Circumstances surrounding the onset of stroke: a qualitative study
Bibliographic record
Abstract
AIM: To document perceptions of circumstances spontaneously associated with the occurrence of the stroke on that particular day. BACKGROUND: Known triggers of stroke include birthday or negative emotions. However, specific circumstances relating to that birthday or emotion have not yet been documented. DESIGN: Phenomenological perspective where data were collected between October 2011-June 2012. METHOD: In-depth interviews conducted 5-8 weeks post stroke with 37 participants, with a mean age of 56·3 years (sd 11·9) and 40·5% (14/37) of whom were female. An interview guide composed of open-ended questions and developed with experts was used to explore in detail free associations surrounding the stroke. All interviews were audiotaped and transcribed. Data were rigorously analysed by two team members and discussed in team meetings until reaching consensus on essential themes. FINDINGS: Relationships emerged as being the overarching theme related to stroke triggers with the interrelated subthemes of: (1) birthday or anniversary; (2) parenting; (3) being sick seen as a benefit; and (4) alcohol or drug abuse. The stroke happened on a day which was related in some way to a relationship with a significant other affected by tension, a lack of transparency or an overinvestment of emotional/affective state. CONCLUSIONS: There is a need to address individuals' beliefs as a part of secondary prevention interventions to be truly client-centred, which the phenomenological perspective allows. Relationships as a potential source of stress should be added as a theme to discuss with patients for a holistic approach to stroke prevention including psychosocial factors.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".