“Until the day I die, this will be with me”: Qualitative study to identify coping strategies used during post-stroke return-to-work
Bibliographic record
Abstract
BackgroundAlthough work is reported to positively affect wellbeing and life satisfaction post-stroke, returning to work can be challenging.ObjectiveThe study objective was to identify the strategies used to cope by adults who had stroke during return-to-work processes.MethodThis was an exploratory qualitative study grounded in interpretative approaches. Individuals who have had stroke were recruited. Semi-structured interviews were conducted to understand the coping strategies that participants used. Transcripts were analyzed deductively.ResultsTwenty-seven participants completed the face-to-face interviews. The median age of participants was 61 years (interquartile range = 55-64). A majority were male (n = 19, 70.4%), Chinese (n = 20, 74.1%), and married (n = 21, 78.8%). All participants were employed before their stroke. Twenty participants (74.1%) reported that they had returned to work. The findings indicated that participants utilized a mix of problem- and emotion-focused coping strategies during their return-to-work process. While both types of coping strategies were used, participants who returned to work predominantly utilized problem-focused coping strategies.ConclusionsIndividuals returned to work by utilizing a combination of coping strategies to manage the effects of stroke. This suggests that comprehensive services are important to address personal and occupational challenges to assist stroke victims in resuming work.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".