Adaptation and coping following a first stroke: a qualitative analysis of a phenomenological orientation
Bibliographic record
Abstract
Stroke can have consequences in all areas of a person's life. If not coped with optimally, this life event will have a deleterious effect on the quality of life. The aim of this study was to improve understanding of appraisal and coping, post-stroke. Ten individuals were purposely recruited upon admission for a first stroke to participate in this qualitative study. Participants were asked to share their personal experiences with regard to their efforts to deal with the consequences of the stroke. In-depth interviews were transcribed verbatim and the content was analyzed using a rigorous method, inspired by a phenomenological orientation. Seven themes related to appraisal (unpredictability, overwhelming, feeling out of control, threat, turning point, acceptance/resignation and future prospects) and five themes related to coping (active and passive compensation, escape, change how the situation is perceived and utilization of resources) emerged from the content analysis of the in-depth interviews. In conclusion, since returning to the previous life style and activities is rather improbable, changing how the situation is perceived appears to be the most effective way of coping, in order to reach a state of acceptance/resignation favourable to an optimal quality of life.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".