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Record W6967089380 · doi:10.5281/zenodo.10157422

Motives and Motivations for Peer Mentors of Caregivers with Children who have Fetal Alcohol Spectrum Disorder

2023· other· en· W6967089380 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typeother
Languageen
FieldMedicine
TopicAnorectal Disease Treatments and Outcomes
Canadian institutionsWestern University
Fundersnot available
KeywordsQualitative researchPerceptionTelephone interviewPeer mentoringFetal Alcohol Spectrum DisorderPeer groupInterpersonal relationshipFocus groupSelf-disclosure

Abstract

fetched live from OpenAlex

Fetal alcohol spectrum disorder (FASD) refers to a spectrum of neurodevelopmental conditions that significantly impact an individual's physical appearance, learning, and behaviour. A consistent caregiver and home life are known to reduce the occurrence or severity of adverse outcomes. Peer mentors can be important sources of support to caregivers with children who have FASD. The purpose of this study was to identify the motives1 and motivations2 of peer mentors to caregivers of children and youth with FASD. Ten mentors with lived experience raising a dependent with FASD participated in in-person or telephone interviews that included the focal question: "Why do you want to be a peer mentor?" Responses were analyzed with a qualitative content analysis procedure. Four themes were generated from the responses. Mentors wanted to provide emotional support as a means of improving mentee wellbeing through therapeutic means and relationship development. They wanted to share lived experience as a means of educating mentees through the provision of personal knowledge, strategies, and skills. Mentors also chose to become involved for personal or mutual benefit, including fulfilling a call to give back or for personal growth and development. Finally, mentors participated to alter the perceptions and expectations held by mentees regarding caring for a child with FASD by sharing personal values and opinion statements. The themes were compared and contrasted with existing literature.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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