A scoping review of risk factors for urinary incontinence in older men
Bibliographic record
Abstract
BACKGROUND: Most epidemiological studies have not systematically identified or categorized risk factors for urinary incontinence (UI) in older men, despite a higher prevalence than in younger men. Considering the burden of UI, an understanding of risk factors can inform cost-effective prevention/treatment programs. This scoping review aimed to identify and categorise risk factors for UI in older men, identify gaps in the evidence, and opportunities for future research. METHODS: The Joanna Briggs Institute (JBI) method for scoping reviews guided the conduct and reporting of this review alongside the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping reviews checklist. JBI's Population, Concept, and Context approach framed the inclusion criteria (all evidence sources on UI risk factors that included older men [65 +]). We employed JBI's three-step search strategy, which included a limited initial search in Ovid MEDLINE, a detailed comprehensive database search, and a search of reference lists of included studies, Google Scholar and grey literature. There were no restrictions on language, study type, or publication date. Two independent reviewers screened, selected, and extracted eligible studies. Data were analyzed using descriptive statistics and qualitative content analysis. RESULTS: Forty-seven articles that met the inclusion criteria identified 98 risk factors across six categories. Behavioural risk factors, reported by only two studies, were the least investigated of all the categories, whereas medical factors/diseases were the most investigated. No genetic factors were documented. The top five risk factors were increasing age/advanced age (n = 12), Benign Prostatic Hyperplasia (n = 11), Diabetes Mellitus (n = 11), Detrusor overactivity (n = 10), limitation in physical function/ADL disability (n = 10), increased Body Mass Index (BMI)/overweight/obesity (n = 8), Dementia (n = 8), and Parkinson's disease (n = 7). CONCLUSION: There is a dearth of evidence to describe the role behavioural risk factors have in UI in older men. These factors may play a role in health promotion and disease prevention in this area. REGISTRATION: A protocol detailing the methods was developed and published, and is registered in the Open Science Framework [Feb 07 2023; https://osf.io/xsrge/ ].
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 | 0.032 | 0.117 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.033 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".