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Record W4399097443 · doi:10.3389/fcdhc.2024.1356060

Supporting healthy lifestyles for First Nations women and communities through co-design: lessons and early findings from remote Northern Australia

2024· article· en· W4399097443 on OpenAlexaboutno aff
Tara Dias, Diana MacKay, Karla Canuto, Jacqueline Boyle, Denella Hampton, Kim Martin, Jessica Phillips, Norlisha Bartlett, David McIntyre, Sian Graham, Sumaria Corpus, Christine Connors, Leisa McCarthy, Renae Kirkham, Louise Maple‐Brown

Bibliographic record

VenueFrontiers in Clinical Diabetes and Healthcare · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNational Health and Medical Research Council
KeywordsParticipatory action researchSustainabilityCommunity-based participatory researchMedicinePacific islandersCommunity engagementNursingGerontologyEnvironmental healthPolitical sciencePublic relationsSociologyPopulation

Abstract

fetched live from OpenAlex

Background: The period before, during, and after pregnancy presents an opportunity to reduce diabetes-related risks, which in Australia disproportionately impact Aboriginal and Torres Strait Islander women. Collaboration with Aboriginal and Torres Strait Islander women/communities is essential to ensure acceptability and sustainability of lifestyle modifications. Using a novel co-design approach, we aimed to identify shared priorities and potential lifestyle strategies. We also reflected on learnings from this approach. Methods: We conducted 11 workshops and 8 interviews at two sites in Australia's Northern Territory (Central Australia and Top End), using experience-based co-design (EBCD) and incorporating principles of First Nations participatory research. Workshops/interviews explored participant' experiences and understanding of diabetes in pregnancy, contextual issues, and potential lifestyle strategies. Participants included three groups: 1) Aboriginal and Torres Strait Islander women of reproductive age (defined as aged 16-45 years); 2) Aboriginal and Torres Strait Islander community members; and 3) health/community services professionals. The study methodology sought to amplify the voices of Aboriginal women. Findings: Participants included 23 women between ages 16-45 years (9 with known lived experience of diabetes in pregnancy), 5 community members and 23 health professionals. Key findings related to identified priority issues, strategies to address priorities, and reflections on use of EBCD methodology. Priorities were largely consistent across study regions: access to healthy foods and physical activity; connection to traditional practices and culture; communication regarding diabetes and related risks; and the difficulty for women of prioritising their health among competing priorities. Strategies included implementation of a holistic women's program in Central Australia, while Top End participants expressed the desire to improve nutrition, peer support and community awareness of diabetes. EBCD provided a useful structure to explore participants' experiences and collectively determine priorities, while allowing for modifications to ensure co-design methods were contextually appropriate. Challenges included the resource-intensive nature of stakeholder engagement, and collaborating effectively with services and communities when researchers were "outsiders". Conclusions: A hybrid methodology using EBCD and First Nations participatory research principles enabled collaboration between Aboriginal women, communities and health services to identify shared priorities and solutions to reduce diabetes-related health risks. Genuine co-design processes support self-determination and enhance acceptability and sustainability of health strategies.

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)0.003
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.111
GPT teacher head0.445
Teacher spread0.333 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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