity. Employers may thus facilitate sleep in workers with FWA by implementing strategies promoting detachment at individual and workgroup levels.

Introduction: Flexible work arrangements (FWAs) may allow employees to structure their work to promote sufficient physical activity and sleep, which are key components of health-promoting physical behaviors that are important for musculoskeletal health. However, FWAs may challenge employees' ability to detach from work, which may result in less physical activity and sleep. Since detachment may be associated with sleep patterns and physical activity in FWAs, interventions promoting detachment could facilitate these behaviors. Despite this, interventions targeting detachment and its potential impact on physical behaviors, including sleep, remain scarce. This study examines the effects of a workplace intervention on the 24-hour composition of physical behaviors among office workers with flexible work.

Methods: The intervention comprised an individual-level course developing digital skills to increase the ability to plan, structure, prioritize, and gain control over work, and a workgroup-level workshop to create common rules and routines for flexible work. Accelerometer and diary data were collected to document sleep and physical activity at baseline in an intervention group (receiving both intervention activities, n=27) and a control group (no intervention, n=21), and at a 12-month follow-up of both groups after the intervention. Using compositional data analysis, we calculated two log-transformed ratios, i.e. ILR1: sleep relative to time awake, and ILR2: physical activity relative to inactivity within time awake. Intervention effects were analyzed using Repeated Measures MANOVA and ANOVA. 

Results: In the intervention group, sleep increased from 26% of the day at baseline to 29% at follow-up, corresponding to an increase of about 45 minutes, while active time remained at 6% and inactivity decreased from 68% to 65% of the day. In contrast, the control group experienced a decline in sleep from 29% to 27%, a slight increase in active time from 5% to 6%, and a rise in inactivity from 66% to 67%. The intervention significantly affected sleep relative to time awake (ILR 1), whereas no significant differences in physical activity relative to inactivity (ILR 2) were observed between the groups.

Discussion: Our findings suggest that the intervention helped office workers to increase their time in sleep relative to time awake, likely through better detachment from work. The effect on physical activity was insignificant, indicating that the intervention primarily facilitated recovery during sleep rather than promoted activity throughout the day. Although health outcomes were not directly measured, the findings may inspire musculoskeletal disorder (MSD) prevention in flexible work, as insufficient recovery is a known risk factor for MSDs. 

Conclusion: The intervention successfully increased sleep in the intervention group compared to the control group but did not significantly affect physical activity relative to inactivity. This suggests employers can support better recovery from work among employees with flexible work by implementing strategies to enhance detachment at individual and workgroup levels. Improved recovery through longer sleep may, in turn, contribute to preventing MSDs. 

Introduction: Repetitive work is associated with increased risk for musculoskeletal disorders (MSDs). We collaborated with a commercial laundromat to design and implement a job rotation (JR) inspired by the Goldilocks Work paradigm. The JR was designed to increase within-worker variability and positively impact worker health. The aim of the study was to evaluate the effectiveness of the JR by assessing pre-post changes in within-worker variability (assessed as within-worker variance) and health related outcomes. 

Methods: This pre-post case study had a 12-month follow-up after company implementation of the co-created JR intervention. All day-shift operations employees (N=57) were included in the JR. We measured trapezius (Trap) and forearm (FA) muscle activity at baseline for all 21 JR tasks and created a task exposure matrix (TEM). Estimates of within-worker variance were made for all individual workers at baseline, for the planned JR, and for the actual JR observed at follow-up using the TEM combined with the tasks performed (self-reported at baseline and follow-up) and the planned JR schedule. Variance estimates for the planned and actual JR were compared to baseline estimates to determine the theoretical and actual effects of the JR. Self-reported health-related outcomes on fatigue, recovery and MSD symptoms were collected by survey at follow-up. JR delivery and adherence to were assessed

Results: At follow-up, the JR intervention had been delivered to 65% of all day-shift operations workers, all of whom demonstrated adherence to the JR.  The planned JR showed the potential to increase the average within-worker variance in Trap and FA muscle activity by 45% compared with baseline. At follow-up, the actual JR was shown to have achieved approximately 80% of the planned increase.  Positive health-related changes were also evident at follow-up: approximately 40% of participants reported both lower physical and mental occupational demands, and over 50% of workers reported less fatigue after work and feeling more rested and recovered when starting a workday at follow-up compared to baseline. The number of workers experiencing upper extremity MSD problems ‘fairly often’ or ‘very often’ showed a slight increase at follow-up compared to baseline. 

Discussion: This is the first JR study to demonstrate a positive effect on both within-worker variability and health related variables.  Consideration of variability is key to JR studies since the proposed effects of a JR on improved musculoskeletal health are expected occur through JR-related increases in variability. Further, the positive findings on decreased self-reported physical and mental demands and fatigue and increased recovery lend support for the theory that a re-distribution of existing tasks can increase the average within-worker variability for the workers in the JR and that this increase may lead to health benefits. However, no positive changes in MSD were associated with the JR. 

Conclusion: This case study demonstrated both the potential (planned) and actual effectiveness of the JR to increase within-worker variability in Trap and FA muscle activity. Further, the findings suggest the JR had positive impacts on health-related outcomes. 

Background: Time-varying exposures, such as muscle activity and postural angles, are key risk factors for work-related musculoskeletal disorders when accumulated for long, uninterrupted periods. Traditional exposure metrics, however, often ignore the temporal structure of exposure. Exposure Variation Analysis (EVA) captures both the levels and sequence duration of exposures, thus offering a two-dimensional documentation of exposure variation.

Purpose: We aimed to summarize and critically appraise the use of EVA, examine methodological variability between studies, and identify opportunities for future development.

Methods: We performed a comprehensive review of studies published between 1991 and 2024 that explicitly utilized EVA. Searches were performed using citation tracking and database queries. Key information was extracted on exposure types, level and sequence duration intervals, EVA derivatives, and statistical analyses of EVA.

Results: A total of 94 studies were included in this review, mainly in occupational and public health sciences and sports. EVA has most frequently been used for analyzing electromyographic and postural data, but physical behaviors are a growing application. We found a wide variation in how studies defined categories for level and sequence duration intervals. Several studies simplified or post-processed the EVA matrix to extract summary measures, such as marginal distributions or variability indices. However, only one study accounted for the compositional structure of EVA data. Most statistical analyses were conducted on summary measures, not the full EVA matrix.

Conclusions: EVA has been applied in a range of research areas, mainly to document exposures rather than analyzing association with health outcomes. The large variety of level and sequence duration intervals highlight the need for standardization and further development. Future work should focus on defining reference interval sets for different exposure types, developing EVA derivatives, analyzing log-term effects on health of different EVA structures, and developing appropriate statistical models reflecting these analysis needs.