An Exploration of the Oral Health-Seeking Behaviour of Adults A Mixed-Methods Systematic Literature Review
Bibliographic record
Abstract
BACKGROUND: Despite oral diseases being preventable, they affect nearly half of the global population. However, it is estimated that 46% of individuals do not routinely visit the dentist. The delayed utilisation of dental services results in irreversible morbidity, reduced quality of life, loss of economic productivity, and mortality. OBJECTIVES: To assess the oral health-seeking behaviour (OHSB) of adults and explore factors influencing it. METHODS: Following the Johanna Briggs Institute (JBI) guidelines, a systematic search of PubMed, Medline, Scopus, CINAHL, and Google Scholar was conducted for articles from 2015 to 2025 that included adults aged 18 and older. Quantitative, qualitative and mixed-methods studies were included and assessed for inclusion using the JBI appraisal tools. The thematic analysis approach was used to synthesize and present findings. RESULTS: Three themes emerged regarding the OHSB of adults: the delayed use of dental services, non-utilisation of dental services, and enablers of dental service utilisation (DSU). Sub-themes emerging under delayed use of dental services were socioeconomic and psychosocial factors. Under non-utilisation of dental services, sociodemographic, intrapersonal factors and the use of alternative treatment pathways were sub-themes. Sub-themes emerging under enablers of DSU were need and health system factors. CONCLUSION: Poor OHSB of adults results in morbidity, reduced quality of life, and mortality. The avoidance of dental services is influenced by sociodemographic, intrapersonal factors and the use of alternative treatment pathways. Delayed DSU is driven by socioeconomic and psychosocial factors, and need and health system factors are enablers of DSU. However, further in-depth research is required on how social, cultural, and health system factors influence OHSB in varying contexts.
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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 | 0.027 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.028 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".