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Record W6962465724 · doi:10.17605/osf.io/dtp6w

Mapping sex and gender differences in falls among older adults: a scoping review protocol

2022· other· en· W6962465724 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)PopulationHuman factors and ergonomicsPoison controlInjury preventionSuicide preventionOccupational safety and healthInterpretability

Abstract

fetched live from OpenAlex

Abstract Objective: The objective of this scoping review is to map the nature, extent, and types of literature examining sex and gender differences in falls among older adults. We will also identify gaps that exist in the current literature and opportunities for further research. Introduction: Due to the high prevalence and impact of falls on the aging population in Canada, there is a need to identify subgroups of individuals at greater risk of falls to allow for more targeted fall prevention interventions. In particular, a growing body of literature has examined differences in sex and gender among those who have fallen or those who are at risk of falling. However, there is currently a lack of literature within falls research that defines and operationalizes sex and gender terms, limiting the interpretability of health outcomes and how outcomes differ between males and females and individuals with different gender characteristics. A scoping review has been deemed appropriate due to the broad nature of this topic to focus on and inform future research. Inclusion: Studies must include individuals 60 years or older and discuss concepts related to falls and sex or gender to be eligible for inclusion. Studies will be included if the mean age of participants is 60 years or over. Methods: MEDLINE, Embase, CINAHL, Ageline, and Psychinfo databases will be searched from inception to March 2, 2022. Following the removal of duplicate studies, titles and abstracts will be screened and selected according to predefined inclusion criteria by two or more reviewers. The selected full texts will also be screened and reasons for exclusion will be reported. Data will be extracted from included studies by two or more independent reviewers according to the Participant, Concept and Context Framework. Information regarding the aims of this review will be extracted and presented in a tabular format accompanied by a narrative summary.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0060.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0270.000

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 head0.053
GPT teacher head0.380
Teacher spread0.327 · 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
GenreProtocol

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

Citations0
Published2022
Admission routes1
Has abstractyes

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