Enhancing Understanding of Parental Engagement During Family-Focused Cognitive Behavioural Therapy for Early-Onset Pediatric Obsessive-Compulsive Disorder
Bibliographic record
Abstract
Introduction: Family-focused cognitive behavioural therapy (FFCBT) is emphasized as an approach to optimize treatment outcomes for early-onset obsessive-compulsive disorder (OCD). Parental engagement is critical to successful treatment. However, few studies have examined how to promote parental engagement during FFCBT. Additionally, from a parental perspective, there is a limited understanding of factors that influence parental engagement throughout treatment, including the role of nurses. Aims: To determine (i) how parents experience and understand their engagement in FFCBT provided for their child with early-onset OCD in community or outpatient mental health programs, and (ii) how parents describe the role of nurses related to parental engagement during the treatment process. Methods: This study used an interpretive description approach. Semi-structured interviews were completed with parents (n = 17) recruited from community or outpatient children’s mental health programs in the Hamilton Region of Southwestern Ontario. Treatment provider interviews (n = 9) augmented the data collected from parents’ perceptions of their engagement and the role of nurses during FFCBT. Interviews were analyzed using Braun and Clark’s (2006) thematic analysis process. Results: A conceptualized model was constructed to display and communicate the individual, interpersonal, and contextual influences identified by parents and treatment providers. These influences facilitated or inhibited parental engagement during treatment across distinct phases, levels, and stages of engagement. Six distinct nursing roles were identified that promoted parental engagement throughout treatment.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".