Exploring the potential for online peer support mentorship: Perspectives of pediatric solid organ transplant patients
Bibliographic record
Abstract
OBJECTIVE: Self-management for patients who have undergone solid organ transplantation is demanding and a challenge for adolescents transitioning into adult-oriented healthcare systems. This study explores whether adolescent and young adult solid organ transplant patients support the use of online peer support programs that encourage peer mentorship as an approach to improve disease self-management. METHODS: A qualitative descriptive design comprised of semi-structured interviews with adolescent and young adult transplant patients. Individual interviews were audio-recorded, transcribed verbatim, and subject to content analysis. Emergent categories and themes were refined through member checking and team consensus following saturation. RESULTS: Interviews were conducted across organ groups with 15 participants (60% female) ages 14 to 22 years. Participants expressed unanimous support for an online peer support mentorship program to aid disease self-management in the pediatric transplant patient population. Three themes emerged from the interviews: (a) self-management care can be "taxing"; (b) there would be value in peer mentorship for adolescent transplant patients; and (c) online peer mentorship is the "best" option but still requires relationship building. Logistical preferences of an online peer mentorship program were solicited. The preferred peer "match" was someone of the same organ transplant group and gender who was able to have weekly contact via texting. CONCLUSIONS: Creating tailored, online peer mentorship programs is gaining evidence to justify further development. Findings from this study will support program modifications for adolescent and young adult solid organ transplant patients. Next steps will involve usability and feasibility testing of an adapted online program for this patient group.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".