Application and Implementation Gaps in the Conical Model for Older Adults’ Mobility: A Scoping Review
Bibliographic record
Abstract
Background: The 2010 Conical Model of Theoretical Framework for Mobility in Older Adults examines how various factors impact elderly mobility. A decade later, describing the model’s application in research, clinical practice, and policy is crucial. Objective: This scoping review aims to identify studies utilizing the Conical Model in older adult research, clinical practice, and policy while pinpointing implementation gaps. Methods: Seven databases (MEDLINE (PubMed), Embase, CINAHL, PsycINFO, Scopus, Web of Science, GooogleScholar) from 2010 to April 2025 with a well-defined search strategy. Pairs of reviewers independently conducted title/abstract and full-text screening, extracted data, and assessed study quality using modified Downs and Black Checklist (quantitative), Consolidated Criteria for Reporting Qualitative Research (qualitative), and Mixed Methods Appraisal Tool (mixed methods). Results: Twenty-four studies (20 cross-sectional quantitative studies, 2 mixed methods, one concept and one e-Delphi study) were included, with one advancing the Conical Model, eleven testing it, and twelve incorporating it into study development. Findings showed a consistent association between physical and social factors with mobility, although the assessment of mobility factors varied among studies. The quality of articles ranged from good (23%) to excellent (77%). Conclusion: No evidence was found on the Conical Model’s application in clinical practice or policy, despite its theoretical relevance; therefore, there is a need for further validation of the model in real-world applications.
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 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 | 0.238 | 0.457 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.033 | 0.030 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".