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Record W4289274883 · doi:10.1093/nutrit/nuac050

The socioecological correlates of meal skipping in community-dwelling older adults: a systematic review

2022· review· en· W4289274883 on OpenAlexaboutno aff
Holly Wild, Yeji Baek, Shivangi Shah, Danijela Gašević, Alice Owen

Bibliographic record

VenueNutrition Reviews · 2022
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLPsycINFOMedicineMEDLINEGerontologyMealPsychological interventionEnvironmental healthInternal medicineBiologyPsychiatry

Abstract

fetched live from OpenAlex

CONTEXT: Meal skipping may contribute to nutrient deficiency across the lifespan. Multiple socioecological factors have been identified as correlates of meal skipping in adolescents and adults, but evidence in older adults is limited. OBJECTIVE: To determine the socioecological correlates of meal skipping in community-dwelling older adults. DATA SOURCE: Embase, PsycINFO, CINAHL, and MEDLINE electronic databases were systematically searched from inception to March 2021. DATA EXTRACTION: A total of 473 original research studies on socioecological factors and meal skipping among community-dwelling adults aged ≥65 years were identified. Title, abstract, and full-text review was performed by 2 reviewers independently, and a third reviewer resolved disagreements. A total of 23 studies met our inclusion criteria. Data were extracted by 1 reviewer from these studies and independently verified by another. The Newcastle-Ottawa Scale was used to assess methodological quality. DATA ANALYSIS: The frequency of meal skipping in included studies ranged between 2.1% and 61%. This review identified 5 domains of socioecological correlates associated with meal skipping in older adults: sociodemographic, behavioral, biomedical, psychological, and social. CONCLUSION: Understanding the factors associated with meal skipping in older adults can inform the development of targeted interventions to improve nutrition and health. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42021249338.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.130
GPT teacher head0.419
Teacher spread0.290 · 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

Citations14
Published2022
Admission routes1
Has abstractyes

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