MétaCan
Menu
Back to cohort
Record W2394819450 · doi:10.1177/0308022616648172

Training older adults with low vision to use a computer tablet: A feasibility study

2016· article· en· W2394819450 on OpenAlexaboutno aff
Jennifer Kaldenberg, Stacy Smallfield

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)MedicineLow visionPhysical therapyActivities of daily livingPhysical medicine and rehabilitationGerontologyNursingOptometry

Abstract

fetched live from OpenAlex

Introduction The purpose of this feasibility study was to investigate the potential use of a computer tablet as a low vision device to facilitate performance of and satisfaction with daily activities for older adults with low vision. Method A repeated measures design was used to measure outcomes. Four older adult women with low vision completed 10 weekly sessions of group training in tablet use. The feasibility of this research method and intervention was examined by evaluating recruitment capability, data collection procedures, outcome measures, intervention procedures, resources, and preliminary responses to intervention. Results The four participants were all women, with a mean age of 74.25 years (68–81). Visual acuity ranged from 20/160 to 20/4000. Mean change in performance and satisfaction on the Canadian Occupational Performance Measure were 3.45 and 3.65, respectively. Daily tablet use increased from 15 minutes at pretest to 3 hours at posttest to 4.5 hours at follow-up. Conclusion Group training in computer tablet use for older adults with low vision shows promise to improve performance and satisfaction in a variety of daily activities. With appropriate resources, the research method is feasible for a larger study examining this community-based intervention for older adults with low vision.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.057
GPT teacher head0.354
Teacher spread0.298 · 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 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

Citations22
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of Occupational TherapySame topicTechnology Use by Older AdultsFrench-language works237,207