“Employment and arthritis: making it work” a randomized controlled trial evaluating an online program to help people with inflammatory arthritis maintain employment (study protocol)
Bibliographic record
Abstract
BACKGROUND: Arthritis and musculoskeletal conditions are the leading cause of long-term work disability (WD), an outcome with a major impact on quality of life and a high cost to society. The importance of decreased at-work productivity has also recently been recognized. Despite the importance of these problems, few interventions have been developed to reduce the impact of arthritis on employment. We have developed a novel intervention called "Making It Work", a program to help people with inflammatory arthritis (IA) deal with employment issues, prevent WD and improve at-work productivity. After favorable results in a proof-of-concept study, we converted the program to a web-based format for broader dissemination and improved accessibility. The objectives of this study are: 1) to evaluate in a randomized controlled trial (RCT) the effectiveness of the program at preventing work cessation and improving at-work productivity; 2) to perform a cost-utility analysis of the intervention. METHODS/DESIGN: 526 participants with IA will be recruited from British Columbia, Alberta, and Ontario in Canada. The intervention consists of a) 5 online group sessions; b) 5 web-based e-learning modules; c) consultations with an occupational therapist for an ergonomic work assessment and a vocational rehabilitation counselor. Questionnaires will be administered online at baseline and every 6 months to collect information about demographics, disease measures, costs, work-related risk factors for WD, quality of life, and work outcomes. Primary outcomes include at-work productivity and time to work cessation of > 6 months for any reason. Secondary outcomes include temporary work cessation, number of days missed from work per year, reduction in hours worked per week, quality adjusted life year for the cost utility analysis, and changes from baseline in employment risk factors. Analysis of Variance will evaluate the intervention's effect on at-work productivity, and multivariable Cox regression models will estimate the risk of work cessation associated with the intervention after controlling for risk factors for WD and other important predictors imbalanced at baseline. DISCUSSION: This program fills an important gap in arthritis health services and addresses an important and costly problem. Knowledge gained from the RCT will be useful to health care professionals, policy planners and arthritis stakeholders. TRIAL REGISTRATION: ClinicalTrials.gov NCT01852851; registered April 13, 2012; first participant randomized on July 6, 2013.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".