Service Provider Perspectives on the Feasibility and Acceptability of Implementing a Systems Navigator Role in the BEAM Program, an App-Based Mental Health Program for Families of Young Children
Bibliographic record
Abstract
Systems navigators, which connect families to health and social services that address chronic stressors, have potential to support unmet family needs in the context of mental health programs. With aims of embedding a systems navigator role within an app-based parenting and mental health program for parents with young children called Building Emotional Awareness and Mental Health (BEAM; thebeamprogram.com), we facilitated focus groups with mental health and family service providers to discuss its feasibility and acceptability. Four themes were constructed: (1) Barriers to Service Access and Provision; (2) Facilitators to Service Access and Provision; (3) Fit of a Systems Navigator; and (4) Identified Support Needs. The discussions highlighted the value of a systems navigator who connects families to services for mental health and other chronic stressors. Providers emphasized that navigators should undergo adequate training and foster positive relationships with diverse community agencies to be able to effectively connect families to services. A systems navigator who offers online and in-person services depending on the family’s needs was also preferred to mitigate barriers to accessing support. This research informed the implementation of a systems navigator in conjunction with the BEAM program to address the needs of families.
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 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 | 0.033 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".