Experiences, hope, and coping in relation to attending a community-based cancer bereavement support program: A mixed method study
Bibliographic record
Abstract
Background: With increasing numbers of cancer-related deaths, timely access to bereavement support is crucial for those who have lost a loved one to cancer.Psychosocial and instrumental services provided by community-based organizations increasingly play a central role in ensuring that people affected by cancer get the support that they need.Hope & Cope, a Montreal-based organization, provides various services and programs to address the needs of people diagnosed with cancer and those of bereaved individuals.Given the relevance of community resources and the paucity of evidence regarding their impact, the studies reported herein sought to document participant experiences with Hope & Cope bereavement support programs and well as potential changes in hope and coping as programs unfolded.In addition, the student researcher's experience while conducting these studies is appended.The main thesis work reported includes two research-based manuscripts.Manuscript 1 focuses on the potential contributions of Living with Loss by 1) quantitatively comparing participants' levels of hope and coping pre and post bereavement program completion and 2) qualitatively exploring participants' perceptions and experiences across program delivery.Manuscript 2 sheds insight into how distinct bereavement program formats (open vs. closed) are perceived by program users.More specifically, through indepth interviews, participant perceptions are explored considering their taking part in an open-(Mourning Walk) or closed-group program (Living with Loss).Methods and results: In Manuscript 1, Living with Loss registrants (N = 11) completed a brief sociodemographic sheet and self-report e-questionnaires.Self-report measures included hopefulness (Herth Hope Index) and coping (Brief Cope Scale) completed pre-and post-program attendance.Semi-structured interviews were conducted before, during and at program
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".