Assessing actigraphy performance for daytime sleep detection following stroke: insights from inpatient monitoring in a rehabilitation hospital.

Study Objectives: Stroke can result in or exacerbate various sleep disorders. The presence of behaviors such as daytime sleepiness poststroke can indicate underlying sleep disorders which can significantly impact functional recovery and thus require prompt detection and monitoring for improved care. Actigraphy, a quantitative measurement technology, has been primarily validated for nighttime sleep in healthy adults; however, its validity for daytime sleep monitoring is currently unknown. Therefore this study aims to identify the best-performing actigraphy sensor and algorithm for detecting daytime sleep in poststroke individuals. Methods: Participants wore Actiwatch Spectrum and ActiGraph wGT3X-BT on their less-affected wrist, while trained observers recorded daytime sleep occurrences and activity levels (active, sedentary, and asleep) during non-therapy times. Algorithms, Actiwatch (Autoscore AMRI) and ActiGraph (Cole-Kripke, Sadeh), were compared with on-site observations and assessed using F2 scores, emphasizing sensitivity to detect daytime sleep. Results: Twenty-seven participants from an inpatient stroke rehabilitation unit contributed 173.5 hours of data. The ActiGraph Cole-Kripke algorithm (minute sleep time = 15 minutes, bedtime = 10 minutes, and wake time = 10 minutes) achieved the highest F2 score (0.59). Notably, when participants were in bed, the ActiGraph Cole-Kripke algorithm continued to outperform Sadeh and Actiwatch AMRI, with an F2 score of 0.69. Conclusions: The study demonstrates both Actiwatch and ActiGraph's ability to detect daytime sleep, particularly during bed rest. ActiGraph (Cole-Kripke) algorithm exhibited a more balanced sleep detection profile and higher F2 scores compared to Actiwatch, offering valuable insights for optimizing daytime sleep monitoring with actigraphy in stroke patients.

Determining If COPD Self-Management Televisit-Based Interventions Are Evaluated Among and Equitably Effective Across Diverse Patient Populations to Reduce Acute Care Use: A Scoping Review.

TOPIC IMPORTANCE: With telemedicine's expansion during the COVID-19 pandemic, it has become critical to evaluate whether patients have equitable access and capabilities to use televisits optimally for improved COPD outcomes such as reduced hospitalizations. This scoping review evaluated whether televisit-based interventions are evaluated and equitably effective in improving health care use outcomes among diverse patient populations with COPD. REVIEW FINDINGS: Using a systematic search for televisit-based COPD self-management interventions, we found 20 studies for inclusion, all but one of which were published before the COVID-19 pandemic. Most (11/20) were considered good-quality studies. Most studies (19/20) reported age and sex; few provided race (3/20) or income (1/20) data. The most frequently used televisit-based methods were in person plus phone (6/20), video only (6/20), and phone only (4/20). Most studies (12/20) showed a significant reduction in at least one health care use metric; nine studies found hospitalization-related reductions. Effective interventions typically used two methods (eg, in person plus televisits), a video methods, or both. SUMMARY: Most studies failed to report on participants' race or income, leading to a lack of data on the equity of interventions' effectiveness across diverse patient populations. Multimethod televisit-based interventions, particularly with an in-person component, most commonly were effective; no associations were seen with study quality or size. With the increasing reliance on telemedicine to provide chronic disease care, the lack of data among diverse populations since the COVID-19 pandemic began limits generalizability of these findings for real-world clinical settings. More comprehensive evaluations of televisit-based interventions are needed in the era after the pandemic within and across diverse patient populations.

Wireless wearable sensors can facilitate rapid detection of sleep apnea in hospitalized stroke patients.

STUDY OBJECTIVES: To evaluate wearable devices and machine learning for detecting sleep apnea in patients with stroke at an acute inpatient rehabilitation facility (IRF). METHODS: A total of 76 individuals with stroke wore a standard home sleep apnea test (ApneaLink Air), a multimodal, wireless wearable sensor system (ANNE), and a research-grade actigraphy device (ActiWatch) for at least one night during their first week after IRF admission as part of a larger clinical trial. Logistic regression algorithms were trained to detect sleep apnea using biometric features obtained from the ANNE sensors and ground truth apnea rating from the ApneaLink Air. Multiple algorithms were evaluated using different sensor combinations and different apnea detection criteria based on the Apnea-Hypopnea Index (AHI≥5, AHI≥15). RESULTS: Seventy-one (96%) participants wore the ANNE sensors for multiple nights. In contrast, only forty-eight participants (63%) could be successfully assessed for OSA by ApneaLink; 28 (37%) refused testing. The best-performing model utilized photoplethysmography (PPG) and finger temperature features to detect moderate-severe sleep apnea (AHI≥15), with 88% sensitivity and a positive likelihood ratio (LR+) of 44.00. This model was tested on additional nights of ANNE data achieving 71% sensitivity (10.14 LR+) when considering each night independently and 86% accuracy when averaging multi-night predictions. CONCLUSIONS: This research demonstrates the feasibility of accurately detecting moderate-severe sleep apnea early in the stroke recovery process using wearable sensors and machine learning techniques. These findings can inform future efforts to improve early detection for post-stroke sleep disorders, thereby enhancing patient recovery and long-term outcomes.

Restoring Trust in Science and Medicine: Empowering and Educating Future Physicians in Science Communication With the Public.

While the traditional medical school curriculum specializes in teaching doctor-patient communication at the individual patient level, the need to train physicians to communicate science and medicine effectively to the public at large is, for the most part, ignored. With the unchecked proliferation of misinformation and disinformation during the COVID-19 pandemic, it is critical that current and future medical professionals learn to engage in the public arena using multiple methods (written, oral, social media) across multimedia platforms to dispel misinformation and accurately educate the public. This article describes the authors' interdisciplinary approach at the University of Chicago Pritzker School of Medicine to teaching science communication to medical students, early experiences, and future directions in this vein. The authors' experiences show that medical students are viewed as trusted sources of health-related information, and thus, need the skills and training to tackle misinformation and that students across these learning experiences appreciated the opportunity to choose a topic of their interest according to what matters to them and their communities most. The feasibility of successfully teaching scientific communication in an undergraduate and medical education curriculum is confirmed. These early experiences support the feasibility and impact of training medical students to improve communication about science with the general public.

Testing a digitally distributed method to recruit a network of community organizations to fight the consequences of the drug epidemic: A study in 13 American states.

To mitigate the opioid epidemic, a concerted effort to educate, prevent, diagnose, treat, and engage residents is required. In this study, a digitally distributed method to form a large network of organizations was tested with 99 counties in regions with high vulnerability to hepatitis C virus (HCV). The method involved a cascade of contacts going from email to phone calls, to videoconferencing and measuring the number of contacts required, amount of time taken, and the proportion of success at recruiting at least one community organization per county. A recruitment period of 5 months and 2118 contact attempts led to the recruitment of organizations from 73 out of our 99 target counties. Organizations belonging to health departments required more attempts and time to recruit but ultimately enrolled at higher rates than did other organizations such as coalitions and agencies. Organizations from counties more (vs. less) vulnerable to HCV outbreaks required more attempts to recruit and, using multiple recruitment methods (e.g., emails, phone calls, and Zoom meetings), improved enrollment success. Overall, this method proved to be successful at remotely engaging a large-scale network of communities with different levels of risk within a large geographic region.

Complex solutions for a complex problem: A meta-analysis of the efficacy of multiple-behavior interventions on change in outcomes related to HIV.

OBJECTIVE: The purpose of this meta-analysis was to examine the success of multiple-behavior interventions and to identify whether the efficacy of such programs depends on the number of recommendations prescribed and the type of outcomes measured. METHOD: We conducted a synthesis of 136 research reports (N = 59,330) using a robust variance estimate model (Tanner-Smith et al., 2016) to study change between baseline and the first follow-up across multiple-behavior interventions, single-behavior interventions, and passive controls. RESULTS: Multiple-behavior interventions were more efficacious than their single-behavior counterparts (multiple-behaviors: d = .44 [95% confidence interval, CI [.27, .60]); single-behavior: d = .21 [95% CI [.00, .43]), with efficacy varying based on the type of outcomes measured. Publication bias analysis revealed a small asymmetry but controlling for it did not eliminate these effects. There was a strong linear relation between the number of recommendations prescribed by an intervention and intervention efficacy (B = .07, SE = .01, p < .001), with strongest improvements observed for interventions making five or more recommendations. These patterns remained when controlling for other intervention and population characteristics. CONCLUSIONS: Multiple-behavior interventions are successful in the HIV domain and increasing the number of recommendations made in the intervention generally maximizes improvements. These findings provide insights that may guide the design and implementation of integrated interventions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Naïve definitions of action and inaction: a study of free associations using natural language processing and top-down coding / Definiciones Naïve de Acción e Inacción: un Estudio de Asociaciones Libres Realizado con Procesamiento de Lenguaje Natural y Codificación Jerárquica

BACKGROUND: Even though the terms "action" and "inaction" have been used to describe objects of attitudes, behaviors, and goals, the meaning of action and inaction for lay people has not been investigated. METHOD: In Study 1, participants were asked to spontaneously generate words and behaviors associated with action or inaction. In Studies 2 and 3, participants were presented with behaviors and asked to report whether each behavior involved agency, effort, and change. RESULTS: Natural language processing of the responses from Study 1 revealed lay conceptualizations included topics related to occurrence, agency, effort, and change. In Studies 2 and 3, simple regressions showed agency, effort, and change correlated with judgments of action and inaction. However, once these predictors were simultaneously entered into a multiple regression, effort captured most of the variance. CONCLUSIONS: These fi ndings suggest that, even though agency and change are important to the defi nition of action and inaction, effort is Paramount

Naïve de Acción e Inacción: un Estudio de Asociaciones Libres Realizado con Procesamiento de Lenguaje Natural y Codifi cación Jerárquica. ANTECEDENTES: pese a que los términos "acción" e "inacción" se han utilizado para describir objetos de actitudes, comportamientos y metas, no se ha investigado el significado de acción e inacción para los ciudadanos de a pie. MÉTODO: en el Estudio 1 se pidió a los participantes que generaran espontáneamente palabras y comportamientos asociados con la acción o la inacción. En los Estudios 2 y 3 se presentaron comportamientos y los participantes reportaron si cada comportamiento involucraba intencionalidad, esfuerzo y cambio. RESULTADOS: un procesamiento de lenguaje natural de las respuestas del Estudio 1 reveló conceptualizaciones naïve que incluían temas relacionados con la ocurrencia, la intencionalidad, el esfuerzo y el cambio. En los Estudios 2 y 3, regresiones simples mostraron que las dimensiones de intencionalidad, esfuerzo y cambio se correlacionaban con juicios de acción e inacción. Sin embargo, una vez que estos predictores se incluyeron simultáneamente en una regresión múltiple, el esfuerzo capturó la mayor parte de la varianza. CONCLUSIÓN: estos hallazgos sugieren que aunque el cambio y la intencionalidad son importantes para la defi nición de acción e inacción, la dimensión de esfuerzo es primordial

Naïve Definitions of Action and Inaction: A Study of Free Associations Using Natural Language Processing and Top-Down Coding.

BACKGROUND: Even though the terms "action" and "inaction" have been used to describe objects of attitudes, behaviors, and goals, the meaning of action and inaction for lay people has not been investigated. METHOD: In Study 1, participants were asked to spontaneously generate words and behaviors associated with action or inaction. In Studies 2 and 3, participants were presented with behaviors and asked to report whether each behavior involved agency, effort, and change. RESULTS: Natural language processing of the responses from Study 1 revealed lay conceptualizations included topics related to occurrence, agency, effort, and change. In Studies 2 and 3, simple regressions showed agency, effort, and change correlated with judgments of action and inaction. However, once these predictors were simultaneously entered into a multiple regression, effort captured most of the variance. CONCLUSIONS: These findings suggest that, even though agency and change are important to the definition of action and inaction, effort is paramount.

Mistaking an Intention for a Behavior: The Case of Enacting Behavioral Decisions Versus Simply Intending to Enact Them.

Five experiments investigated a previously unrecognized phenomenon-remembering that one enacted a mundane behavioral decision when one only intended to do so-and its psychological mechanisms. The theoretical conceptualization advanced in this research proposes that this error stems from a misattribution when an intention and a behavior are similar. Intentions and behaviors are similar when the physical aspects of the behavior resemble the intention (e.g., both require similar keystrokes) and when the behavior and the intention share mental contents (e.g., both rely on the same criterion). Experiments 1 and 2 introduced a paradigm with similar intentions and enactments and showed misreports and subsequent performance errors even when controlling for guessing. Experiments 3 and 4 demonstrated greater confusion when the physical involvement and mental criteria for intention and behavior were similar. Finally, Experiment 5 indicated that monitoring enactment is highly effective at reducing this error and more effective than monitoring intention.

More behavioral recommendations produce more change: A meta-analysis of efficacy of multibehavior recommendations to reduce nonmedical substance use.

Death and morbidity associated with substance use have risen continuously over the last few decades, increasing the need for rigorous examination of promising programs. Interventions attempting to change multiple behaviors have been designed to address interconnected problems such as use of both alcohol and drugs. This meta-analysis aimed to examine the efficacy of multibehavior interventions to curb nonmedical substance use in relation to the theoretical relation among different substance use behaviors. Specifically, our synthesis aimed to estimate the optimal number of recommendations for intervention efficacy and evaluate the impact of different combinations of recommendations on intervention efficacy. A synthesis of multibehavior interventions addressing nonmedical substance use was conducted to measure behavioral changes between the pretest and the follow-up. These changes were then compared across different numbers of recommendations. Sixty-nine reports and 233 effect sizes (k of conditions = 155, n = 28,295) were included. A positive linear relation was found between the number of targeted behaviors and intervention efficacy, which was stronger for drug use than alcohol use. Furthermore, recommendations on drug use worked better when paired with recommendations targeting other behaviors, whereas recommendations on alcohol use worked more independently. Lastly, multibehavior interventions were especially efficacious when delivered by experts. Overall, our synthesis indicated that targeting multiple substances is beneficial for changing drug use outcomes, but less so for alcohol use outcomes. Therefore, in the current substance use epidemic, innovative multibehavior programs appear to hold promise, especially to combat nonmedical drug use. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A meta-intervention to increase completion of an HIV-prevention intervention: Results from a randomized controlled trial in the state of Florida.

OBJECTIVE: A randomized control trial with 722 eligible clients from a health department in the State of Florida was conducted to identify a simple, effective meta-intervention to increase completion of an HIV-prevention counseling program. METHOD: The overall design involved 2 factors representing an empowering and instrumental message, as well as an additional factor indicating presence or absence of expectations about the counseling. Completion of the 3-session counseling was determined by recording attendance. RESULTS: A logistic regression analysis with the 3 factors of empowering message, instrumental message, and presence of mediator measures, as well as all interactions, revealed significant interactions between instrumental and empowering messages and between instrumental messages and presence of mediator measures. Results indicated that (a) the instrumental message alone produced most completion than any other message, and (b) when mediators were not measured, including the instrumental message led to greater completion. CONCLUSIONS: The overall gains in completion as a result of the instrumental message were 16%, implying success in the intended facilitation of counseling completion. The measures of mediators did not detect any experimental effects, probably because the effects were happening without much conscious awareness. (PsycINFO Database Record