Objectives Studies usually investigate a limited number or a predefined combinations of risk factors for sickness absence in employees with pain. We examined frequently occurring combinations across a wide range of work-related factors and pain perceptions.Design Cross-sectional study.Setting Belgian companies that are under supervision of IDEWE, an external service for prevention and protection at work.Participants In total, 249 employees experiencing pain for at least 6 weeks were included and filled out an online survey.Outcomes Latent profile analysis was used to differentiate profiles of work-related factors (physical demands, workload, social support and autonomy) and pain perceptions (catastrophising, fear-avoidance beliefs and pain acceptance). Subsequently, profiles were compared on sociodemographics (age, gender, level of education, work arrangement, duration of complaints, multisite pain and sickness absence in the previous year) and predictors of sickness absence (behavioural intention and perceived behavioural control).Results Four profiles were identified. Profile 1 (38.2%) had favourable scores and profile 4 (14.9%) unfavourable scores across all indicators. Profile 2 (33.3%) had relatively high physical demands, moderate autonomy levels and favourable scores on the other indicators. Profile 3 (13.7%) showed relatively low physical demands, moderate autonomy levels, but unfavourable scores on the other indicators. Predictors of profiles were age (OR 0.93 and 95% CI (0.89 to 0.98)), level of education (OR 0.28 and 95% CI (0.1 to 0.79)) and duration of sickness absence in the previous year (OR 2.29 and 95% CI (0.89 to 5.88)). Significant differences were observed in behavioural intention (χ2=8.92, p=0.030) and perceived behavioural control (χ2=12.37, p=0.006) across the four profiles.Conclusion This study highlights the significance of considering the interplay between work-related factors and pain perceptions in employees. Unfavourable scores on a single work factor might not translate into maladaptive pain perceptions or subsequent sickness absence, if mitigating factors are in place. Special attention must be devoted to employees dealing with unfavourable working conditions along with maladaptive pain perceptions. In this context, social support emerges as an important factor influencing sickness absence.

Background: Pain complaints are an important problem for employees, employers, and society. Up to 60% of the working population suffers from pain and these complaints are responsible for a third of all absenteeism. Pain is a complex phenomenon influenced by physical and psychosocial factors. Digital technologies such as smartphone applications offer opportunities to empower employees and help them manage and cope with their pain. However, lack of empirical evidence and user-friendly design hinder the adoption of these technologies in practice. This one group open label pilot aimed at evaluating the impact and user experience of an innovative smartphone application that includes monitoring as well as coaching to help employees manage their pain. Methods: An extensive co-design process including 262 end-users and seven domain experts was used to develop an app that contains 1) a monitoring part with questionnaires and integration with an activity tracker and 2) a coaching part including online information and exercises to help improve pain-related cognitions and other pain-management skills. Afterwards, 66 employees (experiencing pain for at least six weeks) of a large Belgian hospital used the smartphone app for six months. Every six weeks, participants were asked to complete a standardized questionnaire measuring work expectations, pain-related perceptions, and pain behavior. Finally, 12 employees participated in a semi-structured interview to help understand the quantitative findings, evaluate the user experience, and formulate recommendations towards the use of pain-management apps for employees. Quantitative and qualitative analyses by means of SPSS (version 28.0.1.0) and NVivo (version 1.0) were conducted to test the hypotheses. Results: Forty-eight participants had complaints, mostly located in the back (80%) and neck (74%), for at least one year. Only pain catastrophizing (χ2=15.934, p = .001) and fear avoidance (χ2=8.934, p = .030) were improved after using the app for six months. Participants experienced the app as useful and well elaborated. Based on the thematic analysis, seven recommendations emerged: 1) awareness and education about pain and pain perceptions stimulates behavior change, but make sure that the focus is on coping with pain and valued activities and not on the pain itself, 2) monitoring should be user friendly, accurate, and relevant, 3) the ability to explore and learn at your own pace is a must, 4) app functionalities should be attractive and provide maximal reward while requiring minimal effort from the user, 5) personalized and job-specific content is a must, 6) a blended approach, i.e. digital tools combined with human contact with a professional expert, is recommended, and 7) integration within a broader well-being policy at work is required. Conclusion: A smartphone application may help employees to monitor and cope with their pain at work. Provided that it meets some specific requirements: 1) an app is not used as a standalone but integrated within a broader wellbeing policy at work, 2) there is the possibility to interact with a professional, and 3) an app contains personal and job-specific recommendations tailored to the workplace and specific needs of the user.

Work-related Musculoskeletal disorders (MSDs) account for 60% of sickness-related absences and even permanent inability to work in the Europe.Long term impacts of MSDs include "Pain chronification" which is the transition of temporary pain into persistent pain.Preventive pain management can lower the risk of chronic pain.It is therefore important to appropriately assess pain in advance, which can assist a person in improving their fear of returning to work.In this study, we analysed pain data acquired over time by a smartphone application from a number of participants.We attempt to forecast a person's future pain levels based on his or her prior pain data.Due to the self-reported nature of the data, modelling daily pain is challenging due to the large number of missing values.For pain prediction modelling of a test subject, we employ a subset selection strategy that dynamically selects a closest subset of individuals from the training data.The similarity between the test subject and the training subjects is determined via dynamic time warping-based dissimilarity measure based on the time limited historical data until a given point in time.The pain trends of these selected subset subjects is more similar to that of the individual of interest.Then, we employ a Gaussian processes regression model for modelling the pain.We empirically test our model using a leave-one-subject-out cross validation to attain 20% improvement over state-of-the-art results in early prediction of pain.

OBJECTIVES:Knowledge is lacking on the interaction between fear of movement (FOM) and work-related physical and psychosocial factors in the development and persistence of musculoskeletal disorders (MSDs).METHODS:In this cross-sectional study, 305 healthcare workers from several Belgian hospitals filled out a questionnaire including sociodemographic factors, work-related factors (social support, autonomy at work, workload, and physical job demands), FOM, and MSDs for different body regions during the past year. Path analysis was performed to investigate (1) the association between the work-related factors, FOM and MSDs, and (2) the moderating role of FOM on the association between the work-related factors and MSDs among healthcare workers.RESULTS:Complaints were most frequently located at the neck-shoulder region (79.5%) and lower back (72.4%). Physical job demands (odds ratio [OR] 2.38 and 95% confidence interval [CI] 1.52-3.74), autonomy at work (OR 1.64 CI [1.07-2.49]) and FOM (OR 1.07 CI [1.01-1.14] and OR 1.12 CI [1.06-1.19]) were positively associated with MSDs. Healthcare workers who experienced high social support at work (OR 0.61 CI [0.39-0.94]) were less likely to have MSDs. Fear of movement interacted negatively with workload (OR 0.92 CI [0.87-0.97]) and autonomy at work (OR 0.94 CI [0.88-1.00]) on MSDs.CONCLUSIONS:Work-related physical and psychosocial factors as well as FOM are related to MSDs in healthcare workers. FOM is an important moderator of this relationship and should be assessed in healthcare workers in addition to work-related physical and psychosocial factors to prevent or address MSDs.