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Record W3175656852 · doi:10.1177/13674935211028694

Working with parents of children with complex mental health issues to improve care: A qualitative inquiry

2021· article· en· W3175656852 on OpenAlexaffabout
Brenda Leung, Cynthia Wandler, Tamara Pringsheim, Maria Santana

Bibliographic record

VenueJournal of Child Health Care · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of CalgaryUniversity of Lethbridge
Fundersnot available
KeywordsMental healthQualitative researchMedicineMental health carePsychologyNursingPsychiatrySociology

Abstract

fetched live from OpenAlex

The study objective was to explore the experiences of parents of children (6–17 years) with complex mental healthcare needs in accessing healthcare services in Alberta, Canada. Parents were interviewed using a semi-structured guide with open-ended and probing questions. Interviews were audio recorded and transcribed verbatim. Thematic analysis revealed three main themes: (1) Fragmented healthcare services profoundly impacted participants’ experience of mental health care due to (a) a lack of a collaborative approach across disciplines in the healthcare system; (b) unavailability of information related to mental health care and (c) a lack of patient-centred care. (2) Navigating the complex healthcare system was difficult due to fragmented services and was hindered by gaps in accessing and receiving care, lack of continuity of care and lack of resources. (3) Distressed parents discussed the emotional challenges, financial burdens, self-advocacy and stigma they experienced in navigating the system. Parents offered insights into potential solutions to these gaps. Parents recommended the creation of a one-stop shop service with a team approach led by a navigator to facilitate and support navigations across healthcare services that work collaboratively across disciplines among healthcare services and across sectors inclusive of social services, education, policing and community programmes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.399
Teacher spread0.350 · 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 teacher head, 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

Citations32
Published2021
Admission routes2
Has abstractyes

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