Different Methods to Detect Stress in Knowledge Workers: A Pilot Study for Long-term Monitoring.

Stress is a common part of working life, but knowledge is lacking on how to identify it early and with little effort on the part of the employee. We investigated whether simple stress reports and computer usage data could be useful tools for long-term assessment of stress in real life. 38 experts responded to a baseline questionnaire on need for recovery (NFR) and psychological distress (General Health Questionnaire, GHQ12). Their computer usage for work was recorded for 5 months, during which they filled in a 4-month simple diary and a 2-week detailed diary on, for example, stress and productivity. Salivary cortisol and heart rate variability were collected on 3 consecutive days. Generalized estimating equations models were used for the analyses. High NFR and GHQ12 predicted self-reported stress during work, and a decrease in (some) mouse usage features, but not keyboard usage features, over the following months. Some mouse usage features were associated with stress and productivity. The results provide some support for the usefulness of simple stress questions and mouse usage features in assessing long-term stress in real life.

Role of physical activity in the relationship between recovery from work and insomnia among early childhood education and care professionals: a cross-sectional study.

OBJECTIVES: This study aimed to investigate the association between recovery from work and insomnia and the role of objectively measured leisure-time physical activity and occupational physical activity in this association. DESIGN: Cross-sectional. SETTING AND PARTICIPANTS: Study with female early childhood education and care professionals (N=224) in Finland was conducted between April 2017 and September 2018. METHODS: Recovery from work was measured with the Need for Recovery scale and insomnia with the Jenkins Sleep Scale. Physical activity was measured with an accelerometer for 7 days and analysed to represent leisure-time physical activity and occupational physical activity (min/day). RESULTS: Both Jenkins Sleep Scale and occupational physical activity significantly predicted Need for Recovery (ß=0.29; 95% CI 0.17 to 0.42 and ß=0.14; 95% CI 0.01 to 0.27, respectively). A low relationship was observed between the Need for Recovery and Jenkins Sleep Scale (r=0.32, 95% Cl 0.19 to 0.44). After categorising participants into four groups based on median splits of occupational and leisure-time physical activity, relationships between the Need for Recovery and Jenkins Sleep Scale were low to moderate in the high occupational physical activity and leisure time physical activity group (r=0.38, 95% Cl 0.14 to 0.61), and in the high occupational physical activity and low leisure-time physical activity group (r=0.40, 95% Cl 0.18 to 0.63). CONCLUSION: Both insomnia and physical activity at work seem to be relevant in recovery from work. To enhance recovery, especially those involved in high physical activity at work, should seek methods to improve recovery, by incorporating activities that promote recuperation both during their workday and in their leisure time. Further research on the relevance of physical activity in recovery with longitudinal setting is warranted. TRIAL REGISTRATION NUMBER: NCT03854877.

High compassion predicts fewer sleep difficulties: A general population study with an 11-year follow-up.

INTRODUCTION: This study investigated the cross-sectional and longitudinal associations between self-reported compassion and sleep quality. METHODS: The data came from the population-based Young Finns Study with an 11-year follow-up on compassion and sleep (n = 1064). We used regression models, multilevel models, and cross-lagged panel models to analyze the data. RESULTS: The results showed that high compassion was cross-sectionally associated with lesser sleep deficiency and fewer sleep difficulties. High compassion also predicted fewer sleep difficulties over an 11-year follow-up (adjusted for age, gender, socioeconomic position in childhood and adulthood, body mass index, health behaviors, and working conditions). This association disappeared when controlling for depressive symptoms. The predictive pathway seemed to proceed more likely from high compassion to fewer sleep difficulties than vice versa. DISCUSSION: Compassion may buffer against sleep difficulties, possibly via reducing depressive symptoms.

Relationship between occupational and leisure-time physical activity and the need for recovery after work.

BACKGROUND: Health benefits of physical activity are very well acknowledged but the role of both occupational physical activity (OPA) and leisure time physical activity (LTPA) in recovery after work is not thoroughly understood. The purpose of this study was to investigate the association between accelerometer-measured OPA and LTPA and the need for recovery after work (NFR) in early childhood education and care (ECEC) professionals. METHODS: The study participants were 217 female ECEC professionals aged 17-64. Physical activity was recorded with a three-axis accelerometer (ActiGraph GT9X Link, ActiGraph, USA) for seven consecutive days. Separate analyses were conducted for both OPA and LTPA and reported as hours/day based on different intensity levels (light, moderate, vigorous, very vigorous). The NFR was measured with the Need For Recovery (NFR) scale (0%-100%). RESULTS: Participants' average physical activity for both OPA and LTPA was about 4 h/day, and the mean NFR score was 38.4%. OPA was significantly associated with the NFR but not with LTPA. The relationship remained significant after adjustments for age, body mass index, work ability, mental health status, and sleep difficulties (p < 0.024). CONCLUSION: According to this study, the OPA level is related to the level of the NFR in female ECEC professionals. Based on the results, it seems that LTPA has no relevance to the NFR. Results suggest that long-lasting OPA, even without strenuous physical activity at work, may predispose individuals to a high NFR.

Hospital physicians´ working hour characteristics and sleep quality: a cross-sectional analysis of realized working hour and survey data.

BACKGROUND: Hospital physicians' work includes on-call duties to provide 24/7 health care. Previous studies using self-reported survey data have associated long working hours and on-call work with sleep difficulties. To reduce recall bias, we complemented survey data with payroll-based objective data to study whether hospital physicians' realized working hours are associated with sleep. METHODS: The study was nested within the Finnish Public Sector study. We used survey data on 728 hospital physicians (mean age 43.4 years, 62% females) from 2015 linked to realized daily working hour data from 3 months preceding the survey. The associations of working hour characteristics with sleep quantity and quality were studied with multinomial logistic regression analysis adjusted for demographics, overall stressfulness of life situation, control over scheduling of shifts, and hospital district. RESULTS: One fourth (26%) of the participants reported short (≤6.5 h) average sleep duration. Frequent night work (> 6 shifts/91 days) was associated with short sleep (OR 1.87 95%CI 1.23-2.83) compared to no night work. Approximately one third (32%) of the physicians reported insufficient sleep. Physicians with long weekly working hours (> 48 hours) had higher odds for insufficient sleep (OR 1.78 95%CI 1.15-2.76) than physicians with short weekly working hours (< 40 hours). Insufficient sleep was also associated with frequent on-call duties (> 12 shifts/3 months OR 2.00 95%CI 1.08-3.72), frequent night work (OR 1.60 95%CI 1.09-2.37), and frequent short shift intervals (≤11 hours; > 12 times/3 months OR 1.65 95%CI 1.01-2.69) compared to not having these working hour characteristics. Nearly half of the physicians (48%) reported at least one sleep difficulty at least two times a week and frequent night work increased odds for difficulties in initiating sleep (OR 2.43 95%CI 1.04-5.69). Otherwise sleep difficulties were not associated with the studied working hour characteristics. CONCLUSION: We used realized working hour data to strengthen the evidence on on-call work and sleep quality and our results advice to limit the frequency of night work, on-call shifts, short shift intervals and long weekly working hours to promote hospital physicians' sufficient sleep.

The self-reported stress and stressors in tram and long-haul truck drivers.

Work stress may compromise professional drivers' health and driving capacity. Differences between driver groups in terms of on-duty stress are understudied. Therefore, we examined self-reported stress (Stockholm University Stress Scale) of shift-working tram and long-haul truck drivers (n = 75) across 2-3 weeks. Furthermore, stressors were self-reported retrospectively and categorised as related to the job, driving conditions, personal, or other causes. Stress levels were generally low, but moderate to high stress (≥6) was more frequently reported among the tram drivers. Stressors related to the job (54%) and driving conditions (19% of all shifts) were frequently reported among the tram and truck drivers, respectively. Moderate to high stress was associated with categorised stressors related to the job and other causes among the tram drivers, and all categorised stressors among the truck drivers. Altogether, self-reported stress and stressors differ by driver group, but the role of shift type is less significant.

Working hours, on-call shifts, and risk of occupational injuries among hospital physicians: A case-crossover study.

OBJECTIVE: To investigate the association of hospital physicians' working hours and on-call shifts with the risk of occupational injuries. METHODS: In this nested cohort study of 556 Finnish hospital physicians, we linked electronic records from working-hour and on-call duty payroll data to occupational injury data obtained from the Finnish Workers' Compensation Center for the period 2005-2019. We used a case-crossover design with matched intervals for a 7-day 'case window' immediately prior to occupational injury and a 'control window' 7 days prior to the beginning of the case window, and analyzed their associations using conditional logistic regression models. RESULTS: We noted 556 occupational injuries, 281 at the workplace and 275 while commuting. Having three to four long (>12 h) work shifts on the preceding 7 days was associated with a higher probability of an occupational injury (odds ratio [OR] 2.14, 95% confidence interval [CI] 1.11, 4.09), and the OR for three to four on-call shifts was 3.54 (95%CI 2.11, 5.92) in comparison to having none of these work shift types. A higher number of several consecutive working days was associated with a higher probability of injury in a dose-response manner. Moreover, increasing weekly working hours was associated with an increased likelihood of injury (OR 1.03, 95%CI 1.01, 1.04), whereas the number of normal (≤12 h) work shifts reduced this likelihood (OR 0.79, 95%CI 0.64, 0.98). CONCLUSIONS: Our findings suggest that accumulated working-hour load, as opposed to single, very long (>24 h) work shifts, may increase the risk of occupational injury among hospital physicians.

Do holidays change subjective sleep length or sleep debt in shift work disorder?

In shift work disorder (SWD), disturbed sleep acutely impairs employees' recovery, but little attention has been paid to sleep during longer recovery periods. We examined how holidays affect self-estimated sleep length, sleep debt, and recovery in cases of SWD. Twenty-one shift workers with questionnaire-based SWD and nine reference cases without SWD symptoms completed a questionnaire on recovery and sleep need. They also reported sleep length on two separate occasions: during a work period and after ≥ 2 weeks of holidays. Sleep debt was calculated by subtracting sleep length from sleep need. We used parametric tests to compare the groups and the periods. The groups reported shorter sleep on workdays than during holidays (median difference: SWD group 1.7 h, p<0.001; reference group 1.5 h; p<0.05). The SWD group's self-estimated sleep during holidays increased less above the sleep need (median 0.0 h) than the reference group's sleep (1.0 h, p<0.05). In addition, the SWD group reported good recovery from irregular working hours less often (14%) than the reference group (100%, p<0.001). Although holidays were generally associated with longer sleep estimates than workdays, employees with SWD experienced consistently less efficient recovery than those without SWD.

Association of working hour characteristics and on-call work with risk of short sickness absence among hospital physicians: A longitudinal cohort study.

Physicians often work long hours and on-call shifts, which may expose them to circadian misalignment and negative health outcomes. However, few studies have examined whether these working hour characteristics, ascertained using objective working hour records, are associated with the physicians' risk of sickness absence. We investigated the associations of 14 characteristics of payroll-based working hours and on-call work with the risk of short sickness absence among hospital physicians. In this cohort study, 2845 physicians from six Finnish hospital districts were linked to electronic payroll-based records of daily working hours, on-call duty and short (1-3 days) sickness absence between 2005 and 2019. A case-crossover design was applied using conditional logistic regression with the 28 day case and control windows to estimate odds ratios (ORs) and 95% confidence intervals (CI) for short sickness absence. After controlling for weekly working hours and the number of normal (≤12 h) shifts, a higher number of long (>12 h) shifts (ORs for ≥5 versus none: 2.54, 95% CI 1.68-3.84), very long (>24 h) shifts (ORs for ≥5 versus none: 2.62, 95%CI 1.61-4.27), and on-call shifts (OR for ≥5 versus none: 2.15, 95% CI 1.44-3.21) and a higher number of short (<11 h) shift intervals (OR for ≥5 versus none: 12.61, 95% CI 8.88-17.90) were all associated with the increased risk of short sickness absence. These associations did not differ between male and female physicians or between age groups. To conclude, the findings from objective working hour records show that long work shifts, on-call shifts and short shift intervals are related to the risk of short (1-3 days) sickness absence among hospital physicians.

Sleep, sleepiness and need for recovery of industrial employees after a change from an 8- to a 12-hour shift system.

Employees often prefer 12-hour work shifts but they can increase sleepiness and injury risk. We assessed whether sleep, sleepiness, satisfaction and need for recovery changed after changing from an 8-hour to a 12-hour shift system. The participants were 178 employees of the paper, pulp and chemical industries. Using a quasi-experimental controlled intervention design, 83 employees, who changed from an 8-hour shift schedule to a 12-hour shift schedule were compared to those who remained in the 8-hour shift schedule (n=95). Participants filled in a survey on sleep, sleepiness, satisfaction and need for recovery at baseline and 9-12 months after the shift schedule change. We used generalized estimation equation models adjusted for age, sex, shift work experience in years and baseline shift system. Sleep length was longer in the 12-hour shift schedule before the first morning shift and between morning shifts. Sleepiness during morning shifts was less frequent and satisfaction with the shift system was more prevalent in the 12-hour shift schedule. Also, perceived negative associations of the current shift system with work-life balance were less common in the 12-hour shift schedule. The differences found between the shift systems were minor and the results did not indicate significant disadvantages of the 12-hour fast forward-rotating shift system.

Sleep-time physiological recovery is associated with eating habits in distressed working-age Finns with overweight: secondary analysis of a randomised controlled trial.

BACKGROUND: Association of physiological recovery with nutrition has scarcely been studied. We investigated whether physiological recovery during sleep relates to eating habits, i.e., eating behaviour and diet quality. METHODS: Cross-sectional baseline analysis of psychologically distressed adults with overweight (N = 252) participating in a lifestyle intervention study in three Finnish cities. Recovery measures were based on sleep-time heart rate variability (HRV) measured for 3 consecutive nights. Measures derived from HRV were 1) RMSSD (Root Mean Square of the Successive Differences) indicating the parasympathetic activation of the autonomic nervous system and 2) Stress Balance (SB) indicating the temporal ratio of recovery to stress. Eating behaviour was measured with questionnaires (Intuitive Eating Scale, Three-Factor Eating Questionnaire, Health and Taste Attitude Scales, ecSatter Inventory™). Diet quality was quantified using questionnaires (Index of Diet Quality, Alcohol Use Disorders Identification Test Consumption) and 48-h dietary recall. RESULTS: Participants with best RMSSD reported less intuitive eating (p = 0.019) and less eating for physical rather than emotional reasons (p = 0.010) compared to those with poorest RMSSD; participants with good SB reported less unconditional permission to eat (p = 0.008), higher fibre intake (p = 0.028), higher diet quality (p = 0.001), and lower alcohol consumption (p < 0.001) compared to those with poor SB, although effect sizes were small. In subgroup analyses among participants who reported working regular daytime hours (n = 216), only the associations of SB with diet quality and alcohol consumption remained significant. CONCLUSIONS: Better nocturnal recovery showed associations with better diet quality, lower alcohol consumption and possibly lower intuitive eating. In future lifestyle interventions and clinical practice, it is important to acknowledge sleep-time recovery as one possible factor linked with eating habits. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT01738256 , Registered 17 August 2012.

Self-reported reasons for on-duty sleepiness among commercial airline pilots.

Experimental and epidemiological research has shown that human sleepiness is determined especially by the circadian and homeostatic processes. The present field study examined which work-related factors airline pilots perceive as causing on-duty sleepiness during short-haul and long-haul flights. In addition, the association between the perceived reasons for sleepiness and actual sleepiness levels was examined, as well as the association between reporting inadequate sleep causing sleepiness and actual sleep-wake history. The study sample consisted of 29 long-haul (LH) pilots, 28 short-haul (SH) pilots, and 29 mixed fleet pilots (flying both SH and LH flights), each of whom participated in a 2-month field measurement period, yielding a total of 765 SH and 494 LH flight duty periods (FDPs) for analyses (FDP, a period between the start of a duty and the end of the last flight of that duty). The self-reports of sleepiness inducers were collected at the end of each FDP by an electronic select menu. On-duty sleepiness was rated at each flight phase by the Karolinska Sleepiness Scale (KSS). The sleep-wake data was collected by a diary and actigraph. The results showed that "FDP timing" and "inadequate sleep" were the most frequently reported reasons for on-duty sleepiness out of the seven options provided, regardless of FDP type (SH, LH). Reporting these reasons significantly increased the odds of increased on-duty sleepiness (KSS ≥ 7), except for reporting "inadequate sleep" during LH FDPs. Reporting "inadequate sleep" was also associated with increased odds of a reduced sleep-wake ratio (total sleep time/amount of wakefulness ≤ 0.33). Both "FDP timing" and "inadequate sleep" were most frequently reported during early morning and night FDPs, whereas the other options showed no such phenomenon. The present study suggests that airline pilots' perceptions of work-related factors that make them sleepy at work are in line with the previous experimental and epidemiological studies of sleepiness regulation.

Association of shift work with mood disorders and sleep problems according to chronotype: a 17-year cohort study.

Both evening chronotype and shift work are associated with depressive symptoms. This study examined whether the association between shift work and mood disorders and sleep problems varies by chronotype. The study population included 10637 participants from the Finnish Hospital Personnel Cohort Study. Work schedule was assessed using repeated questionnaires between 2000 and 2017. Chronotype, assessed using a single item from the Diurnal Type Scale, was categorized into definite morning, somewhat morning, somewhat evening, and definite evening types. The presence of mood disorders was identified by the 12-item General Health Questionnaire. Sleep problems were assessed by self-reported frequency of difficulty falling asleep and maintaining asleep. Longitudinal fixed effects models were used to examine the associations between shift work and the presence of mood disorders and sleep problems, stratified by chronotype. We found that fixed night work was associated with mood disorders among somewhat evening (adjusted odds ratio [OR] 1.91, 95% CI 1.09-3.34) and definite evening-type workers (adjusted OR 2.05, 95% CI 1.06-3.98). Shift work with night shifts was associated with mood disorders among definite evening-type workers (adjusted OR 1.75, 95% CI 1.18-2.60). Similarly, fixed night work was associated with difficulty maintaining sleep only among evening-type workers. In conclusion, evening chronotype increase the vulnerability to mood disorders and sleep disturbances related to night work.

Differential DNA methylation in recovery from shift work disorder.

The human DNA methylome is responsive to our environment, but its dynamics remain underexplored. We investigated the temporal changes to DNA methylation (DNAme) in relation to recovery from a shift work disorder (SWD) by performing a paired epigenome-wide analysis in an occupational cohort of 32 shift workers (25 men, age = 43.8 ± 8.8 years, 21 SWD cases). We found that the effect of vacation on DNAme was more prominent in the SWD-group as compared to controls, with respect to the amount of significantly differentially methylated positions (DMPs; Punadj < 0.05) 6.5 vs 3.7%, respectively. The vast majority (78%) of these DMPs were hypomethylated in SWD but not in controls (27%) during the work period. The Gene Ontology Cellular component "NMDA glutamate receptor" (PFDR < 0.05) was identified in a pathway analysis of the top 30 genes in SWD. In-depth pathway analyses revealed that the Reactome pathway "CREB phosphorylation through the activation of CaMKII" might underlie the recovery. Furthermore, three DMPs from this pathway, corresponding to GRIN2C, CREB1, and CAMK2B, correlated with the degree of recovery (Punadj < 0.05). Our findings provide evidence for the dynamic nature of DNAme in relation to the recovery process from a circadian disorder, with biological relevance of the emerging pathways.

High need for recovery from work and sleep problems are associated with workers' unhealthy dietary habits.

OBJECTIVE: We aimed to examine the association of recovery from work and sleep with workers' dietary habits. DESIGN: Cross-sectional study. Need for recovery (NFR) from work was assessed with a validated questionnaire. Sleep was assessed with five questions from the Nordic Sleep Questionnaire and sleep quality question. Dietary habits were estimated using a validated sixteen food groups-containing questionnaire. Ordered logistic regression was used to explore the associations of NFR and sleep with dietary habits adjusted for age, education, marital status, work schedule, working full or part time and occupation. SETTING: Follow-up visits of type 2 diabetes prevention study cohort in a Finnish airline company. PARTICIPANTS: The study included 737 men and 605 women. RESULTS: Poor recovery from work was associated with a higher eating frequency (OR = 1·03, 95 % CI 1·00, 1·06), higher intake of fast food (OR = 1·05, 95 % CI 1·02, 1·08) and sweets (OR = 1·05, 95 % CI 1·02, 1·08) as well as lower intake of vegetables (OR = 0·96, 95 % CI 0·93, 0·98) and fruits (OR = 0·96, 95 % CI 0·93, 0·98) among men. In women, poor recovery from work was associated with higher fast food (OR = 1·06, 95 % CI 1·02, 1·09) and desserts consumption (OR = 1·04, 95 % CI 1·00, 1·07). Among men and women, sleep problems were associated with higher eating frequency (men: OR = 1·04, 95 % CI 1·00, 1·07, women: OR = 1·06, 95 % CI 1·02, 1·11), consumption of fast food (men: OR = 1·07, 95 % CI 1·04, 1·11, women: OR = 1·06, 95 % CI 1·02, 1·10) and sweets (men: OR = 1·05, 95 % CI 1·01, 1·08, women: OR = 1·04, 95 % CI 1·00, 1·08). CONCLUSIONS: Poor recovery from work and sleep problems were associated with unfavourable dietary habits especially in men.

Ageing shift workers' sleep and working-hour characteristics after implementing ergonomic shift-scheduling rules.

We studied whether implementing binding ergonomic shift-scheduling rules change ageing (≥45 years) social and healthcare employees' (mean age 52.5 years, 95% women) working-hour characteristics (e.g. weekly working hours, number and length of night shifts, and short shift intervals) and sleep. We compared an intervention group (n = 253) to a control group (n = 1,234) by survey responses (baseline 2007/2008, follow-up 2012) and objective working-hour characteristics (intervention group n = 159, control group n = 379) from 91 days preceding the surveys. Changes in working-hour characteristics were analysed with repeated measures general linear models. The fully adjusted model (sociodemographics and full-/part-time work) showed that proportion of short shift intervals (<11 hr, p = .033) and weekend work (p = .01) decreased more in the intervention than in the control group. Changes in sleep outcomes were analysed with generalised logit model to binomial and multinomial variables. The fully adjusted model (sociodemographics, full-/part-time work, job strain, health behaviours, and perceived health) revealed higher odds in the intervention group for long sleep (≥9 hr; odds ratio [OR] 5.53, 95% confidence interval [CI] 2.21-13.80), and lower odds of short sleep (<6 hr; OR 0.72, 95% CI 0.57-0.92), having at least two sleep difficulties often (OR 0.55, 95% CI 0.43-0.70), and more specifically difficulties in falling asleep (OR 0.56, 95% CI 0.41-0.77), waking up several times per night (OR 0.43, 95% CI 0.34-0.55), difficulties in staying asleep (OR 0.64, 95% CI 0.49-0.82), and non-restorative sleep (OR 0.70, 95% CI 0.54-0.90) than the control group. In conclusion, implementation of ergonomic shift-scheduling rules resulted in minor changes in ageing employees' objective working hours and a consistent buffering effect against worsening of sleep.

The Associations of Electronic Health Record Usability and User Age With Stress and Cognitive Failures Among Finnish Registered Nurses: Cross-Sectional Study.

BACKGROUND: Electronic health records (EHRs) are expected to provide many clinical and organizational benefits. Simultaneously, the end users may face unintended consequences, such as stress and increased cognitive workload, due to poor EHR usability. However, whether the effects of usability depend on end user characteristics, such as career stage or age, remains poorly understood. OBJECTIVE: The objective of this study was to examine the associations of EHR usability and user age with stress related to information systems and cognitive failures among registered nurses. METHODS: A cross-sectional survey design was employed in Finland in 2017. A total of 3383 registered nurses responded to the nationwide electronic survey. Multiple linear regression was used to examine the associations of EHR usability (eg, how easily information can be found and a patient's care can be documented) and user age with stress related to information systems and cognitive failures. Interaction effects of EHR usability and age were also tested. Models were adjusted for gender and employment sector. RESULTS: Poor EHR usability was associated with higher levels of stress related to information systems (ß=.38; P<.001). The strength of the association did not depend on user age. Poor EHR usability was also associated with higher levels of cognitive failures (ß=.28; P<.001). There was a significant interaction effect between age and EHR usability for cognitive failures (ß=.04; P<.001). Young nurses who found the EHR difficult to use reported the most cognitive failures. CONCLUSIONS: Information system stress due to poor EHR usability afflicts younger and older nurses alike. However, younger nurses starting their careers may be more cognitively burdened if they find EHR systems difficult to use compared to older nurses. Adequate support in using the EHRs may be particularly important to young registered nurses, who have a lot to learn and adopt in their early years of practice.

The effects of using participatory working time scheduling software on working hour characteristics and wellbeing: A quasi-experimental study of irregular shift work.

BACKGROUND: Studies in the health care sector indicate that good work time control is associated with better perceived wellbeing but also with non-ergonomic work schedules, such as compressed work schedules. Participatory working time scheduling is a collaborative approach to scheduling shift work. Currently, there is a lack of information on whether working hour characteristics and employees' wellbeing in irregular shift work change after implementing participatory working time scheduling. OBJECTIVE: To investigate the effects of using digital participatory working time scheduling software on working hour characteristics and well-being among Finnish hospital employees. PARTICIPANTS AND METHODS: We compared changes in objective working hour characteristics and wellbeing between 2015 and 2017 among employees (n = 677, mainly nurses and practical nurses) when using participatory working time scheduling software (participatory scheduling, n = 283) and traditional shift scheduling (traditional scheduling, n = 394). The statistical analyses were conducted using the repeated measures general linear model and the generalized logit model for binomial and multinomial variables adjusted for age, sex, education, shift work experience, control over scheduling of shifts at baseline (where applicable) and hospital district. RESULTS: The proportion of long work shifts (≥ 12 h) increased to a greater extent (F = 4.642, p = 0.032) with the participatory scheduling than with the traditional scheduling. In comparison to traditional scheduling, the perceived control over scheduling of shifts increased (OR 3.24, 95% CI 1.73-6.06) and excessive sleepiness in connection with evening shifts decreased (OR 0.40, 95% CI 0.16-0.99) significantly with participatory scheduling. None of the other wellbeing variables showed statistically significant changes in the adjusted models. CONCLUSIONS: The proportion of long work shifts and perceived control over scheduling of shifts increased more among employees using participatory working time scheduling than among those using traditional scheduling. Otherwise, using participatory working time scheduling software had little effect on both objectively measured working hour characteristics and perceived wellbeing in comparison to traditional scheduling. The results merit confirmation in a larger sample with a longer follow-up. Tweetable abstract Participatory working time scheduling combines individual flexibility and staffing requirements in shift work.

Personalized mental stress detection with self-organizing map: From laboratory to the field.

Stress has become a major health concern and there is a need to study and develop new digital means for real-time stress detection. Currently, the majority of stress detection research is using population based approaches that lack the capability to adapt to individual differences. They also use supervised learning methods, requiring extensive labeling of training data, and they are typically tested on data collected in a laboratory and thus do not generalize to field conditions. To address these issues, we present multiple personalized models based on an unsupervised algorithm, the Self-Organizing Map (SOM), and we propose an algorithmic pipeline to apply the method for both laboratory and field data. The performance is evaluated on a dataset of physiological measurements from a laboratory test and on a field dataset consisting of four weeks of physiological and smartphone usage data. In these tests, the performance on the field data was steady across the different personalization levels (accuracy around 60%) and a fully personalized model performed the best on the laboratory data, achieving accuracy of 92% which is comparable to state-of-the-art supervised classifiers. These results demonstrate the feasibility of SOM in personalized mental stress detection both in constrained and free-living environment.