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Record W3210530381 · doi:10.33137/utjph.v2i2.36840

Patient and Family Engagement

2021· article· en· W3210530381 on OpenAlexaffabout
Bonnie Hope Cai

Bibliographic record

VenueUniversity of Toronto Journal of Public Health · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMental healthGeneral partnershipHealth careNursingPortfolioPsychologyMedicinePsychiatryPolitical scienceBusiness

Abstract

fetched live from OpenAlex

British Columbia Mental Health and Substance Use Services (BCMHSUS) provides mental health services, education, and health promotion initiatives to people with mental health and substance use issues across the province of BC. As a Project Coordinator in the Patient and Community Engagement portfolio, I performed a variety of work to support patient and family engagement under the newly created Patient Engagement Framework. Engaging patients and families as active participants and co-designers of their own care is an important component of patient-centred care that improves healthcare quality, health outcomes, and overall experiences of care at a system level. To work towards this goal, I developed a trauma-informed policy and procedure for BCMHSUS on patient and family engagement to serve as a guideline for giving patients and families a voice in the design and delivery of their mental health care. I also drafted two patient engagement playbooks called Managing Conflict and Respecting Emotions and Engaging Mandated and Incarcerated Patients, which focus on barriers and solutions to engaging patients in vulnerable circumstances. Moreover, I worked with provincial stakeholders to write the annual report for the BC Partners, which is a collaborative mental health promotion partnership between BCMHSUS and 7 provincial organizations with different mental health and substance use specialties (e.g. BC Schizophrenia Society, The Mood Disorders Association of BC, Canadian Institute for Substance Use Research, etc.). I also performed a literature review of the evidence supporting family engagement in patient- and family-centred care, and I made infographics and other visual designs to translate research and knowledge in visually appealing ways. Overall, my practicum helped me contribute towards advancing public mental health by valuing patients' knowledge, skills, and lived experience in the health system and working on a variety of initiatives to promote mental health in the province.

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)0.018
metaresearch head score (Gemma)0.055
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0080.005
Open science0.0020.015
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0720.011

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 head0.235
GPT teacher head0.376
Teacher spread0.141 · 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
GenreCommentary

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

Citations5
Published2021
Admission routes2
Has abstractyes

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