Literature Collection

IMPORTANCE: Sleep is crucial for healthy growth, academic success, executive functioning, and mental health. However, sleep is not consistently and rigorously addressed in pediatric primary care. OBJECTIVE: To describe the development and reach, adoption, implementation, effectiveness, and maintenance of a well-child visit, electronic sleep screener with educational resources in a large primary care network. DESIGN, SETTING, AND PARTICIPANTS: In this case-control study of primary care practices in Pennsylvania and New Jersey, retrospective, observational electronic health records and implementation data were drawn for preimplementation (November 1, 2018, to September 30, 2019), phased-scaling (October 1, 2019, to June 30, 2021), implementation (July 1, 2021, to June 30, 2022), and maintenance (July 1, 2022, to June 30, 2023) periods. Multivariate logistic regression examined the effectiveness by comparing implementation vs preimplementation rates of sleep disorder diagnosis, polysomnogram orders, and sleep-related referrals. Patients were seen for a well-child visit during the preimplementation and implementation periods, without exclusions. Data were analyzed from October 10, 2023, to May 2, 2025. EXPOSURE: An age-based, electronic sleep screener assessing infant bed sharing, frequent snoring (≥3 nights/week), perceived sleep problems, insufficient sleep duration, and adolescent daytime sleepiness. MAIN OUTCOMES AND MEASURES: The Reach, Effectiveness, Adoption, Implementation, and Maintenance framework guided the outcomes including sleep screener use, results, and primary care clinician (PCC)-rendered sleep disorder diagnosis, polysomnogram orders, and sleep-related referrals at the well-child visit. RESULTS: A total of 409 217 well-child visits for 288 307 unique patients aged 18 years or younger (51.2% male; 49.9% White non-Hispanic or Latine) were included in the preimplementation and implementation periods. During implementation, 204 872 unique patients in 31 practices completed the screener, with adoption in 89.5% of all well-child visits. Overall, 9.7% of patients endorsed frequent snoring, 12.2% sleep problems, and 34.4% insufficient sleep. Infant bed sharing was endorsed in 6.5% of infants, whereas 14.7% of adolescents endorsed daytime sleepiness. Compared with the preimplementation period, at well-child visits with a completed sleep screener, PCCs were significantly more likely to render a sleep disorder diagnosis (odds ratio, 1.64 [95% CI, 1.56-1.73]), order a polysomnogram (odds ratio, 2.67 [95% CI, 2.32-3.20]), and refer to sleep (odds ratio, 6.48 [95% CI, 5.03-8.34]) or otolaryngology (odds ratio, 4.46 [95% CI, 3.95-5.02]) clinics. Minimal adaptations occurred during implementation, and adoption was high and persistent (92.5% of well-child visits) during the maintenance period. CONCLUSIONS AND RELEVANCE: In this case-control study, a brief, electronic well-child visit sleep screener was widely adopted and maintained in a sociodemographically diverse primary care network and was associated with increased recognition and management of sleep problems.

PURPOSE: Rural communities often have a high incidence of medical and behavioral health problems along with more limited access to care. This paper describes an innovative approach to providing integrated care in rural school-based health clinics in which graduate students serve as behavioral health interns. The purpose of this manuscript is 1) to describe a model for providing school-based integrated health services in a rural community and 2) to evaluate services provided by graduate interns embedded in school-based clinics. MATERIALS AND METHODS: Graduate interns completed a session checklist to track services provided in each session and collected data from participating students who received behavioral health services. Students completed the Outcome Rating Scale (ORS) after each session. Repeated measures MANOVAs were used to analyze the data for changes over time. RESULTS: Services provided most often by interns included assessment, engagement, positive reinforcement, coping skills, goal setting, and clinical intervention. The data suggest that students receiving at least three sessions improved over time on self-reported wellbeing. DISCUSSION: The results demonstrate the feasibility of providing integrated health care via school-based clinics that rely on graduate internships for behavioral health services. Challenges to implementing and sustaining school-based integrated health clinics are discussed. CONCLUSION: The ongoing challenges to meeting the medical and behavioral health needs of rural communities call for innovative approaches to providing integrated care. The clinics described here responded to these challenges through teamwork and strong university-community partnerships.

BACKGROUND: Contingency management (CM) is an effective yet underutilized behavioral intervention that uses rewards to improve outcomes in medication for opioid use disorder (MOUD) treatment. Prior implementation attempts have focused on specialized addiction clinics, using intensive daily treatment with methadone and high reward values (e.g. >$200 total). However, many people get MOUD from less specialized, more accessible, family medicine clinics. These clinics could also benefit from CM, yet present unique challenges for CM. Family medicine clinics typically use buprenorphine as their primary medication, which requires less intensive dosing schedules and thus provides fewer CM opportunities. They may also have lower institutional willingness to use high-value rewards. As an initial step in user-centered design of a low value reward (<$75 total) CM program for the family medicine context, we conducted qualitative interviews with patients and staff in the buprenorphine treatment program of a family medicine department. We gathered and analyzed qualitative data on CM knowledge, preferred program parameters, and implementation considerations. METHOD: Participants (N = 24) were buprenorphine treatment staff (n = 12) and patients (n = 12). Participants completed 30-50-minute semi-structured interviews, analyzed using rapid matrix analysis. RESULTS: Participants had little experience with CM, but generally viewed CM as acceptable, appropriate, and feasible. Interviewees coalesced around having staff who were not providers with prescription privileges conduct CM, consistent rather than escalating payments, and physical rewards delivered in-person. Potential challenges included medical record integration, demands on staff time, and confirmation of patients' goal completion. CONCLUSIONS: Patient and staff feedback was well-aligned, especially regarding rewards as an opportunity for staff-patient connection and the need for simplicity. Some consensus suggestions (e.g. non-escalating rewards) conflict with extant CM literature. Implications for implementation of CM in this setting are presented. These findings inform user-centered design and iteration of a CM program for this accessible, non-specialized family medicine setting.