Identifying the key features and outcomes of family navigation services for mental health and/or addictions concerns: a Delphi study
Bibliographic record
Abstract
BACKGROUND: Family navigation in mental health and addictions is a mode of support aimed at helping families through the complex mental health and addictions system, making well-informed service matches, and engaging with families throughout their care journeys. As family navigation services emerge and grow, understanding their unique features and impacts is essential to defining evaluation measures and driving good outcomes for families. METHODS: This Delphi study investigated the defining features of family mental health and addictions navigation, factors involved in a successful service match, and important outcomes of the process through perspectives of clients and team members of a family navigation program, as well as those of local mental health and/or addictions service providers. In the first phase, participants (n = 41), were asked to respond to a series of prompts pertaining to 1) the key features of a successful family navigation process, 2) the features of good matches between youth or families and the services to which they are navigated, and 3) the outcomes of importance in family navigation. In Phase 2, findings from Phase 1 were presented to participants (n = 32) to select and rank their top ten responses to each prompt. Responses which passed a cut-point were carried into Phase 3, in which participants (n = 20), rated the importance of the remaining items. Items rated as "very" or "extremely" important by 80% or more of participants in Phase 3 had achieved consensus. Intra-class correlation coefficients were calculated to confirm participant agreement on all items having achieved consensus. RESULTS: Sample items with 100% consensus were as follows: navigator determines the best fit by understanding and considering the youth and families' needs, by collaborating with team members and service providers, and by providing individualized suggestions; navigation involves knowledge and understanding of mental health and addictions system and existing services; referred service providers are knowledgeable and up-to-date on evidence-based practice and have multidisciplinary perspectives in service. Overall ICC across all finalized statements following Phase 3 was .84. CONCLUSIONS: Exploring the key features of successful navigation, outcomes of importance to stakeholders, and elements of successful matches can inform the development of navigation services that address families' needs, can support service providers in ensuring well-matched services, and lend vital support to families seeking services within a complex system.
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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 | 0.039 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".