Inability to Work Fulltime, Prevalence and Associated Factors Among Applicants for Work Disability Benefit

Purpose Inability to work fulltime is an important outcome in the assessment of workers applying for a disability benefit. However, limited knowledge is available about the prevalence and degree of the inability to work fulltime, the associations between disease-related and socio-demographic factors with inability to work fulltime and whether the prevalence and the associations differ across disease groups. Methods Anonymized register data on assessments of workers with residual work capacity (n = 30,177, age 48.8 +/- 11.0, 53.9% female) applying for a work disability benefit in 2016 were used. Inability to work fulltime was defined as being able to work less than 8 h per day. Results The prevalence of inability to work fulltime was 39.4%, of these 62.5% could work up to 4 h per day. Higher age (OR 1.01, 95% CI 1.01-1.01), female gender (OR 1.45, 95% CI 1.37-1.52), higher education (OR 1.44, 95% CI 1.33-1.55) and multimorbidity (OR 1.06, 95% CI 1.01-1.11) showed higher odds for inability to work fulltime. Highest odds for inability to work fulltime were found for diseases of the blood, neoplasms and diseases of the respiratory system. Within specific disease groups, different associations were identified between disease-related and socio-demographic factors. Conclusion The prevalence and degree of inability to work fulltime in work disability benefit assessments is high. Specific chronic diseases are found to have higher odds for inability to work fulltime, and associated factors differ per disease group

Residual work capacity and (in)ability to work fulltime among a year cohort of cancer survivors who claim a disability benefit

PURPOSE: Residual work capacity (RWC) and inability to work fulltime (IWF) are important outcomes in disability benefit assessments for workers diagnosed with cancer. The aim of this study is to gain insight into the prevalence of both outcomes, the associations of disease-related and socio-demographic factors and if these differ across cancer diagnosis groups.METHODS: A year cohort of anonymized register data of cancer survivors who claim a disability benefit after 2 years of sick leave (n = 3690, age 53.3 ± 8.8, 60.4% female) was used. Having no RWC was defined as having no possibilities to perform any work at all, whereas IWF was defined as being able to work less than 8 h per day.RESULTS: The prevalence of being assessed with no RWC was 42.6%. Of the applicants with RWC (57.4%), 69.8% were assessed with IWF. Cancers of the respiratory organs showed the highest odds for having no RWC, whereas lymphoid and haematopoietic cancers showed the highest odds for IWF. Within specific cancer diagnosis groups, different associations were identified for both outcomes.CONCLUSION: The prevalence of no RWC and IWF in applicants of work disability benefits diagnosed with cancer is high compared to the prevalence in other diagnoses. The odds for no RWC, IWF, and associated factors differ per cancer diagnosis group.IMPLICATIONS FOR CANCER SURVIVORS: Being diagnosed with cancer has an enormous impact on work (dis)ability. Our results show that 2 years after being diagnosed with cancer, the majority of the disability benefit applicants are assessed with RWC; however, only 15% of all applicants with cancer had a normal ability to work fulltime, and therefore, it is of great importance to accompany them in their return to work.</p

Unravelling perceived fatigue and activity pacing in maintaining a physically active lifestyle after stroke rehabilitation:a longitudinal cohort study

Purposes To identify fatigue trajectories during/after stroke rehabilitation, to determine characteristics associated with trajectory membership before discharge and to investigate how these trajectories and activity pacing are associated with sustained physical activity after rehabilitation. Methods People after stroke (n = 206) were followed from 3–6 weeks before discharge (T0) to 14 (T1), 33 (T2) and 52 (T3) weeks after discharge from rehabilitation in the ReSpAct study. Latent Class analysis was used to identify trajectories of perceived fatigue. Binomial multivariable logistic regression analyses were performed to determine characteristics associated with trajectory membership (T0). Multilevel regression analyses were used to investigate how perceived fatigue and activity pacing were associated with self-reported physical activity (T0–T3). Results Three fatigue trajectories were identified: high (n = 163), low (n = 41) and recovery (n = 2). Compared with the high fatigue trajectory, people in the low fatigue trajectory were more likely to report higher levels of health-related quality of life (HR-QoL) (OR = 3.07, 95%CI = 1.51–6.26) and physical activity (OR = 1.93, 95%CI = 1.07–3.47). Sustained high levels of physical activity after rehabilitation were significantly associated with low perceived fatigue and high perceived risk of overactivity. Conclusions Three fatigue trajectories after stroke rehabilitation were identified. High levels of HR-QoL and physical activity before discharge identified people in the low fatigue trajectory. A physically active lifestyle after rehabilitation was associated with low perceived fatigue and perceived risk of overactivity. IMPLICATIONS FOR REHABILITATION Since almost 80% of people after stroke in this study perceived severe fatigue up to 1 year after stroke rehabilitation, activities focusing on the management of fatigue symptoms should be integrated in general stroke rehabilitation. In clinical practice, low levels of health-related quality of life and low levels of self-reported physical activity before discharge from stroke rehabilitation should be considered by rehabilitation professionals (e.g., physicians, physiotherapists, and physical activity counsellors) since these characteristics can predict chronic perceived fatigue up to 1 year after stroke rehabilitation. A physical activity counselling programme delivered during and after stroke rehabilitation may be improved by incorporating tailored advice regarding the management of fatigue

The implementation of a physical activity counseling program in rehabilitation care:findings from the ReSpAct study

Purpose: This study aimed to evaluate the implementation of a physical activity counseling program in rehabilitation and to study heterogeneity in received counseling and investigate its association with changes in patients? physical activity outcomes. Methods: This prospective cohort study was conducted in 18 rehabilitation institutions. Data were collected using surveys completed by professionals (n= ?70) and patients (n?=?1719). Implementation was evaluated using different process outcomes: reach, dosage, satisfaction, maintenance. Patients? physical activity outcomes included changes in total minutes/week of physical activity. Latent class analyses were conducted to identify profiles of received counseling characteristics and multilevel models were used to investigate associations with physical activity outcomes. Results: 5873 Patients were provided with motivational interviewing-based counseling after rehabilitation. Professionals and patients were positive about the program. Sixteen institutions (89%) formally agreed to continue the program. The four identified profiles of counseling characteristics illustrate a large variation in received counseling among patients. No substantial differences in physical activity outcomes were found between profiles. Conclusion: After a three-year program period, the physical activity counseling centers were sustainably implemented in Dutch rehabilitation care. This study illustrated an innovative approach to assess heterogeneity in implementation outcomes (e.g., counseling profiles) in relation to program outcomes (e.g., physical activity)

Assessment of Activity Pacing in Relation to Physical Activity and Health-Related Quality of Life in Adults with Multiple Sclerosis

Background: Activity pacing is a behavioral strategy for coping with fatigue, optimizing physical activity (PA) levels, and achieving a paced approach to lifestyle and sustainable self-regulated exercise practice to optimize health and well-being. Yet little is known about how activity pacing affects PA and health-related quality of life (HRQOL) while controlling for fatigue and demographic characteristics over time in adults with multiple sclerosis (MS). This study examined the natural use of activity pacing and how it is associated with PA and HRQOL over time in adults with MS. Methods: Sixty-eight adults with MS (mean ± SD age, 45.2 ± 10.9 years) completed questionnaires on their activity pacing, fatigue, PA, and HRQOL 14, 33, and 52 weeks after rehabilitation. Associations between the variables were examined using multilevel models. Results: No associations were found between activity pacing and PA (β = -0.01, P = .89) or between activity pacing and HRQOL (β = -0.15, P = .09). Conclusions: This study provides an initial understanding of how activity pacing relates to PA and HRQOL in people with MS over time and indicates that there is no clear strategy among adults with MS that is successful in improving PA and HRQOL in the short or long term. Persons with MS may benefit from goal-directed activity pacing interventions to improve longitudinal engagement in PA, and the present study provides a foundation for further intervention development

Longitudinal associations between activity pacing, fatigue, and physical activity in adults with multiple sclerosis

PURPOSE: The purpose of this study was to evaluate how activity pacing relates to physical activity and health-related quality of life over a one year period in a sample of adults with multiple sclerosis. METHODS: 68 adults with multiple sclerosis (mean age= 42 ± 11 years) filled in questionnaires on their active engagement in pacing decisions and perceived difficulty in preventing overactivity (5-point Activity Pacing and 2-point Risk of Overactivity Questionnaire), fatigue (7-point Fatigue Severity Scale), physical activity (adapted Short Questionnaire to Assess Health-Enhancing Physical Activity) and health-related quality of life (RAND-12 Health Survey) post rehabilitation and at one year follow up, as part of the Rehabilitation, Sports and Active lifestyle study (a nationwide multi-centre program aimed at stimulating and promoting an active lifestyle in rehabilitation in the Netherlands). Multilevel modelling was used to analyse the associations between activity pacing, fatigue, physical activity and health-related quality of life. RESULTS: No associations were found between activity pacing and physical activity (β = -0.21; p > 0.05), and between activity pacing and health-related quality of life (β = -0.10; p > 0.05) at long-term. Fatigue was negatively related to health-related quality of life (β = -0.35; p < 0.001). Perceived risk of overactivity moderated the association between fatigue and health-related quality of life (β = -0.13; p = 0.039). CONCLUSIONS: These findings suggest that persons who experience decreases in health-related quality of life with increased fatigue, are more likely to be engaging in ‘overactive’ behaviour. The lack of associations between activity pacing and physical activity, and between activity pacing and health-related quality of life suggests there is no clear strategy among persons with MS that is successful in improving physical activity and quality of life either in short or long-term when no interventions are introduced