Dataset Information

Quickscan assesses risk factors of long-term sickness absence: A cross-sectional (factorial) construct validation study.

ABSTRACT:

Objectives

The number of sick-listed employees has increased dramatically worldwide. Therefore, many countries aim to stimulate early and sustainable return to work opportunities to obtain better health outcomes and lower costs for disability pensions. To effectively orientate resources to patients with a high risk of not resuming work spontaneously, it is necessary to screen patients early in their sickness absence process. In this study, we validate "Quickscan", a new instrument to assess return-to-work needs and to predict risks of long-term sick leave.

Methods

As part of the Quickscan validation process, we tested and compared the reliability and construct validity of the questionnaire in two different populations. First, we conducted a cross-sectional study in which the screening instrument was sent to sick-listed individuals in healthcare insurance. In a second cross-sectional study, sick-listed workers who consulted the occupational health physician for return-to-work assessment were asked to fill out the questionnaire. We compared both samples for descriptive statistics: frequencies, means and standard deviations. Reliability of the scales was calculated using Cronbach's alpha. Confirmatory factor analysis was performed to evaluate the construct (factorial) validity of the studied scales using software package AMOS 24.

Results

The screening tool was shown to be an instrument with reliable scales (except for the perfectionism and health perception patient scale) in both populations. The construct validity was satisfactory: we found that the hypothesized measurement models with the theoretical factors fitted the data well in both populations. In the first sample, the model improved for scales concerning stressful life events and showed worse fit for person-related factors. Work-related factors and functioning factors both showed similar fit indices across samples. We found small differences in descriptive statistics, which we could explain by the differences in characteristics of both populations.

Conclusions

We can conclude that the instrument has considerable potential to function as a screening tool for disability management and follow-up of sick-leave, provided that some adaptations and validation tests are executed.

SUBMITTER: Goorts K

PROVIDER: S-EPMC6329504 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Quickscan assesses risk factors of long-term sickness absence: A cross-sectional (factorial) construct validation study.

Goorts Kaat K Vandenbroeck Sofie S Vander Elst Tinne T Rusu Dorina D Du Bois Marc M Decuman Saskia S Godderis Lode L

PloS one 20190111 1

<h4>Objectives</h4>The number of sick-listed employees has increased dramatically worldwide. Therefore, many countries aim to stimulate early and sustainable return to work opportunities to obtain better health outcomes and lower costs for disability pensions. To effectively orientate resources to patients with a high risk of not resuming work spontaneously, it is necessary to screen patients early in their sickness absence process. In this study, we validate "Quickscan", a new instrument to ass ...[more]

PMID: 30633762

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Project description:BACKGROUND:Societal expenditures on work-disability benefits is high in most Western countries. As a precursor of long-term work restrictions, long-term sickness absence (LTSA) is under continuous attention of policy makers. Different healthcare professionals can play a role in identification of persons at risk of LTSA but are not well trained. A risk prediction model can support risk stratification to initiate preventative interventions. Unfortunately, current models lack generalizability or do not include a comprehensive set of potential predictors for LTSA. This study is set out to develop and validate a multivariable risk prediction model for LTSA in the coming year in a working population aged 45-64?years. METHODS:Data from 11,221 working persons included in the prospective Study on Transitions in Employment, Ability and Motivation (STREAM) conducted in the Netherlands were used to develop a multivariable risk prediction model for LTSA lasting ?28 accumulated working days in the coming year. Missing data were imputed using multiple imputation. A full statistical model including 27 pre-selected predictors was reduced to a practical model using backward stepwise elimination in a logistic regression analysis across all imputed datasets. Predictive performance of the final model was evaluated using the Area Under the Curve (AUC), calibration plots and the Hosmer-Lemeshow (H&L) test. External validation was performed in a second cohort of 5604 newly recruited working persons. RESULTS:Eleven variables in the final model predicted LTSA: older age, female gender, lower level of education, poor self-rated physical health, low weekly physical activity, high self-rated physical job load, knowledge and skills not matching the job, high number of major life events in the previous year, poor self-rated work ability, high number of sickness absence days in the previous year and being self-employed. The model showed good discrimination (AUC 0.76 (interquartile range 0.75-0.76)) and good calibration in the external validation cohort (H&L test: p =?0.41). CONCLUSIONS:This multivariable risk prediction model distinguishes well between older workers with high- and low-risk for LTSA in the coming year. Being easy to administer, it can support healthcare professionals in determining which persons should be targeted for tailored preventative interventions.

Project description:Background:Musculoskeletal pain is a major cause of work disability. Many patients with musculoskeletal pain seek care from health care providers other than their general practitioners, including a range of musculoskeletal practitioners. Therefore, these musculoskeletal practitioners may play a key role by engaging in sickness absence management and work disability prevention. This study aimed to determine the prevalence of musculoskeletal practitioners' practice behaviours, and their perceptions and beliefs about sickness absence management by using Scandinavian chiropractors as an example, as well as to examine the association between these characteristics and two different practice behaviours. Methods:As part of a mixed-methods study, we surveyed members of the national chiropractic associations in Denmark, Norway, and Sweden in 2016. Descriptive statistics were used to describe prevalence. Multilevel logistic regression with backwards stepping was used to estimate odds ratios with 95% confidence intervals between each of the two practice behaviours and the characteristics. Results:Out of the 802 respondents (response rate 56%), 372 were Danish, 349 Norwegian, and 81 Swedish. In Denmark and Norway, 38.7 and 37.8% always/often considered if sick leave was appropriate for their patient compared to 21.0% in Sweden (p =?0.007); and 86.5% of the Norwegian chiropractors always/often recommended to return-to-work versus 64.5 and 66.7% in Denmark and Sweden respectively (p <?0.001). In the final models, factors associated with the two practice behaviours were age, level of clinical experience, working as a teacher, the tendency to be updated on current legislations and policies using social services, contact with general practitioners, relevance of engagement in SAM, consideration of workplace factors, SAM as part of the clinical tool box, patient out-of-pocket fee, and recommending fast return-to-work. Conclusions:Whilst not always engaged in sickness absence management with regards to musculoskeletal pain, chiropractors favour a 'return-to-work' rather than a 'stay-at-home' approach. Several practice behaviours and perceptions and beliefs are associated with these outcomes; however, system or organisational barriers are linked to clinician non-engagement.

Project description:BackgroundLong-term sickness absence results in increased risks of permanent disability and a compromised quality of life. Return to work is an important factor in reducing these risks. Little is known about return to work factors for long-term sick-listed workers with subjective health complaints. The aim of this study was to evaluate prognostic factors for partial or full return to a paid job for at least 28 days for long-term sick-listed workers with subjective health complaints, and to compare these factors with those of workers with other disorders.MethodsData from a prospective cohort study of 213 participants with subjective health complaints and 1.037 reference participants were used. The participants answered a questionnaire after 84 weeks of sickness absence. Return to work was measured after one and two years. Univariable logistic regression analyses were performed (P ≤ 0.157) for variables per domain with return to work (i.e. demographic, socio-economic and work-related, health-related, and self-perceived ability). Subsequently, multivariable logistic regression analyses with backward selection (P ≤ 0.157) were performed. Remaining factors were combined in a multivariable and final model (P ≤ 0.05).ResultsBoth for workers with subjective health complaints and for the reference group, non-health-related factors remained statistically significant in the final model. This included receiving a partial or complete work disability benefit (partial: OR 0.62, 95% CI 0.26-1.47 and OR 0.69, 95% CI 0.43-1.12; complete: OR 0.24, 95% CI 0.10-0.58 and OR 0.12, 95% CI 0.07-0.20) and having a positive self-perceived possibility for return to work (OR 1.06, 95% CI 1.01-1.11 and OR 1.08, 95% CI 1.05-1.11).ConclusionsNon-health-related factors seem to be more important than health-related factors in predicting return to work after long-term sickness absence. Receiving a work disability benefit and having negative expectations for return to work seem to complicate return to work most for workers with subjective health complaints. With respect to return to work predictors, workers with subjective health complaints do not differ from the reference group.

Dataset Information

Quickscan assesses risk factors of long-term sickness absence: A cross-sectional (factorial) construct validation study.

Objectives

Methods

Results

Conclusions

Publications

Quickscan assesses risk factors of long-term sickness absence: A cross-sectional (factorial) construct validation study.

Similar Datasets

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