Storytelling Through Music With Parents Whose Children Have Died From Cancer: A Randomized Controlled Feasibility Trial
Bibliographic record
Abstract
BACKGROUND: Bereaved parents have significantly higher morbidity and mortality than non-bereaved parents. Despite national guidelines recommending bereavement care, resources for bereaved parents are scarce. Most intervention studies lack empirical evidence of effectiveness or alignment with key theoretical concepts. AIMS: To evaluate the feasibility of a 6-week intervention with parents of children who have died from cancer. Storytelling Through Music (STM) combines multiple modalities of expression (storytelling, reflective writing, songwriting) and psychoeducation to facilitate loss- and restoration-oriented coping by creating a legacy piece (self-written story paired with a song) to help bereaved parents adapt to a life-long process of finding meaning after loss. METHODS: Two-group, randomized controlled trial, utilizing multiple methods. Participants were randomized to STM or waitlist control. The intervention is delivered online and in a group setting. Descriptive statistics were used for feasibility data, content analysis to evaluate open-ended acceptability questions, and RM ANOVA to evaluate the differences between psychosocial, coping, and grief outcomes. RESULTS: Twenty-three parents were enrolled. Average age was (range: 32-68) and the child's average age was 18.9 (range: 1.5-35). This study indicates that the online delivery of STM is feasible and acceptable and provides preliminary evidence of reducing prolonged grief and loneliness. CONCLUSIONS: STM is a theoretically driven, innovative approach to addressing grief in a high-risk, underserved population. Findings suggest STM can be delivered online and is acceptable to participants. Adding music to storytelling and reflective writing provides a unique expression and preliminary data suggests improvements in psychosocial well-being, coping, and grief intensity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".