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BackgroundMultiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients’ lives. ObjectiveThis study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. MethodsIn this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. ResultsRecruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. ConclusionsWith self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. Trial RegistrationClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. International Registered Report Identifier (IRRID)DERR1-10.2196/25175

BackgroundDepressive symptoms are the most prevalent mental health concern among older adults (possibly heightened during the COVID-19 pandemic), which raises questions about how such symptoms can be lowered in this population. Existing research shows that offline social connectedness is a protective factor against depression in older adults; however, it is unknown whether web-based social connectedness can have similar effects. ObjectiveThis study investigates whether social connectedness on a support website protects older adults against depressive symptoms over the course of a year, above and beyond the protective effect of offline social connectedness. The secondary aim is to determine whether older adults with increased depressive symptoms are more likely to engage in social connectedness on this website. Thus, we examine depressive symptoms as both an outcome and predictor of web-based social connectedness to fully understand the chain of causality among these variables. Finally, we compare web-based social connectedness with offline social connectedness in their ability to lower depressive symptoms among older adults. MethodsA total of 197 adults aged 65 years or older were given access to a social support website, where they were able to communicate with each other via a discussion forum for a year. Participants’ social connectedness on the web-based platform, conceptualized as message production and consumption, was measured using behavioral log data as the number of messages participants wrote and read, respectively, during the first 6 months (t1) and the following 6 months (t2) of the study. Participants self-reported their offline social connectedness as the number of people in their support networks, and they reported their depressive symptoms using the Patient Health Questionnaire-8 both at baseline (t1) and at 12-month follow-up (t2). To ascertain the flow of causality between these variables, we employed a cross-lagged panel design, in which all variables were measured at t1 and t2. ResultsAfter controlling for the effect of offline support networks at t1, web-based message consumption at t1 decreased older adults’ depressive symptoms at t2 (β=−.11; P=.02), but web-based message production at t1 did not impact t2 depressive symptoms (β=.12; P=.34). Web-based message consumption had a larger effect (β=−.11; P=.02) than offline support networks (β=−.08; P=.03) in reducing older adults’ depressive symptoms over time. Higher baseline depressive symptoms did not predict increased web-based message consumption (β=.12; P=.36) or production (β=.02; P=.43) over time. ConclusionsThe more messages older adults read on the web-based forum for the first 6 months of the study, the less depressed they felt at the 1-year follow-up, above and beyond the availability of offline support networks at baseline. This pinpoints the substantial potential of web-based communication to combat depressive symptoms in this vulnerable population. International Registered Report Identifier (IRRID)RR2-10.1186/s13063-015-0713-2

To examine the effects of numerical evidence and message framing in communicating vaccine efficacy information about infectious diseases, an online experiment presented to U.S. adults different versions of a vaccination promotional message that vary by numerical vaccine efficacy evidence: (low efficacy rate: 60% vs. high efficacy rate: 95%), outcome framing (preventing disease-related infection vs. preventing disease-related severe illness), and gain vs. loss framing, using a factorial between-subjects design. While there was no significant interaction between numerical vaccine efficacy evidence and message framing, findings showed that a higher vaccine efficacy rate increased positive beliefs about vaccination and outcome framing emphasizing infection prevention increased message processing fluency. Given that infectious diseases pose higher risks for severe illness among older adults, follow-up analyses by age showed that only younger adults were sensitive to message framing where outcome framing emphasizing infection prevention increased processing fluency. [ABSTRACT FROM AUTHOR]

Although low socio-economic status (SES) persons with diabetes show low levels of physical activity (PA), there is limited knowledge regarding which media is effective in improving their PA. This study aimed to determine the appropriate media for providing PA-related information to persons with diabetes in low SES compared with those in high SES. The data of 770 persons with diabetes in low or high SES were extracted from Multimedia Audience Research Systems 2013, a nationwide cross-sectional study. The relationships among media use for health information (i.e. magazine, television and Internet use), PA, and high and low SES were examined using regression analysis. Additional analysis was conducted to examine whether the above relationships differ by age, which influences the use of media. The relationships of media use for health information with PA levels varied by SES; while television use was associated with increased PA levels, Internet use was associated with decreased PA levels in older, low SES persons with diabetes. The findings indicated that television can be a useful resource to provide PA-related information to low SES persons with diabetes and suggest the significance of choosing appropriate media to provide PA-related information for them.

The intersection of consumer culture and civic life has long been a topic of academic discubion. This study revisits the relationship between consumption and civic engagement and investigates the moderators of this relationship. Specifically, we focus on news consumption and opinion leadership as intervening factors that condition the way consumption and civic life are interconnected. Our data reveal that both socially conscious consumption and status-oriented consumption are positively related with civic participation. The positive relationships become stronger when news consumption increases or when one's opinion leadership is strong. Implications for research on consumer culture and civic engagement are discubed.

Beyond a consciousness-raising hashtag, #MeToo has become a transnational movement, crossing the borders of many societies. However, outsized attention has been paid to the manifestations of #MeToo in the US and on Twitter when the reach of this movement was not restricted to a single country, language, or platform. Drawing from the concept of hybridization, we seek to understand how the uses of #MeToo are contextualized across cultures, languages, and social media platforms. By establishing a macroscopic computational approach, we examine the global diffusion of #MeToo as a hybrid communicative process across different language groups (English, Spanish, and Korean) and social media platforms (Twitter, Facebook, and Instagram). Through time-series analysis and comparative descriptions of language groups and platforms, we demonstrate how discourse flows, language characteristics, and actors differ across cultural and platform contexts and how public discourse of #MeToo was reappropriated and re-signified in different parts of the world to localize connective action. [ABSTRACT FROM AUTHOR]

Medication for opioid use disorder (MOUD) improves treatment retention and reduces illicit opioid use. A-CHESS is an evidence-based smartphone intervention shown to improve addiction-related behaviors. The authors tested the efficacy of MOUD alone versus MOUD plus A-CHESS to determine whether the combination further improved outcomes. In an unblinded parallel-group randomized controlled trial, 414 participants recruited from outpatient programs were assigned in a 1:1 ratio to receive either MOUD alone or MOUD+A-CHESS for 16 months and were followed for an additional 8 months. All participants were on methadone, buprenorphine, or injectable naltrexone. The primary outcome was abstinence from illicit opioid use; secondary outcomes were treatment retention, health services use, other substance use, and quality of life; moderators were MOUD type, gender, withdrawal symptom severity, pain severity, and loneliness. Data sources were surveys comprising multiple validated scales, as well as urine screens, every 4 months. There was no difference in abstinence between participants in the MOUD+A-CHESS and MOUD-alone arms across time (odds ratio=1.10, 95% CI=0.90–1.33). However, abstinence was moderated by withdrawal symptom severity (odds ratio=0.95, 95% CI=0.91–1.00) and MOUD type (odds ratio=0.57, 95% CI=0.34–0.97). Among participants without withdrawal symptoms, abstinence rates were higher over time for those in the MOUD+A-CHESS arm than for those in the MOUD-alone arm (odds ratio=1.30, 95% CI=1.01–1.67). Among participants taking methadone, those in the MOUD+A-CHESS arm were more likely to be abstinent over time (b=0.28, SE=0.09) than those in the MOUD-alone arm (b=0.06, SE=0.08), although the two groups did not differ significantly from each other (∆b=0.22, SE=0.11). MOUD+A-CHESS was also associated with greater meeting attendance (odds ratio=1.25, 95% CI=1.05–1.49) and decreased emergency department and urgent care use (odds ratio=0.88, 95% CI=0.78–0.99). Overall, MOUD+A-CHESS did not improve abstinence relative to MOUD alone. However, MOUD+A-CHESS may provide benefits for subsets of patients and may impact treatment utilization. [ABSTRACT FROM AUTHOR]

Political polarization surrounding the COVID-19 health crisis has been on the rise since the beginning of the pandemic. We combine prior research on motivated reasoning, selective exposure, and news framing to understand the association between partisan media use and social distancing behavior related to COVID-19. To do so, we collected media content data and national survey data during the onset of the pandemic. We employed structural topic modeling (STM), dependency parsing, word co-occurrence, and manual coding to examine the media coverage. Next, we analyzed survey data collected with a Qualtrics panel from a sample of U.S. residents for factors explaining social distancing behaviors. Results reveal coverage from the right leaning outlets downplayed the virus and highlighted the consequences of lockdowns on the economy. Our survey findings show that even after accounting for a range of demographic, political orientation, and COVID-19 awareness variables, conservative media use was linked, although modestly, with a lower likelihood of social distancing behavior. Our findings echo past research on media framing of pandemics and their association with public attitudes and behavior. [ABSTRACT FROM AUTHOR]

Understanding the implications of aggressive political debate style amid corrosive modes of campaign politics requires fine-grained analyses of political performance, attending to multiple communication modalities. Politicians’ facial expressions, emotional tone, and speech content can all independently convey aggression and dominance, and often work in combination for purposes of emphasis. Yet micro-coding individual visual, tonal, and verbal features across more than a handful of debate segments becomes extremely labor intensive, hampering research, especially historical, longitudinal, and cross-cultural work. To address this limitation, we develop a novel multimodal classifier using an Interaction Canonical Correlation Network (ICCN) that incorporates video and audio features with speech coding of candidate debate performance, trained on a 20% sample of 10- second segments from each of the first televised U.S presidential debates between 1980 and 2020. In the analysis, we demonstrate this classifier can accurately detect aggression by political candidates in U.S. debates. We sharpen its performance by distinguishing between debate eras characterized by lower and higher levels of aggression and validate the approach by comparing the performance of unimodal with multimodal classification. This classifier opens new avenues for computational social science research, including explaining candidate behavior within debates at a larger scale and across different eras. [ABSTRACT FROM AUTHOR]

This research considers how distinct news frames work in combination to influence information processing. It extends framing research grounded in prospect theory (Tversky & Kahneman, 1981) and attribution theory (Iyengar, 1991) to study conditional framing effects on associative memory. Using a 2 x 3 experimental design embedded within a probability survey (N = 379), tests examined the effects of two different frame dimensions--loss-gain and individual-societal--on the complexity of individuals' thoughts concerning the issue of urban growth. Findings indicate that news frames interact to generate more or less complex cognitive responses, with societal-gain frame combinations generating the most detailed cognitions about the causes, components, and consequences of urban growth. Directions for research on media framing are discussed.