?Are you better?? A qualitative study of the meaning of recovery
Bibliographic record
Abstract
PURPOSE: Research into the meaning of illness has often focused on an individual's transition into a state of being ill, for example the adoption of a sick role. The question "Are you better?" addresses the transition out of this state and is fundamental to the patient-clinician relationship, guiding decisions about treatment. However, the question assumes that all patients have the same meaning for "being better." The purpose of this study was to explore the meaning of the concept of recovery (getting better) in a group of people with upper limb musculoskeletal disorders. METHODS: Qualitative (grounded theory) methods were used. Individual interviews were conducted with 24 workers with work-related musculoskeletal disorders of the upper limb. The audiotaped interviews were transcribed and coded for content. Categories were linked, comparisons made, and a theory built about how people respond to the question "Are you better?" RESULTS: The perception of "being better" is highly contextualized in the experience of the individual. Being better is not only reflected in changes in the state of the disorder (resolution) but could be an adjustment of life to work around the disorder (readjustment) or an adaptation to living with the disorder (redefinition). The experience of the disorder can be influenced by factors such as the perceived legitimacy of the disorder, the comparators used to define health and illness, and coping styles, which in turn can influence being better. CONCLUSION: Two patients could mean very different things when saying that they are better. Some may not actually have a change in disease state as measured by symptoms, impairments, or function.
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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 | 0.022 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".