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Record W7133020029

‘Nothing about us Without us’ – Development of a Patient- centered Digital Health Self-care Program for Marginalized, Underserved Populations with Heart Failure

2023· dissertation· W7133020029 on OpenAlexaboutno aff
Sahr Wali

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionContext (archaeology)mHealthIndigenousGeneral partnershipDigital healthHealth equityCommunity engagementInfluencer marketing
DOInot available

Abstract

fetched live from OpenAlex

Heart failure (HF) is a global pandemic affecting over 26 million people worldwide. In high-income-countries (HICs), the use of evidence-based self-care models has led to a decline in HF prevalence. However, these improvements are less evident in low-and-middle-income countries (LMICs) and marginalized subgroup populations in HICs, like the Indigenous People, due to factors related to poor disease control and the disparities in a population’s social determinants of health. With the inequitable distribution of health services, digital health has been offered as an avenue to assist populations with limited resources. While mobile phones have become increasingly utilized, many digital health interventions have failed to be adopted, as they have been designed for usage in high-resource settings. With the current mismatch between technological innovation and local community priorities, this research sought to 1) evaluate the state of heart health within the remote communities in Northern Ontario and Northern Uganda, 2) investigate the contextual requirements to design of a community-based digital health program, and 3) adapt the program according to the identified design requirements. In Study 1a, we established that Indigenous communities and LMICs valued the use of digital tools, but its adoption would be dependent on its cultural compatibility. To better understand how cultural context should be integrated within digital tool design, Study 1b explored how various community engagement strategies could be utilized. Using these findings, in Study 1c, a research partnership was established with each community. In Study 2, a community-based needs assessment was conducted to evaluate the contextual influencers impacting community heart health. In Study 3, we developed a series of design requirements focused on empowering existing community resources and cultural values. In a society where the distribution of wealth is heavily unbalanced, there is concern that the digital divide will compound the effects of socioeconomic divisions. While the COVID-19 pandemic triggered the momentum for digital health, populations with a history of being overlooked, continue to be left with minimal support. As such, to close the gap associated with the digital divide, interventions need to be designed in reflection of the contextual circumstances contributing to a population’s poorer health outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.057
GPT teacher head0.353
Teacher spread0.296 · 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 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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