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Record W2604754271 · doi:10.2196/diabetes.6930

How’s Your Sugar? Evaluation of a Website for Aboriginal People With Diabetes

2017· article· en· W2604754271 on OpenAlexvenueno aff
Karen Adams, Anna Liebzeit, Jennifer Browne, Petah Atkinson

Bibliographic record

VenueJMIR Diabetes · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsSugarDiabetes mellitusAdvertisingPsychologyFood scienceMedicineInternet privacyBusinessBiologyComputer scienceEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Australia's Aboriginal and Torres Strait Islander peoples (hereafter referred to as "Aboriginal people") have the longest continuing culture in the world, living sustainably for at least 65,000 years on the Australian continent. In relatively recent times, colonization processes have resulted in Aboriginal people experiencing unacceptable health inequalities compared with other Australians. One disease introduced due to colonization is diabetes, the second leading cause of death for Aboriginal peoples. OBJECTIVES: The objective of this study was to describe the construction and utilization of the website "How's Your Sugar, " a website for Aboriginal people with type 2 diabetes (herein after referred to as diabetes). The questions for the evaluation were as follows: how was the website constructed; did target groups utilize the website; and did engagement with the website improve diabetes management. METHODS: A mixed-method study design was employed. A content analysis of project documents provided information about the website construction. Data from Google analytics provided information about website utilization. To describe patterns of website sessions, percentages and numbers were calculated. A voluntary survey provided more information on website utilization and diabetes self-management. Percentage, numbers, and 95% CIs were calculated for each variable. A chi-square test was performed for Aboriginal status, age, gender, and Aboriginal diabetic status using Australian population estimates and Aboriginal diabetes rates. RESULTS: The website development drew on Aboriginal health, social marketing, interactive health promotion frameworks, as well as evidence for diabetes self-management. The website build involved a multidisciplinary team and participation of Aboriginal diabetics, Aboriginal diabetic family members, and Aboriginal health workers. This participation allowed for inclusion of Aboriginal ways of knowing and being. The highest number of website sessions came from Australia, 98.15% (47,717/48,617) and within Australia, Victoria 50.97% (24,323/47,717). There were 129 survey respondents, and the distribution had more female, 82.9% (107/129, 95% CI 76-88), Aboriginal, 21.7% (28/129, 95% CI 16-30), and Aboriginal diabetic, 48% (13/27, 95% CI 31-66) respondents than expected with P<.001 for these three groups. Most common reasons for visits were university assignment research, 40.6% (41/101), and health workers looking for information, 20.8% (21/101). The sample size was too small to calculate diabetes self-management change. CONCLUSIONS: Inclusion of Aboriginal ways of knowing and being alongside other theoretical and evidence models in Web design is possible. Aboriginal people do utilize Web-based health promotion, and further understanding about reaching to this population would be of use. Provision of an education resource would likely have enhanced educational engagement. Web-based technologies are rapidly evolving, and these can potentially measure behavior change in engaging ways that also have benefits for the participant. A challenge for designers is inclusivity of cultural diversity for self-determination.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.364
Teacher spread0.337 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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