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Record W1794109811 · doi:10.1186/s12877-015-0079-z

Purchasing and Using Personal Emergency Response Systems (PERS): how decisions are made by community-dwelling seniors in Canada

2015· article· en· W1794109811 on OpenAlexaffabout
Alexandra C. McKenna, Marita Kloseck, Richard Crilly, Jan Miller Polgar

Bibliographic record

VenueBMC Geriatrics · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsGrounded theoryAging in placeFocus groupQualitative researchGerontologyContext (archaeology)MedicineRetirement communityRehabilitationIndependent livingNursingPsychologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: As the demographic of older people continues to grow, health services that support independence among community-dwelling seniors have become increasingly important. Personal Emergency Response Systems (PERS) are medical alert systems, designed to serve as a safety net for seniors living alone. Health care professionals often recommend that seniors in danger of falls or other medical emergencies obtain a PERS. The purpose of the study was to investigate the experience of seniors living with and using a PERS in their daily lives, using a qualitative grounded theory approach. METHODS: Five focus groups and 10 semi-structured interviews, with a total of 30 participants, were completed using a grounded theory approach. All participants were PERS subscribers over the age of 80, living alone in a naturally occurring retirement community (NORC) with high health service utilization in a major urban centre in Ontario. Constant comparative analysis was used to develop themes and ultimately a model of why and how seniors obtain and use the PERS. RESULTS: Two core themes, unpredictability and decision-making around PERS activation, emerged as major features of the theoretical model. Being able to get help and the psychological value of PERS informed the context of living with a PERS. CONCLUSIONS: A number of theoretical conclusions related to unpredictability and the decision-making process around activating PERS were generated.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.132
GPT teacher head0.359
Teacher spread0.227 · 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

Citations17
Published2015
Admission routes2
Has abstractyes

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