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PURPOSE: The purpose of the study was to describe the development and feasibility of implementing the DM-BOOST program in support of an established diabetes self-management education and support (DSMES) program. METHODS: A patient panel of 4 adults with type 2 diabetes (T2DM) codesigned DM-BOOST. DM-BOOST is a patient-focused program that includes peer-written text messages about diabetes self-management behaviors and digital health training to improve patient portal use and initiate goal setting prior to a scheduled DSMES appointment. Adults with T2DM and A1C ≥8.0% participated in a 6-month feasibility pilot. Participants were randomly assigned (1:1) to receive either DM-BOOST or usual care. Outcomes included DSMES engagement (scheduled and attended DSMES appointments) and changes in diabetes self-efficacy and treatment satisfaction. RESULTS: Pilot participants (n = 60) were 60.0% female with mean age 45.5 years (SD 8.3) and A1C 10.1% (SD 1.8%). All DM-BOOST participants (30/30, 100%) had DSMES appointments scheduled compared to 86.7% of usual care (26/30). DM-BOOST participants had fewer DSMES appointment no-shows/cancellations (3/30, 10%) compared to usual care (10/26, 35%). There was greater improvement in diabetes self-efficacy in the DM-BOOST group compared to usual care and no difference in treatment satisfaction. CONCLUSIONS: DM-BOOST, leveraging peer-written text messaging and digital health training, increased DSMES engagement. Implementation of DM-BOOST was determined to be feasible, with several system-level barriers identified, including obtaining provider referrals and scheduling appointments. An effectiveness trial of DM-BOOST is needed to evaluate the impact on clinical outcomes.
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Objective: To investigate what overweight or obese adults with prediabetes in the United States report being told by providers about 1) having prediabetes, 2) diabetes risk, and 3) losing weight and the associations of these communications with attempted weight loss. Methods: Data from 2015 to 2018 National Health and Nutrition Examination Surveys (NHANES) for adults with a body mass index in the overweight or obesity ranges and HbA1c in the prediabetes range were examined (n = 2085). Patient reported data on what providers told them about having prediabetes, being at risk for diabetes, and losing weight were compared with attempted weight loss. Results: Most participants (66.4%) reported never being told they had prediabetes nor being at risk for diabetes, 13.0% reported being told they had prediabetes, 10.6% at risk for diabetes, and 8.0% both messages. 18.3% of participants reported being told to lose weight. Participants who reported being told they had prediabetes and at increased diabetes risk were more likely to report attempted weight loss (adjusted odds ratio (AOR) 1.8, 95% confidence interval (CI) 1.1-3.2). Reporting that they were told to lose weight was not significantly associated with an increase in reported weight loss attempts. Conclusions: In this cohort of individuals with overweight/obesity and prediabetic HbA1c values, low rates communications with providers about prediabetes and diabetes risk were reported. When both were discussed, patients reported greater attempted weight loss. These findings draw attention to the potential impact that provider communications about prediabetes and diabetes risk may have on lifestyle behavior change.
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BACKGROUND: The number of individuals using digital health devices has grown in recent years. A higher rate of use in patients suggests that primary care providers (PCPs) may be able to leverage these tools to effectively guide and monitor physical activity (PA) for their patients. Despite evidence that remote patient monitoring (RPM) may enhance obesity interventions, few primary care practices have implemented programs that use commercial digital health tools to promote health or reduce complications of the disease. OBJECTIVE: This formative study aimed to assess the perceptions, needs, and challenges of implementation of an electronic health record (EHR)-integrated RPM program using wearable devices to promote patient PA at a large urban primary care practice to prepare for future intervention. METHODS: Our team identified existing workflows to upload wearable data to the EHR (Epic Systems), which included direct Fitbit (Google) integration that allowed for patient PA data to be uploaded to the EHR. We identified pictorial job aids describing the clinical workflow to PCPs. We then performed semistructured interviews with PCPs (n=10) and patients with obesity (n=8) at a large urban primary care clinic regarding their preferences and barriers to the program. We presented previously developed pictorial aids with instructions for (1) providers to complete an order set, set step-count goals, and receive feedback and (2) patients to set up their wearable devices and connect them to their patient portal account. We used rapid qualitative analysis during and after the interviews to code and develop key themes for both patients and providers that addressed our research objective. RESULTS: In total, 3 themes were identified from provider interviews: (1) providers' knowledge of PA prescription is focused on general guidelines with limited knowledge on how to tailor guidance to patients, (2) providers were open to receiving PA data but were worried about being overburdened by additional patient data, and (3) providers were concerned about patients being able to equitably access and participate in digital health interventions. In addition, 3 themes were also identified from patient interviews: (1) patients received limited or nonspecific guidance regarding PA from providers and other resources, (2) patients want to share exercise metrics with the health care team and receive tailored PA guidance at regular intervals, and (3) patients need written resources to support setting up an RPM program with access to live assistance on an as-needed basis. CONCLUSIONS: Implementation of an EHR-based RPM program and associated workflow is acceptable to PCPs and patients but will require attention to provider concerns of added burdensome patient data and patient concerns of receiving tailored PA guidance. Our ongoing work will pilot the RPM program and evaluate feasibility and acceptability within a primary care setting.
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Registros Electrónicos de Salud , Ejercicio Físico , Obesidad , Investigación Cualitativa , Dispositivos Electrónicos Vestibles , Humanos , Ejercicio Físico/psicología , Masculino , Femenino , Obesidad/terapia , Adulto , Persona de Mediana Edad , Atención Primaria de SaludRESUMEN
Background: Obesity increases risk of atrial fibrillation (AF) at least in part due to pro-inflammatory effects, but has been paradoxically associated with improved mortality. Although statins have pleiotropic anti-inflammatory properties, their interaction with obesity and clinical outcomes in AF is unknown. We explored the relationship between BMI, statin use, and all-cause mortality and AF/congestive heart failure (CHF)-related encounters, hypothesizing that statin exposure may be differentially associated with improved outcomes in overweight/obesity. Methods: This was a single center retrospective cohort study of adults with AF diagnosed between 2011-2018. Patients were grouped by body mass index (BMI) and statin use at time of AF diagnosis. Outcomes included all-cause mortality and ED or inpatient encounters for AF or CHF. Results and Conclusions: A total of 2503 subjects were included (median age 66 years, 43.4 % female, median BMI 29.8 kg/m2, 54.6 % on baseline statin therapy). Increasing BMI was associated with decreased mortality hazard but not associated with AF/CHF encounter risk. Adjusting for statin-BMI interaction, demographics, and cardiovascular comorbidities, overweight non-statin users experienced improved mortality (adjusted hazard ratio [aHR] 0.55, 95 % CI 0.35-0.84) compared to statin users (aHR 0.98, 95 % CI 0.69-1.40; interaction P-value = 0.013). Mortality hazard was consistently lower in obese non-statin users than in statin users, however interaction was insignificant. No significant BMI-statin interactions were observed in AF/CHF encounter risk. In summary, statin use was not differentially associated with improved mortality or hospitalization risk in overweight/obese groups. These findings do not support statins for secondary prevention of adverse outcomes based on overweight/obesity status alone.
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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 48â 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.
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Agresión , Internado y Residencia , Resiliencia Psicológica , Humanos , Agresión/psicologíaRESUMEN
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.
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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.
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Diabetes Mellitus Tipo 2 , Telemedicina , Adulto , Humanos , Femenino , Persona de Mediana Edad , Diabetes Mellitus Tipo 2/terapia , Hemoglobina Glucada , Glucemia , Calidad de VidaRESUMEN
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.
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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.
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Estado Prediabético , Humanos , Hemoglobina Glucada , Ritmo Circadiano , Sueño , Descanso , Glucemia/metabolismoRESUMEN
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.
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Depresión , Distrés Psicológico , Adulto , Humanos , Femenino , Masculino , Depresión/terapia , Depresión/psicología , Ansiedad/terapia , Trastornos de Ansiedad , EncéfaloRESUMEN
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.
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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. NICOTINEï¼TOBACCO 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.
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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.
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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.
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COVID-19 , Depresión , Depresión/terapia , Humanos , Obesidad , Atención Primaria de Salud , TeléfonoRESUMEN
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.
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COVID-19 , Depresión , Adulto , Ansiedad/terapia , COVID-19/terapia , Depresión/complicaciones , Depresión/terapia , Humanos , Obesidad/complicaciones , Obesidad/terapia , Calidad de VidaRESUMEN
Importance: Wide-spread distribution of diagnostics is an integral part of the United Statesâ™ COVID-19 strategy; however, few studies have assessed the effectiveness of this intervention at reducing transmission of community COVID-19. Objective: To assess the impact of the Say Yes! Covid Test (SYCT!) Michigan program, a population-based program that distributed 20,000 free rapid antigen tests within Ann Arbor and Ypsilanti, Michigan in June-August 2021, on community prevalence of SARS-CoV-2. Design: This ecological study analyzed cases of SARS-CoV-2 from March to October 2021 reported to the Washtenaw County Health Department. Setting: Washtenaw County, Michigan. Participants: All residents of Washtenaw County. Interventions: Community-wide distribution of 500,000 rapid antigen tests for SARS-CoV-2 to residents of Ann Arbor and Ypsilanti, Michigan. Each household was limited to one test kit containing 25 rapid antigen tests. Main Outcome and Measures: Community prevalence of SARS-CoV-2, as measured through 7-day average cases, in Ann Arbor and Ypsilanti was compared to the rest of Washtenaw County. A generalized additive model was fitted with non-parametric trends for control and relative differences of trends in the pre-intervention, intervention, and post-intervention periods to compare intervention municipalities of Ann Arbor and Ypsilanti to the rest of Washtenaw County. Model results were used to calculate average cases prevented in the post-intervention period. Results: In the post-intervention period, there were significantly lower standardized average cases in the intervention communities of Ann Arbor/Ypsilanti compared to the rest of Washtenaw County (p<0.001). The estimated standardized relative difference between Ann Arbor/Ypsilanti and the rest of Washtenaw County was -0.016 cases per day (95% CI: -0.020 to -0.013), implying that the intervention prevented 40 average cases per day two months into the post-intervention period if trends were consistent. Conclusions and Relevance: Mass distribution of rapid antigen tests may be a useful mitigation strategy to combat community transmission of SARS-CoV-2, especially given the recent relaxation of social distancing and masking requirements.
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BACKGROUND: After hospital discharge, patients with acute coronary syndrome (ACS) often experience symptoms that prompt them to seek acute medical attention. Early evaluation of postdischarge symptoms by health care providers may reduce unnecessary acute care utilization. However, hospital-initiated follow-up encounters are insufficient for timely detection and assessment of symptoms. While digital health tools can help address this issue, little is known about the intention to use such tools in ACS patients. OBJECTIVE: This study aimed to assess ACS patients' intention to use digital health apps that support postdischarge symptom monitoring by health care providers and identify patient-perceived facilitators and barriers to app use. METHODS: Using email invitations or phone calls, we recruited ACS patients discharged from a central Massachusetts health care system between December 2020 and April 2021, to participate in the study. Surveys were delivered online or via phone to individual participants. Demographics and access to technology were assessed. The intention to use a symptom monitoring app was assessed using 5-point Likert-type (from strongly agree to strongly disagree) items, such as "If this app were available to me, I would use it." Responses were compared across demographic subgroups and survey delivery methods. Two open-ended questions assessed perceived facilitators and barriers to app use, with responses analyzed using qualitative content analysis. RESULTS: Among 100 respondents (response rate 8.1%), 45 (45%) completed the survey by phone. The respondents were on average 68 years old (SD 13 years), with 90% (90/100) White, 39% (39/100) women, and 88% (88/100) having access to the internet or a mobile phone. Most participants (65/100, 65%) agreed or strongly agreed that they would use the app, among which 53 (82%) would use the app as often as possible. The percentage of participants with the intention to use the app was 75% among those aged 65-74 years and dropped to 44% among those older than 75 years. The intention to use was higher in online survey respondents (vs phone survey respondents; odds ratio 3.07, 95% CI 1.20-7.88) after adjusting for age and access to technology. The analysis of open-ended questions identified the following 4 main facilitators (motivations): (1) easily reaching providers, (2) accessing or providing information, (3) quickly reaching providers, and (4) consulting providers for symptoms, and the following 4 main barriers: (1) privacy/security concerns, (2) uncomfortable using technology, (3) user-unfriendly app interface, and (4) preference for in-person/phone care. CONCLUSIONS: There was a strong intention to use a symptom monitoring app postdischarge among ACS patients. However, this intent decreased in patients older than 75 years. The survey identified barriers related to technology use, privacy/security, and the care delivery mode. Further research is warranted to determine if such intent translates into app use, and better symptom management and health care quality.