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Record W2955418743 · doi:10.1111/1756-185x.13600

Work disability and musculoskeletal disease

2019· letter· en· W2955418743 on OpenAlexaboutno aff
E. Michael Shanahan

Bibliographic record

VenueInternational Journal of Rheumatic Diseases · 2019
Typeletter
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMusculoskeletal diseasePhysical therapyDiseaseMEDLINEPhysical medicine and rehabilitationFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

The value of good work for individuals and the community is clear. Work provides financial security for individuals and their families and gives people a sense of purpose and meaning. It is also clearly associated with significant health benefits. Productive work is also one of the pillars upon which the wealth of the community is built. Loss of work is a common consequence of ill health. Chronic illness has particularly significant effects on long-term work participation. Individuals with chronic health problems often require long-term social security support, particularly as the burden of disease accumulates with age. Among the most significant diseases contributing to this burden are the musculoskeletal diseases. The true burden of work impairment from musculoskeletal disease is uncertain and difficult to study. Despite a large amount of work that has gone into the area, the nature and causes of work disability remain complex and befuddled by definitional and methodological problems. Work instability, work impairment, absenteeism, presenteeism, and under- or unemployment are all terms frequently used as outcome measures in studies relating to arthritis and work. Each of these outcome measures are different and may have different explanations. For example, Tillet et al examined the factors that influenced work disability in psoriatic arthritis and found that reduced effectiveness at work was associated with measures of disease activity, whereas unemployment was associated with employer factors, age and disease duration.1 Studies tend to focus heavily on causality or associations (many of these studies are cross-sectional with all their inherent limitations) and relatively few look at prevention or management. So what do we know about work disability and arthritis? First, we know that work disability from arthritis is best understood as a biopsychosocial construct. Multiple elements contribute to this construct. From a biological point of view work disability is dependent on the nature of the disease studied, the severity of that disease in individuals, the duration of the disease and the subsequent accumulated burden of the disease. Personal factors such as the age of the individual, the presence or absence of comorbidities (especially their psychological health), educational status, a second income in the home and the presence of dependents all impact on the likelihood or otherwise of work disability. Social factors contributing to work disability include the nature of and ability to access social security, and the economic climate of the day. Additionally, the nature of the work involved, the presence of meaningful support in the workplace and workplace flexibility and work modification may all impact on an individual's ability to stay at work. How many of these elements contribute to any one individuals' work status will vary across the life of the individual as well as where (and when) they live. The study by Abu Baker et al2 contributes to our knowledge in this area by examining the experience of a cohort of Malaysian patients with systemic lupus erythematosus. This is quite a specific population to study, and yet given the variables involved in determining work disability, it is important for Malaysia to understand what is happening in their own population and socio-political environment. This study found high rates of work disability in this cohort, mainly in patients with higher disease activity and the presence of renal involvement and organ damage. However, despite all the methodological challenges, we do know the burden of work disability in patients with arthritis is very significant. We know for example, that in one study 37% of Dutch patients with rheumatoid arthritis (RA) reported being work-disabled compared to 9% of the general Dutch population3 and in Britain RA patients are 32 times more likely to stop working compared with controls.4 We also know that despite work disability being very important to our patients,5 it is frequently ignored or not given sufficient importance by clinicians.6 What about the effects of treatment? There is some evidence that early treatment might reduce the impact of inflammatory disease on work disability.7 A number of studies have looked at the role of biologics specifically and their impact on work disability. These studies have been the subject of at least one systematic review suggesting that their introduction may have had a possible benefit on work disability.8 However, many studies on this topic are confounded by disease severity, with sicker patients tending to use biologics more frequently that less severely ill patients. Also, the heterogeneity of the populations, study designs and outcome measures make it difficult to compare or combine these studies. Although the degree of work impairment in inflammatory arthritis might be falling, this improvement may not relate entirely to the increased use of biologic agents. Rather, it might relate to more intensive and earlier disease control9 and other factors such as changes in access to social security10 or changes in a country's economic climate. This is where studies such as that by Claudepierre et al11 are valuable. Although the follow up was insufficient to look at the impact of these medications on long-term unemployment rates, the prospective nature and real-life experience of the cohort clearly demonstrates a positive benefit on work productivity in patients with ankylosing spondylitis when using biologic agents. An area of potential for reducing work disability in chronic disease is workplace intervention. We know that workplace support is likely to be beneficial for retaining people in the workplace but the precise nature of this support is difficult to define or study. Does workplace support translate into flexibility of tasks and hours? Does it involve permanently altering workplaces or retraining individuals? Is the mere fact of employers and colleagues expressing their support for their colleagues during the acute phases of their illness enough? Do we need to re-examine our social security systems and orientate them to encourage people to stay at work, rather than simply give them support when they are absent from work? Do we need new services orientated toward better managing people's work disabilities before they become permanent, as suggested for Britain by Dame Carol Black?12 There are important questions here which may best lend themselves to qualitative research approaches and largely remain unanswered. Finally, no discussion on the work impact of arthritis would be complete without reference to the burden of disease from osteoarthritis (OA). Evidence is mounting that the work loss from OA is significant and increasing with our aging demographics. For example a recent study from Canada suggested that OA may also contribute significantly to the burden of work impairment from arthritis and this is likely to worsen over the next 5 years.13 Given its prevalence in the community, even relatively small excesses in work disability are likely to contribute significantly to the overall burden. Combining this with the suggestion from a recent US study that disability from OA may be more recalcitrant to medical intervention compared to inflammatory disease,14 then we have another significant musculoskeletal contributor to the overall burden of work disability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.375
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations7
Published2019
Admission routes1
Has abstractyes

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