Development of an Electronic Screening and Brief Intervention to Address Perinatal Substance Use in Home Visiting: Qualitative User-Centered Approach
Bibliographic record
Abstract
BACKGROUND: Perinatal substance use (SU) is prevalent during pregnancy and the postpartum period and may increase the risks to maternal and child health. Many pregnant and postpartum women do not seek treatment for SU because of fear of child removal. Home visiting (HV), a voluntary supportive program for high-risk families during the perinatal period, is a promising avenue for addressing unmet SU needs. Confidential delivery of screening and brief intervention (BI) for SU via computers has demonstrated high user satisfaction among pregnant and postpartum women as well as efficacy in reducing perinatal SU. This study describes the development of the electronic screening and BI for HV (e-SBI-HV), a digital screening and BI program that is adapted from an existing electronic screening and BI (e-SBI) for perinatal SU and tailored to the HV context. OBJECTIVE: This study aimed to describe the user-centered intervention development process that informed the adaptation of the original e-SBI into the e-SBI-HV, present specific themes extracted from the user-centered design process that directly informed the e-SBI-HV prototype and describe the e-SBI-HV prototype. METHODS: Adaptation of the original e-SBI into the e-SBI-HV followed a user-centered design process that included 2 phases of interviews with home visitors and clients. The first phase focused on adaptation and the second phase focused on refinement. Themes were extracted from the interviews using inductive coding methods and systematically used to inform e-SBI-HV adaptations. Participants included 17 home visitors and 7 clients across 3 Healthy Families America programs in New Jersey. RESULTS: The e-SBI-HV is based on an existing e-SBI for perinatal SU that includes screening participants for SU followed by a brief motivational intervention. On the basis of the themes extracted from the user-centered design process, the original e-SBI was adapted to address population-specific motivating factors, address co-occurring problems, address concerns about confidentiality, acknowledge fear of child protective services, capitalize on the home visitor-client relationship, and provide information about SU treatment while acknowledging that many clients prefer not to access the formal treatment system. The full e-SBI-HV prototype included 2 digital intervention sessions and home visitor facilitation protocols. CONCLUSIONS: This study describes a user-centered approach for adapting an existing e-SBI for SU for use in the HV context. Despite the described challenges, home visitors and clients generally reacted favorably to the e-SBI-HV, noting that it has the potential to fill a significant gap in HV services. If proven effective, the e-SBI-HV could provide a way for clients to receive help with SU within HV, while maintaining their privacy and avoiding the overburdening of home visitors. The next step in this study would be to test the feasibility and preliminary efficacy of the e-SBI-HV.
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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 | 0.026 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 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".