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BACKGROUND: The SF-6Dv2 classification system assesses health states in six domains-physical functioning, role function, bodily pain, vitality, social functioning, and mental health. Scores have previously been derived from the SF-36v2® Health Survey. We aimed to develop a six-item stand-alone SF-6Dv2 Health Utility Survey (SF-6Dv2 HUS) and evaluate its comprehensibility. METHODS: Two forms of a stand-alone SF-6Dv2 HUS were developed for evaluation. Form A had 6 questions with 5-6 response choices, while Form B used 6 headings and 5-6 statements describing the health levels within each domain. The two forms were evaluated by 40 participants, recruited from the general population. Participants were randomized to debrief one form of the stand-alone SF-6Dv2 HUS during a 75-min interview, using think-aloud techniques followed by an interviewer-led detailed review. Participants then reviewed the other form of SF-6Dv2 and determined which they preferred. Any issues or confusion with items was recorded, as was as overall preference. Data were analyzed using Microsoft Excel and NVivo Software (v12). RESULTS: Participants were able to easily complete both forms. Participant feedback supported the comprehensibility of the SF-6Dv2 HUS. When comparing forms, 25/40 participants preferred Form A, finding it clearer and easier to answer when presented in question/response format. The numbered questions and underlining of key words in Form A fostered quick and easy comprehension and completion of the survey. However, despite an overall preference for Form A, almost half of participants (n = 19) preferred the physical functioning item in Form B, with more descriptive response choices. CONCLUSION: The results support using Form A, with modifications to the physical functioning item, as the stand-alone SF-6Dv2 HUS. The stand-alone SF-6Dv2 HUS is brief, easy to administer, and comprehensible to the general population.

OBJECTIVE: This study aimed to gain insight into decision-making strategies individuals used when evaluating pairs of SF-6Dv2 health states in discrete choice experiments (DCEs). METHODS: This qualitative, cross-sectional, noninterventional study asked participants to use a think-aloud approach to compare SF-6Dv2 health states in DCEs. Thematic analysis focused on comprehension and cognitive strategies used to compare health states and make decisions. RESULTS: Participants (N = 40) used 3 main strategies when completing DCEs: (1) trading, (2) reinterpretation, and (3) relying on previous experience. Trading was the most common strategy, used by everyone at least once, and involved prioritizing key attributes, such as preferring a health state with significant depression but no bodily pain. Reinterpretation was used by 17 participants and involved reconstructing health states by changing underlying assumptions (eg, rationalizing selecting a health state with significant pain because they could take pain medications). Finally, some (n = 13) relied on previous experience when making decisions on some choice tasks. Participants with experience dealing with pain, for instance, prioritized health states with the least impact in this dimension. CONCLUSIONS: Qualitatively evaluating the decision-making strategies used in DCEs allows researchers to evaluate whether the tasks and attributes are interpreted accurately. The findings from this study add to the understanding of the generation of SF-6Dv2 health utility weights and the validity of these weights (e.g., reinterpreting health states could undermine the validity of DCEs and utility weights), and the overall usefulness of the SF-6Dv2. The methodology described in this study can and should be carried forth in valuing other health utility measures, not just the SF-6Dv2.

Objectives This study determined the prospective relation between physical workload and long-term sickness absence (LTSA) and examined if work-unit social capital may buffer the effect of high physical workload on LTSA. Methods We included 28 925 participants from the Danish Well-being in HospitAL Employees (WHALE) cohort, and followed them for two years. Physical workload and social capital were self-reported and categorized into low, medium, and high. Physical workload was analyzed on the individual level, whereas social capital was analyzed on the work-unit level. LTSA data were obtained from the employers' payroll system. We performed two-level logistic regression analyses: joint-effect and stratified analyses adjusted for baseline covariates. Results High versus low physical workload was associated with a higher risk of LTSA [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.40-1.72]. There was a multiplicative interaction (P=0.007) and a tendency of sub-additive interaction [relative excess risk due to interaction (RERI) -0.49, 95% CI -1.03-0.06] between physical workload and social capital. Doubly exposed employees had the highest risk of LTSA (OR 2.45; 95% CI 2.02-2.98), but this effect was smaller than expected from the sum of their main effects. Conclusions We found a prospective relation between physical workload and LTSA but no evidence of high social capital buffering the effect of high physical workload. High physical workload was a risk factor for LTSA at all levels of social capital and employees exposed to both exposures had the highest risk of LTSA. Interventions should aim at both improving social capital and reducing physical workload in order to efficiently prevent LTSA.

Objective: The objective of this study was to develop the classification system for version of the SF-6D (SF-6Dv2) from the SF-36v2. SF-6Dv2 is an improved version of SF-6D, one of the most widely used generic measures of health for the calculation of quality-adjusted life years. Study Design and Setting: A 3-step process was undertaken to generate a new classification system: (1) factor analysis to establish dimensionality; (2) Rasch analysis to understand item performance; and (3) tests of differential item function. To evaluate robustness, Rasch analyses were performed in multiple subsets of 2 large cross-sectional datasets from recently discharged hospital patients and online patient samples. Results: On the basis of factor analysis, other psychometric evidence, cross-cultural considerations, and amenability to valuation, the 6-dimension classification used in SF-6D was maintained. SF-6Dv2 resulted in the following modifications to SF-6D: a simpler classification of physical function with clearer separation between levels; a more detailed 5-level description of role limitations; using negative wording to describe vitality; and using pain severity rather than pain interference. Conclusions: The SF-6Dv2 classification system describes more distinct levels of health than SF-6D, changes the descriptions used for a number of dimensions and provides clearer wording for health state valuation. The second stage of the study has developed a utility value set using discrete choice methods so that the measure can be used in health technology assessment. Further work should investigate the psychometric characteristics of the new instrument.

Objectives This systematic review and meta-analysis combined published study-level data and unpublished individual-participant data with the aim of quantifying the relation between long working hours and the onset of depressive symptoms. Methods We searched PubMed and Embase for published prospective cohort studies and included available cohorts with unpublished individual-participant data. We used a random-effects meta-analysis to calculate summary estimates across studies. Results We identified ten published cohort studies and included unpublished individual-participant data from 18 studies. In the majority of cohorts, long working hours was defined as working ≥55 hours per week. In multivariable-adjusted meta-analyses of 189 729 participants from 35 countries [96 275 men, 93 454 women, follow-up ranging from 1-5 years, 21 747 new-onset cases), there was an overall association of 1.14 (95% confidence interval (CI) 1.03-1.25] between long working hours and the onset of depressive symptoms, with significant evidence of heterogeneity (I2=45.1%, P=0.004). A strong association between working hours and depressive symptoms was found in Asian countries (1.50, 95% CI 1.13-2.01), a weaker association in Europe (1.11, 95% CI 1.00-1.22), and no association in North America (0.97, 95% CI 0.70-1.34) or Australia (0.95, 95% CI 0.70-1.29). Differences by other characteristics were small. Conclusions This observational evidence suggests a moderate association between long working hours and onset of depressive symptoms in Asia and a small association in Europe.

Item response theory, health-related quality of life, questionnaire, health status