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Record W2919333400 · doi:10.1177/0733464819832198

Chronic Disease Self-Management Among Iranian Older Adults: A Scoping Review

2019· review· en· W2919333400 on OpenAlexaff
Aein Zarrin, Nima Tourchian, George Heckman

Bibliographic record

VenueJournal of Applied Gerontology · 2019
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsResearch Institute for AgingYork UniversityUniversity of Waterloo
FundersCenters for Disease Control and Prevention
KeywordsCINAHLCoachingGerontologyMedicineMEDLINESelf-managementChronic diseaseQuality of life (healthcare)Disease managementNursingFamily medicinePsychologyPsychological interventionAlternative medicineHealth management system

Abstract

fetched live from OpenAlex

Background: Implementing care models that emphasize chronic disease self-management (CDSM) strategies may be an effective approach to the growing prevalence of chronic conditions in Iran. We, therefore, conducted a scoping review on CDSM among older Iranians to identify existing gaps and opportunities to improve chronic disease care. Method: We conducted a search in CINAHL, EMBASE, MEDLINE/PubMed, and Cochrane library. Selected articles were charted based on year of publication, language, objectives, methods, target chronic disease(s), sample demographics, self-management type, and key findings. Results: We selected 73 articles. The main components of CDSM addressed were social support, education, physical activity, nutrition, self-monitoring, spirituality, and financial support. Older Iranians reported low levels of physical activity. Conclusion: Enhancing the quality of CDSM research and provision of coaching to enhance older adults’ social and mental health are among the main strategies to enhance CDSM among the Iranian older population.

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)0.001
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.353
Teacher spread0.319 · 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 designSystematic review
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

Citations21
Published2019
Admission routes1
Has abstractyes

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