The influence of stroke severity on depression, anxiety, burden and life-satisfaction in partners of patients with stroke
Bibliographic record
Abstract
Aim To investigate the change in feelings of depression, anxiety, burden and life satisfaction in partners of stroke survivors between two and six months after stroke and to determine which factors that are derived from the severity of stroke can predict these feelings in the period there is frequent contact with healthcare professionals. \nMethods Patients from stroke units with partner (N = 215) of the Restore4stroke study were included in a predictive study. Depression and anxiety (Hospital Depression and Anxiety Scale), burden (Caregiver Strain Index) and life-satisfaction (2 life-satisfaction questions) were the outcome measures, assessed at two and six months. Independency in activities of daily living (Barthel Index), cognition (Montreal Cognitive Assessment), communication (item 9 of National Institute of Health Stroke Scale) of the patient, and determinants of patient and partner were used as predictors. A paired samples t-test was used to measure the change in outcome of the partner. Predictors for the outcome on two and six months after stroke were identified, using multivariate linear regression. \nResults The only significant change in outcome was the decrease of anxiety. Most important predictors for the outcome at two months were rehabilitation in a rehabilitation centre or geriatric centre; participation of the partner before stroke in lesser extent. Passive coping style of the partner was predictive for all outcome measures at six months. Of the stroke factors independency in ADL was predictive for depression; cognition and rehabilitation in a rehabilitation centre were predictive for burden. \nConclusion Between two and six months, stroke severity becomes less important to predict the outcome of the partner, predictors of the partner become more important. \nClinical Relevance Support for partners of patients with stroke should focus on aspects of stroke, but also on the coping style of the partner.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".