MétaCan
Menu
← Back to cohort
Record W4413117909

Managing patient mental health disclosures in Canadian dental and dental hygiene programs.

2025· article· en· W4413117909 on OpenAlexaffabout
Maranda M Mazoka, Zul Kanji

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDental hygieneDental healthMental healthMental hygieneHygieneMedicineOral hygieneDentistryPsychologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective: This narrative literature review aims to explore the current landscape regarding the management of patient mental health disclosures and gaps in resources and protocols within Canadian dental and dental hygiene programs. Methods: were used to search for literature published between 2001 and 2023. Results: A total of 54 sources were included, primarily comprising original research articles, systematic and other literature reviews. Discussion: The prevalence of mental health disclosures is rising, with 1 in 5 Canadians living with a mental health condition. Current dental and dental hygiene programs lack explicit protocols for managing patient mental health disclosures, and the literature reveals a scarcity of research on students' preparedness. This review underscores the importance of adopting humanistic language to reduce stigma and emphasizes educational institutions' roles in evaluating and facilitating mental health services to support the mental health lived experiences of dental and dental hygiene patients. Conclusion: The review identifies 3 key research gaps: the absence of qualitative research on the student experience of managing patient disclosures, unclear integration of mental health education, and a scarcity of comprehensive evaluations of mental health services. Recommendations include incorporating mental health training in entry-to-practice curricula, aligning with established community support frameworks, and creating dedicated resources for the effective management of mental health disclosures for patients in educational settings.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.592

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.047
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.012
Science and technology studies0.0040.002
Scholarly communication0.0050.002
Open science0.0030.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.010
GPT teacher head0.262
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuePubMed→Same topicDental Health and Care Utilization→French-language works237,207→