Automated Analysis of Preceptor Comments: A Pilot Study Using Sentiment Analysis to Identify Potential Student Issues in Experiential Education.

OBJECTIVE: The purpose of this paper is to describe a sentiment analysis program that aids in identifying pharmacy students at risk for progression issues by automatically scoring preceptor comments as positive or negative. METHODS: An R-based program to analyze advanced pharmacy practice experiences and introductory pharmacy practice experiences midpoint evaluation of preceptor comments was piloted in phase 1 by comparing the sentiment analysis algorithm results to human coding. The algorithm was refined in phase 2. In phase 3, the validation phase, the final sentiment analysis algorithm analyzed all midpoint student evaluations (n = 1560). Sentiment scores were generated for each preceptor comment, and correlations were performed between sentiment scores and the quantitative scoring provided on the assessment. RESULTS: In phase 1, agreement between faculty coders and sentiment analysis was 96%, and in phase 2, agreement between the final codes and sentiment analysis was 92.4% once keywords were added to the sentiment dictionary. In phase 3, a total of 3919 comments from 1560 evaluations were analyzed, and overall, the sentiment analysis results aligned with the quantitative data. CONCLUSION: This sentiment analysis algorithm was accurate in capturing positive and negative comments corresponding to pharmacy student performance. Given the accuracy of this preliminary validation for flagging preceptor comments, there are numerous implications when considering the use of sentiment analysis in pharmacy education. Using a sentiment analysis program minimizes the number of qualitative preceptor comments needing review by experiential faculty, as this program can aid in identifying students at risk of progression issues.

Consistency between Household and County Measures of Onsite Schooling during the COVID-19 Pandemic.

The academic, socioemotional, and health impacts of school policies throughout the COVID-19 pandemic have been a source of many questions that require accurate information about the extent of onsite schooling occurring. This article investigates school operational status datasets during the pandemic, comparing (1) self-report data collected nationally on the household level through a Facebook-based survey, (2) county-level school policy data, and (3) a school-level closure status dataset based on phone GPS tracking. The percentage of any onsite instruction within states and counties are compared across datasets from December 2020 to May 2021. Sources were relatively consistent at the state level and for large counties, but key differences were revealed between units of measurement, showing differences between policy and household decisions surrounding children's schooling experiences. The consistency levels across sources support the usage of each of the school policy sources to answer questions about the educational experiences, factors, and impacts related to K-12 education across the nation during the pandemic, but it remains vital to think critically as to which unit of measurement is most relevant to targeted research questions.

An introduction to text analytics for educators.

OUR SITUATION: Educators often find themselves in possession of large amounts of text-based materials, such as student reflections, narrative feedback, and assignments. While these materials can provide critical insight into topics of interest, they also require a substantial amount of time to read, interpret, and use. The purpose of this article is to describe and provide recommendations for text analytics. METHODOLOGICAL LITERATURE REVIEW: An overview of text analytics is provided, including a brief history, common types of contemporary techniques, and the basic phases of text analytics. Several examples of common text analytics techniques are used to illustrate this approach. OUR RECOMMENDATIONS AND THEIR APPLICATIONS: Practical recommendations are provided to support the use of text analytics in pharmacy education. These recommendations include: (1) clarify the purpose of the text analytics; (2) ensure the research questions are relevant and grounded in the literature; (3) develop a processing strategy and create a dictionary; (4) explore various tools for analysis and visualization; (5) establish tolerance for error; (6) train, calibrate, and validate the analytic strategy; and (7) collaborate and equip yourself. POTENTIAL IMPACT: Text analytics provide a systematic approach to generating information from text-based materials. Several benefits to this approach are apparent, such as improving the efficiency of analyzing text and elucidating new knowledge. Despite recent developments in text analytics techniques, limitations to this approach remain. Efforts to improve usability and accessibility of text analytics remain ongoing, and pharmacy educators should position their work within the context of these limitations.

Association of Non-Pharmaceutical Interventions to Reduce the Spread of SARS-CoV-2 With Anxiety and Depressive Symptoms: A Multi-National Study of 43 Countries.

Objectives: To examine the association of non-pharmaceutical interventions (NPIs) with anxiety and depressive symptoms among adults and determine if these associations varied by gender and age. Methods: We combined survey data from 16,177,184 adults from 43 countries who participated in the daily COVID-19 Trends and Impact Survey via Facebook with time-varying NPI data from the Oxford COVID-19 Government Response Tracker between 24 April 2020 and 20 December 2020. Using logistic regression models, we examined the association of [1] overall NPI stringency and [2] seven individual NPIs (school closures, workplace closures, cancellation of public events, restrictions on the size of gatherings, stay-at-home requirements, restrictions on internal movement, and international travel controls) with anxiety and depressive symptoms. Results: More stringent implementation of NPIs was associated with a higher odds of anxiety and depressive symptoms, albeit with very small effect sizes. Individual NPIs had heterogeneous associations with anxiety and depressive symptoms by gender and age. Conclusion: Governments worldwide should be prepared to address the possible mental health consequences of stringent NPI implementation with both universal and targeted interventions for vulnerable groups.

Factors associated with county-level mental health during the COVID-19 pandemic.

The objective of this study is to determine county-level factors associated with anxiety, depression, and isolation during the coronavirus disease 2019 (COVID-19) pandemic. This study used daily data from 23,592,355 respondents of a nationwide Facebook-based survey from April 2020 to July 2021, aggregated to the week-county level to yield 212,581 observations. Mental distress prevalences were modeled using weighted linear mixed-effects models with a county random effect. These models revealed that weekly percentages of mental distress were higher in counties with higher unemployment rates, populations, and education levels; higher percentages of females, young adults, individuals with a medical condition, and individuals very worried about their finances and COVID-19; and lower percentages of individuals who were working outside the home, living with children, without health insurance, and Black. Anxiety peaked in April 2020, depression in October 2020, and isolation in December 2020. Therefore, United States counties experienced the mental health effects of the pandemic differently dependent upon their characteristics, and mental distress prevalence varied across time.

Characterizing Research About Interprofessional Education Within Pharmacy.

Objective. To determine how interprofessional education (IPE) in pharmacy has been studied, namely which disciplines have engaged in IPE research initiatives, the research methodologies that have been used, and what journals have published in this area.Findings. In the 145 IPE studies included in the review, the authors represented 13 different disciplines (3.2±1.5 disciplines per study). Pharmacy authors most commonly published with co-authors from nursing, medicine, and health management and support and most frequently served as first author or last author. The IPE activities involved 4.0 student disciplines (SD = 1.9) and 211.8 students (SD = 280.1), and most commonly included nursing (n = 104, 71.7%), medicine (n = 102, 70.3%), and health management and support students (n = 50, 34.5%). Most studies did not include an author from each student discipline involved in the IPE (n = 88, 60.7%). Further, a majority of studies used nonrandomized groupings (n = 103, 71.0%) with quantitative data (n = 74, 51.0%) and most were published in an interprofessional journal (n = 65, 44.8%) or pharmacy-specific journal (n = 45, 31.0%).Summary. Pharmacists have increased their engagement in IPE research as demonstrated by the number of articles published and authorship order position. However, mismatches between student disciplines and author disciplines on published papers elucidate opportunities to foster collaborations that position students for success within a collaborative healthcare environment.

Household COVID-19 risk and in-person schooling.

In-person schooling has proved contentious and difficult to study throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Data from a massive online survey in the United States indicate an increased risk of COVID-19-related outcomes among respondents living with a child attending school in person. School-based mitigation measures are associated with significant reductions in risk, particularly daily symptoms screens, teacher masking, and closure of extracurricular activities. A positive association between in-person schooling and COVID-19 outcomes persists at low levels of mitigation, but when seven or more mitigation measures are reported, a significant relationship is no longer observed. Among teachers, working outside the home was associated with an increase in COVID-19-related outcomes, but this association is similar to that observed in other occupations (e.g., health care or office work). Although in-person schooling is associated with household COVID-19 risk, this risk can likely be controlled with properly implemented school-based mitigation measures.

Determining Predictors of Weight Loss in a Behavioral Intervention: A Case Study in the Use of Lasso Regression.

OBJECTIVE: This study investigates predictors of weight loss among individuals with serious mental illness participating in an 18-month behavioral weight loss intervention, using Lasso regression to select the most powerful predictors. METHODS: Data were analyzed from the intervention group of the ACHIEVE trial, an 18-month behavioral weight loss intervention in adults with serious mental illness. Lasso regression was employed to identify predictors of at least five-pound weight loss across the intervention time span. Once predictors were identified, classification trees were created to show examples of how to classify participants into having likely outcomes based on characteristics at baseline and during the intervention. RESULTS: The analyzed sample contained 137 participants. Seventy-one (51.8%) individuals had a net weight loss of at least five pounds from baseline to 18 months. The Lasso regression selected weight loss from baseline to 6 months as a primary predictor of at least five pound 18-month weight loss, with a standardized coefficient of 0.51 (95% CI: -0.37, 1.40). Three other variables were also selected in the regression but added minimal predictive ability. CONCLUSIONS: The analyses in this paper demonstrate the importance of tracking weight loss incrementally during an intervention as an indicator for overall weight loss, as well as the challenges in predicting long-term weight loss with other variables commonly available in clinical trials. The methods used in this paper also exemplify how to effectively analyze a clinical trial dataset containing many variables and identify factors related to desired outcomes.

A Five-Minute Situational Judgment Test to Assess Empathy in First-Year Student Pharmacists.

Objective. To design, implement, and evaluate the utility of a situational judgment test (SJT) to assess empathy in first-year student pharmacists as part of an end-of-year capstone experience. Methods. First-year students completed a five-minute SJT in lieu of a multiple mini interview (MMI) during the end-of-year capstone. For each SJT item, students selected the two most appropriate response options from a list of five. Various strategies to score the SJT were compared to evaluate the psychometric properties of the test. Student performance on the SJT was examined in relationship to performance on other measures, (eg, MMI stations, personality assessments, and admissions data). Results. A total of 135 first-year pharmacy students completed an average of 9.5 items. Scoring keys based on subject matter experts' and student responses demonstrated high reliability. There was a positive, weak relationship between student performance on the SJT and performance on the adaptability station used in the capstone, and an inverse, weak relationship with students' agreeableness scores. Conclusion. This study suggests that the SJT may be a feasible and efficient assessment strategy in pharmacy education. Additional research is needed to inform SJT design, implementation, and interpretation.