MétaCan
Menu
← Back to cohort
Record W2946898479 · doi:10.1093/pch/pxz066.154

155 Qualitative evaluation of a patient navigator program for children with developmental and mental health diagnoses

2019· article· en· W2946898479 on OpenAlexaffabout
Wid Yaseen, Valerie Steckle, Dorjana Vojvoda, Michael Sgro, Tony Barozzino, Shazeen Suleman

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsChild healthMedicineMental healthLibrary scienceSociologyPediatricsFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

Children with mental health and developmental diagnoses require social and community programs for therapy and support, yet few have adequate access to these services. To connect these families with necessary services and funding, a pediatric patient navigator program was launched for children with mental health and developmental diagnoses living in a large urban setting in Canada. The experiences, benefits, and limitations of a navigation program in this patient population have not been well documented. To explore the experiences of various stakeholders with a new pediatric patient navigation program at an urban, inner-city pediatric clinic in Canada, as well as barriers and facilitators to successful program outcomes. This was a qualitative study using a formative research framework. In-depth interviews (IDIs) and participant observations were conducted with patients’ caregivers, general and developmental pediatricians, allied health staff, clinic administrators, and the patient navigator. Data were recorded, transcribed, and coded using deductive and inductive coding methods by two independent coders. Coded excerpts were analyzed within and across stakeholder groups using thematic analysis and supported by group discussion. A total of 25 IDIs and 3 participant observations were conducted across all stakeholder groups. High inter-rater reliability was confirmed by pooled Cohen’s kappa coefficient of 0.85. Before the navigator, caregivers reported difficulty finding and receiving services while healthcare providers described their abilities to find services as ineffective. The navigator’s role was described as multifaceted: completing paperwork, finding funding options, offering emotional support, liaising between physicians and patients, and advocating with schools and agencies. Physicians emphasized the navigator’s support in reducing burnout and allowing for more focused medical visits, while caregivers felt personally supported and better able to access services. However, despite multiple workshops, healthcare providers’ understanding of referral criteria varied, which may lead to inappropriate referrals and longer wait times. Families and caregivers alike face challenges in accessing developmental and mental health services. Patient navigation programs may be a useful strategy to improve patient access to services in a supportive way. More research is needed to reveal the long-term impact of navigation programs on children’s developmental and health outcomes.

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)0.024
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0150.012
Scholarly communication0.0040.003
Open science0.0030.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.427
Teacher spread0.390 · 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 designQualitative
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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child Health→Same topicChild and Adolescent Health→French-language works237,207→