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Record W4386392239 · doi:10.31234/osf.io/6yegk

Indigenous Child Wellness: A Scoping Review of Best Practices with Initial Advising from Indigenous Community Members on Contextual Considerations and Next Steps

2023· review· en· W4386392239 on OpenAlexaffabout
Sydney Levasseur-Puhach, Leslie E. Roos, Sandra Hunter, Lynette Bonin

Bibliographic record

Venuenot available
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsIndigenousPsycINFOMEDLINEHarmSystematic reviewMedicineMedical educationPsychologyPolitical sciencePublic relationsSocial psychology

Abstract

fetched live from OpenAlex

Background. The measurement of wellness among Indigenous Peoples is crucial to understanding the needs of communities today and for generations to come. Here, we summarize extant research on assessments relevant to measuring the wellbeing of Indigenous children and families in Canada through an examination of existing international practices. A thoughtful identification of wellness metrics aligned with Indigenous cultural contexts is important because, in the past, wellness assessments that were not co-developed by Indigenous partners have perpetuated systemic harm. Objectives. The purpose of this study is to identify feasible and acceptable approaches to measuring Indigenous child and family wellness. Research objectives were to (1) to consult with Indigenous advisors to inform this phase and subsequent phases an overarching project (2) examine the available literature based on existing Canadian and international practices in wellness assessments as it relates to feasibility and acceptability of measuring wellness for Indigenous people. Eligibility Criteria. Measures and frameworks were eligible for synthesis in this review if they were used or developed across Canada, the United States, Australia, and New Zealand; written in English between 2010-2020; related to wellness or adjacent topics; focused on wellness related to children, youth, adults, and/or families. Sources of Evidence. Databases consulted for the review included Google Scholar, PubMed, ProQuest, MEDLINE, and PsycINFO. Methods. Semi-structured interviews were held with four Indigenous community members to advise on the process of developing such a project and to gauge considerations on the appropriateness of assessing wellness for Indigenous families. The review portion of the study was conducted by the first author and a research assistant using the PRISMA extension for scoping reviews protocol. Results. Results from interviews highlight a unique set of factors to consider from an Indigenous values perspective when assessing child wellness. These include incorporating elements of self-determination in both measure development and usage. Themes of family, community, strength-based approaches, and wholism were also emphasized. Results from the review found a total 896 relevant abstracts. Of these, 88 articles were reviewed, 16 measures, and four frameworks were eligible for synthesis. Conclusions. Findings exemplified an emerging assessment base for measuring wellness, though minimal work to date is directly designed to be culturally appropriate for Indigenous children and families. Moving forward, we will seek to fill this gap by supporting the development of a wellness measure with the potential to promote the adequate and equitable dispersion of support and resources to Indigenous families.

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)0.052
metaresearch head score (Gemma)0.104
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.225
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.104
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0250.030
Science and technology studies0.0040.003
Scholarly communication0.0060.004
Open science0.0050.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.192
GPT teacher head0.454
Teacher spread0.263 · 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 designSystematic review
Domainnot available
GenreReview

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 routes2
Has abstractyes

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