Barriers and enablers to general practitioner referral of older adults to hearing care: a systematic review using the theoretical domains framework
Bibliographic record
Abstract
PURPOSE: The purpose of this systematic review was to identify and synthesise the literature regarding barriers and enablers affecting general practitioner (GP) referral to hearing care for their older patients (50 years and over). METHODS: A search of peer-reviewed articles reporting primary empirical studies was conducted across CINAHL, Ovid Medline and Scopus, with search terms relating to the search domains "General Practitioner", "Referral", "Hearing loss", and "adults aged 50 and older". Qualitative and quantitative studies were included if they reported barriers or enablers to referral. A mixed-methods approach was used to synthesise the findings of the included studies, firstly into the Theoretical Domains Framework of behaviour change, and then into more granular sub-themes. RESULTS: The initial search yielded 859 unique studies. Title and abstract screening identified 21 studies of possible relevance, and full text review identified seven studies for inclusion in this review. A total of 19 unique themes were identified and coded to 10 of the 14 domains of the Theoretical Domains Framework; however thematic overlap between studies was low and fewer than half of these themes were consistently identified as either a barrier or enabler. Four main barriers to referral to hearing care were identified: Lack of time, lack of familiarity with diagnostic criteria and tools, lack of knowledge of treatments and higher relative importance of other health conditions. CONCLUSION: The minimal overlap of themes and low agreement on which of these constitute barriers and enablers for referral indicates a need for further research to provide greater clarity in this area and explain the heterogeneity of these results.
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 | 0.039 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".