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Record W2007838912 · doi:10.5539/gjhs.v5n6p30

The Long-Term Impact of Education on Diabetes for Older People: A Systematic Review

2013· review· en· W2007838912 on OpenAlexvenueno aff
Soontareeporn Meepring, Malinee Youjaiyen

Bibliographic record

VenueGlobal Journal of Health Science · 2013
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsycINFOMedicineGlycemicCochrane LibraryMEDLINEGerontologyCINAHLEnthusiasmDiabetes managementDiabetes mellitusNursingFamily medicineType 2 diabetesPsychologyRandomized controlled trialSurgeryPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Although enthusiasm is growing for diabetic education programs for older people, data regarding their effectiveness and their long-term impact on self-management were neglected. PURPOSE: To systematically review diabetes mellitus education that has long-term effects on the self-management of older diabetic people. DATA SOURCES: The authors searched multiple sources dated through September 2012, including the Cochrane Library, MEDLINE, PsycINFO, Nursing and Allied Health databases, and the bibliographies of 50 previous reviews. METHODS AND DATA EXTRACTION: Electronic databases were searched for controlled studies in English, published from 1987 to 2012, assessing the effects of long-term education for older people. Reviewers extracted study data using a structured abstraction form. Aggregated information about the effects of long-term education programs on older people with diabetes was used for making adjustments in the review. RESULTS: The pooled estimate of the long-term effects of education was a 0.5 percentage point reduction (95% confidence interval), modest but significant improvement. The evidence also supports that long-term education is beneficial for improving diabetic patient self-care management in terms of glycemic control.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.453
Teacher spread0.407 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2013
Admission routes1
Has abstractyes

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