Performance of and Severe Acute Respiratory Syndrome Coronavirus 2 Diagnostics Based on Symptom Onset and Close Contact Exposure: An Analysis From the Test Us at Home Prospective Cohort Study.

Background: Understanding changes in diagnostic performance after symptom onset and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure within different populations is crucial to guide the use of diagnostics for SARS-CoV-2. Methods: The Test Us at Home study was a longitudinal cohort study that enrolled individuals across the United States between October 2021 and February 2022. Participants performed paired antigen-detection rapid diagnostic tests (Ag-RDTs) and reverse-transcriptase polymerase chain reaction (RT-PCR) tests at home every 48 hours for 15 days and self-reported symptoms and known coronavirus disease 2019 exposures immediately before testing. The percent positivity for Ag-RDTs and RT-PCR tests was calculated each day after symptom onset and exposure and stratified by vaccination status, variant, age category, and sex. Results: The highest percent positivity occurred 2 days after symptom onset (RT-PCR, 91.2%; Ag-RDT, 71.1%) and 6 days after exposure (RT-PCR, 91.8%; Ag-RDT, 86.2%). RT-PCR and Ag-RDT performance did not differ by vaccination status, variant, age category, or sex. The percent positivity for Ag-RDTs was lower among exposed, asymptomatic than among symptomatic individuals (37.5% (95% confidence interval [CI], 13.7%-69.4%) vs 90.3% (75.1%-96.7%). Cumulatively, Ag-RDTs detected 84.9% (95% CI, 78.2%-89.8%) of infections within 4 days of symptom onset. For exposed participants, Ag-RDTs detected 94.0% (95% CI, 86.7%-97.4%) of RT-PCR-confirmed infections within 6 days of exposure. Conclusions: The percent positivity for Ag-RDTs and RT-PCR tests was highest 2 days after symptom onset and 6 days after exposure, and performance increased with serial testing. The percent positivity of Ag-RDTs was lowest among asymptomatic individuals but did not differ by sex, variant, vaccination status, or age category.

Global scientific trends in healthy aging in the early 21st century: A data-driven scientometric and visualized analysis.

Background: According to the World Health Organization (WHO), healthy aging is the process of developing and maintaining the functional capacity for health in old age. A rapidly growing number of research studies on healthy aging have been conducted worldwide. The purpose of this research work is to explore global scientific landscape of healthy aging research over the last 22 years. Methods: Scientific publications on healthy aging from January 1, 2000 to October 11, 2022 were retrieved from the Web of Science Core Collection (WoSCC) on October 11, 2022. A total of 6420 publications were included in the scientometric analysis. VOSviewer (1.6.18) was used to conduct scientometric and visualized analysis. Results: The publication growth rate was 35.68 from 2000 to 2021. The United States of America (USA) led in both productivity and citations. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA was prominent in terms of both the highest citation count and the highest average citation count. The National Institute on Aging (NIA) and Evans, Michele K. were the most influential organization and author, respectively. Research hotspots in healthy aging were identified based on the co-occurrence analysis of keywords: (1) physical activity and mental health of older adults; (2) diseases impacting the health and lifespan of older adults; and (3) neuroscience. Our analysis indicates that gut microbiota, loneliness, frailty, mitochondria and resilience were the emerging themes in healthy aging research. Conclusions: The quantity of annual publications on healthy aging has rapidly increased over the past 22 years, especially during 2018-2021. This analysis identified the status, trends, hot topics, and frontiers of healthy aging research. These findings will help researchers quickly understand the global representation of healthy aging research, influence resource dissemination, promote international collaborations, guide policy formulation, and improve health services for older adults.

Educating Family Physician Residents for Anesthetic Preoperative Evaluation and Assessment.

Introduction: Encounters for preoperative assessments are common within primary care offices, so it is imperative that family medicine residents learn how to perform preoperative evaluations. We assessed family medicine residents' knowledge of preoperative evaluation in preparation for surgery by providing a pre- and post-test alongside a didactic seminar. Methods: A didactic seminar on preoperative evaluations was presented at a family medicine resident didactics session by two senior anesthesiology residents. A 16-question, multiple choice test was used as both a pre-test and post-test to assess family medicine residents' knowledge. Results: A total of 31 participants took the pre-test (residents = 24; medical students = 7), and 30 participants took the post-test (residents = 23; medical students = 7). Mean scores and standard deviations were calculated for both tests with an average score of 37.50% ± 10.58% and 45.42% ± 11.12% on the pre- and post-test, respectively. Using the Kruskal-Wallis test, residents showed a significant improvement in test scores following the didactic presentation (p = 0.041), while overall results (residents and medical students) also reported a significant difference (p = 0.004). Conclusions: Our results demonstrated that educating family medicine residents and medical students on preoperative evaluation showed significant, quantifiable gains in knowledge following a brief didactic presentation. Given the current gap between guidelines and practice, our results emphasize the need for a formal medical school and residency-based curriculum related to preoperative patient evaluation.

Association of neighborhood-level sociodemographic factors with Direct-to-Consumer (DTC) distribution of COVID-19 rapid antigen tests in 5 US communities.

BACKGROUND: Many interventions for widescale distribution of rapid antigen tests for COVID-19 have utilized online, direct-to-consumer (DTC) ordering systems; however, little is known about the sociodemographic characteristics of home-test users. We aimed to characterize the patterns of online orders for rapid antigen tests and determine geospatial and temporal associations with neighborhood characteristics and community incidence of COVID-19, respectively. METHODS: This observational study analyzed online, DTC orders for rapid antigen test kits from beneficiaries of the Say Yes! Covid Test program from March to November 2021 in five communities: Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; and Ann Arbor/Ypsilanti, Michigan. Using spatial autoregressive models, we assessed the geospatial associations of test kit distribution with Census block-level education, income, age, population density, and racial distribution and Census tract-level Social Vulnerability Index. Lag association analyses were used to measure the association between online rapid antigen kit orders and community-level COVID-19 incidence. RESULTS: In total, 164,402 DTC test kits were ordered during the intervention. Distribution of tests at all sites were significantly geospatially clustered at the block-group level (Moran's I: p < 0.001); however, education, income, age, population density, race, and social vulnerability index were inconsistently associated with test orders across sites. In Michigan, Georgia, and Kentucky, there were strong associations between same-day COVID-19 incidence and test kit orders (Michigan: r = 0.89, Georgia: r = 0.85, Kentucky: r = 0.75). The incidence of COVID-19 during the current day and the previous 6-days increased current DTC orders by 9.0 (95% CI = 1.7, 16.3), 3.0 (95% CI = 1.3, 4.6), and 6.8 (95% CI = 3.4, 10.2) in Michigan, Georgia, and Kentucky, respectively. There was no same-day or 6-day lagged correlation between test kit orders and COVID-19 incidence in Indiana. CONCLUSIONS: Our findings suggest that online ordering is not associated with geospatial clustering based on sociodemographic characteristics. Observed temporal preferences for DTC ordering can guide public health messaging around DTC testing programs.

Mobile Health Intervention in Patients With Type 2 Diabetes: A Randomized Clinical Trial.

Importance: Clinical pharmacists and health coaches using mobile health (mHealth) tools, such as telehealth and text messaging, may improve blood glucose levels in African American and Latinx populations with type 2 diabetes. Objective: To determine whether clinical pharmacists and health coaches using mHealth tools can improve hemoglobin A1c (HbA1c) levels. Design, Setting, and Participants: This randomized clinical trial included 221 African American or Latinx patients with type 2 diabetes and elevated HbA1c (≥8%) from an academic medical center in Chicago. Adult patients aged 21 to 75 years were enrolled and randomized from March 23, 2017, through January 8, 2020. Patients randomized to the intervention group received mHealth diabetes support for 1 year followed by monitored usual diabetes care during a second year (follow-up duration, 24 months). Those randomized to the waiting list control group received usual diabetes care for 1 year followed by the mHealth diabetes intervention during a second year. Interventions: The mHealth diabetes intervention included remote support (eg, review of glucose levels and medication intensification) from clinical pharmacists via a video telehealth platform. Health coach activities (eg, addressing barriers to medication use and assisting pharmacists in medication reconciliation and telehealth) occurred in person at participant homes and via phone calls and text messaging. Usual diabetes care comprised routine health care from patients' primary care physicians, including medication reconciliation and adjustment. Main Outcomes and Measures: Outcomes included HbA1c (primary outcome), blood pressure, cholesterol, body mass index, health-related quality of life, diabetes distress, diabetes self-efficacy, depressive symptoms, social support, medication-taking behavior, and diabetes self-care measured every 6 months. Results: Among the 221 participants (mean [SD] age, 55.2 [9.5] years; 154 women [69.7%], 148 African American adults [67.0%], and 73 Latinx adults [33.0%]), the baseline mean (SD) HbA1c level was 9.23% (1.53%). Over the initial 12 months, HbA1c improved by a mean of -0.79 percentage points in the intervention group compared with -0.24 percentage points in the waiting list control group (treatment effect, -0.62; 95% CI, -1.04 to -0.19; P = .005). Over the subsequent 12 months, a significant change in HbA1c was observed in the waiting list control group after they received the same intervention (mean change, -0.57 percentage points; P = .002), while the intervention group maintained benefit (mean change, 0.17 percentage points; P = .35). No between-group differences were found in adjusted models for secondary outcomes. Conclusions and Relevance: In this randomized clinical trial, HbA1c levels improved among African American and Latinx adults with type 2 diabetes. These findings suggest that a clinical pharmacist and health coach-delivered mobile health intervention can improve blood glucose levels in African American and Latinx populations and may help reduce racial and ethnic disparities. Trial Registration: ClinicalTrials.gov Identifier: NCT02990299.

Mediating Effects of Neural Targets on Depression, Weight, and Anxiety Outcomes of an Integrated Collaborative Care Intervention: The ENGAGE-2 Mechanistic Pilot Randomized Clinical Trial.

Background: Integrated treatments for comorbid depression (often with anxiety) and obesity are lacking; mechanisms are poorly investigated. Methods: In a mechanistic pilot trial, adults with body mass index ≥30 and Patient Health Questionnaire-9 scores ≥10 were randomized to usual care (n = 35) or an integrated behavioral intervention (n = 71). Changes at 6 months in body mass index and Depression Symptom Checklist-20 scores were co-primary outcomes, and Generalized Anxiety Disorder Scale-7 score was a secondary outcome. Changes at 2 months in the activation and functional connectivity of regions of interest in the negative affect circuit were primary neural targets, and secondary targets were in the cognitive control, default mode, and positive affect circuits. Results: Participants were 47.0 years (SD = 11.9 years), 76% women, 55% Black, and 20% Latino. Depression Symptom Checklist-20 (between-group difference, -0.3 [95% CI: -0.6 to -0.1]) and Generalized Anxiety Disorder Scale-7 (-2.9 [-4.7 to -1.1]) scores, but not body mass index, decreased significantly at 6 months in the intervention versus usual care groups. Only Generalized Anxiety Disorder Scale-7 score changes at 6 months significantly correlated with neural target changes at 2 months in the negative affect (anterior insula, subgenual/pregenual anterior cingulate cortex, amygdala) and cognitive control circuits (dorsal lateral prefrontal cortex, dorsal anterior cingulate cortex). Effects were medium to large (0.41-1.18 SDs). Neural target changes at 2 months in the cognitive control circuit only differed by treatment group. Effects were medium (0.58-0.79 SDs). Conclusions: Compared with usual care, the study intervention led to significantly improved depression but not weight loss, and the results on neural targets were null for both outcomes. The significant intervention effect on anxiety might be mediated through changes in the cognitive control circuit, but this warrants replication.

The association between rest-activity parameters and hemoglobin A1c in patients with prediabetes.

Circadian abnormalities can adversely affect glucose metabolism. This study determined whether behavioral circadian parameters, as assessed by rest-activity rhythm, were predictors of glycemic control in patients with prediabetes. Seventy-nine patients with prediabetes participated. Nonparametric rest-activity rhythm parameters, sleep duration and efficiency were obtained from 7-d actigraphy recordings. Sleep-disordered breathing severity was assessed using a home sleep apnea test. Hemoglobin A1c (HbA1c) was obtained to evaluate glycemic control. The results revealed that shorter sleep duration, lower relative amplitude and higher L5 (average activity of the least active 5-h period) were associated with higher HbA1c, while other sleep variables were not related to HbA1c. Multiple stepwise regression analysis adjusting for age, sex, body mass index and sleep duration revealed that lower relative amplitude, but not L5, was independently associated with higher HbA1c (B = -0.027, p = 0.031). In summary, among patients with prediabetes, an abnormal circadian rhythm was associated with higher HbA1c, implying a greater risk of developing diabetes. These results support the role of circadian rhythmicity in glucose control among those with prediabetes.

Effects of a virtual voice-based coach delivering problem-solving treatment on emotional distress and brain function: a pilot RCT in depression and anxiety.

Consumer-based voice assistants have the ability to deliver evidence-based treatment, but their therapeutic potential is largely unknown. In a pilot trial of a virtual voice-based coach, Lumen, delivering problem-solving treatment, adults with mild-to-moderate depression and/or anxiety were randomized to the Lumen intervention (n = 42) or waitlist control (n = 21). The main outcomes included changes in neural measures of emotional reactivity and cognitive control, and Hospital Anxiety and Depression Scale [HADS] symptom scores over 16 weeks. Participants were 37.8 years (SD = 12.4), 68% women, 25% Black, 24% Latino, and 11% Asian. Activation of the right dlPFC (neural region of interest in cognitive control) decreased in the intervention group but increased in the control group, with an effect size meeting the prespecified threshold for a meaningful effect (Cohen's d = 0.3). Between-group differences in the change in activation of the left dlPFC and bilateral amygdala were observed, but were of smaller magnitude (d = 0.2). Change in right dlPFC activation was also meaningfully associated (r ≥ 0.4) with changes in self-reported problem-solving ability and avoidance in the intervention. Lumen intervention also led to decreased HADS depression, anxiety, and overall psychological distress scores, with medium effect sizes (Cohen's d = 0.49, 0.51, and 0.55, respectively), compared with the waitlist control group. This pilot trial showed promising effects of a novel digital mental health intervention on cognitive control using neuroimaging and depression and anxiety symptoms, providing foundational evidence for a future confirmatory study.

Performance of Rapid Antigen Tests Based on Symptom Onset and Close Contact Exposure: A secondary analysis from the Test Us At Home prospective cohort study.

Background: The performance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) in temporal relation to symptom onset or exposure is unknown, as is the impact of vaccination on this relationship. Objective: To evaluate the performance of Ag-RDT compared with RT-PCR based on day after symptom onset or exposure in order to decide on 'when to test'. Design Setting and Participants: The Test Us at Home study was a longitudinal cohort study that enrolled participants over 2 years old across the United States between October 18, 2021 and February 4, 2022. All participants were asked to conduct Ag-RDT and RT-PCR testing every 48 hours over a 15-day period. Participants with one or more symptoms during the study period were included in the Day Post Symptom Onset (DPSO) analyses, while those who reported a COVID-19 exposure were included in the Day Post Exposure (DPE) analysis. Exposure: Participants were asked to self-report any symptoms or known exposures to SARS-CoV-2 every 48-hours, immediately prior to conducting Ag-RDT and RT-PCR testing. The first day a participant reported one or more symptoms was termed DPSO 0, and the day of exposure was DPE 0. Vaccination status was self-reported. Main Outcome and Measures: Results of Ag-RDT were self-reported (positive, negative, or invalid) and RT-PCR results were analyzed by a central laboratory. Percent positivity of SARS-CoV-2 and sensitivity of Ag-RDT and RT-PCR by DPSO and DPE were stratified by vaccination status and calculated with 95% confidence intervals. Results: A total of 7,361 participants enrolled in the study. Among them, 2,086 (28.3%) and 546 (7.4%) participants were eligible for the DPSO and DPE analyses, respectively. Unvaccinated participants were nearly twice as likely to test positive for SARS-CoV-2 than vaccinated participants in event of symptoms (PCR+: 27.6% vs 10.1%) or exposure (PCR+: 43.8% vs. 22.2%). The highest proportion of vaccinated and unvaccinated individuals tested positive on DPSO 2 and DPE 5-8. Performance of RT-PCR and Ag-RDT did not differ by vaccination status. Ag-RDT detected 78.0% (95% Confidence Interval: 72.56-82.61) of PCR-confirmed infections by DPSO 4. For exposed participants, Ag-RDT detected 84.9% (95% CI: 75.0-91.4) of PCR-confirmed infections by day five post-exposure (DPE 5). Conclusions and Relevance: Performance of Ag-RDT and RT-PCR was highest on DPSO 0-2 and DPE 5 and did not differ by vaccination status. These data suggests that serial testing remains integral to enhancing the performance of Ag-RDT.

Association between sleep hygiene practices scale and sleep quality in Black and Latinx patients with uncontrolled type 2 diabetes.

Objective: We explored the relationship between the Sleep Hygiene Practices Scale (SHPS) and sleep quality and sleep-related impairment in Black and Latinx adults with type 2 diabetes (T2DM). Methods: Forty Black and Latinx adults with T2DM participated. Self-reported measures include the Pittsburg Sleep Quality Index (PSQI), Patient Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance (SD) and Sleep-Related Impairment (SRI) measures, and SHPS (domains include sleep schedule and timing, arousal-related behaviors, poor eating/drinking habits prior to sleep, and poor sleep environment). Results: SHPS Cronbach's alpha coefficients were 0.58 (schedule), 0.78 (arousal), 0.29 (eating), 0.81 (environment) and 0.88 (overall for four domains). SHPS scores correlated with PSQI (Pearson correlation r = 0.67, 95% CI [0.44, 0.81], PROMIS-SD (r = 0.61 [0.36-0.77]), and PROMIS-SRI (r = 0.43, [0.13-0.65]). There remained a significant relationship between sleep hygiene and both sleep quality and sleep-related impairment adjusting for hemoglobin A1c, age, and body mass index in regression models. Conclusions: We observed moderate correlations between sleep quality and sleep-related impairment with sleep hygiene using the SHPS in Black and Latinx adults with T2DM.

Predicting Adolescent Intervention Non-responsiveness for Precision HIV Prevention Using Machine Learning.

Interventions to teach protective behaviors may be differentially effective within an adolescent population. Identifying the characteristics of youth who are less likely to respond to an intervention can guide program modifications to improve its effectiveness. Using comprehensive longitudinal data on adolescent risk behaviors, perceptions, sensation-seeking, peer and family influence, and neighborhood risk factors from 2564 grade 10-12 students in The Bahamas, this study employs machine learning approaches (support vector machines, logistic regression, decision tree, and random forest) to identify important predictors of non-responsiveness for precision prevention. We used 80% of the data to train the models and the rest for model testing. Among different machine learning algorithms, the random forest model using longitudinal data and the Boruta feature selection approach predicted intervention non-responsiveness best, achieving sensitivity of 85.4%, specificity of 78.4% and AUROC of 0.93 on the training data, and sensitivity of 84.3%, specificity of 67.1%, and AUROC of 0.85 on the test data. Key predictors include self-efficacy, perceived response cost, parent monitoring, vulnerability, response efficacy, HIV/AIDS knowledge, communication about condom use, and severity of HIV/STI. Machine learning can yield powerful predictive models to identify adolescents who are unlikely to respond to an intervention. Such models can guide the development of alternative strategies that may be more effective with intervention non-responders.

Global trends in smoking cessation research from 2002 to 2021: A bibliometric and visual analysis.

This study aimed to analyze the scientific outputs of smoking cessation research and explore its hotspots and frontiers from 2002 to 2021, using bibliometric methods. We use the core collection of Web of Science as a data source, and apply bibliometric methods to visually analyze articles published in smoking cessation research from 2002 to 2021, including publication year, countries/regions, journals, authors, institutions, and keywords. The VOSviewer (1.6.16) tool was used for the analysis. A total of 8797 articles related to smoking cessation research were identified. The USA was the leading contributor with 4671 publications. NICOTINE＆TOBACCO RESEARCH contributed the most publications (528), with the most citations (13746) and the highest H-index (59). The most contributing institutions were the University College London and University of California San Francisco. Robert West was most productive author. We found active collaborations among both productive authors and productive institutions. There were five hot topics in smoking cessation research: (1) Public health harm from tobacco; (2) The role of e-health in smoking cessation; (3) Role of primary health care in eliminating tobacco dependence; (4) Nicotine replacement therapy and pharmacotherapy; (5) The biological and clinical understanding of addiction. Our current study showed a growing trend in smoking cessation based on the number of published articles over the last 20 years. There was active cooperation between institutions, and authors. Electronic cigarettes, mHealth, eHealth, public health and mental health are foci of new and emerging research.

Design and Formative Evaluation of a Virtual Voice-Based Coach for Problem-solving Treatment: Observational Study.

BACKGROUND: Artificial intelligence has provided new opportunities for human interactions with technology for the practice of medicine. Among the recent artificial intelligence innovations, personal voice assistants have been broadly adopted. This highlights their potential for health care-related applications such as behavioral counseling to promote healthy lifestyle habits and emotional well-being. However, the use of voice-based applications for behavioral therapy has not been previously evaluated. OBJECTIVE: This study aimed to conduct a formative user evaluation of Lumen, a virtual voice-based coach developed as an Alexa skill that delivers evidence-based, problem-solving treatment for patients with mild to moderate depression and/or anxiety. METHODS: A total of 26 participants completed 2 therapy sessions-an introductory (session 1) and a problem-solving (session 2)-with Lumen. Following each session with Lumen, participants completed user experience, task-related workload, and work alliance surveys. They also participated in semistructured interviews addressing the benefits, challenges and barriers to Lumen use, and design recommendations. We evaluated the differences in user experience, task load, and work alliance between sessions using 2-tailed paired t tests. Interview transcripts were coded using an inductive thematic analysis to characterize the participants' perspectives regarding Lumen use. RESULTS: Participants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions for both Lumen sessions. However, participants experienced a higher temporal workload during the problem-solving session, suggesting a feeling of being rushed during their communicative interactions. On the basis of the qualitative analysis, the following themes were identified: Lumen's on-demand accessibility and the delivery of a complex problem-solving treatment task with a simplistic structure for achieving therapy goals; themes related to Lumen improvements included streamlining and improved personalization of conversations, slower pacing of conversations, and providing additional context during therapy sessions. CONCLUSIONS: On the basis of an in-depth formative evaluation, we found that Lumen supported the ability to conduct cognitively plausible interactions for the delivery of behavioral therapy. Several design suggestions identified from the study including reducing temporal and cognitive load during conversational interactions, developing more natural conversations, and expanding privacy and security features were incorporated in the revised version of Lumen. Although further research is needed, the promising findings from this study highlight the potential for using Lumen to deliver personalized and accessible mental health care, filling a gap in traditional mental health services.

Use of a Digital Assistant to Report COVID-19 Rapid Antigen Self-test Results to Health Departments in 6 US Communities.

Importance: Widespread distribution of rapid antigen tests is integral to the US strategy to address COVID-19; however, it is estimated that few rapid antigen test results are reported to local departments of health. Objective: To characterize how often individuals in 6 communities throughout the United States used a digital assistant to log rapid antigen test results and report them to their local departments of health. Design, Setting, and Participants: This prospective cohort study is based on anonymously collected data from the beneficiaries of the Say Yes! Covid Test program, which distributed more than 3 000 000 rapid antigen tests at no cost to residents of 6 communities (Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; Ann Arbor and Ypsilanti, Michigan; and Chattanooga, Tennessee) between April and October 2021. A descriptive evaluation of beneficiary use of a digital assistant for logging and reporting their rapid antigen test results was performed. Interventions: Widespread community distribution of rapid antigen tests. Main Outcomes and Measures: Number and proportion of tests logged and reported to the local department of health through the digital assistant. Results: A total of 313 000 test kits were distributed, including 178 785 test kits that were ordered using the digital assistant. Among all distributed kits, 14 398 households (4.6%) used the digital assistant, but beneficiaries reported three-quarters of their rapid antigen test results to their state public health departments (30 965 tests reported of 41 465 total test results [75.0%]). The reporting behavior varied by community and was significantly higher among communities that were incentivized for reporting test results vs those that were not incentivized or partially incentivized (90.5% [95% CI, 89.9%-91.2%] vs 70.5%; [95% CI, 70.0%-71.0%]). In all communities, positive tests were less frequently reported than negative tests (60.4% [95% CI, 58.1%-62.8%] vs 75.5% [95% CI, 75.1%-76.0%]). Conclusions and Relevance: These results suggest that application-based reporting with incentives may be associated with increased reporting of rapid tests for COVID-19. However, increasing the adoption of the digital assistant may be a critical first step.

Integrated collaborative care intervention for depression and obesity in primary care: translation from research to practice.

The objective of this study was to present lessons learned about engagement, delivery modality and pandemic impact while delivering a collaborative care intervention with a socioeconomically, racially and ethnically diverse sample. Participants completed a post-intervention survey (n = 41) on experiences and preferred intervention delivery modality, coronavirus 2019 (COVID-19) Impact Survey (n = 50) and provided open-ended feedback about the intervention (n = 27). Intervention process data included attendance, modality, and withdrawals. Data were analyzed using descriptive statistics and inductive content analyses. Of 71 intervention participants, 6 (8%) withdrew before session 1. Completers adhered to intervention timeline better than withdrawals. Participants liked the in-person interaction, efficient coach support, accountability of in-person and Zoom vs. phone sessions and the flexibility and convenience of phone and Zoom vs. in-person sessions. A majority of participants reported experiencing pandemic impacts such as heightened emotional distress, decreased activity engagement, poorer eating behaviors and being unable to meet basic needs. Participants deviating from intervention timelines may be re-engaged by targeted outreach attempts. Videoconference has the potential for providing as-needed coaching. Future interventions may be optimized to account for and address areas impacted by the pandemic. Findings revealed specific strategies that can be implemented in future interventions to improve emotional and physical health among diverse populations.

Association of COVID-19 impact with outcomes of an integrated obesity and depression intervention: Posthoc analysis of an RCT.

OBJECTIVE: To examine the association between COVID-19 impact and clinical outcomes of an integrated collaborative care intervention for adults with obesity and comorbid depression. METHODS: Latent class analysis identified clusters of self-reported COVID-19 impact. Cluster characteristics were examined using Fishers' least significant difference method and canonical discriminant analysis. Intervention vs. usual care effects on primary (body mass index [BMI], depressive symptoms) and secondary (anxiety symptoms and other psychosocial) outcomes stratified by cluster were examined using linear mixed models. RESULTS: Three clusters were identified: mental health and sleep impact (cluster 1, n = 37), economic impact (cluster 2, n = 18), and less overall impact (cluster 3, n = 20). Clusters differed in age, income, diet, and baseline coping skills. The intervention led to improvements across several health outcomes compared with usual care, with medium to large effects on functional impairments (standardized mean difference, -0.7 [95% CI: -1.3, -0.1]) in cluster 1, depressive symptoms (-1.1 [95% CI: -2.0, -0.1]) and obesity-related problems (-1.6 [95% CI: -2.8, -0.4]) in cluster 2, and anxiety (-1.1 [95% CI: -1.9, -0.3]) in cluster 3. CONCLUSIONS: People with obesity and comorbid depression may have varied intervention responses based on COVID-19 impact. Interventions tailored to specific COVID-19 impact clusters may restore post-pandemic health.

Design and Preliminary Findings of Adherence to the Self-Testing for Our Protection From COVID-19 (STOP COVID-19) Risk-Based Testing Protocol: Prospective Digital Study.

BACKGROUND: Serial testing for SARS-CoV-2 is recommended to reduce spread of the virus; however, little is known about adherence to recommended testing schedules and reporting practices to health departments. OBJECTIVE: The Self-Testing for Our Protection from COVID-19 (STOP COVID-19) study aims to examine adherence to a risk-based COVID-19 testing strategy using rapid antigen tests and reporting of test results to health departments. METHODS: STOP COVID-19 is a 12-week digital study, facilitated using a smartphone app for testing assistance and reporting. We are recruiting 20,000 participants throughout the United States. Participants are stratified into high- and low-risk groups based on history of COVID-19 infection and vaccination status. High-risk participants are instructed to perform twice-weekly testing for COVID-19 using rapid antigen tests, while low-risk participants test only in the case of symptoms or exposure to COVID-19. All participants complete COVID-19 surveillance surveys, and rapid antigen results are recorded within the smartphone app. Primary outcomes include participant adherence to a risk-based serial testing protocol and percentage of rapid tests reported to health departments. RESULTS: As of February 2022, 3496 participants have enrolled, including 1083 high-risk participants. Out of 13,730 tests completed, participants have reported 13,480 (98.18%, 95% CI 97.9%-98.4%) results to state public health departments with full personal identifying information or anonymously. Among 622 high-risk participants who finished the study period, 35.9% showed high adherence to the study testing protocol. Participants with high adherence reported a higher percentage of test results to the state health department with full identifying information than those in the moderate- or low-adherence groups (high: 71.7%, 95% CI 70.3%-73.1%; moderate: 68.3%, 95% CI 66.0%-70.5%; low: 63.1%, 59.5%-66.6%). CONCLUSIONS: Preliminary results from the STOP COVID-19 study provide important insights into rapid antigen test reporting and usage, and can thus inform the use of rapid testing interventions for COVID-19 surveillance.

If you build it, will they use it? Use of a Digital Assistant for Self-Reporting of COVID-19 Rapid Antigen Test Results during Large Nationwide Community Testing Initiative.

Importance: Wide-spread distribution of rapid-antigen tests is integral to the United States' strategy to address COVID-19; however, it is estimated that few rapid-antigen test results are reported to local departments of health. Objective: To characterize how often individuals in six communities throughout the United States used a digital assistant to log rapid-antigen test results and report them to their local Department of Health. Design: This prospective cohort study is based on anonymously collected data from the beneficiaries of The Say Yes! Covid Test program, which distributed 3,000,000 rapid antigen tests at no cost to residents of six communities between April and October 2021. We provide a descriptive evaluation of beneficiaries' use of digital assistant for logging and reporting their rapid antigen test results. Main Outcome and Measures: Number and proportion of tests logged and reported to the Department of Health through the digital assistant. Results: A total of 178,785 test kits were ordered by the digital assistant, and 14,398 households used the digital assistant to log 41,465 test results. Overall, a small proportion of beneficiaries used the digital assistant (8%), but over 75% of those who used it reported their rapid antigen test results to their state public health department. The reporting behavior varied between communities and was significantly different for communities that were incentivized for reporting test results (p < 0.001). In all communities, positive tests were less reported than negative tests (60.4% vs 75.5%; p<0.001). Conclusions and Relevance: These results indicate that app-based reporting with incentives may be an effective way to increase reporting of rapid tests for COVID-19; however, increasing the adoption of the digital assistant is a critical first step.