MétaCan
Menu
Back to cohort
Record W3090931040 · doi:10.1177/2055668320958327

Peace of mind: A community-industry-academic partnership to adapt dementia technology for Anishinaabe communities on Manitoulin Island

2020· article· en· W3090931040 on OpenAlexfundaboutno aff
Kristen Jacklin, Karen Pitawanakwat, Melissa Blind, Andrine Lemieux, Adam Sobol, Wayne Warry

Bibliographic record

VenueJournal of Rehabilitation and Assistive Technologies Engineering · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersAGE-WELL
KeywordsIndigenousGeneral partnershipParticipatory action researchCommunity-based participatory researchDementiaFocus groupParticipatory designPublic relationsSociologyPolitical scienceMedicineEngineeringEcology

Abstract

fetched live from OpenAlex

INTRODUCTION: Aging Technologies for Indigenous Communities in Ontario (ATICON) explores the technology needs of Anishinaabe older adults in the Manitoulin region of Northern Ontario. Our program of research addresses inequitable access to supportive technologies that may allow Indigenous older adults to successfully age in place. METHODS: Using Indigenous research methodologies (IRM) and community-based participatory research (CBPR) we explored the acceptability of CareBand - a wearable location and activity monitoring device for people living with dementia using a LoRaWAN, a low-power wide-area network technology. We conducted key informant consultations and focus groups with Anishinaabe Elders, formal and informal caregivers, and health care providers (n = 29) in four geographically distinct regions. RESULTS: Overall, participants agreed that CareBand would improve caregivers' peace of mind. Our results suggest refinement of the technology is necessary to address the challenges of the rural geography and winter weather; to reconsider aesthetics; address privacy and access; and to consider the unique characteristics of Anishinaabe culture and reserve life. CONCLUSION: All three partners in this research, including the Indigenous communities, industry partner, and academic researchers, benefited from the use of CBPR and IRM. As CareBand is further developed, community input will be crucial for shaping a useful and valued device.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.320
Teacher spread0.282 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Rehabilitation and Assistive Technologies EngineeringSame topicIndigenous Health, Education, and RightsFrench-language works237,207