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BackgroundBuprenorphine is a life-saving medication for people with opioid use disorder (OUD). U.S. federal law allows advanced practice clinicians (APCs), such as nurse practitioners (NPs) and physician assistants (PAs), to obtain a federal waiver to prescribe buprenorphine in office-based practices. However, states regulate APCs' scope of practice (SOP) variously, including requirements for physician supervision. States may also have laws entirely banning NP/PA buprenorphine prescribing or requiring that supervising physicians have a federal waiver to prescribe buprenorphine. We sought to identify prevalence of state laws other than SOP laws that either 1) prohibit NP/PA buprenorphine prescribing entirely, or 2) require supervision by a federally waivered physician.MethodsWe searched for state statutes and regulations in all 50 states and Washington D.C. regulating prescribing of buprenorphine for OUD by APCs during summer 2021. We excluded general scope of practice laws, laws only applicable to Medicaid-funded clinicians, laws not applicable to substance use disorder (SUD) treatment, and laws only applicable to NPs/PAs serving licensed SUD treatment facilities. We then conducted content analysis.ResultsOne state prohibits all APCs from prescribing buprenorphine for OUD, even though the state's general SOP laws permit APC buprenorphine prescribing. Five states require PA supervision by a federally waivered physician. Three states require NP supervision by a federally waivered physician.ConclusionsAside from general scope of practice laws, several states have created laws explicitly regulating buprenorphine prescribing by APCs outside of licensed state SUD facilities.

Most research on mathematical play and learning is focused on early childhood. This study examines how mathematical play and learning manifest in older children in a mathematical videogame designed by the first author, "Rolly's Adventure." We examined how players experienced mathematical play as they played "Rolly's Adventure," with a particular focus on failure paired with feedback. We used video and audio recordings of the players and their bodies, and screen capture of their gameplay. Spoken language, physical gestures, and digital actions were our primary sources of identifying, understanding, and triangulating mathematical play. We found that players pass through five zones of mathematical play that build upon each other and closely interrelate, and that these zones each involve different types of failure, feedback, and learning experiences. This paper provides a productive definition of mathematical play, introduces a framework that describes players' mathematical play experiences, and presents five design principles that can be leveraged to support mathematical play.

OBJECTIVE: To elicit expert consensus on quality indicators for the hospital-based care of opioidexposed infants. METHODS: We used the ExpertLens online platform to conduct a 3-round modified Delphi panel. Expert panelists included health care providers, parents in recovery, quality experts, and public health experts. We identified 49 candidate quality indicators from a literature review and environmental scan. A total of 32 experts rated the importance and feasibility of the indicators using a 9-point Likert scale (Round 1), reviewed and discussed the initial ratings (round 2), and revised their original ratings (Round 3). Numeric scores corresponded with descriptive ratings of "low" (1-3), "uncertain" (4-6), or "high" (7-9). We measured consensus using the RAND/UCLA Appropriateness Method. RESULTS: Candidate quality indicators assessed structures, processes, and outcomes in multiple domains of clinical care. After the final round, 36 indicators were rated "high" on importance and feasibility. Experts had strong consensus on the importance of quality indicators to assess universal screening of pregnant people for substance use disorder, hospital staff training, standardized assessment for neonatal opioid withdrawal syndrome, nonpharmacologic interventions, and transitions of care. For indicators focused on processes and outcomes, experts saw feasibility as dependent on the information routinely documented in electronic medical records or billing records. To present a more complete picture of hospital quality, experts suggested development of composite measures that summarize quality across multiple indicators. CONCLUSIONS: A panel of experts reached consensus on a range of quality indicators for hospitalbased care of opioid-exposed infants, with potential for use in national benchmarking, intervention studies, or hospital performance measurement. [ABSTRACT FROM AUTHOR]

Background: Homelessness is a traumatic experience, and can have a devastating effect on those experiencing it. People who are homeless often face significant barriers when accessing public services, and have often experienced adverse childhood events, extreme social disadvantage, physical, emotional and sexual abuse, neglect, low self‐esteem, poor physical and mental health, and much lower life expectancy compared to the general population. Rates of problematic substance use are disproportionately high, with many using drugs and alcohol to deal with the stress of living on the street, to keep warm, or to block out memories of previous abuse or trauma. Substance dependency can also create barriers to successful transition to stable housing. Objectives: To understand the effectiveness of different substance use interventions for adults experiencing homelessness. Search Methods: The primary source of studies for was the 4th edition of the Homelessness Effectiveness Studies Evidence and Gaps Maps (EGM). Searches for the EGM were completed in September 2021. Other potential studies were identified through a call for grey evidence, hand‐searching key journals, and unpacking relevant systematic reviews. Selection Criteria: Eligible studies were impact evaluations that involved some comparison group. We included studies that tested the effectiveness of substance use interventions, and measured substance use outcomes, for adults experiencing homelessness in high income countries. Data Collection and Analysis: Descriptive characteristics and statistical information in included studies were coded and checked by at least two members of the review team. Studies selected for the review were assessed for confidence in the findings. Standardised effect sizes were calculated and, if a study did not provide sufficient raw data for the calculation of an effect size, author(s) were contacted to obtain these data. We used random‐effects meta‐analysis and robust‐variance estimation procedures to synthesise effect sizes. If a study included multiple effects, we carried out a critical assessment to determine (even if only theoretically) whether the effects are likely to be dependent. Where dependent effects were identified, we used robust variance estimation to determine whether we can account for these. Where effect sizes were converted from a binary to continuous measure (or vice versa), we undertook a sensitivity analysis by running an additional analysis with these studies omitted. We also assessed the sensitivity of results to inclusion of non‐randomised studies and studies classified as low confidence in findings. All included an assessment of statistical heterogeneity. Finally, we undertook analysis to assess whether publication bias was likely to be a factor in our findings. For those studies that we were unable to include in meta‐analysis, we have provided a narrative synthesis of the study and its findings. Main Results: We included 48 individual papers covering 34 unique studies. The studies covered 15, 255 participants, with all but one of the studies being from the United States and Canada. Most papers were rated as low confidence (n = 25, or 52%). By far the most common reason for studies being rated as low confidence was high rates of attrition and/or differential attrition of study participants, that fell below the What Works Clearinghouse liberal attrition standard. Eleven of the included studies were rated as medium confidence and 12 studies as high confidence. The interventions included in our analysis were more effective in reducing substance use than treatment as usual, with an overall effect size of –0.11 SD (95% confidence interval [CI], −0.27, 0.05). There was substantial heterogeneity across studies, and the results were sensitive to the removal of low confidence studies (−0.21 SD, 95% CI [−0.59, 0.17] − 6 studies, 17 effect sizes), the removal of quasi‐experimental studies (−0.14 SD, 95% CI [−0.30, 0.02] − 14 studies, 41 effect sizes) and the removal of studies where an effect size had been converted from a binary to a continuous outcome (−0.08 SD, 95% CI [−0.31, 0.15] − 10 studies, 31 effect sizes). This suggests that the findings are sensitive to the inclusion of lower quality studies, although unusually the average effect increases when we removed low confidence studies. The average effect for abstinence‐based interventions compared to treatment‐as‐usual (TAU) service provision was –0.28 SD (95% CI, −0.65, 0.09) (6 studies, 15 effect sizes), and for harm reduction interventions compared to a TAU service provision is close to 0 at 0.03 SD (95% CI, −0.08, 0.14) (9 studies, 30 effect sizes). The confidence intervals for both estimates are wide and crossing zero. For both, the comparison groups are primarily abstinence‐based, with the exception of two studies where the comparison group condition was unclear. We found that both Assertative Community Treatment and Intensive Case Management were no better than treatment as usual, with average effect on substance use of 0.03 SD, 95% CI [−0.07, 0.13] and –0.47 SD, 95% CI [−0.72, −0.21] 0.05 SD, 95% CI [−0.28, 0.39] respectively. These findings are consistent with wider research, and it is important to note that we only examined the effect on substance use outcomes (these interventions can be effective in terms of other outcomes). We found that CM interventions can be effective in reducing substance use compared to treatment as usual, with an average effect of –0.47 SD, 95% CI (−0.72, −0.21). All of these results need to be considered in light of the quality of the underlying evidence. There were six further interventions where we undertook narrative synthesis. These syntheses suggest that Group Work, Harm Reduction Psychotherapy, and Therapeutic Communities are effective in reducing substance use, with mixed results found for Motivational Interviewing and Talking Therapies (including Cognitive Behavioural Therapy). The narrative synthesis suggested that Residential Rehabilitation was no better than treatment as usual in terms of reducing substance use for our population of interest. Authors' Conclusions: Although our analysis of harm reduction versus treatment as usual, abstinence versus treatment as usual, and harm reduction versus abstinence suggests that these different approaches make little real difference to the outcomes achieved in comparison to treatment as usual. The findings suggest that some individual interventions are more effective than others. The overall low quality of the primary studies suggests that further primary impact research could be beneficial. [ABSTRACT FROM AUTHOR]

As part of a large pan-European project on co-creating public services we supported the design of a programme in England that attempted to operationalise research on desistance, through a model of co-created, strengths-based working. We then evaluated its implementation and impact. The programme was implemented in a Community Rehabilitation Company. It was delivered in the context of rapid organisational change, often in response to rapidly changing external events and a turbulent policy environment. These factors impeded implementation. An impact evaluation did not identify a statistically significant difference in re-offending rates between the intervention group and a comparator group. However, in-depth qualitative evaluation identified positive examples of co-production and co-creation, with individual case managers and service users supportive and noting positive change. Taken as a whole our findings suggest that a co-created, strengths-based model of probation case management is promising but needs to be accompanied by wider systems change if it is to be embedded successfully. [ABSTRACT FROM AUTHOR]