Development of Prediction Models for Sick Leave Due to Musculoskeletal Disorders

Musculoskeletal Health and Work: Development and Internal-External Cross-Validation of a Model to Predict Risk of Work Absence and Presenteeism in People Seeking Primary Healthcare

PURPOSE

To develop and validate prediction models for the risk of future work absence and level of presenteeism, in adults seeking primary healthcare with musculoskeletal disorders (MSD).

METHODS

Six studies from the West-Midlands/Northwest regions of England, recruiting adults consulting primary care with MSD were included for model development and internal-external cross-validation (IECV). The primary outcome was any work absence within 6 months of their consultation. Secondary outcomes included 6-month presenteeism and 12-month work absence. Ten candidate predictors were included: age; sex; multisite pain; baseline pain score; pain duration; job type; anxiety/depression; comorbidities; absence in the previous 6 months; and baseline presenteeism.

RESULTS

For the 6-month absence model, 2179 participants (215 absences) were available across five studies. Calibration was promising, although varied across studies, with a pooled calibration slope of 0.93 (95% CI: 0.41-1.46) on IECV. On average, the model discriminated well between those with work absence within 6 months, and those without (IECV-pooled C-statistic 0.76, 95% CI: 0.66-0.86). The 6-month presenteeism model, while well calibrated on average, showed some individual-level variation in predictive accuracy, and the 12-month absence model was poorly calibrated due to the small available size for model development.

CONCLUSIONS

The developed models predict 6-month work absence and presenteeism with reasonable accuracy, on average, in adults consulting with MSD. The model to predict 12-month absence was poorly calibrated and is not yet ready for use in practice. This information may support shared decision-making and targeting occupational health interventions at those with a higher risk of absence or presenteeism in the 6 months following consultation. Further external validation is needed before the models' use can be recommended or their impact on patients can be fully assessed.

The relationship between readiness to change pain-related exercise participation and perceived work ability: a cross-sectional study of factory workers

BACKGROUND

Healthy lifestyle behaviours are associated with protection against health disorders and pain. Exercise participation is one such behaviour, associated with improved outcomes in those experiencing pain. Musculoskeletal pain is highly prevalent in the workplace, particularly in factory workers and associated loss of work function is recognised as having a great impact on individuals, society and the economy. A worker's 'readiness to change pain behaviour' is an important factor to consider in achieving a healthy lifestyle behaviour and potentially improved function. This study aimed to examine the relationship between a cohort of factory workers 'readiness to change pain behaviour' such as exercise and their 'perceived work ability'.

METHODS

A cross-sectional study design was used to establish the relationship between 'readiness to change pain behaviours' and 'perceived work ability'. The Multidimensional Pain Related Change Questionnaire 2 (MPRCQ2) was used to measure readiness to change various pain behaviours including exercise. The Work Ability Index (WAI) was used to assess 'perceived work ability'. Seventy-five factory workers, aged over 18 (66 male, 9 female) were recruited using convenience sampling between September-November 2019. Correlation and multiple regression were used for statistical analysis.

RESULTS

Mean WAI, MPRCQ2 and MPRCQ2 exercise component were 41.89 (SD 5.28), 4.26 (SD 1.01) and 4.40 (SD 1.69). MPRCQ2 and MPRCQ2 exercise component were not significant predictors of WAI in factory workers (F (2, 72) = 2.17, p > 0.001). There was no significant relationship between MPRCQ2 and WAI (rs = .09, p > .05). However, there was a significant positive relationship between MPRCQ2 exercise component and WAI (rs = .23, p < .05).

CONCLUSIONS

This study suggests that readiness to change pain-related exercise participation has a positive association with 'perceived work ability'. Further research should explore the causal relationship and consider strength training as a specific type of exercise.

Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes: The 2019 Literature Year in Review

Data science continues to be recognized and used within healthcare due to the increased availability of large data sets and advanced analytics. It can be challenging for nurse leaders to remain apprised of this rapidly changing landscape. In this article, we describe our findings from a scoping literature review of papers published in 2019 that use data science to explore, explain, and/or predict 15 phenomena of interest to nurses. Fourteen of the 15 phenomena were associated with at least one paper published in 2019. We identified the use of many contemporary data science methods (eg, natural language processing, neural networks) for many of the outcomes. We found many studies exploring Readmissions and Pressure Injuries. The topics of Artificial Intelligence/Machine Learning Acceptance, Burnout, Patient Safety, and Unit Culture were poorly represented. We hope that the studies described in this article help readers: (1) understand the breadth and depth of data science's ability to improve clinical processes and patient outcomes that are relevant to nurses and (2) identify gaps in the literature that are in need of exploration.

Workplace musculoskeletal problems in occupational therapy students

Background

Workplace musculoskeletal disorders are the leading cause of morbidity and disability in the Australian workforce. Over one in five occupational therapists report workplace musculoskeletal disorders, with almost half reporting workplace musculoskeletal symptoms. In other health professions, students and novice clinicians (≤5 years practice) experience greater risk but little is known about occupational therapy students.

Methods

In this cross-sectional study, a survey including the self-reported Standardised Nordic Musculoskeletal Questionnaire was administered to occupational therapy students post work-based training. Musculoskeletal problems were defined as aches, pains, numbness or discomfort. Questions explored body sites affected, prevalence, impact on activity, need for medical assistance, demographic and workplace information. Prevalence was reported using descriptive statistics. Factors associated with workplace musculoskeletal problems over the previous 12 months and last 7 days were examined using logistic regression modelling.

Results

Response rate was 53% (n = 211/397). One-third of respondents (33.6%, n = 71/211) reported a workplace musculoskeletal problem over 12 months. Nearly half (47.9%, n = 34/71) of these students reported a problem over the last 7 days. Neck was the most commonly affected area reported for musculoskeletal problems over the past 12 months (24.2%, n = 51/211) and shoulder areas affected over the past 7 days (10.9%, n = 23/211). Musculoskeletal problems preventing daily activities were reported most commonly from lower back problems over 12 months (23.9%, n = 17/71) and for shoulder problems over the last 7 days (21.9%, n = 7/32). Shoulders and knees were the most common body areas requiring medical attention. Previous musculoskeletal problems and female gender were associated with reported problems over 12 months and last 7 days (p < 0.05). Non-standard joint mobility (OR = 3.82, p = 0.002) and working in psychosocially focused caseloads (including mental health or case management) (OR = 3.04, p = 0.044) were also associated with reporting musculoskeletal problems over the last 7 days.

Conclusions

One in three occupational therapy students already experience workplace musculoskeletal problems impacting daily activities and requiring medical assistance prior to graduation. High prevalence of musculoskeletal problems in this study calls for educators and researchers to find sustainable strategies to address these problems, with particular consideration to the impact of previous disorders and working in psychosocially focused caseloads on musculoskeletal health.

Employee Musculoskeletal Complaints and Supervisor Support: Implications for Behavioral Stress Reactions

OBJECTIVE

This research investigated the moderating role of supervisor support for employees with musculoskeletal complaints and their intentions to seek medical advice; take sick leave; transfer jobs; and resign.

METHODS

Cross-sectional questionnaire data were collected from 1024 Australian employees.

RESULTS

Regressions with bootstrapping revealed no support for the buffering role of supervisor support. In contrast to expectations, high supervisor support heightened, rather than lowered, musculoskeletal complaints on intentions to transfer jobs. For sick leave and resignation intentions, high supervisor support buffered the negative effects of musculoskeletal complaints for full-timers but exacerbated such intentions for part-timers. Furthermore, full-timers with high musculoskeletal complaints appeared more vulnerable to the exacerbating effects of low supervisor support compared with part-timers.

CONCLUSIONS

Supervisor support for employees with musculoskeletal complaints both weakens and strengthens behavioral stress reactions, depending on employment status.

Predicting Long-Term Sickness Absence and Identifying Subgroups Among Individuals Without an Employment Contract

Purpose Today, decreasing numbers of workers in Europe are employed in standard employment relationships. Temporary contracts and job insecurity have become more common. This study among workers without an employment contract aimed to (i) predict risk of long-term sickness absence and (ii) identify distinct subgroups of sick-listed workers. Methods 437 individuals without an employment contract who were granted a sickness absence benefit for at least two weeks were followed for 1 year. We used registration data and self-reported questionnaires on sociodemographics, work-related, health-related and psychosocial factors. Both were retrieved from the databases of the Dutch Social Security Institute and measured at the time of entry into the benefit. We used logistic regression analysis to identify individuals at risk of long-term sickness absence. Latent class analysis was used to identify homogenous subgroups of individuals. Results Almost one-third of the study population (n = 133; 30%) was still at sickness absence at 1-year follow-up. The final prediction model showed fair discrimination between individuals with and without long-term sickness absence (optimism adjusted AUC to correct for overfitting = 0.761). Four subgroups of individuals were identified based on predicted risk of long-term sickness absence, self-reported expectations about recovery and return to work, reason of sickness absence and coping skills. Conclusion The logistic regression model could be used to identify individuals at risk of long-term sickness absence. Identification of risk groups can aid professionals to offer tailored return to work interventions.

Assessment of a new tool to improve case manager identification of delayed return to work in the first two weeks of a workers' compensation claim

OBJECTIVE

To determine whether the Plan of Action for a Case (PACE) tool improved identification of workers at risk of delayed return to work.

DESIGN

Prospective cohort of workers with accepted workers' compensation claims in the state of New South Wales, Australia.

INTERVENTIONS

The 41-item PACE tool was completed by the case manager within the first two weeks of a claim. The tool gathered information from the worker, employer and treating practitioner. Multivariate logistic regression models predicted work time loss of at least one and three months.

RESULTS

There were 524 claimants with complete PACE information. A total of 195 (37.2%) had work time loss of at least one month and 83 (15.8%) had time loss of at least three months. Being male, injury location, an Orebro Musculoskeletal Pain Screening Questionnaire-Short Form score >50, having a small employer, suitable duties not being available, being certified unfit, and the worker having low one-month recovery expectations predicted time loss of over one month. For three months, injury location, a Short Form Orebro score >50, no return-to-work coordinator, and being certified unfit were significant predictors. The model incorporating PACE information provided a significantly better prediction of both one- and three-month outcomes than baseline information (area-under-the-curve statistics-one month: 0.85 and 0.68, respectively; three months: 0.85 and 0.69, respectively; both P < 0.001).

CONCLUSION

The PACE tool improved the ability to identify workers at risk of ongoing work disability and identified modifiable factors suited to case manager-led intervention.