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Record W2596023971 · doi:10.1093/jpepsy/jsx062

Been There, Done That: The Experience of Acting as a Young Adult Mentor to Adolescents Living With Chronic Illness

2017· article· en· W2596023971 on OpenAlexafffund
Sara Ahola Kohut, Jennifer Stinson, Paula Forgeron, Stephanie Luca, Lauren Harris

Bibliographic record

VenueJournal of Pediatric Psychology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of OttawaHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMentorshipFocus groupPeer groupQualitative researchPsychologyPersonal developmentPeer supportChronic painPeer mentoringMedicineDevelopmental psychologyPsychiatryMedical educationPsychotherapistPedagogy

Abstract

fetched live from OpenAlex

Objective: To explore the perceived benefits and challenges of acting as a young adult peer mentor to adolescents with chronic illness. Methods: A qualitative descriptive study, using interviews and a focus group, explored the perceptions of young adult peer mentors following participation in the iPeer2Peer program, a Skype-based peer-mentorship program for adolescents with chronic illness. Interviews and focus group data were transcribed and analyzed using inductive content analysis. Results: Ten peer mentors (20.00 ± 1.49 years old, range 17-22 years; diagnosed with chronic pain [n = 4] or juvenile idiopathic arthritis [n = 6]) who mentored four mentees (±2.55 mentees, range = 1-10 mentees) participated. Four main categories were identified: social connection, personal growth, mentor role in mentee growth, and logistics of mentorship. Conclusions: Acting as a peer mentor online is a feasible and rewarding experience that supports the mentor's own illness self-management, social connection, and personal growth.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.456
Teacher spread0.385 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2017
Admission routes2
Has abstractyes

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