Service evaluation of a digital behavioural change programme

Role of Intervention Strategies for At-risk Preterm Infants

20.3 REMOTE COACHING AND TECHNOLOGY FOR TRAINING COMMUNITY HEALTH WORKERS TO TREAT DEPRESSION IN PRIMARY CARE: CASE EXAMPLE FROM INDIA AND OPPORTUNITIES TO SCALE UP MENTAL HEALTH CARE GLOBALLY

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Advocacy groups on both sides of the guns issue frequently point to changing personal behavior--of both parents and children--as a key element in reducing gun violence among youth. Efforts to bring about these changes range from community-based campaigns, to laws and programs that encourage parents to store their guns safely, to educational initiatives that focus on keeping young children away from guns and encouraging youth to resolve disputes without violence. Unfortunately, these behavior-oriented programs have not shown great success in reducing youth gun violence. This article reviews the research surrounding behavioral approaches to gun violence prevention and highlights obstacles that hamper the effectiveness of these programs. Supportive communities can play a key role in protecting youth from violence in general, but the few community-based violence prevention programs that focus on youth have not been shown to decrease youth access to or use of guns. By and large, behavioral programs and legal interventions aimed at parents have not been proven to reduce youth gun violence. This may be due in part to parental misperceptions about children's risk of injury and ability to protect themselves. Children and youth are particularly difficult targets for behavioral change programs. Cognitive immaturity among younger children and perceptions of invulnerability among adolescents may be part of the reason. Most programs that seek to persuade youth to stay away from guns have not been proven effective. The author concludes that, although behavioral programs could be improved, overall they hold only limited promise for reducing youth gun violence.

While weight loss is the primary focus of weight management programmes, it is important that service users establish healthier eating habits to support overall long-term health and weight loss maintenance. Many dietary plans and weight loss programmes are now available, particularly in the digital landscape, but few offer insights into their users’ dietary intakes while following these programmes, and whether they support individuals with meeting dietary recommendations. Slimming World Online, delivered through a website and app, supports members with weight loss through a healthy eating plan, an activity programme, and an online community. This research aims to evaluate the nutrient intakes of members following Slimming World’s digital programme, and compare intakes to UK dietary recommendations and current intakes of the general UK population.Adults who had been members of Slimming World Online for at least 4 weeks were invited to complete a short survey and use a validated online dietary assessment tool, myfood24®, via an advert on the online member website. Food and drink intake over a 3-day period (2 weekdays and 1 weekend day) was collected and compared against UK dietary recommendations and mean general population intakes, as reported in the National Diet and Nutrition Survey (NDNS)(1).61 adults (95.1% female; mean age 51.7±10.5 years) who completed the survey and all food diaries were included in the analysis. Mean daily energy intake was 1424.0±457.8kcal. Compared to the UK general population, members were consuming a lower proportion of energy from fat (25.5% vs 34.1%) and saturated fat (8.6% vs 12.3%). Intakes were in line with UK recommendations of <35.0% and <11.0% of total daily energy respectively. Members were consuming a greater proportion of total daily energy from protein than the general population (25.4% vs 17.0%). Mean protein intake was 90.6±32.0g/day, higher than general population intakes of 76.0g/day. Members, on average, were consuming 8.4±4.9 portions of vegetables and fruit/day, with 68.9% meeting the ‘5 a day’ recommendation, compared to 33.0% of the general population. Mean fibre intake was higher than the general population (27.2±12.9g vs 19.7±8.4g/day), while mean salt intake was in line with UK recommendations of <6g/day and lower than the general population (5.3±2.6g vs 8.4±4.1g/day).In addition to having a reduced energy intake necessary for weight loss, members of Slimming World’s digital programme are consuming a diet which meets current UK dietary guidelines and is of better nutritional quality than that of the general UK population. Limitations include potential underreporting of intakes, the small sample size for males and slight differences to the data collection methodology of the NDNS, who use a 4-day food diary. Further research will aim to address these limitations.

The Canadian Cancer Society’s Centre for Behavioural Research and Program Evaluation (CBRPE) is a national asset for building pan-Canadian capacity to support intervention studies that guide population-level policies and programs. This paper briefly describes CBRPE’s experience in advancing this work in the field of prevention. The aim is to illuminate issues of central importance for advancing the goals of the Population Health Intervention Research Initiative for Canada. According to our experience, success in building the population intervention field will depend heavily on purposeful alignment across organizations to enable integration of research, evaluation, surveillance, policy and practice. CBRPE’s capacity development roles include a) a catalytic role in shaping this aligned inter-organizational milieu and b) investing our resources in building tangible assets (teams, indicators, data systems) that contribute relevant capacities within this emerging milieu. Challenges in building capacity in this field are described.

12070 Background: Post-diagnosis weight gain is common among women with early-stage breast cancer and is associated with increased risk of recurrence, breast cancer death, and all-cause mortality. Intentional weight loss following diagnosis is difficult to maintain. Targeted lifestyle interventions focusing on behavioral changes and education that can be implemented long-term are needed. Methods: This was a prospective single-arm pilot study in patients with history of early-stage breast cancer (NCT04753268). Key eligibility criteria included body mass index (BMI) ≥27.5 kg/m2, stage I-III breast cancer, and completion of active cancer treatment ≥6 months prior to study enrollment. Patients were recruited at the Dempsey Center in Lewiston, ME and via social media. Participants were given access to the Noom mobile application, which utilizes cognitive behavioral therapy, motivational interviewing, and self-determination theory to induce behavior change using an educational curriculum of daily articles, virtual health coaching, social networking, food records, and physical activity logs. The primary endpoint was change in self-reported weight from baseline to 26 weeks. Secondary endpoints included change in physical activity measured using step count and the Global Physical Activity Questionnaire (GPAQ), change in diet patterns analyzed using the Nutrition Data System for Research, patient-reported outcome (PRO) measures, and metrics for engagement with the mobile application. Results: 31 patients were enrolled; 24 at the Dempsey Center and 7 via social media. Mean age was 56.8 and mean baseline BMI was 33.5 kg/m2. Mean weight change was -4.8 kg (range +0.6 to -19.9 kg, p < 0.001) and mean percent weight change was -5.6%; 11/31 patients (35.5%) lost ≥5% of their initial weight. Average daily step count increased by 54.7% (p = 0.004). Mean GPAQ score for physical activity increased from 990 to 1773 (p = 0.01), and the proportion of patients who met physical activity guidelines increased from 45.1% to 74.2%. Mean energy intake did not change significantly over 26 weeks (p = 0.779). Improvements were observed in PROMIS-Physical Functioning T-scores and Body Image Scale scores (p = 0.04, p < 0.001 respectively). Metrics of engagement with Noom that were predictive of weight loss ≥5% included total articles read (p = 0.012), total weights logged (p = 0.006), total food records logged (p = 0.001), messages sent to coach (p = 0.001), and number of times the application was opened (p = 0.014). Conclusions: In this pilot study, breast cancer survivors lost weight and became more physically active using a commercially-available mobile application. This digital weight loss program is a scalable intervention, and these findings support future studies investigating impact on breast cancer outcomes. Clinical trial information: NCT04753268 .

Background: We asked whether the integration of digital behavioral counseling with employer-sponsored annual biometric screening could reduce the risk of obesity-related chronic disease in a U.S. workforce. Methods: We evaluated a cohort (n=113) who participated in an employer-sponsored annual wellness program with year-end biometric screening and enrolled in a digital behavioral counseling program. Individuals were included in the analysis if they participated in the wellness program in 2015, had prediabetes (fasting glucose (FG) 100 to 125mg/dL or Hb1Ac 5.7 to 6.4%) and a BMI ≥25 kg/m2 in 2016, and agreed to participate in a digital behavioral counseling program followed by year-end biometric screening in 2017. Results: The participants were 75% women and 61% Caucasian, 28% African American. At the 2016 year-end biometric screening, which preceded digital behavioral counseling, the characteristics of the cohort (mean± sd) were age, 50.0±9.9 years; BMI, 37.1±8.6 kg/m2; Hb1Ac, 6.1±0.6%; and FG, 106.9±24.2 mg/dL. Following behavioral counseling, 28% of the participants lost 5% or more of body weight. Hb1Ac and FG levels both fell below prediabetic thresholds for 32% of the participants. Other biometric outcome measures improved (Table). Conclusions: Digital behavioral counseling was effective in reducing risk for both diabetes and cardiovascular disease in a workforce cohort.Change in annual biometric screening resultsThe year preceding counseling (2015 to 2016)The year counseling received (2016 to 2017)P value (paired t-Test)BMI (kg/m2)+0.66-1.18<0.0001Hb1Ac (%)+0.06-0.220.001Fasting Glucose (mg/dL)+5.85-2.840.02Triglycerides (mg/dL)+12.0-17.20.0110-year ASCVD risk* (%)+1.83-0.480.01*Atherosclerotic Cardiovascular Disease risk (2013 ACC/AHA Cardiovascular Risk Guideline) Disclosure C.E. Birse: Employee; Self; Quest Diagnostics. Stock/Shareholder; Self; Quest Diagnostics. R.J. Lagier: Employee; Self; Quest Diagnostics. P. Chew: Employee; Self; Omada Health, Inc. C.B. Jasik: Employee; Self; Omada Health, Inc. E.N. Madero: Employee; Self; Omada Health, Inc..

Objective To evaluate whether a multifaceted behavioural change programme increases physical activities in patients with Parkinson’s disease.Design Multicentre randomised controlled trial.Setting 32 community hospitals in the Netherlands, collaborating in a...

BackgroundDigital health programs, which encompass the subsectors of health information technology, mobile health, electronic health, telehealth, and telemedicine, have the potential to generate “big data.”ObjectiveOur aim is to evaluate two digital health programs in India—the maternal mobile messaging service (Kilkari) and the mobile training resource for frontline health workers (Mobile Academy). We illustrate possible applications of machine learning for public health practitioners that can be applied to generate evidence on program effectiveness and improve implementation. Kilkari is an outbound service that delivers weekly gestational age–appropriate audio messages about pregnancy, childbirth, and childcare directly to families on their mobile phones, starting from the second trimester of pregnancy until the child is one year old. Mobile Academy is an Interactive Voice Response audio training course for accredited social health activists (ASHAs) in India.MethodsStudy participants include pregnant and postpartum women (Kilkari) as well as frontline health workers (Mobile Academy) across 13 states in India. Data elements are drawn from system-generated databases used in the routine implementation of programs to provide users with health information. We explain the structure and elements of the extracted data and the proposed process for their linkage. We then outline the various steps to be undertaken to evaluate and select final algorithms for identifying gaps in data quality, poor user performance, predictors for call receipt, user listening levels, and linkages between early listening and continued engagement.ResultsThe project has obtained the necessary approvals for the use of data in accordance with global standards for handling personal data. The results are expected to be published in August/September 2019.ConclusionsRigorous evaluations of digital health programs are limited, and few have included applications of machine learning. By describing the steps to be undertaken in the application of machine learning approaches to the analysis of routine system-generated data, we aim to demystify the use of machine learning not only in evaluating digital health education programs but in improving their performance. Where articles on analysis offer an explanation of the final model selected, here we aim to emphasize the process, thereby illustrating to program implementors and evaluators with limited exposure to machine learning its relevance and potential use within the context of broader program implementation and evaluation.International Registered Report Identifier (IRRID)DERR1-10.2196/11456

A content analysis of written behavior management programs

The field of program, services and technology evaluation in general, and in health care in particular, is going through an important growth and conceptual and methodological diversification. It is also the object of an increasing demand for its participation as an effective supportive instrument in the decision-making process, and a constant need in the dynamics of health systems and services. In this paper, based on literature review, nuclear criteria involved in the organization of all evaluation processes are identified, and articulated with the existing institutionalized evaluation practices in developed countries, that is, program evaluation, quality assessment and management and technology assessment. In conclusion, the incipient development of a methodological evaluation output in Brazil is analyzed.

This research aims to measure how big the results of evaluating online (online) based learning programs are to increase the digital literacy of students at the Khodijah girls' Islamic boarding school. Increasing digital literacy is very important in the current information era, considering the role of Islamic boarding schools in preparing students to face global challenges. The evaluation method applied uses the CIPP (Context, Input, Process, Product) model with a qualitative descriptive approach Data collected through direct observation (case study) and library studies by several books and journals. Research discusses 1). evaluation of online learning programs, 2). The models used in evaluating, one of which is learning used by the CIPP (Context, Input, Process, Product) model, and 3). challenges and opportunities in implementing digital students. 3). Preparing students to fight in the digital world. The research results show that online learning in Islamic boarding schools faces various challenges, such as limited infrastructure and human resource readiness, but also opens up great opportunities in developing digital-based da'wah and learning methods. This evaluation confirms the importance of support for digital literacy programs in Islamic boarding school environments as a strategy to prepare students to face the challenges of the digital era. Researchers hope that the results of this study can contribute as additional insight and reference for the development of Islamic boarding school education in the future.

The teacher-led implementation of healthy eating programs in schools is cost-effective and potentially impactful. Teacher acceptability is important for uptake; however, process evaluations are scarce. This study evaluated the effect of two intensities of teacher training on the evaluation of a vegetable education program for Australian primary schools by teachers. The teachers (n = 65) who implemented the program as part of a cluster RCT (25 schools in two states, New South Wales and South Australia) received either low- (provision with materials and online training) or high (additional face-to-face (F2F) training)-intensity training prior to implementing a 5-week vegetable education program. They evaluated the acceptability of a digital training module and program by indicating the level of agreement with 15 and 18 statements, respectively, using 5-point Likert scales. The average item scores ranged from 3.0 to 4.2. All but one item, including student engagement, alignment to the curriculum and intent for reuse of the program, had a rounded average or median score of 4. The level of training intensity did not impact the teacher acceptability ratings. In conclusion, the teacher acceptability was good, and additional F2F training does not add value above the solely digital training of the teachers.

A strong cooperative bond between the patient and provider ("therapeutic alliance") is robustly associated with better alcohol use disorder (AUD) treatment outcomes. Although digital treatments for AUD have significant potential, the function of the alliance during digital programs is unclear. We compared the validity of patient-reported measures of the alliance with a digital treatment ("digital alliance") for AUD and the alliance with their clinician ("clinician alliance"). We used data from an 8-week, randomized clinical trial of a computerized cognitive behavioral therapy program (CBT4CBT) during outpatient AUD treatment. Treatment conditions included CBT4CBT with minimal clinical monitoring (CBT4CBT + monitor) or with treatment as usual (CBT4CBT + TAU). The digital alliance and clinician alliance were measured with similar versions of the Working Alliance Inventory (WAI). The WAI ratings were completed at the 2nd and 6th treatment sessions. A timeline followback calendar assessed daily alcohol use. Bayesian multilevel models compared the strength of the alliances and tested their associations with future alcohol use. Data from 43 participants were included (age M = 44; 65% male; 51% Black, 40% White, 9% other; 14% Hispanic). The digital alliance ratings had similar internal reliability as the clinician alliance ratings (ω's > 0.90). Differences between digital alliance and clinician alliance ratings were negligible in both treatment conditions (BF01 = 9 and 31). During treatment, within-person increases in the digital alliance and the clinician alliance predicted modest decreases in future drinking to a similar degree (BF01 = 15). Alliance ratings were not associated with future drinking when posttreatment follow-up drinking data were included (BF10 < 3). The digital alliance with CBT4CBT was comparable to the clinician alliance. The digital alliance and clinician alliance had similar, albeit very small, associations with abstinence during treatment. Future research can explore how the digital alliance develops to improve AUD treatment efficacy.