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Record W2220507113 · doi:10.1080/13698575.2014.999749

Risk: ‘I know it when I see it’: how health and social practitioners defined and evaluated living at risk among community-dwelling older adults

2015· article· en· W2220507113 on OpenAlexafffundabout
Heather MacLeod, Robin Stadnyk

Bibliographic record

VenueHealth Risk & Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsGerontologyPsychologyEnvironmental healthSociologyMedicine

Abstract

fetched live from OpenAlex

Older adults are increasingly choosing to stay and age in their home or other place where they normally live, even when a change in their health reduces their ability to live independently creating concerns about their safety. In this context, community practitioners need to be aware of risk assessment and management strategies as they support their clients’ choices when safety is a concern. This requires an understanding of living at risk and an ability to evaluate the client’s risk status. This article is based on a qualitative research study in which we interviewed 12 Canadian community practitioners in 2012 and explored how they defined, perceived, assessed and managed risk and how they balanced their client’s safety and autonomy. We used a grounded theory methodology to collect and analyse the data. We found that participants tended to define living at risk as a judgement about a client’s impairment within an environment that can cause an event that has an increased potential for a negative consequence. We also found practitioners evaluated the client’s risk by considering seven factors: the client’s capacity and their support, the occurrence, imminency and frequency of the event, the severity of the consequences, and the number of other events co-occurring. In this article, we show that practitioners are comprehensive in their evaluation of the client’s risk. Although practitioners saw risk and living at risk from a negative perspective, they were able to acknowledge that it could coexist along a continuum from safe to unsafe.

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)0.017
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0130.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.060
GPT teacher head0.363
Teacher spread0.303 · 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

Citations39
Published2015
Admission routes3
Has abstractyes

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