Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».