Background: The success of flipped classrooms is dependent upon students’ preparation prior to class, the lack of which is the most common challenge associated with this teaching methodology. To mitigate this limitation, it is important to develop and assess methods of engaging learners during pre-class activities. Objective: To determine if quiz delivery method (embedded throughout versus after pre-class videos) affects students’ knowledge retention, grades, and video viewing behavior. Methods: Participating students were randomized to take quizzes, either during pre-class videos via Panopto™ (EQV) or after pre-class videos in the traditional manner via Moodle™ (TMM). Outcomes assessed included students’ knowledge retention, scores on pre- and post-class quizzes, and pre-class video viewing behavior (total views and minutes viewed per student) during a three-week period. Having experienced both quizzing modalities during the semester, the perceptions from students in the EQV group were surveyed. Results: Baseline assessment results of both groups (n = 27 per group) were comparable with a median score of 33% (IQR: 17, 50) in both groups. Performance was also similar on knowledge retention [TMM: 67% (50, 83) vs. EQV: 83% (50, 83)], pre-class quiz scores [TMM: 90% (87, 97) vs. EQV: 93% (90, 95)], and post-class quiz scores [TMM: 93% (80, 100) vs. EQV: 87% (80, 100)], while students in the EQV group had more total views [10 (8, 12)] vs. [5 (2, 11)] and minutes viewed [71 (36, 108) vs. 35 (15, 81)]. Results from the perception survey administered to students in the EQV group (74.1% response rate) indicated a preference for embedded quizzes overall (58%) and for class preparation (75%) when compared with post-video quizzes. Conclusion: Students’ knowledge retention and performance were similar in both EQV and TMM groups, though students in the EQV group were more engaged with videos and most of them preferred this quiz delivery. Using embedded quizzes for formative rather than summative assessment might be an appropriate mechanism to encourage students’ viewing of pre-class videos and their preparation for flipped classes.

Background: Depression is common among adults who smoke cigarettes. Existing depression-specific cessation interventions have limited reach and are unlikely to improve smoking prevalence rates among this large subgroup of smokers. Objective: This study aimed to determine whether a mobile app–based intervention tailored for depression paired with a mailed sample of nicotine replacement therapy (NRT) is efficacious for treating depression and promoting smoking cessation. Methods: A 2-arm nationwide remote randomized clinical trial was conducted in the United States. Adults (N=150) with elevated depressive symptoms (Patient Health Questionnaire-8≥10) who smoked were enrolled. The mobile app (“Goal2Quit”) provided behavioral strategies for treating depression and quitting smoking based on Behavioral Activation Treatment for Depression. Goal2Quit participants also received a 2-week sample of combination NRT. Treatment as usual participants received a self-help booklet for quitting smoking that was not tailored for depression. Primary end points included Goal2Quit usability, change in depression (Beck Depression Inventory-II) across 12 weeks, and smoking cessation including reduction in cigarettes per day, incidence of 24-hour quit attempts, floating abstinence, and 7-day point prevalence abstinence (PPA). Results: In total, 150 participants were enrolled between June 25, 2020, and February 23, 2022, of which 80 were female (53.3%) and the mean age was 38.4 (SD 10.3) years. At baseline, participants on average reported moderate depressive symptoms and smoked a mean of 14.7 (SD 7.5) cigarettes per day. Goal2Quit usability was strong with a mean usability rating on the System Usability Scale of 78.5 (SD 16.9), with 70% scoring above the ≥68 cutoff for above-average usability. Retention data for app use were generally strong immediately following trial enrollment and declined in subsequent weeks. Those who received Goal2Quit and the NRT sample reported lower mean depressive symptoms over the trial duration as compared to treatment as usual (difference of mean 3.72, SE 1.37 points less; P=.01). Across time points, all cessation outcomes favored Goal2Quit. Regarding abstinence, Goal2Quit participants reported significantly higher rates of 7-day PPA at weeks 4 (11% vs 0%; P=.02), 8 (7-day PPA: 12% vs 0%; P=.02), and 12 (16% vs 2%; P=.02). Conclusions: A mobile app intervention tailored for depression paired with a sample of NRT was effective for depression treatment and smoking cessation. Findings support the utility of this intervention approach for addressing the currently unmet public health treatment need for tailored, scalable depression-specific cessation treatments. Trial Registration: ClinicalTrials.gov NCT03837379; https://clinicaltrials.gov/ct2/show/NCT03837379

Background: Communities with robust recovery ecosystems could reduce negative outcomes associated with substance use disorders (SUDs) and facilitate the recovery process. This cross-sectional study examined the relationship between drug overdose mortality rates in the United States and the strength of county-level recovery ecosystems, as measured by the Recovery Ecosystem Index (REI). Methods: The REI assesses the strength of county-level recovery ecosystems in the United States. Comprised of 14 indicators across 3 component classes, overall and component scores ranging from “one” (strongest) to “five” (weakest) were calculated for each county using standardized values of the indicators. County-level analyses included: (1) correlational analyses between drug overdose mortality rates (n = 2076) and REI scores (overall score and by component); and (2) quadrant analysis (n = 2076), dividing counties based on their drug overdose mortality rates and overall REI scores. Results: Drug overdose mortality rates were inversely related to REI overall, SUD treatment component, and continuum of SUD support component scores, indicating that lower (stronger) scores corresponded to higher rates. Conversely, REI infrastructure and social component scores were positively related to rates. Counties were relatively evenly distributed across quadrants, with 26% (n = 537) with a strong REI score and high overdose mortality rate, 24% (n = 489) with a strong REI score and low overdose mortality rate, 20% (n = 409) with a weak REI and high overdose mortality rate, and 31% (n = 641) with a weak REI and low overdose mortality rate. Conclusions: REI scores were generally inversely associated with drug overdose mortality rates in US counties, suggesting that communities have stronger recovery systems and services as the burden of SUD increases. Given relative variation in the scale of drug overdose mortality and strength of recovery ecosystems among counties, results could guide the identification of communities where the need for expanded recovery systems and services may be particularly critical.

Objective: This feasibility, proof-of-concept study aimed to assess the impact of maternal pre-pregnancy body mass index (BMI) on preterm infant fecal fermentation and microbiome. Study Design: An infant cohort study (n = 54) in the NICU at MUSC from June 2021 to September 2022 was grouped according to maternal pre-pregnancy BMI—normal weight (<25 kg/m²), overweight (25–29.9 kg/m²), and obese (≥30 kg/m²). All fecal samples were subjected to 16s rRNA isolation and analysis, as well as short chain fatty acid (SCFA) extraction and analysis. Results: Preterm infants born to overweight and obese mothers did not have differences in microbial diversities but did have different bacterial taxonomic composition and lower relative abundance levels of taxa than those born to normal-weight mothers. While controlling for covariates, we found SCFA propionic acid to be higher and more significant in infant stools born to mothers with a higher pre-pregnancy BMI. Conclusions: This is a novel study investigating the microbiome and SCFA in premature infants while considering maternal pre-pregnancy BMI. This study adds to the current literature, in that the preterm infant gut is generally lower in microbial diversity which can impact infant health. Thus, it is important to understand the mechanisms necessary to modulate the microbiome of preterm infants to improve their health outcomes.

As statisticians develop new methodological approaches, there are many factors that influence whether others will utilize their work. This paper is a bibliometric study that identifies and quantifies associations between characteristics of new biostatistics methods and their citation counts. Of primary interest was the association between numbers of citations and whether software code was available to the reader. Statistics journal articles published in 2010 from 35 statistical journals were reviewed by two biostatisticians. Generalized linear mixed models were used to determine which characteristics (author, article, and journal) were independently associated with citation counts (as of April 1, 2017) in other peer-reviewed articles. Of 722 articles reviewed, 428 were classified as new biostatistics methods. In a multivariable model, for articles that were not freely accessible on the journal’s website, having code available appeared to offer no boost to the number of citations (adjusted rate ratio = 0.96, 95% CI = 0.74 to 1.24, p = 0.74); however, for articles that were freely accessible on the journal’s website, having code available was associated with a 2-fold increase in the number of citations (adjusted rate ratio = 2.01, 95% CI = 1.30 to 3.10, p = 0.002). Higher citation rates were also associated with higher numbers of references, longer articles, SCImago Journal Rank indicator (SJR), and total numbers of publications among authors, with the strongest impact on citation rates coming from SJR (rate ratio = 1.21 for a 1-unit increase in SJR; 95% CI = 1.11 to 1.32). These analyses shed new insight into factors associated with citation rates of articles on new biostatistical methods. Making computer code available to readers is a goal worth striving for that may enhance biostatistics knowledge translation.

Purpose: The purpose of this study is to examine the relationship between telehealth use, telehealth satisfaction, and chronic medical conditions among residents living in Appalachian and non-Appalachian communities. Sample: A COVID-19 public health survey was distributed via social media and healthcare clinics in the tri-state region of central Appalachia. Survey responses were limited to adults aged ≥18 years who consented to participate in the survey that self-identified as an individual with one or more chronic medical conditions (n=195). Method: Simple descriptive statistics including frequencies, percentages, means, and standard deviations (SDs) were calculated for variables of interest both overall and by subgroups of interest. Chi-squared tests were used to compare categorical outcomes between groups of interest, while two-sample t-tests were used for continuous outcomes. Significance for all tests was determined using an α level of 0.05. Findings: There is no statistically significant relationship between respondents with regard to using telehealth services, satisfaction rates related to telehealth use, or reasons for electing not to use telehealth services during the COVID-19 pandemic. However, there was a trending statistical relationship between county status and the use of telehealth services in Appalachia with those counties doing economically better being more likely to use telehealth services as compared to those fairing less well (p=0.053). Findings also suggest that people living in urban areas of Appalachia were more likely to be satisfied using telehealth services than those living in non-urban areas of Appalachia (p=0.01). Conclusions: Research is still limited as to how the expansion of broadband capabilities during the COVID-19 pandemic has benefited those residing in Appalachia in terms of managing chronic health conditions. Future research should focus on expanding participation among Appalachian respondents looking for specific differences related to location within Appalachia, age, gender, ethnicity, and socioeconomic status. Keywords: Telehealth, Satisfaction, Rural, Appalachian, COVID-19
DOI: https://doi.org/10.14574/ojrnhc.v22i2.715