Attitudes toward stress and coping among primary caregivers of patients undergoing hemodialysis: A Q‐methodology study
Bibliographic record
Abstract
Introduction Hemodialysis (HD) causes many life changes, not only for patients undergoing it but also for their families by allowing them to rely on this lifesaving equipment unless they receive a kidney transplant. The stress of the primary caregivers, who spends the most time in the family taking care of the patient undergoing HD, is quite high. This study was to identify attitudes about stress and coping among primary caregivers of HD patients. Methods Q-methodology was undertaken because it integrates quantitative and qualitative research methods. A convenience sample of 33 primary caregivers of HD patients participated. Forty selected Q-samples were obtained from each participant and were classified into a forced normal distribution using a nine-point grid. Data was analyzed using a pc-QUANL program. Findings Three discrete factors emerged as follows: Factor I (they reduced their stress by participating in religious activities; religious sublimation), Factor II (they always worried about the caregiving situations and about the patients' conditions; nervousness), and Factor III (they thought it better to accept their stressful situations; leading handler). Three factors accounted for 44.5% of all the variance, including Factor I (26.0%), Factor II (10.1%), and Factor III (8.4%). The eigenvalues were 8.58, 3.34, and 2.79, respectively. Discussion The subjectivities of the three factors that were identified can be applied during the planning stages of effective interventions for stress and coping. Healthcare workers in clinical practices should consider assesses primary caregivers' attitudes about stress and coping and approaches their situation to cope with it and to adapt to lifestyle changes.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".