Toddlers' preference for prosocial versus antisocial agents: No associations with empathy or attachment security

Research has indicated that the majority of infants and toddlers prefer prosocial to antisocial agents, but little research has examined interindividual differences in children's preference. This study examined whether 24-month-olds' (n = 107) sociomoral preference was associated with attachment security or empathy, assessed with the Attachment Q-Sort and the Empathy Questionnaire. Toddlers were presented with a puppet play, in which a protagonist tried to open a box and was helped by a prosocial agent and hindered by an antisocial agent. Then, toddlers were asked to pick up either the prosocial or the antisocial agent (manual choice), as a measure of their sociomoral preference. Of the 107 toddlers included in this study, 60.7% chose the prosocial over the antisocial agent. Neither empathy nor parent-child attachment was associated with children's preference. Our findings indicate a slight overall preference for the prosocial agent, but with notable interindividual differences not explained by empathy or attachment

The feasibility of using Apple's ResearchKit for recruitment and data collection: Considerations for mental health research

In 2015, Apple launched an open-source software framework called ResearchKit. ResearchKit provides an infrastructure for conducting remote, smartphone-based research trials through the means of Apple's App Store. Such trials may have several advantages over conventional trial methods including the removal of geographic barriers, frequent assessments of participants in real-life settings, and increased inclusion of seldom-heard communities. The aim of the current study was to explore the feasibility of participant recruitment and the potential for data collection in the non-clinical population in a smartphone-based trial using ResearchKit. As a case example, an app called eMovit, a behavioural activation (BA) app with the aim of helping users to build healthy habits was used. The study was conducted over a 9-month period. Any iPhone user with access to the App Stores of The Netherlands, Belgium, and Germany could download the app and participate in the study. During the study period, the eMovit app was disseminated amongst potential users via social media posts (Twitter, Facebook, LinkedIn), paid social media advertisements (Facebook), digital newsletters and newspaper articles, blogposts and other websites. In total, 1,788 individuals visited the eMovit landing page. A total of 144 visitors subsequently entered Apple's App Store through that landing page. The eMovit product page was viewed 10,327 times on the App Store. With 79 installs, eMovit showed a conversion rate of 0.76% from product view to install of the app. Of those 79 installs, 53 users indicated that they were interested to participate in the research study and 36 subsequently consented and completed the demographics and the participants quiz. Fifteen participants completed the first PHQ-8 assessment and one participant completed the second PHQ-8 assessment. We conclude that from a technological point of view, the means provided by ResearchKit are well suited to be integrated into the app process and thus facilitate conducting smartphone-based studies. However, this study shows that although participant recruitment is technically straightforward, only low recruitment rates were achieved with the dissemination strategies applied. We argue that smartphone-based trials (using ResearchKit) require a well-designed app dissemination process to attain a sufficient sample size. Guidelines for smartphone-based trial designs and recommendations on how to work with challenges of mHealth research will ensure the quality of these trials, facilitate researchers to do more testing of mental health apps and with that enlarge the evidence-base for mHealth

Positive Youth Development and Prosocial Behavior: A Systematic Review

Some literature indicated a link between prosocial behavior and positive youth development (PYD; Eisenberg & Fabes, 1998; Keyes, 1998; Domitrovich et al., 2017; Lam, 2012), however, findings so far have not yet been investigated in a systematic way. Therefore, the current study will provide a systematic review of existing literature on this relationship to provide an overview of the available evidence on this topic. With the use of a search string based on the Social Emotional Learning (SEL; Tolan et al., 2016) framework for PYD, existing literature on the relationship between prosocial behavior and PYD will be analyzed, evaluated and summarized. Additionally, we will investigate this relationship in antisocial youth specifically as well, since promotion of these constructs appears as highly valuable in this population. Specifically, prosocial behaviors can serve a protective function against delinquent and antisocial behavior (Carlo & Randall, 2014) and positive developmental experiences can provide youth with the relationships, opportunities and skills needed for social integration, which operate to reduce aggression and violence as well (Benson & Scales, 2009). This review will make the evidence on the relationship between prosocial behavior and PYD more accessible and provide support for the importance of promoting prosocial behavior and PYD, to foster healthy developmental trajectories

Effectiveness of ehealth interventions in improving treatment adherence for adults with obstructive sleep apnea:Meta-analytic review

Background: Poor adherence to continuous positive airway pressure (CPAP) treatment by adults with obstructive sleep apnea (OSA) is a common issue. Strategies delivered by means of information and communication technologies (ie, eHealth) can address treatment adherence through patient education, real-time monitoring of apnea symptoms and CPAP adherence in daily life, self-management, and early identification and subsequent intervention when device or treatment problems arise. However, the effectiveness of available eHealth technologies in improving CPAP adherence has not yet been systematically studied. Objective: This meta-analytic review was designed to investigate the effectiveness of a broad range of eHealth interventions in improving CPAP treatment adherence. Methods: We conducted a systematic literature search of the databases of Cochrane Library, PsycINFO, PubMed, and Embase to identify relevant randomized controlled trials in adult OSA populations. The risk of bias in included studies was examined using seven items of the Cochrane Collaboration risk-of-bias tool. The meta-analysis was conducted with comprehensive meta-analysis software that computed differences in mean postintervention adherence (MD), which was defined as the average number of nightly hours of CPAP use. Results: The meta-analysis ultimately included 18 studies (N=5429 adults with OSA) comprising 22 comparisons between experimental and control conditions. Postintervention data were assessed at 1 to 6 months after baseline, depending on the length of the experimental intervention. eHealth interventions increased the average nightly use of CPAP in hours as compared with care as usual (MD=0.54, 95% CI 0.29-0.79). Subgroup analyses did not reveal significant differences in effects between studies that used eHealth as an add-on or as a replacement to care as usual (P=.95), between studies that assessed stand-alone eHealth and blended strategies combining eHealth with face-to-face care (P=.23), or between studies of fully automated interventions and guided eHealth interventions (P=.83). Evidence for the long-term follow-up effectiveness of eHealth adherence interventions remains undecided owing to a scarcity of available studies and their mixed results. Conclusions: eHealth interventions for adults with OSA can improve adherence to CPAP in the initial months after the start of treatment, increasing the mean nightly duration of use by about half an hour. Uncertainty still exists regarding the timing, duration, intensity, and specific types of eHealth interventions that could be most effectively implemented by health care providers

Effectiveness of eHealth interventions in improving medication adherence for patients with chronic obstructive pulmonary disease or asthma: Systematic review

Background: Poor treatment adherence in patients with chronic obstructive pulmonary disease (COPD) or asthma is a global public health concern with severe consequences in terms of patient health and societal costs. A potentially promising tool for addressing poor compliance is eHealth. Objective: This review investigates the effects of eHealth interventions on medication adherence in patients with COPD or asthma. Methods: A systematic literature search was conducted in the databases of Cochrane Library, PsycINFO, PubMed, and Embase for studies with publication dates between January 1, 2000, and October 29, 2020. We selected randomized controlled trials targeting adult patients with COPD or asthma, which evaluated the effectiveness of an eHealth intervention on medication adherence. The risk of bias in the included studies was examined using the Cochrane Collaboration's risk of bias tool. The results were narratively reviewed. Results: In total, six studies focusing on COPD and seven focusing on asthma were analyzed. Interventions were mostly internet-based or telephone-based, and could entail telemonitoring of symptoms and medication adherence, education, counseling, consultations, and self-support modules. Control groups mostly comprised usual care conditions, whereas a small number of studies used a face-to-face intervention or waiting list as the control condition. For COPD, the majority of eHealth interventions were investigated as an add-on to usual care (5/6 studies), whereas for asthma the majority of interventions were investigated as a standalone intervention (5/7 studies). Regarding eHealth interventions targeting medication adherence for COPD, two studies reported nonsignificant effects, one study found a significant effect in comparison to usual care, and three reported mixed results. Of the seven studies that investigated eHealth interventions targeting medication adherence in asthma, three studies found significant effects, two reported nonsignificant effects, and two reported mixed effects. Conclusions: The mixed results on the effectiveness of eHealth interventions in improving treatment adherence for asthma and COPD are presumably related to the type, context, and intensity of the interventions, as well as to differences in the operationalization and measurement of adherence outcomes. Much remains to be learned about the potential of eHealth to optimize treatment adherence in COPD and asthma

Short- and long-term effects of digital prevention and treatment interventions for cannabis use reduction:A systematic review and meta-analysis

Background: Frequent Cannabis use has been linked to a variety of negative mental, physical, and social consequences. We assessed the effects of digital prevention and treatment interventions on Cannabis use reduction in comparison with control conditions. Methods: Systematic review with two separate meta-analyses. Thirty randomized controlled trials met the inclusion criteria for the review, and 21 were included in the meta-analyses. Primary outcome was self-reported Cannabis use at post-treatment and follow-up. Hedges's g was calculated for all comparisons with non-active control. Risk of bias was examined with the Cochrane risk-of-bias tool. Results: The systematic review included 10 prevention interventions targeting 8138 participants (aged 12 to 20) and 20 treatment interventions targeting 5195 Cannabis users (aged 16 to 40). The meta-analyses showed significantly reduced Cannabis use at post-treatment in the prevention interventions (6 studies, N = 2564, g = 0.33; 95% CI 0.13 to 0.54, p = 0.001) and in the treatment interventions (17 comparisons, N = 3813, g = 0.12; 95% CI 0.02 to 0.22, p = 0.02) as compared with controls. The effects of prevention interventions were maintained at follow-ups of up to 12 months (5 comparisons, N = 2445, g = 0.22; 95% CI 0.12 to 0.33, p < 0.001) but were no longer statistically significant for treatment interventions. Conclusions: Digital prevention and treatment interventions showed small, significant reduction effects on Cannabis use in diverse target populations at post-treatment compared to controls. For prevention interventions, the post-treatment effects were maintained at follow-up up to 12 months later