To meet the diverse needs of youth athletes within contemporary society, the privilege and responsibility of youth sport coaching must be reimagined. Critical positive youth development (CPYD)—which is grounded in Freire’s critical consciousness—emphasizes the urgency to empower youth to promote social justice and increase their ability to contribute to societal change. Considering the scarcity of CPYD in coach education, sport social workers may offer unique educational experiences and critical learning opportunities that may help fulfill a CPYD mandate within the youth sport landscape. From a social constructivist perspective, the aim of the current study was to explore the duality of sport social workers coaching competitive youth sport. Findings from 10 sport social workers suggest that the values, knowledge, and skills of the social work profession—particularly sport social work—seem to offer a transferable skillset and lessons to be emulated by CPYD coach education. For instance, because of their unique education and training, social workers are taught to use a strengths-based approach, maintain a holistic perspective, and teach life skills that contribute to PYD. However, findings also emphasize the notion that education may not solve all challenges concerning the need to foster CPYD, as many other variables make up the sport system.

Popular statistical software provides the Bayesian information criterion (BIC) for multi-level models or linear mixed models. However, it has been observed that the combination of statistical literature and software documentation has led to discrepancies in the formulas of the BIC and uncertainties as to the proper use of the BIC in selecting a multi-level model with respect to level-specific fixed and random effects. These discrepancies and uncertainties result from different specifications of sample size in the BIC's penalty term for multi-level models. In this study, we derive the BIC's penalty term for level-specific fixed- and random-effect selection in a two-level nested design. In this new version of BIC, called , this penalty term is decomposed into two parts if the random-effect variance-covariance matrix has full rank: (a) a term with the log of average sample size per cluster and (b) the total number of parameters times the log of the total number of clusters. Furthermore, we derive the new version of BIC, called , in the presence of redundant random effects. We show that the derived formulae, and , adhere to empirical values via numerical demonstration and that ( indicating either or ) is the best global selection criterion, as it performs at least as well as BIC with the total sample size and BIC with the number of clusters across various multi-level conditions through a simulation study. In addition, the use of is illustrated with a textbook example dataset.

BotGo was started in 2007 by Ravi Panchal, an engineer, after he lost motivation to continue at a managerial role at his job. A hands-on technical person, Panchal was inspired to create an underwater tank-cleaning robot. He started BotGo by bootstrapping it with his savings and roped in his friends for key positions in the company. He also started workshops for robotics education in colleges in order to sustain the company; he called this initiative BotLearn. In 2009, BotGo was incubated and Panchal started franchises for BotLearn as part of his growth plans. This led to a crisis within the company, escalating to a point where Panchal was forced to consider options. This case highlights the importance of a product-to-market fit and examines the decision to franchise in view of the case facts. The case also points towards the mistakes in crisis management, with particular emphasis on channel management. Towards the end of the case, Panchal is faced with a dilemma on whether to continue with the franchises or close them down. The dilemma is further accentuated since Panchal's decision would ultimately affect the growth of BotGo as well as directly challenge his intention to franchise.

Marginal maximum likelihood estimation (MMLE) is commonly used for item response theory item parameter estimation. However, sufficiently large sample sizes are not always possible when studying rare populations. In this paper, empirical Bayes and hierarchical Bayes are presented as alternatives to MMLE in small sample sizes, using auxiliary item information to estimate the item parameters of a graded response model with higher accuracy. Empirical Bayes and hierarchical Bayes methods are compared with MMLE to determine under what conditions these Bayes methods can outperform MMLE, and to determine if hierarchical Bayes can act as an acceptable alternative to MMLE in conditions where MMLE is unable to converge. In addition, empirical Bayes and hierarchical Bayes methods are compared to show how hierarchical Bayes can result in estimates of posterior variance with greater accuracy than empirical Bayes by acknowledging the uncertainty of item parameter estimates. The proposed methods were evaluated via a simulation study. Simulation results showed that hierarchical Bayes methods can be acceptable alternatives to MMLE under various testing conditions, and we provide a guideline to indicate which methods would be recommended in different research situations. R functions are provided to implement these proposed methods.

25 Background: Nutritional and dietary supplements, complementary therapies (CT: acupuncture, yoga), and alternative medicine (AM: tinctures, holistic medicines) can have high out-of-pocket (OOP) costs, driving financial toxicity. We evaluated costs associated with the use of supplements, CT, and AM in patients with breast cancer. Methods: Between 6/7-7/12/2022, Breastcancer.org members completed an anonymous online survey assessing self-identified “unexpectedly high” OOP costs encountered during care. Adjusted multivariable analysis (MVA) evaluated patient characteristics associated with high costs due to supplements, CT, and AM. Results: Among 1,710 eligible patients, 1,437 completed the survey (84% participation rate). Median age was 45 years (IQR: 35-56), and most identified as women (94%) and non-Hispanic White (NHW, 61%). One-quarter (25%) reported high OOP costs from supplements. In MVA, those with an annual income ≥$200k (OR 0.85, 95%CI 0.78-0.93, p<0.01) were less likely than those with income <$50k to report supplements as a financial burden. Those with employer-provided insurance (OR 0.92, 95% CI 0.87-0.98, p=0.02) had lower burdens than those on Medicare. Those with higher educational attainment had higher burdens than those with high school (HS) education or less (some college/post HS (OR 1.08, 95% CI 1.01-1.17, p=0.03), college grad (OR 1.15, 95% CI 1.07-1.24, p<0.01), postgraduate (OR 1.13, 95% CI 1.04-1.24, p<0.01). High OOP costs related to CT were reported by 18% of respondents. In adjusted MVA, self-identified Asian (OR 1.24, 95% CI 1.08-1.44, p<0.01) patients and those with private insurance (OR 1.08, 95% CI 1.01-1.09, p=0.02) were less burdened by CT costs compared to NHW patients and those on Medicare. High OOP costs related to AM were reported by 18% of respondents. In MVA, patients ≥46 years (OR 0.94, 95% CI 0.90-0.99, P=0.02) and those with income ≥$200k (OR 0.91, 95% CI 0.84-0.98, p<0.01) were less burdened by AM costs [compared to those ≤45 and with income <$50k]. Those on Medicaid (OR 1.11, 95% CI 1.04-1.18, p<0.01) had higher burdens than those on Medicare. Those who reported high OOP costs from AM were more likely to alter their use of prescribed medication (i.e., skip pills, not fill prescriptions, etc) to cut costs compared to those who did not report this burden (73% vs. 48%, p<0.01). Those who reported high costs from supplements were more likely to take fewer pills as a cost-cutting measure (28% vs 19%, p<0.01). Conclusions: High costs from supplements, CT, and AM pose a financial burden for up to a quarter of patients with breast cancer, and these burdens may not affect everyone equally. Downstream effects of financial toxicity from tinctures and holistic medicines specifically may decrease adherence to prescribed medications. Discussion regarding the risks, benefits, and costs of supplements, CT, and AM is an essential part of patient-centered cancer education.

South Africa has among the highest rates of intimate partner violence (IPV) globally, with young women at heightened risk due to inequitable gender roles, limited relationship skills, and inadequate social support. Despite an urgent need for violence prevention in low- and middle-income settings, most efficacious approaches are time-intensive and costly to deliver. Digital, interactive chatbots may help young women navigate safer relationships and develop healthier gender beliefs and skills. Young women (18-24 years old) across South Africa were recruited via Facebook for participation in an individually randomised controlled trial (n = 19,643) during the period of June 2021-September 2021. Users were randomly allocated, using a pipeline algorithm, to one of four trial arms: Pure Control (PC) had no user engagement outside of study measures; Attention Treatment (T0) provided didactic information about sexual health through a text-based chatbot; Gamified Treatment (T1) was a behaviourally-informed gamified text-based chatbot; Narrative Treatment (T2) was a behaviourally-informed drama delivered through pre-recorded voice notes. All chatbots were delivered in WhatsApp, through which users were invited to complete brief "quizzes" comprising adapted versions of validated scales. Primary outcomes were short-form adaptations of scales for gender attitudes (Gender Relations Scale) and past-month IPV (WHO Multi-country Study Instrument). Secondary outcomes were identification of unhealthy relationship behaviours (Intimate Partner Violence Attitudes Scale) and brief screener for depressive symptoms (Patient Health Questionnaire). A direct chat link to a trained counsellor was a safety measure (accessed by 4.5% of the sample). We estimated treatment effects using ordinary least squares and heteroskedasticity robust standard errors. The trial retained 11,630 (59.2%) to the primary endpoint of gender attitudes. Compared to control, all treatments led to moderate and significant changes in attitudes towards greater gender equity (Cohen's D = 0.10, 0.29, 0.20 for T0, T1, and T2, respectively). The gamified chatbot (T1) had modest but significant effects on IPV: 56% of young women reported past-month IPV, compared to 62% among those without treatment (marginal effects = -0.07, 95%CI = -0.09to-0.05). The narrative treatment (T2) had no effect on IPV exposure. T1 increased identification of unhealthy relationship behaviours at a moderate and significant level (Cohen's D = 0.25). Neither T1 nor T2 had a measurable effect on depressive symptoms as measured by the brief screener. Interpretation: A behaviourally-informed, gamified chatbot increased gender equitable attitudes and was protective for IPV exposure among young women in South Africa. These effects, while modest in magnitude, could represent a meaningful impact given potential to scale the low-cost intervention.

ABSTRACT Background West Virginia (WV) has been cited as the epicenter of the opioid epidemic. Misinformation has exacerbated stigmatizing behaviors among community members in WV. To evaluate the impact of an initiative addressing substance use disorder (SUD) stigma, a WV-based media campaign and associated study were conducted to analyze the use of media and marketing tools to improve public perception of SUD. Methods This study incorporated a quasi-experimental pretest-posttest design. Baseline measures of stigma toward SUDs were assessed via a pretest survey in August 2019. A community-wide media and marketing campaign was released September 2019. Participants were reevaluated to assess attitude change after exposure to the campaign. Results The e-mail marketing strategy was the most successful component of the campaign. The majority of survey participants found stigmatizing behavior to be a serious problem. Statistically significant results (p < .05) were noted among specific pre- and post-survey elements including hope for recovery, trust, openness toward drug therapies, and fixation on drug seeking behavior. Conclusions A generalized approach to reduce stigmatizing attitudes toward individuals with SUD was not statistically significant; however, results from this research lay the groundwork for future studies to employ targeted approaches to reduce stigmatizing attitudes and bias toward individuals with SUD.

To demonstrate the value of integrating surgical resident Entrustable Professional Activity (EPA) data into a learning analytics platform that provides meaningful feedback for formative and summative decision-making. Description of the Surgical Entrustable Professional Activities (SEPA) analytics dashboard, and examples of summary analytics and intuitive display features. Department of Surgery, University of Wisconsin Hospital and Clinics. Surgery residents, faculty, and residency program administrators. We outline the major functionalities of the SEPA dashboard and offer concrete examples of how these features are utilized by various stakeholders to support progressive entrustment decisions for surgical residents. Our intuitive analytics platform allows for seamless integration of SEPA microassessment data to support Clinical Competency Committee (CCC) decisions for resident evaluation and provides point of training feedback to faculty and trainees in support of progressive autonomy.

Background: While randomized controlled trials (RCTs) are typically considered the gold standard of program evaluation, they are infrequently chosen by public sector leaders, defined as government and nonprofit decision-makers, when an impact evaluation is required. Objectives: This study provides descriptive evidence on RCT aversion among public sector leaders and attempts to understand what factors affect their likelihood of choosing RCTs for impact evaluations. Research Design: The authors ask if public sector leaders follow similar preference patterns found among non-public sector leaders when choosing either an RCT or a quasi-experimental design and use a survey experiment to determine which factors affect the RCT choice. Subjects: The study sample includes 2050 public sector leaders and a comparison group of 2060 respondents who do not lead public sector organizations. Measures: The primary outcome measure is selecting an RCT as the preferred evaluation option. Results: When asked to make a decision about an impact evaluation, the majority of people do not choose an RCT. While also averse to RCTs, public sector leaders are about 13% more likely to prefer a RCT to a quasi-experimental evaluation compared to the general population. Public sector leaders are less likely to use RCTs for evaluations of more intense interventions, potentially because they are perceived to be superior to the options available for the control group. Conclusion: Funders should be aware that when given a choice, public sector leaders prefer other options to RCTs. Greater awareness of the benefits of RCTs could increase their use in the public sector.