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Modeling sickness absence data: A scoping review.

ABSTRACT: The identification of sick leave determinants could positively influence decision making to improve worker quality of life and to reduce consequently costs for society. Sick leave is a research topic of interest in economics, psychology, health and social behaviour. The question of choosing an appropriate statistical tool to analyse sick leave data can be challenging. In fact, sick leave data have a complex structure, characterized by two dimensions: frequency and duration, and involve numerous features related to individual and environmental factors. We conducted a scoping review to characterize statistical approaches to analyse individual sick leave data in order to synthesise key insights from the extensive literature, as well as to identify gaps in research. We followed the PRISMA methodology for scoping reviews and searched Medline, World of Science, Science Direct, Psycinfo and EconLit for publications using statistical modeling for explaining or predicting sick leave at the individual level. We selected 469 articles from the 5983 retrieved, dated from 1981 to 2019. In total, three types of model were identified: univariate outcome modeling using for the most part count models (438 articles), bivariate outcome modeling (14 articles), such as multistate models and structural equation modeling (22 articles). The review shows that there was a lack of evaluation of the models as predictive accuracy was only evaluated in 18 articles and the explanatory accuracy in 43 articles. Further research based on joint models could bring more insights on sick leave spells, considering both their frequency and duration.

SUBMITTER: Duchemin T

PROVIDER: S-EPMC7491724 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Modeling sickness absence data: A scoping review.

Duchemin Tom T Hocine Mounia N MN

PloS one 20200915 9

The identification of sick leave determinants could positively influence decision making to improve worker quality of life and to reduce consequently costs for society. Sick leave is a research topic of interest in economics, psychology, health and social behaviour. The question of choosing an appropriate statistical tool to analyse sick leave data can be challenging. In fact, sick leave data have a complex structure, characterized by two dimensions: frequency and duration, and involve numerous ...[more]

PMID: 32931519

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Project description:AimEarlier research has revealed a strong relationship between alcohol use and sickness absence. The aim of this review was to explore and uncover this relationship by looking at differences in type of design (cross-sectional vs. longitudinal), type of data (self-reported vs. registered data), and type of sickness absence (long-term vs. short term).MethodSix databases were searched through June 2020. Observational and experimental studies from 1980 to 2020, in English or Scandinavian languages reporting the results of the association between alcohol consumption and sickness absence among working population were included. Quality assessment, and statistical analysis focusing on differences in the likelihood of sickness absence on subgroup levels were performed on each association, not on each study. Differences in the likelihood of sickness absence were analyzed by means of meta-analysis. PROSPERO registration number: CRD42018112078.ResultsFifty-nine studies (58% longitudinal) including 439,209 employees (min. 43, max. 77,746) from 15 countries were included. Most associations indicating positive and statistically significant results were based on longitudinal data (70%) and confirmed the strong/causal relationship between alcohol use and sickness absence. The meta-analysis included eight studies (ten samples). The increased risk for sickness absence was likely to be found in cross-sectional studies (OR: 8.28, 95% CI: 6.33-10.81), studies using self-reported absence data (OR: 5.16, 95% CI: 3.16-8.45), and those reporting short-term sickness absence (OR: 4.84, 95% CI: 2.73-8.60).ConclusionThis review supports, but also challenges earlier evidence on the association between alcohol use and sickness absence. Certain types of design, data, and types of sickness absence may produce large effects. Hence, to investigate the actual association between alcohol and sickness absence, research should produce and review longitudinal designed studies using registry data and do subgroup analyses that cover and explain variability of this association.

Project description:BackgroundOver the past decade, growing attention has been given to the mental health of workers. One way to examine the mental health of workers is to look at the incidence rates of mental illness-related sickness absence. There is a scarcity of literature in which the incidence rates of mental illness-related sickness absence among different countries have been considered together. The purpose of this systematic literature review is to address the question: Are there similarities and differences in the incidence rates of mental disorder-related sickness absence among and within OECD identified Social Democratic, Liberal and Latin American country categories? In this paper, we seek to identify differences and similarities in the literature rather than to explain them. With this review, we lay the groundwork for and point to areas for future research as well as to raise questions regarding reasons for the differences and similarities.MethodsA systematic literature search of the following databases were performed: Medline Current, Medline In-process, PsycINFO, Econlit and Web of Science. The search period covered 2002-2013. The systematic literature search focused on working adults between 18-65 years old who had not retired and who had mental and/or substance abuse disorders. Intervention studies were excluded. The search focused on medically certified sickness absences.ResultsA total of 3,818 unique citations were identified. Of these, 10 studies met the inclusion/exclusion criteria; six were from Social Democratic countries. Their quality ranged from good to excellent. There was variation in the incidence rates reported by the studies from the Social Democratic, Liberal and Latin American countries in this review.ConclusionsThe results of this systematic review suggest that this is an emerging area of inquiry that needs to continue to grow. Priority areas to support growth include cross jurisdictional collaboration and development of a typology characterizing the benefit generosity and work integration policies of sickness absence schemes. Finally, the literature should be updated to reflect changes in sickness absence benefit schemes over time.

Project description:BackgroundFrequent sickness absence-that is, 3 or more episodes of sickness absence in 1 year-is a problem for employers and employees. Many employees who have had frequent sickness absence in a prior year also have frequent sickness absence in subsequent years: 39% in the first follow-up year and 61% within 4 years. Moreover, 19% have long-term sickness absence (≥6 weeks) in the first follow-up year and 50% within 4 years. We developed an electronic health (eHealth) intervention, consisting of fully automated feedback and advice, to use either as a stand-alone tool (eHealth intervention-only) or combined with consultation with an occupational physician (eHealth intervention-occupational physician).ObjectiveThis study aimed to evaluate the effect of the eHealth intervention, with or without additional occupational physician consultation, to reduce sickness absence frequency for employees with frequent sickness absence, versus care as usual (CAU).MethodsThis study was a three-armed randomized controlled trial. Employees with frequent sickness absence received invitational letters, which were distributed by their employers. The primary outcome measure was the number of register-based sickness absence episodes 12 months after completing the baseline questionnaire. Secondary outcome measures were register-based total sickness absence days and self-assessed burnout, engagement, and work ability. In a process evaluation 3 months after baseline, we examined adherence to the intervention and additional actions such as general practitioner and occupational physician visit, communication with the manager, and lifestyle change.ResultsA total of 82 participants were included in the analyses, 21 in the eHealth intervention-only group, 31 in the eHealth intervention-occupational physician group, and 30 in the CAU group. We found no significant difference in sickness absence frequency between the groups at 1-year follow-up. Sickness absence frequency decreased in the eHealth intervention-only group from 3 (interquartile range, IQR 3-4) to 1 episode (IQR 0.3-2.8), in the eHealth intervention-occupational physician group from 4 (IQR 3-5) to 3 episodes (IQR 1-4), and in the CAU group from 3 (IQR 3-4) to 2 episodes (IQR 1-3). For secondary outcomes, we found no significant differences between the intervention groups and the control group. The process evaluation showed that only 3 participants from the eHealth intervention-occupational physician group visited the occupational physician on invitation.ConclusionsAmong employees with frequent sickness absence, we found no effect from the eHealth intervention as a stand-alone tool in reducing sickness absence frequency, nor on total sickness absence days, burnout, engagement, or work ability. This might be due to low adherence to the intervention because of insufficient urgency to act. We cannot draw any conclusion on the effect of the eHealth intervention tool combined with an occupational physician consultation (eHealth intervention-occupational physician), due to very low adherence to the occupational physician consultation. An occupational physician consultation could increase a sense of urgency and lead to more focus and appropriate support. As this was the first effectiveness study among employees with frequent sickness absence, strategies to improve recruitment and adherence in occupational eHealth are included.Trial registrationNetherlands Trial Register NTR4316; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4316 (Archived by WebCite at http://www.webcitation.org/713DHhOFU).

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Modeling sickness absence data: A scoping review.

Publications

Modeling sickness absence data: A scoping review.

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