Unpacking Early Work Experiences of Young Adults With Rheumatic Disease: An Examination of Absenteeism, Job Disruptions, and Productivity Loss
Bibliographic record
Abstract
OBJECTIVE: To examine work absenteeism, job disruptions, and perceived productivity loss and factors associated with each outcome in young adults living with systemic lupus erythematosus (SLE) and juvenile arthritis (JA). METHODS: One hundred forty-three young adults, ages 18-30 years with SLE (54.5%) and JA (45.5%), completed an online survey of work experiences. Demographic, health (e.g., fatigue, disease activity), psychosocial (e.g., independence, social support), and work context (e.g., career satisfaction, job control, self-disclosure) information was collected. Participants were asked about absenteeism, job disruptions, and perceived productivity loss in the last 6 months. Log Poisson regression analyses examined factors associated with work outcomes. RESULTS: A majority of participants (59%) were employed and reported a well-managed health condition. Employed respondents were satisfied with their career progress and indicated moderate job control. More than 40% of participants reported absenteeism, job disruptions, and productivity loss. Greater job control and self-disclosure, and less social support, were related to a higher likelihood of absenteeism. More disease activity was related to a greater likelihood of reporting job disruptions. Lower fatigue and higher job control were associated with a reduced likelihood of a productivity loss. CONCLUSION: Young adult respondents with rheumatic disease experienced challenges with employment, including absenteeism, job disruptions, and productivity loss. While related to greater absenteeism, job control could play a role in a young person's ability to manage their health condition and sustain productive employment. Greater attention should also be paid to understanding health factors and social support in early work experiences.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".