Wolastoqiyik adaptation of the Aaniish Naa Gegii: the Childrenâs Health and Well-Being Measure
Bibliographic record
Abstract
INTRODUCTION: Indigenous children in Canada represent one of the fastest-growing pediatric populations and experience severe health inequities. There is an ongoing need for new research on relevant methods to measure the health and wellbeing of Indigenous children that considers the cultural differences between communities. The Aaniish Naa Gegii: the Children's Health and Well-Being Measure (ACHWM) is a self-reported questionnaire that was developed to meet this need and to include the voices of Indigenous children. The purpose of this study was to assess the cultural relevance of the ACHWM for Wolastoqiyik children and to determine what revisions may be needed to ensure that the questions are well understood and culturally appropriate. METHODS: We recruited a community-based sample of nine Wolastoqiyik children (ages 8 to 16 years), two caregivers, and a community Elder within the Madawaska Maliseet First Nation community in New Brunswick. Through a process of cognitive debriefing, we probed children's comprehension of the 62 questions of the First Nation French version of the ACHWM. We analyzed the information reported to determine the participants' understandings relative to the other participants and to the original intent of the ACHWM content. RESULTS: Each of the nine children identified at least one item they recommended for revision during the interview. We observed similarities in the suggestions offered by several respondents. A total of 23 questions were considered, and 14 questions (22.6%) were modified, taking into consideration all participants' suggestions. CONCLUSION: While measures like the ACHWM offer useful information, relying solely on a 'one size fits all' Indigenous questionnaire is insufficient. Our findings underline the importance of having methods that are easily accessible, adaptable, and culturally appropriate for assessing and addressing Indigenous children's unique health and wellbeing. Such information allows clinicians to develop interventions that are culturally relevant, addressing children's individual needs within the context of their distinct cultural identity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".