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Record W4385331380 · doi:10.1017/s0714980823000375

You’ve Got E-Mail: A Pilot Study Examining the Feasibility and Impact of a Group-Based Technology-Training Intervention Among Older Adults Living in Residential Care

2023· article· en· W4385331380 on OpenAlexafffund
Renate Ysseldyk, Thomas A. Morton, Catherine Haslam, S. Alexander Haslam, Jennifer Boger, E. Giau, E. Macdonald, Amy Matharu, Madeline McCoy

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsResearch Institute for AgingUniversity of WaterlooCarleton University
FundersResearch Institute for Aging, University of WaterlooSocial Sciences and Humanities Research Council of Canada
KeywordsIntervention (counseling)GerontologyPsychologyMedicineMedical educationPhysical therapyFamily medicineNursing

Abstract

fetched live from OpenAlex

Abstract Older adults living in residential care often experience challenges in sustaining meaningful social relationships, which can result in compromised health and well-being. Online social networking has the potential to mitigate this problem, but few studies have investigated its implementation and its effectiveness in maintaining or enhancing well-being. This pilot study used a cluster-randomized pre–post design to examine the feasibility of implementing a 12-week group-based technology-training intervention for older adults ( n = 48) living in residential care by exploring how cognitive health, mental health, and confidence in technology were impacted. Analysis of variance revealed significant increases in life satisfaction, positive attitudes toward computer use, and self-perceived competence among participants who received the intervention, but increased depressive symptoms for the control group. These findings suggest that, despite challenges in implementing the intervention in residential care, group-based technology training may enhance confidence among older adults while maintaining or enhancing mental health.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.282
Teacher spread0.256 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicTechnology Use by Older AdultsFrench-language works237,207