Project description:mHealth interventions can help to improve the physical well-being of participants. Unfortunately, mHealth interventions often have low adherence and high attrition. One possible way to increase adherence is instructing participants to complete self-affirmation exercises. Self-affirmation exercises have been effective in increasing many types of positive behaviors. However, self-affirmation exercises often involve extensive essay writing, a task that is not easy to complete on mobile platforms.This study aimed to adapt a self-affirmation exercise to a form better suited for delivery through a mobile app targeting healthy eating behaviors, and to test the effect of differing self-affirmation doses on adherence to behavior change goals over time.We examined how varied self-affirmation doses affected behavior change in an mHealth app targeting healthy eating that participants used for 28 days. We divided participants into the 4 total conditions using a 2×2 factorial design. The first independent variable was whether the participant received an initial self-affirmation exercise. The second independent variable was whether the participant received ongoing booster self-affirmations throughout the 28-day study. To examine possible mechanisms through which self-affirmation may cause positive behavior change, we analyzed three aspects of self-affirmation effects in our research. First, we analyzed how adherence was affected by self-affirmation exercises. Second, we analyzed whether self-affirmation exercises reduced attrition rates from the app. Third, we examined a model for self-affirmation behavior change.Analysis of 3556 observations from 127 participants indicated that higher doses of self-affirmation resulted in improved adherence to mHealth intervention goals (coefficient 1.42, SE 0.71, P=.04). This increased adherence did not seem to translate to a decrease in participant attrition (P value range .61-.96), although our definition of attrition was conservative. Finally, we examined the mechanisms by which self-affirmation may have affected intentions of behavior change; we built a model of intention (R2=.39, P<.001), but self-affirmation did not directly affect final intentions (P value range .09-.93).Self-affirmations can successfully increase adherence to recommended diet and health goals in the context of an mHealth app. However, this increase in adherence does not seem to reduce overall attrition. The self-affirmation exercises we developed were simple to implement and had a low cost for both users and developers. While this study focused on an mHealth app for healthy eating, we recommend that other mHealth apps integrate similar self-affirmation exercises to examine effectiveness in other behaviors and contexts.

Project description:BackgroundHealthcare providers frequently engage patients in conversations about health behavior change and are encouraged to use patient-centered approaches, such as Motivational Interviewing. Training in and sustainment of these skills are known to require feedback based on actual or role-played patient encounters. The behavior change counseling index (BECCI) is a pragmatic measure to assess healthcare providers' patient-centered behavior change counseling skills that was developed as an alternative to resource-intensive "gold standard" measures, which are difficult to use in routine practice. We are not aware of any studies that examine the criterion-related validity of this measure using an alternative gold standard measure. We examined the criterion-related validity of the BECCI as rated by a simulated patient actor immediately after a brief behavior change intervention role-play using objective ratings on the motivational interviewing treatment integrity (MITI) scale.MethodsWe conducted a secondary analysis of data from a 25-site clinical trial of screening and intervention for posttraumatic stress disorder and comorbidities with patients at level I trauma centers in the USA. Participants were 64 providers representing diverse professional roles trained to deliver a multi-component intervention with study patients. As part of the training, providers role-played counseling a patient to reduce risky alcohol use with a simulated patient actor. These 20-min role-plays were conducted by telephone and audio recorded. Immediately after the role-play, the simulated patient actor rated the quality of the providers' patient-centered behavior change counseling skills using the BECCI. A third-party expert MITI rater later listened to the audio recordings of the role-plays and rated the quality of the providers' patient-centered behavior change counseling skills using the MITI 3.1.1.ResultsAll correlations observed were statistically significant. The overall BECCI score correlated strongly (≥ 0.50) with five of the six MITI scores and moderately (0.33) with MITI percent complex reflections.ConclusionsThis study provides evidence of criterion-related validity of the BECCI with a sample of healthcare providers representing a range of professional roles. Simulated patient actor rating using the BECCI is a pragmatic approach to assessing the quality of brief behavior change interventions delivered by healthcare providers.

Project description:National Eating Disorders Association conducts a NEDAwareness week every year, during which it publishes content on social media and news aimed to raise awareness of eating disorders. Measuring the impact of these actions is vital for maximizing the effectiveness of such interventions. This study is an effort to empirically measure the change in behavior of users who engage with NEDAwareness content, and compare the detected changes between campaigns in two different years. We analyze a total of 35,895 tweets generated during two campaigns of NEDAwareness campaigns in 2019 and 2020. In order to assess the reach of each campaign, we consider the users participating in the campaigns and their number of followers, as well as retweeting engagement. We use the Linguistic Inquiry and Word Count (LIWC) text modeling and causal impact analysis in order to gauge the change in self-expression of users who have interacted with the NEDAwareness content, compared to a baseline group of users. We further enrich our understanding of the users by extracting gender information from their display names. We find that, despite large media corporations (such as MTV and Teen Vogue) participating in the campaign, it is governmental and nonprofit accounts who are among the accounts that attract the most retweets. Whereas the most influential accounts were well-connected in 2019, the 2020 campaign saw little retweeting between such accounts, negatively impacting the reach of the material. Both campaigns engaged women at around 40% and men 17%, supporting previous research showing women to be more likely to share their experiences with eating disorders. Further, women were more likely to mention other health topics within the 15 days of the intervention, including pregnancy and abortion, as well as depression and anxiety, and to discuss the developing COVID pandemic in 2020. Despite the positive message of the campaign, we find that the users who have engaged with this content were more likely to mention the linguistic categories concerning anxiety and risk. Thus, we illustrate the complex, gender-specific effects of NEDAwareness online health intervention campaign on the continued self-expression of its audience and provide actionable insights for potential improvement of such public health efforts.

Project description:BackgroundSocial media public health campaigns have the advantage of tailored messaging at low cost and large reach, but little is known about what would determine their feasibility as tools for inducing attitude and behavior change.ObjectiveThe aim of this study was to test the feasibility of designing, implementing, and evaluating a social media-enabled intervention for skin cancer prevention.MethodsA quasi-experimental feasibility study used social media (Twitter) to disseminate different message "frames" related to care in the sun and cancer prevention. Phase 1 utilized the Northern Ireland cancer charity's Twitter platform (May 1 to July 14, 2015). Following a 2-week "washout" period, Phase 2 commenced (August 1 to September 30, 2015) using a bespoke Twitter platform. Phase 2 also included a Thunderclap, whereby users allowed their social media accounts to automatically post a bespoke message on their behalf. Message frames were categorized into 5 broad categories: humor, shock or disgust, informative, personal stories, and opportunistic. Seed users with a notable following were contacted to be "influencers" in retweeting campaign content. A pre- and postintervention Web-based survey recorded skin cancer prevention knowledge and attitudes in Northern Ireland (population 1.8 million).ResultsThere were a total of 417,678 tweet impressions, 11,213 engagements, and 1211 retweets related to our campaign. Shocking messages generated the greatest impressions (shock, n=2369; informative, n=2258; humorous, n=1458; story, n=1680), whereas humorous messages generated greater engagement (humorous, n=148; shock, n=147; story, n=117; informative, n=100) and greater engagement rates compared with story tweets. Informative messages, resulted in the greatest number of shares (informative, n=17; humorous, n=10; shock, n=9; story, n=7). The study findings included improved knowledge of skin cancer severity in a pre- and postintervention Web-based survey, with greater awareness that skin cancer is the most common form of cancer (preintervention: 28.4% [95/335] vs postintervention: 39.3% [168/428] answered "True") and that melanoma is most serious (49.1% [165/336] vs 55.5% [238/429]). The results also show improved attitudes toward ultraviolet (UV) exposure and skin cancer with a reduction in agreement that respondents "like to tan" (60.5% [202/334] vs 55.6% [238/428]).ConclusionsSocial media-disseminated public health messages reached more than 23% of the Northern Ireland population. A Web-based survey suggested that the campaign might have contributed to improved knowledge and attitudes toward skin cancer among the target population. Findings suggested that shocking and humorous messages generated greatest impressions and engagement, but information-based messages were likely to be shared most. The extent of behavioral change as a result of the campaign remains to be explored, however, the change of attitudes and knowledge is promising. Social media is an inexpensive, effective method for delivering public health messages. However, existing and traditional process evaluation methods may not be suitable for social media.

Project description:Antimicrobial resistance (AMR) is an economic, food security, and global health threat accelerated by a multitude of factors including the overuse and misuse of antimicrobials in the human health, animal health, and agriculture sectors. Given the rapid emergence and spread of AMR and the relative lack of development of new antimicrobials or alternative therapies, there is a need to develop and implement non-pharmaceutical AMR mitigation policies and interventions that improve antimicrobial stewardship (AMS) practices across all sectors where antimicrobials are used. We conducted a systematic literature review per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify peer-reviewed studies that described behavior-change interventions that aimed to improve AMS and/or reduce inappropriate antimicrobial use (AMU) among human health, animal health, and livestock agriculture stakeholders. We identified 301 total publications- 11 in the animal health sector and 290 in the human health sector-and assessed described interventions using metrics across five thematic areas- (1) AMU, (2) adherence to clinical guidelines, (3) AMS, (4) AMR, and (5) clinical outcomes. The lack of studies describing the animal health sector precluded a meta-analysis. Variation across intervention type, study type, and outcome precluded a meta-analysis for studies describing the human health sector; however, a summary descriptive analysis was conducted. Among studies in the human health sector, 35.7% reported significant (p<0.05) pre- to post-intervention decreases in AMU, 73.7% reported significant improvements in adherence of antimicrobial therapies to clinical guidelines, 45% demonstrated significant improvements in AMS practices, 45.5% reported significant decreases in the proportion of isolates that were resistant to antibiotics or the proportion of patients with drug-resistant infections across 17 antimicrobial-organism combinations. Few studies reported significant changes in clinical outcomes. We did not identify any overarching intervention type nor characteristics associated with successful improvement in AMS, AMR, AMU, adherence, nor clinical outcomes.

Project description:ObjectiveTo test effectiveness of the LEAP (Learn Engage Act Process) Program on engaging frontline Veteran Health Administration (VHA) medical center teams in continuous quality improvement (QI), a core capability for learning health systems.Data sources and study settingData sources included VHA electronic health record (EHR) data, surveys, and LEAP coaching field notes.Study designA staggered difference-in-differences study was conducted. Fifty-five facilities participated in LEAP across eight randomly assigned clusters of 6-8 facilities per cluster over 2 years. Non-participating facilities were used as controls. A MOVE! weight management program team completed a Plan-Do-Study-Act cycle of change supported by learning curriculum, coaching, and virtual collaboratives in LEAP facilities. Primary outcome was program reach to Veterans. A mixed-effects model compared pre- versus post-LEAP periods for LEAP versus control facilities. LEAP adherence, satisfaction, and cost to deliver LEAP were evaluated.Data collection/extraction methodsThirty months of facility-level EHR MOVE! enrollment data were included in analyses. LEAP Satisfaction and QI skills were elicited via surveys at baseline and 6-month post-LEAP.Principal findingsFifty-five facilities were randomly assigned to eight time-period-based clusters to receive LEAP (71% completed LEAP) and 82 non-participating facilities were randomly assigned as controls. Reach in LEAP and control facilities was comparable in the 12-month pre-LEAP period (p = 0.07). Though LEAP facilities experienced slower decline in reach in the 12-month post-LEAP period compared with controls (p < 0.001), this is likely due to unexplained fluctuations in controls. For LEAP facilities, satisfaction was high (all mean ratings >4 on a 5-point scale), self-reported use of QI methods increased significantly (p-values <0.05) 6 months post-LEAP, and delivery cost was $4024 per facility-based team.ConclusionControl facilities experienced declining reach in the 12-month post-LEAP period, but LEAP facilities did not, plus they reported higher engagement in QI, an essential capability for learning health systems.

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How Donors Can Collaborate to Improve Reach, Quality, and Impact in Social and Behavior Change for Health.

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How Donors Can Collaborate to Improve Reach, Quality, and Impact in Social and Behavior Change for Health.

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