Screen media exposure and young children's vocabulary learning and development: A meta-analysis.

This meta-analysis synthesizes research on media use in early childhood (0-6 years), word-learning, and vocabulary size. Multi-level analyses included 266 effect sizes from 63 studies (Ntotal = 11,413) published between 1988-2022. Among samples with information about race/ethnicity (51%) and sex/gender (73%), most were majority White/Non-Hispanic and between 40%-60% female. Analyses revealed a small overall positive relation between screen media exposure and vocabulary (r = .23). Experimental studies yielded a small-to-medium effect (r = .30), with stronger effects for e-books than TV/video or games/apps, and non-significant effects for video chat. In correlational studies, there was no overall association between vocabulary size and naturalistic media exposure (r = .07), with the exception of naturalistic exposure to educational media (r = .17).

Using Smart Displays to Implement an eHealth System for Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial.

BACKGROUND: Voice-controlled smart speakers and displays have a unique but unproven potential for delivering eHealth interventions. Many laptop- and smartphone-based interventions have been shown to improve multiple outcomes, but voice-controlled platforms have not been tested in large-scale rigorous trials. Older adults with multiple chronic health conditions, who need tools to help with their daily management, may be especially good candidates for interventions on voice-controlled devices because these patients often have physical limitations, such as tremors or vision problems, that make the use of laptops and smartphones challenging. OBJECTIVE: The aim of this study is to assess whether participants using an evidence-based intervention (ElderTree) on a smart display will experience decreased pain interference and improved quality of life and related measures in comparison with participants using ElderTree on a laptop and control participants who are given no device or access to ElderTree. METHODS: A total of 291 adults aged ≥60 years with chronic pain and ≥3 additional chronic conditions will be recruited from primary care clinics and community organizations and randomized 1:1:1 to ElderTree access on a smart display along with their usual care, ElderTree access on a touch screen laptop along with usual care, or usual care alone. All patients will be followed for 8 months. The primary outcomes are differences between groups in measures of pain interference and psychosocial quality of life. The secondary outcomes are between-group differences in system use at 8 months, physical quality of life, pain intensity, hospital readmissions, communication with medical providers, health distress, well-being, loneliness, and irritability. We will also examine mediators and moderators of the effects of ElderTree on both platforms. At baseline, 4 months, and 8 months, patients will complete written surveys comprising validated scales selected for good psychometric properties with similar populations. ElderTree use data will be collected continuously in system logs. We will use linear mixed-effects models to evaluate outcomes over time, with treatment condition and time acting as between-participant factors. Separate analyses will be conducted for each outcome. RESULTS: Recruitment began in August 2021 and will run through April 2023. The intervention period will end in December 2023. The findings will be disseminated via peer-reviewed publications. CONCLUSIONS: To our knowledge, this is the first study with a large sample and long time frame to examine whether a voice-controlled smart device can perform as well as or better than a laptop in implementing a health intervention for older patients with multiple chronic health conditions. As patients with multiple conditions are such a large cohort, the implications for cost as well as patient well-being are significant. Making the best use of current and developing technologies is a critical part of this effort. TRIAL REGISTRATION: ClinicalTrials.gov NCT04798196; https://clinicaltrials.gov/ct2/show/NCT04798196. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37522.

Effect of an eHealth intervention on older adults' quality of life and health-related outcomes: a randomized clinical trial.

BACKGROUND: By 2030, the number of US adults age ≥65 will exceed 70 million. Their quality of life has been declared a national priority by the US government. OBJECTIVE: Assess effects of an eHealth intervention for older adults on quality of life, independence, and related outcomes. DESIGN: Multi-site, 2-arm (1:1), non-blinded randomized clinical trial. Recruitment November 2013 to May 2015; data collection through November 2016. SETTING: Three Wisconsin communities (urban, suburban, and rural). PARTICIPANTS: Purposive community-based sample, 390 adults age ≥65 with health challenges. EXCLUSIONS: long-term care, inability to get out of bed/chair unassisted. INTERVENTION: Access (vs. no access) to interactive website (ElderTree) designed to improve quality of life, social connection, and independence. MEASURES: Primary outcome: quality of life (PROMIS Global Health). Secondary: independence (Instrumental Activities of Daily Living); social support (MOS Social Support); depression (Patient Health Questionnaire-8); falls prevention (Falls Behavioral Scale). Moderation: healthcare use (Medical Services Utilization). Both groups completed all measures at baseline, 6, and 12 months. RESULTS: Three hundred ten participants (79%) completed the 12-month survey. There were no main effects of ElderTree over time. Moderation analyses indicated that among participants with high primary care use, ElderTree (vs. control) led to better trajectories for mental quality of life (OR=0.32, 95% CI 0.10-0.54, P=0.005), social support received (OR=0.17, 95% CI 0.05-0.29, P=0.007), social support provided (OR=0.29, 95% CI 0.13-0.45, P<0.001), and depression (OR= -0.20, 95% CI -0.39 to -0.01, P=0.034). Supplemental analyses suggested ElderTree may be more effective among people with multiple (vs. 0 or 1) chronic conditions. LIMITATIONS: Once randomized, participants were not blind to the condition; self-reports may be subject to memory bias. CONCLUSION: Interventions like ET may help improve quality of life and socio-emotional outcomes among older adults with more illness burden. Our next study focuses on this population. TRIAL REGISTRATION: ClinicalTrials.gov ; registration ID number: NCT02128789.

A Web-Based eHealth Intervention to Improve the Quality of Life of Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial.

BACKGROUND: Multiple 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. OBJECTIVE: This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. METHODS: In 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. RESULTS: Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. CONCLUSIONS: With 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 REGISTRATION: ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/25175.

Effects of Web-Based Social Connectedness on Older Adults' Depressive Symptoms: A Two-Wave Cross-Lagged Panel Study.

BACKGROUND: Depressive 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. OBJECTIVE: This 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. METHODS: A 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. RESULTS: After controlling for the effect of offline support networks at t1, web-based message consumption at t1 decreased older adults' depressive symptoms at t2 (ß=-.11; P=.02), but web-based message production at t1 did not impact t2 depressive symptoms (ß=.12; P=.34). Web-based message consumption had a larger effect (ß=-.11; P=.02) than offline support networks (ß=-.08; P=.03) in reducing older adults' depressive symptoms over time. Higher baseline depressive symptoms did not predict increased web-based message consumption (ß=.12; P=.36) or production (ß=.02; P=.43) over time. CONCLUSIONS: The 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.

Preschoolers' choices of television characters as sources of information: Effects of character type, format, and topic domain.

Educational television (TV) for preschoolers often features unrealistic (anthropomorphic and/or animated) characters, and it is unclear how children perceive such characters as sources of information. In this study, 92 3- to 5-year-olds saw images of characters and chose which would be best for learning about six topics across three domains: animal biology, human biology, and socioemotional. Children were randomized to one of three conditions in which they chose between paired images of (1) live-action humans versus animated humans (i.e., holding character type constant and varying format), (2) animated humans versus animated anthropomorphic animals (i.e., holding format constant and varying character type), or (3) live-action humans versus animated anthropomorphic animals (i.e., most realistic vs. least realistic character choices). Results indicated that children chose animated characters over live-action characters (Conditions 1 and 3). They did not choose humans significantly more often than animals even for human biology and socioemotional lessons (Conditions 2 and 3). However, in Condition 2, they chose animals significantly more often than humans for animal biology lessons. In sum, children showed little sign of prioritizing realism. The study adds children's perspectives to the literature on the effects of reality cues on early learning from educational TV.

Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study.

BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: The outcomes according to the RE-AIM framework are as follows: Reach-Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness-Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption-Patients sustained high levels of Seva use-between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation-At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance-Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.

The Doctor Versus the Internet: Effects of Low-, Medium-, and High-Quality Websites on Intentions to Follow the Doctor's Advice.

How do patients respond when advice on health websites differs from advice given by a doctor? To test effects of advice concordance, 418 participants 25-80 years old were randomly assigned to read real websites that varied in quality of information about diabetes: high (medically accurate and complete), medium (accurate but incomplete), and low (inaccurate). The control group read travel sites. Participants then watched a video of a physician making treatment recommendations for a diabetic patient, and indicated how they would respond if they were the patient. There was no direct effect of condition on ratings of doctor credibility or intentions to adhere to the treatment plan, but there was an indirect effect: Those who read high-quality websites gave higher ratings of doctor-website concordance, which predicted greater confidence in the doctor's recommendations, which in turn predicted greater intention to comply.

The effect of bundling medication-assisted treatment for opioid addiction with mHealth: study protocol for a randomized clinical trial.

BACKGROUND: Opioid dependence has devastating and increasingly widespread consequences and costs, and the most common outcome of treatment is early relapse. People who inject opioids are also at disproportionate risk for contracting the human immunodeficiency virus (HIV) and hepatitis C virus (HCV). This study tests an approach that has been shown to improve recovery rates: medication along with other supportive services (medication-assisted treatment, or MAT) against MAT combined with a smartphone innovation called A-CHESS (MAT + A-CHESS). METHODS/DESIGN: This unblinded study will randomly assign 440 patients to receive MAT + A-CHESS or MAT alone. Eligible patients will meet criteria for having an opioid use disorder of at least moderate severity and will be taking methadone, injectable naltrexone, or buprenorphine. Patients with A-CHESS will have smartphones for 16 months; all patients will be followed for 24 months. The primary outcome is the difference between patients in the two arms in percentage of days using illicit opioids during the 24-month intervention. Secondary outcomes are differences between patients receiving MAT + A-CHESS versus MAT in other substance use, quality of life, retention in treatment, health service use, and, related to HIV and HCV, screening and testing rates, medication adherence, risk behaviors, and links to care. We will also examine mediators and moderators of the effects of MAT + A-CHESS. We will measure variables at baseline and months 4, 8, 12, 16, 20, and 24. At each point, patients will respond to a 20- to 30-min phone survey; urine screens will be collected at baseline and up to twice a month thereafter. We will use mixed-effects to evaluate the primary and secondary outcomes, with baseline scores functioning as covariates, treatment condition as a between-subject factor, and the outcomes reflecting scores for a given assessment at the six time points. Separate analyses will be conducted for each outcome. DISCUSSION: A-CHESS has been shown to improve recovery for people with alcohol dependence. It offers an adaptive and extensive menu of services and can attend to patients nearly as constantly as addiction does. This suggests the possibility of increasing both the effectiveness of, and access to, treatment for opioid dependence. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02712034 . Registered on 14 March 2016.

Implementing an mHealth system for substance use disorders in primary care: a mixed methods study of clinicians' initial expectations and first year experiences.

BACKGROUND: Millions of Americans need but don't receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs' implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients' health tracking and relapses. We examined (a) clinicians' initial perspectives about implementing Seva, and (b) the first year of implementation at Site 1. METHODS: Prior to staggered implementation at three FQHCs (Midwest city in WI vs. rural town in MT vs. metropolitan NY), interviews, meetings, and focus groups were conducted with 53 clinicians to identify core themes of initial expectations about implementation. One year into implementation at Site 1, clinicians there were re-interviewed. Their reports were supplemented by quantitative data on clinician and patient use of Seva. RESULTS: Clinicians anticipated that Seva could help patients and make behavioral health appointments more efficient, but they were skeptical that physicians would engage with Seva (given high caseloads), and they were uncertain whether patients would use Seva. They were concerned about legal obligations for monitoring patients' interactions online, including possible "cries for help" or inappropriate interactions. One year later at Site 1, behavioral health care providers, rather than physicians, had incorporated Seva into patient care, primarily by discussing it during appointments. Given workflow/load concerns, only a few key clinicians monitored health tracking/relapses and prompted outreach when needed; two researchers monitored the discussion board and alerted the clinic as needed. Clinician turnover/leave complicated this approach. Contrary to clinicians' initial concerns, patients showed sustained, mutually supportive use of Seva, with few instances of misuse. CONCLUSIONS: Results suggest the value of (a) focusing implementation on behavioral health care providers rather than physicians, (b) assigning a few individuals (not necessarily clinicians) to monitor health tracking, relapses, and the discussion board, (c) anticipating turnover/leave and having designated replacements. Patients showed sustained, positive use of Seva. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT01963234 ).

When meaning matters more: Media preferences across the adult life span.

Two studies considered age differences in the roles of emotion and meaningfulness in adults' media preferences. Socioemotional Selectivity Theory (SST) suggests that with increasing age, positive emotions become more meaningful, and emotional meaningfulness matters more for situation selection. Other developmental descriptions suggest that negative affect may be meaningful and interesting in youth. In Study 1, United States 18-86 year olds read descriptions of TV programs that varied in levels of warmth, funniness, sadness, and fright; in Study 2, United States and German 18-82 year olds watched film trailers that varied in levels of gore and meaningfulness. Participants rated their anticipated emotions, anticipated meaningfulness of the content, and their viewing interest. Consistent with SST, in both studies, anticipated meaningfulness was a stronger predictor of viewing interest for older adults relative to younger adults, and the indirect path (Emotion → Meaning → Interest) was stronger for older relative to younger adults. In Study 1, warmth (but not funniness) was more predictive of meaningfulness for older relative to younger adults; sadness and fear were not more predictive of meaningfulness for younger adults. In Study 2, there were age differences in the effects of fright on interest, in part via effects on anticipated fun and suspense (but not arousal). Overall, the results provide limited evidence that positive or negative emotions are more meaningful or interesting at different ages. However, they support the argument that emotional meaningfulness matters more to older than to younger adults. (PsycINFO Database Record

"Vámonos means go, but that's made up for the show": reality confusions and learning from educational TV.

Educational television for young children often combines factual content with fantasy. In 2 experiments, we examined 3- to 5-year-olds' reality judgments and the implications for their learning. In the 1st study, 145 children watched 3 clips featuring (respectively) a Hispanic, a Chinese American, and an Anglo character. Responses indicated age differences in character-reality judgments (e.g., "X can hear me"), acceptance of fantasy (e.g., talking backpacks), rejection of factual content (i.e., Spanish and Chinese words are "just pretend") but not perceived learning. Perceived reality of Chinese and Spanish words used by the characters partially mediated age differences in word comprehension, controlling for viewer ethnicity. In the 2nd study, 114 children were randomly assigned to see clips featuring either Hispanic or Chinese traditions and words. Age differences in reality judgments were replicated and were partially mediated by children's use of evidence or arguments to justify reality judgments and (to a lesser extent) by their cognitive flexibility. Further, children's reality judgments partially mediated age differences in learning of the educational content. Results suggest that reality distinctions improve with age, contributing to children's learning. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Integrating addiction treatment into primary care using mobile health technology: protocol for an implementation research study.

BACKGROUND: Healthcare reform in the United States is encouraging Federally Qualified Health Centers and other primary-care practices to integrate treatment for addiction and other behavioral health conditions into their practices. The potential of mobile health technologies to manage addiction and comorbidities such as HIV in these settings is substantial but largely untested. This paper describes a protocol to evaluate the implementation of an E-Health integrated communication technology delivered via mobile phones, called Seva, into primary-care settings. Seva is an evidence-based system of addiction treatment and recovery support for patients and real-time caseload monitoring for clinicians. METHODS/DESIGN: Our implementation strategy uses three models of organizational change: the Program Planning Model to promote acceptance and sustainability, the NIATx quality improvement model to create a welcoming environment for change, and Rogers's diffusion of innovations research, which facilitates adaptations of innovations to maximize their adoption potential. We will implement Seva and conduct an intensive, mixed-methods assessment at three diverse Federally Qualified Healthcare Centers in the United States. Our non-concurrent multiple-baseline design includes three periods - pretest (ending in four months of implementation preparation), active Seva implementation, and maintenance - with implementation staggered at six-month intervals across sites. The first site will serve as a pilot clinic. We will track the timing of intervention elements and assess study outcomes within each dimension of the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, including effects on clinicians, patients, and practices. Our mixed-methods approach will include quantitative (e.g., interrupted time-series analysis of treatment attendance, with clinics as the unit of analysis) and qualitative (e.g., staff interviews regarding adaptations to implementation protocol) methods, and assessment of implementation costs. DISCUSSION: If implementation is successful, the field will have a proven technology that helps Federally Qualified Health Centers and affiliated organizations provide addiction treatment and recovery support, as well as a proven strategy for implementing the technology. Seva also has the potential to improve core elements of addiction treatment, such as referral and treatment processes. A mobile technology for addiction treatment and accompanying implementation model could provide a cost-effective means to improve the lives of patients with drug and alcohol problems. TRIAL REGISTRATION: ClinicalTrials.gov (NCT01963234).