The Effect of Benson’s Relaxation Technique on Coping Strategies Among Informal Caregivers of Cancer Patients
Bibliographic record
Abstract
BACKGROUND: Informal caregivers of cancer patients often experience high levels of stress and burden, leading to the adoption of ineffective coping strategies. This can result in psychological problems for the caregivers and inadequate care provision. OBJECTIVE: This study aimed to investigate the impact of Benson's relaxation technique (BRT) on coping strategies among informal caregivers of cancer patients. METHODS: This open-label randomized clinical trial enrolled 113 caregivers visiting the radiotherapy and chemotherapy departments of Vasei Hospital in Sabzevar, Iran, who scored ≥48 on the Novak and Guest Caregiver Burden Inventory. The participants were randomly allocated to either the intervention group or the control group. The intervention group received BRT, with participants performing the technique twice a day for 20 minutes each time over a 1-month period. The control group did not receive any intervention. Coping strategies were assessed using Endler and Parker's coping strategies inventory. RESULTS: The findings of the study revealed that the intervention group showed an increase in the utilization of problem-oriented coping strategies ( P = .076) and a decrease in the utilization of emotion-oriented coping strategies ( P < .001) and avoidance-oriented coping strategies in the intervention group compared with the control group ( P = .004). CONCLUSIONS: Findings suggest that BRT, as a cost-effective and nonpharmacological intervention, effectively reduces the reliance on emotion-oriented and avoidance-oriented coping strategies among informal caregivers of cancer patients. IMPLICATIONS FOR PRACTICE: Healthcare professionals working in oncology settings are encouraged to incorporate BRT into their care practices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".