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Record W4200030264 · doi:10.1177/10497323211061345

PTSD Symptoms and Dementia in Older Veterans Who are Living in Long-Term Care

2021· article· en· W4200030264 on OpenAlexaffabout
Kim Ritchie, Heidi Cramm, Alice Aiken, Catherine Donnelly, Catherine Goldie

Bibliographic record

VenueQualitative Health Research · 2021
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsDalhousie UniversityQueen's University
Fundersnot available
KeywordsDementiaPosttraumatic stressLong-term carePsychological interventionAggressionMedicinePsychiatryPsychologyClinical psychologyDisease

Abstract

fetched live from OpenAlex

Co-occurring posttraumatic stress disorder symptoms and dementia can result in increased symptoms, such as suspicion, aggression, and nightmares in Veterans that can be difficult to manage in long-term care environments. The objective of the study was to explore how the co-occurrence of posttraumatic stress disorder symptoms and dementia are understood in Canadian Veterans who are living in long-term care. A descriptive multiple case study was conducted in two Veteran long-term care facilities in Canada. Data collection consisted of semi-structured interviews with Veterans, their family caregivers, and health care providers, non-participant observation, and a chart audit. Three major themes emerged relating to symptom expression and care approach: a) symptoms are the same but different; b) differences in the complexity of care; and c) added dimensions involved in care. The results of this study contribute foundational information about co-occurring posttraumatic and dementia symptoms that can inform policy, care approaches, and potential interventions.

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 score0.425
Threshold uncertainty score0.846

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.341
GPT teacher head0.606
Teacher spread0.266 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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