Frailty in Older Populations of Arabic-Speaking Countries: Protocol for a Scoping Review
Bibliographic record
Abstract
Introduction: With the globally aging population, the impact of frailty is expected to increase, and frailty has come into focus as a challenging manifestation of aging. Although frailty has been thoroughly investigated in developed countries, it has been understudied in developing countries. Like other countries worldwide, Arabic-speaking countries (ASCs) are experiencing an increase in the aging population; thus, the risk of frailty increases, and it becomes imperative to address the limitations of diagnosis, treatment, and prevention of frailty in this area of the world.Objective: This protocol describes a scoping review that will investigate what is known about frailty in older adults living in ASCs. The aim is to synthesize and map the literature addressing the concept of frailty, its association with other geriatric conditions, and measurement tools used to identify or assess frailty among this subpopulation in this part of the world.Methods: This review will employ Joanna Briggs Institute guidelines (JBI). Studies considered for this review must involve the concept of frailty among older adults living in the Arabic-speaking world. Conclusion/Discussion: This scoping review protocol outlines the specific methodologies to improve the overall quality of the finalized scoping review. The finalized scoping review will present an overview of the current literature on frailty in older adults living in ASCs and summarize the knowledge gaps in frailty assessment and interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.079 | 0.097 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.065 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".