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Record W2018295123 · doi:10.1093/ageing/29.5.401

Review. Adherence to recommendations of community-based comprehensive geriatric assessment programmes

2000· review· en· W2018295123 on OpenAlexaff
Faranak Aminzadeh

Bibliographic record

VenueAge and Ageing · 2000
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsQueensway-Carleton Hospital
Fundersnot available
KeywordsCINAHLMedicineMEDLINEPsychological interventionIntervention (counseling)Family medicineGeriatricsSystematic reviewNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: non-adherence to the recommendations of short-term community-based consultative comprehensive geriatric assessment programmes is a threat to the effectiveness of these programmes. OBJECTIVE: to synthesize the literature on patient and physician adherence to recommendations of community-based comprehensive geriatric assessment programmes. METHOD: I identified papers cited by an English language literature search of MEDLINE, Health Star and CINAHL databases from January 1980 to November 1999. This search was supplemented with literature identified from the reference sections of these publications. RESULTS: patient adherence rates ranged from 46 to 76%, which approximates to the rates for the consulting physician adherence (49-79%). I identified many characteristics of patient, treatment, care provider and clinical setting which influenced adherence. Understanding these factors has led to the development of adherence-enhancing strategies. However, without systematic evaluations it is difficult to evaluate the relative effectiveness of these interventions. CONCLUSION: further research which targets more representative samples and uses validated assessment tools and multiple data collection methods is needed to expand our knowledge of patterns and predictors of adherence and to evaluate the relative effectiveness of adherence-enhancing intervention strategies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.125
GPT teacher head0.430
Teacher spread0.305 · 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 designOther design
Domainnot available
GenreReview

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

Citations42
Published2000
Admission routes1
Has abstractyes

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