Identifying return-to-work trajectories using sequence analysis in a cohort of workers with
                    work-related musculoskeletal disorders

McLeod, Chris; Reiff, Eline; Maas, Esther T.; Bültmann, Ute

doi:10.5271/sjweh.3701

Cited by 26 publications

(36 citation statements)

References 24 publications

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“…Using sequence and cluster analysis provided a more comprehensive picture of various SA and DP patterns among injured bicyclist. This can be seen as a good complement to traditional regression analysis [30][31][32]43]. The advantage of methods allowing for complex pattern analysis is illustrated in the present study especially by the clusters "Episodic SA" and "Long-term SA", where the heterogeneity of SA and DP can be seen.…”

Section: Discussionmentioning

confidence: 69%

“…Sequence analysis could be a suitable method to also gain knowledge on different patterns over time regarding, e.g., individuals' timing, duration, and order of different types of events, such as SA and DP [29] and the interest for such analyses has increased lately. Sequence analysis has been used in several studies, with the observation that the identified heterogeneity between the sequences can be a good complement and adds additional value to traditional regression analyses [30][31][32]. Thus, to get a more complete picture of the long-term patterns regarding SA and DP in relation to a bicycle crash there is a need for studies using more comprehensive methods.…”

Section: Introductionmentioning

confidence: 99%

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Sequence analysis of sickness absence and disability pension in the year before and the three years following a bicycle crash; a nationwide longitudinal cohort study of 6353 injured individuals

et al. 2020

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Background Bicyclists are the road user group with the highest number of severe injuries in the EU, yet little is known about sickness absence (SA) and disability pension (DP) following such injuries. Aims To explore long-term patterns of SA and DP among injured bicyclists, and to identify characteristics associated with the specific patterns. Methods A longitudinal register-based study was conducted, including all 6353 individuals aged 18–59 years and living in Sweden in 2009, who in 2010 had incident in-patient or specialized out-patient healthcare after a bicycle crash. Information about sociodemographic factors, the injury, SA (SA spells > 14 days), and DP was obtained from nationwide registers. Weekly SA/DP states over 1 year before through 3 years after the crash date were used in sequence and cluster analyses. Multinomial logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for factors associated with each identified sequence cluster. Results Seven clusters were identified: “No SA or DP” (58.2% of the cohort), “Low SA or DP” (7.4%), “Immediate SA” (20.3%), “Episodic SA” (5.9%), “Long-term SA” (1.7%), “Ongoing part-time DP” (1.7%), and “Ongoing full-time DP” (4.8%). Compared to the cluster “No SA or DP”, all other clusters had higher ORs for women, and higher age. All clusters but “Low SA and DP” had higher ORs for inpatient healthcare. The cluster “Immediate SA” had a higher OR for: fractures (OR 4.3; CI 3.5–5.2), dislocation (2.8; 2.0–3.9), sprains and strains (2.0; 1.5–2.7), and internal injuries (3.0; 1.3–6.7) compared with external injuries. The cluster “Episodic SA” had higher ORs for: traumatic brain injury, not concussion (4.2; 1.1–16.1), spine and back (4.5; 2.2–9.5), torso (2.5; 1.4–4.3), upper extremities (2.9; 1.9–4.5), and lower extremities (3.5; 2.2–5.5) compared with injuries to the head, face, and neck (not traumatic brain injuries). The cluster “Long-term SA” had higher ORs for collisions with motor vehicles (1.9;1.1–3.2) and traumatic brain injury, not concussion (18.4;2.2–155.2). Conclusion Sequence analysis enabled exploration of the large heterogeneity of SA and DP following a bicycle crash. More knowledge is needed on how to prevent bicycle crashes and especially those crashes/injuries leading to long-term consequences.

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Section: Discussionmentioning

confidence: 69%

Section: Introductionmentioning

confidence: 99%

Sequence analysis of sickness absence and disability pension in the year before and the three years following a bicycle crash; a nationwide longitudinal cohort study of 6353 injured individuals

et al. 2020

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“…Statistics Norway provided detailed administrative register data [16] on income, employment, welfare benefits (FD-Trygd), education (the Norwegian National Education Database), and demographics (the Central Population register). In previous studies of RTW using sequence analysis, register data has been linked to subsamples based on intervention [3, 9, 10] or region [11] with follow-up times of a few years. Here, individual’s labour-market participation was followed from 2004Q1 to 2013Q4 (excluding those who are self-employed).…”

Section: Methodsmentioning

confidence: 99%

“…Here, individual’s labour-market participation was followed from 2004Q1 to 2013Q4 (excluding those who are self-employed). A quarterly time-scale was used to facilitate the classification of trajectories, which can be complicated by long sequences [11, 17]. Individuals who died during the study period ( n = 198) or who had missing baseline socio-demographic characteristics ( n = 1421) were excluded.…”

Section: Methodsmentioning

confidence: 99%

Return to work after first incidence of long-term sickness absence: A 10-year prospective follow-up study identifying labour-market trajectories using sequence analysis

Madsen

2019

Scand J Public Health

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Aims: The study aim was to identify prototypical labour-market trajectories following a first incidence of long-term sickness absence (LTSA), and to assess whether baseline socio-demographic characteristics are associated with the return-to-work (RTW) process and labour-market attachment (LMA). Methods: This prospective study used Norwegian administrative registers with quarterly information on labour-market participation to follow all individuals born 1952–1978 who underwent a first LTSA during the first quarter of 2004 ( n =9607) over a 10-year period (2004–2013). Sequence analysis was used to identify prototypical labour-market trajectories and LMA; trajectory membership was examined with multinomial logistic regression. Results: Sequence analysis identified nine labour-market trajectories illustrating the complex RTW process, with multiple states and transitions. Among this sample, 68.2% had a successful return to full-time work, while the remaining trajectories consisted of part-time work, unemployment, recurrence of LTSA, rehabilitation and disability pension (DP). A higher odds ratio (OR) for membership to trajectories of weaker LMA was found for females and older participants, while being married/cohabitating, having children, working in the public sector, and having a higher education, income and occupational class were associated with a lower OR of recurrence, unemployment, rehabilitation and DP trajectories. These results are consistent with three LMA indicators. Conclusions: Sequence analysis revealed prototypical labour-market trajectories and provided a holistic overview of the heterogeneous RTW processes. While the most frequent outcome was successful RTW, several unfavourable labour-market trajectories were identified, with trajectory membership predicted by socio-demographic measures.

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“…In a previous study, we showed the importance of measuring RTW as a trajectory, and thereby including modified RTW as one of the events in the sickness absence trajectory to explain time to RTW [ 34 ]. In this study we were able to show that MJHs in most cases take longer to RTW compared to SJHs, but future studies would benefit from addressing the issue of more refined or detailed measures of RTW, as well as the description of MJHs.…”

Section: Discussionmentioning

confidence: 99%

Return-to-work for multiple jobholders with a work-related musculoskeletal disorder: A population-based, matched cohort in British Columbia

2018

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IntroductionMultiple jobholders (MJHs) have a higher risk of injury compared to single jobholders (SJHs), but it is unknown if return-to-work (RTW) after a work injury is affected by multiple jobholding. This study examined the association between multiple versus single jobholding and time to RTW for workers with a work-related musculoskeletal disorder (MSD).MethodsWe used administrative workers’ compensation data to identify injured workers with an accepted MSD lost-time claim between 2010–2014 in British Columbia, Canada (n = 125,639 SJHs and 9,029 MJHs). The outcome was days until RTW during twelve months after the first day of time-loss. The MJH and SJH cohorts were balanced using coarsened exact matching that yielded a final matched cohort of 8,389 MJHs and 8,389 SJHs. The outcome was estimated with Cox regression, using piecewise models, and the hazard ratios were stratified by type of MSD, a serious injury indicator, gender, weekly workdays preceding MSD, and wage categories.ResultsMJHs were less likely to RTW compared to SJHs within the first six months after the first time-loss day, with greater and longer lasting effects for males, workers with a serious injury, and a higher wage. No difference between MJHs and SJHs was found for workers who had a six- or seven-day work week preceding MSD, for workers with dislocations, and for workers who were still off work after six months.ConclusionsOverall, MJHs with a workweek of maximum five days are disadvantaged compared to SJHs in terms of RTW following a work-related MSD within the first six months after the first time-loss day. This difference might be caused by more precarious job contracts for MJHs that challenges RTW because of lack of support for modified work, higher workload, and reduced likelihood that MJHs file a workers’ compensation claim. Despite adjusting for type of MSD, severity of injury and occupation, the differences persisted for the vast majority of the study sample.

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Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders

Cited by 26 publications

References 24 publications

Sequence analysis of sickness absence and disability pension in the year before and the three years following a bicycle crash; a nationwide longitudinal cohort study of 6353 injured individuals

Sequence analysis of sickness absence and disability pension in the year before and the three years following a bicycle crash; a nationwide longitudinal cohort study of 6353 injured individuals

Return to work after first incidence of long-term sickness absence: A 10-year prospective follow-up study identifying labour-market trajectories using sequence analysis

Return-to-work for multiple jobholders with a work-related musculoskeletal disorder: A population-based, matched cohort in British Columbia

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