“It Just Made Me Feel Better": Qualitative Examination of the Implementation of a Novel Virtual Psychosocial Support Program for Adolescents with Cancer
Bibliographic record
Abstract
Abstract Purpose Adolescents with cancer routinely report feelings of isolation and exclusion, including from medical decision-making. To address this problem and support adolescents, we designed and implemented the novel, virtual, weekly Teens4Teens peer support group and patient education program. We examined the views of participating adolescents, program guest speakers, and program moderators as they pertained to the need for the program, its feasibility, acceptability, and perceived impact. Methods We recruited all available adolescents, moderators, and guest speakers who participated in Teens4Teens to take part in audio-recorded, semi-structured interviews. Interviews were transcribed, coded, and analyzed using thematic analysis. Results We conducted 21 interviews across participant groups. We identified four broad themes: pathways into the Teen4Teens program, Teens4Teens implementation capacity, perspectives of the positive impact of Teens4Teens and suggestions to improve Teens4Teens. These themes described a perceived need for adolescent-centered psychosocial programing in pediatric cancer care, provided lessons on how best to build and apply such a program, and highlighted the value of the program for both adolescents and clinicians' acceptability, feasibility, and perceived utility. Conclusion Adolescents, guest speakers, and moderators valued Teens4Teens and made suggestions to improve capacity to routinely implement the program. Adolescent-tailored psychosocial programming such as Teens4Teens is positioned to be integrated into clinical care with relative ease and may serve to improve the cancer care experience of adolescents and their families. This study has potential to provide researchers and clinicians with valuable information about the content, design, and delivery of virtual peer support programming for adolescents with cancer.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".