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Record W2058452284 · doi:10.1080/1360786021000007009

Televisits: Sustaining long distance family relationships among institutionalized elders through technology

2002· article· en· W2058452284 on OpenAlexaff
Maureen Mickus, Clare Luz

Bibliographic record

VenueAging & Mental Health · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsCentre for Family Medicine
Fundersnot available
KeywordsNursing homesVideophoneSocial isolationPsychologyNursingGerontologyIsolation (microbiology)Aging in placeFamily caregiversTest (biology)MedicineComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

The role of social support in the health of older persons is well documented. This support is particularly important for isolated nursing home residents. The purpose of this study was to test the feasibility of using low-cost videophones to enhance communication between nursing home residents and their families. Ten pairs of residents and family members received videophones and engaged in regular televisits for six months. All participants completed brief survey instruments prior to and after the study period to determine the effects of the televisits on the frequency and quality of contacts. A post-study survey assessed ease and satisfaction with using videophones. Findings include identification of technical and design problems, possible solutions, factors affecting actual use of equipment, and conditions under which benefits of use may be optimal. Categories for estimating potential actual users are suggested. Importantly, the study demonstrates that videophones can be used successfully by a wide range of frail nursing home residents and can enhance social interactions, regardless of distance. Affordable videophone technology offers the potential for reduced isolation among institutionalized elders and others with distance and mobility barriers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.050
GPT teacher head0.327
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations84
Published2002
Admission routes1
Has abstractyes

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