Chronic pain in episodic illness and its influence on work occupations: A scoping review
Bibliographic record
Abstract
OBJECTIVES: The aim of this review was to understand and synthesize the realm of knowledge on intermittent work capacity (IWC) about strategies to support work sustainability. Specifically, this review focused on literature that examined productive work with individuals who have chronic pain due to Fibromyalgia, Breast Cancer, Multiple Sclerosis, and Human Immunodeficiency Virus. METHODS: A scoping review of research conducted across 10 databases. Nature of the knowledge base on return to work barriers and strategies and future recommended strategies needed to support persons with IWC in maintaining work participation were charted and thematically analyzed and organized into micro, meso and macro categories. RESULTS: Majority of the knowledge base reflects factors impeding and facilitating employment or re-employment at the micro level. At the micro level, self advocacy was a strategy that persons with IWC used to maintain employment and navigate stigmatizing work environments to meet their needs. At the meso level education and knowledge sharing with employers to increase awareness was underscored; at the macro level introduction of new policies was recommended. CONCLUSIONS: These findings suggest the need for future greater examination of the dialectical relationships across micro, meso and macro level strategies to overcome work disparities for persons with IWC.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".