mhealth intervention
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2022 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Sheri A. Rowland ◽  
Athena K. Ramos ◽  
Natalia Trinidad ◽  
Sophia Quintero ◽  
Rebecca Johnson-Beller ◽  
...  

Nutrients ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 270
Author(s):  
Cristina Lugones-Sánchez ◽  
José I. Recio-Rodríguez ◽  
Marta Menéndez-Suárez ◽  
Alicia Saz-Lara ◽  
José I. Ramirez-Manent ◽  
...  

A balanced diet can help in the prevention of chronic diseases. The aim of this study was to evaluate the effect of an mHealth intervention on the distribution of macronutrients and the intake of food groups. A total of 650 participants were included in this multi-center, clinical, randomized, controlled trial (Evident 3 study). All participants were given brief advice about diet and exercise. The intervention group received, in addition, an app (Evident 3) for the self-recording of their diet and an activity tracker wristband for 3 months. Follow-up visits were performed at 3 and 12 months to collect the diet composition using the Food Frequency Questionnaire. There were decreases in the intake of total calories, fat, protein and carbohydrates in both groups throughout the study, without significant differences between them. The intervention group reduced the intake of cholesterol (−30.8; 95% CI −59.9, −1.7) and full-fat dairies (−23.3; 95% CI −42.8, −3.8) and increased the intake of wholemeal bread (3.3; 95% CI −6.7, 13.3) and whole-grain cereals (3.4; 95% CI −6.8, 13.7) with respect to the control group. No differences were found in the rest of the nutritional parameters. The brief advice is useful to promote a healthier diet, and the app can be a support tool to obtain changes in relevant foods, such as integral foods, and the intake of cholesterol. Trial registration: ClinicalTrials.gov with identifier NCT03175614.


2022 ◽  
Author(s):  
Kayla Mae Knowles ◽  
Nadia Lauren Dowshen ◽  
Susan Lee ◽  
Amanda Tanner

BACKGROUND Engaging adolescents and young adults (AYA) who are at elevated risk for HIV acquisition or who are living with HIV in healthcare has posed a major challenge in HIV prevention and care efforts. Mobile health (mHealth) interventions are a popular and accessible strategy to support AYA engagement despite barriers to care present along the HIV care continuum. Even with progress in the field of mHealth research, expert recommendations for the process of designing, evaluating, and implementing HIV-related mHealth interventions are underdeveloped. OBJECTIVE The aim of this study was to compile expert recommendations on the development, evaluation, and implementation of AYA-focused HIV prevention and care mHealth interventions. METHODS Experts from adolescent mHealth HIV research networks and investigators of recently funded HIV mHealth projects and programs were identified and invited to complete a series of electronic surveys related to the design, implementation, and evaluation of HIV-related mHealth interventions. A modified Delphi method was used to ask experts to score 35 survey items on a 4-point Likert scale from not important to very important and encouraged experts to leave additional comments in text boxes. Responses were reviewed by the researchers, a team of four HIV mHealth intervention experts. The average importance ratings from survey responses were calculated and then categorized as retained (high importance), flagged (mid-level importance), or dropped (no/low importance). Additionally, thematic analysis of expert comments helped modify survey items for the next survey round. An evaluation of the level of agreement among experts on the most important items followed each round until consensus was reached. RESULTS Of the 35 invited experts, 23 completed the first survey representing a variety of roles within a research team. Following two rounds of Delphi surveys, experts scored 86% of the 30 survey items included in round two as important to very important. The final consensus items included 24 recommendations related to the mHealth intervention design process (n=15), evaluation (n=2), and implementation (n=7). The three survey items with the highest average scores focused on the design process, specifically, (1) creating a diverse team including researchers, app software developers, youth representation, (2) the importance of AYA-focused content, and the (3) value of an iterative process. Additionally, experts highlighted the importance of establishing the best ways to collect data and the types of data for collection during the evaluation process as well as constructing a plan for participant technology disruption when implementing an mHealth intervention. CONCLUSIONS The modified Delphi method was a useful tool to convene experts to determine recommendations for AYA-focused HIV prevention and care mHealth interventions. These recommendations can inform future mHealth interventions. To ensure acceptability, feasibility, and efficacy of these AYA HIV prevention interventions, the focus must be on specific needs of AYA by including representation of AYA in the process, including consistent and relevant content, ensuring appropriate data is collected, and considering technology and health accessibility barriers.


10.2196/25586 ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. e25586
Author(s):  
Yiran Li ◽  
Yan Guo ◽  
Y Alicia Hong ◽  
Yu Zeng ◽  
Aliza Monroe-Wise ◽  
...  

Background The dose–response relationship between patient engagement and long-term intervention effects in mobile health (mHealth) interventions are understudied. Studies exploring long-term and potentially changing relationships between patient engagement and health outcomes in mHealth interventions are needed. Objective This study aims to examine dose–response relationships between patient engagement and 3 psychosocial outcomes in an mHealth intervention, Run4Love, using repeated measurements of outcomes at baseline and 3, 6, and 9 months. Methods This study is a secondary analysis using longitudinal data from the Run4Love trial, a randomized controlled trial with 300 people living with HIV and elevated depressive symptoms to examine the effects of a 3-month mHealth intervention on reducing depressive symptoms and improving quality of life (QOL). We examined the relationships between patient engagement and depressive symptoms, QOL, and perceived stress in the intervention group (N=150) using 4–time-point outcome measurements. Patient engagement was assessed using the completion rate of course assignments and frequency of items completed. Cluster analysis was used to categorize patients into high- and low-engagement groups. Generalized linear mixed effects models were conducted to investigate the dose–response relationships between patient engagement and outcomes. Results The cluster analysis identified 2 clusters that were distinctively different from each other. The first cluster comprised 72 participants with good compliance to the intervention, completing an average of 74% (53/72) of intervention items (IQR 0.22). The second cluster comprised 78 participants with low compliance to the intervention, completing an average of 15% (11/72) of intervention items (IQR 0.23). Results of the generalized linear mixed effects models showed that, compared with the low-engagement group, the high-engagement group had a significant reduction in more depressive symptoms (β=−1.93; P=.008) and perceived stress (β=−1.72; P<.001) and an improved QOL (β=2.41; P=.01) over 9 months. From baseline to 3, 6, and 9 months, the differences in depressive symptoms between the 2 engagement groups were 0.8, 1.6, 2.3, and 3.7 points, respectively, indicating widening between-group differences over time. Similarly, between-group differences in QOL and perceived stress increased over time (group differences in QOL: 0.9, 1.9, 4.7, and 5.1 points, respectively; group differences in the Perceived Stress Scale: 0.9, 1.4, 2.3, and 3.0 points, respectively). Conclusions This study revealed a positive long-term dose–response relationship between patient engagement and 3 psychosocial outcomes among people living with HIV and elevated depressive symptoms in an mHealth intervention over 9 months using 4 time-point repeat measurement data. The high- and low-engagement groups showed significant and widening differences in depressive symptoms, QOL, and perceived stress at the 3-, 6-, and 9-month follow-ups. Future mHealth interventions should improve patient engagement to achieve long-term and sustained intervention effects. Trial Registration Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https://www.chictr.org.cn/showproj.aspx?proj=21019


2022 ◽  
Author(s):  
Megan MacPherson ◽  
Kohle Merry ◽  
Sean Locke ◽  
Mary Jung

UNSTRUCTURED With thousands of mHealth solutions on the market, patients and healthcare providers struggle to identify which solution to use/prescribe. The lack of evidence-based mHealth solutions may be due to limited research on intervention development and continued use of traditional research methods for mHealth evaluation. The Multiphase Optimization Strategy (MOST) is a framework which aids in developing interventions which are economical, affordable, scalable, and effective (EASE). MOST Phase I highlights the importance of formative intervention development, a stage often overlooked and rarely published. The aim of MOST Phase I is to identify candidate intervention components, create a conceptual model, and define the optimization objective. While MOST sets these three targets, the framework itself does not provide robust guidance on how to conduct quality research within Phase I, and what steps can be taken to identify potential intervention components, develop the conceptual model, and achieve intervention EASE with the implementation context in mind. To advance the applicability of MOST within the field of implementation science, this paper provides an account of the methods used to develop an mHealth intervention. Specifically, we provide a comprehensive example of how to achieve the goals of MOST Phase I by outlining the formative development of an mHealth prompting intervention within a diabetes prevention program. Additionally, recommendations are proposed for future researchers to conduct formative research on mHealth interventions with implementation in mind. Given its considerable reach, mHealth has the potential to positively impact public health by decreasing implementation costs and improving accessibility. MOST is well-suited for the efficient development and optimization of mHealth interventions. By using an implementation-focused lens and outlining the steps in developing an mHealth intervention using MOST Phase I, this work can may guide future intervention developers towards maximizing the impact of mHealth outside of the research laboratory.


Author(s):  
Craig F. Garfield ◽  
Elizabeth Kerrigan ◽  
Rebecca Christie ◽  
Kathryn L. Jackson ◽  
Young S. Lee

10.2196/32575 ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. e32575
Author(s):  
Tianyu Wang ◽  
Philip R Stanforth ◽  
R Y Declan Fleming ◽  
J Stuart Wolf Jr ◽  
Dixie Stanforth ◽  
...  

Background Complying with a prehabilitation program is difficult for patients who will undergo surgery, owing to transportation challenges and a limited intervention time window. Mobile health (mHealth) using smartphone apps has the potential to remove barriers and improve the effectiveness of prehabilitation. Objective This study aimed to develop a mobile app as a tool for facilitating a multidisciplinary prehabilitation protocol involving blood flow restriction training and sport nutrition supplementation. Methods The app was developed using “Appy Pie,” a noncoding app development platform. The development process included three stages: (1) determination of principles and requirements of the app through prehabilitation research team meetings; (2) app prototype design using the Appy Pie platform; and (3) app evaluation by clinicians and exercise and fitness specialists, technical professionals from Appy Pie, and non–team-member users. Results We developed a prototype of the app with the core focus on a multidisciplinary prehabilitation program with accessory features to improve engagement and adherence to the mHealth intervention as well as research-focused features to evaluate the effects of the program on frailty status, health-related quality of life, and anxiety level among patients awaiting elective surgery. Evaluations by research members and random users (n=8) were consistently positive. Conclusions This mobile app has great potential for improving and evaluating the effectiveness of the multidisciplinary prehabilitation intervention in the format of mHealth in future.


2021 ◽  
pp. 174239532110674
Author(s):  
Caitlin S. Sayegh ◽  
Ellen Iverson ◽  
Clarissa Newman ◽  
Diane Tanaka ◽  
Ellen F. Olshansky ◽  
...  

Objectives Adolescents and young adults (AYA) with chronic illnesses often struggle with illness self-management. The objective of this study is to understand how AYA with various chronic illnesses develop self-management skills and which mobile health (mHealth) strategies they believe could be helpful. Methods Semi-structured interviews were conducted with patients, between 16 to 20 years old, living with at least one chronic illness (N = 19), between 2018 and 2019 in Los Angeles, CA. Three coders completed thematic coding to understand how AYA develop and maintain self-management skills, to inform the development of mHealth interventions appropriate across a variety of chronic conditions. Results Results suggest that AYA develop self-management skills through several strategies, including (1) getting organized, (2) making it work for me and (3) keeping the right mentality. AYA described developing these strategies through: (1) receiving social support, (2) accessing helpful tools and technologies, and (3) going through a maturation process. They provided recommendations for mHealth intervention developers. Discussion The results suggest that an appealing mHealth intervention could support AYA patients in proactively acquiring self-management skills and prevent having to rely on trial and error or uneven access to guidance and support. Interventions should be responsive to individual technology preferences and practices.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 934-935
Author(s):  
Melba Hernandez-Tejada ◽  
Sundaravadivel Balasubramanian ◽  
John Bian ◽  
Mohan Madisetti ◽  
Alexis Nagel ◽  
...  

Abstract Objective We evaluated components of an integrated mobile (m)Health-based intervention "Activate for Life" (AFL) on health outcomes in lower-income older adults (65 years and older). Method: AFL incorporates balance (Otago; OG), physical strength (Gentle Yoga and Yogic Breathing; GYYB), and mental engagement (Behavioral Activation; BA) components. Thirty participants were randomly allocated to one of three Arms (n=10 per each arm): OG (Arm 1), (OG+GYYB (Arm2), or OG+GYYB+BA (Arm 3, or full AFL). Groups were evaluated for physical, functional and physiological endpoints at baseline, and posttreatment (12-weeks and/or 3-month follow up). Results Improvements over time in pain interference and 1,5 Ag biomarker were noted for all groups. No significant changes were observed in other physical, functional and physiological measures. DiscussionThis study illustrated potential benefits of the AFL intervention on the health of lower-income older adults and lessons learned from this pilot will be used to make improvements for a large-scale randomized controlled trial.


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