The Role of Support and Prayer in Enhancing the Psychological Well-Being of Cancer Patients in Canada
Bibliographic record
Abstract
Purpose of the Study The purpose of the study was to investigate the role of family support, friends' support, community support, and prayer on the psychological well-being of cancer patients in Canada. Methodology A survey research method was used in this study. The survey was distributed through the QuestionPro audience and had 721 viewers, 674 respondents, and 400 participants (i.e., those who completed the survey). The survey completion rate was 59.35%, with an average completion time of 9 minutes. Most participants were Christians (62.0%), some were unaffiliated (29.5%), and the remaining participants were either Muslims, World Religion, Buddhism, Hinduism, etc. (3.0%) (See Table 2). A quantitative approach, combining multivariate analysis of variance and structural equation modeling, was used to analyse the data. Results Four research questions were posed to examine the role of family, friends, faith community, and prayer in enhancing the psychological well-being of cancer patients in Canada. The results indicated significant differences among types of cancer in the linear combination of psychological well-being. They also showed a significant main effect for prayer of Supplication and Confession, a significant Diagnosis time effect for Thanksgiving and Supplication, and a significant interaction effect for the prayer of Reception and Adoration. Greater support from family, friends, and faith community results in more positive psychological well-being (β=.30, p< .001). Prayer partially mediates the influence of support on psychological well-being (β=.197, p< .001). Higher levels of prayer appear to lead to more positive psychological well-being (β=.30, p< .001). Total effects (direct and indirect) explain about 30% (R2=.30) of the variance in psychological well-being. Conclusion The objective of this study was to investigate the role of support (from spouse, family, friends, faith community) and prayer in enhancing the psychological well-being of cancer patients in Canada. As such, the researcher has been able to determine the nature of the relationship between psychological well-being and types of cancer, diagnosis time, and the extent to which prayer is related to types of cancer and the year(s) since diagnosis. It was evident that support and prayer are strong predictors of psychological well-being, and that both factors enhance psychological well-being.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".