Effects of goal-setting and of goal levels on weight loss induced by self-monitoring

1982 ◽  
Vol 31 (3) ◽  
pp. 369-382 ◽  
Author(s):  
Pierre Baron ◽  
Robert G Watters
Keyword(s):  
Weight Loss ◽  
Goal Setting ◽  
Self Monitoring

scholarly journals Persuasive System Design Principles and Behavior Change Techniques to Stimulate Motivation and Adherence in Electronic Health Interventions to Support Weight Loss Maintenance: Scoping Review (Preprint)

2019 ◽  
Author(s):  
Rikke Aune Asbjørnsen ◽  
Mirjam Lien Smedsrød ◽  
Lise Solberg Nes ◽  
Jobke Wentzel ◽  
Cecilie Varsi ◽  
...  
Keyword(s):  
Weight Loss ◽  
Behavior Change ◽  
Goal Setting ◽  
Weight Loss Maintenance ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Support Weight ◽  
And Behavior ◽  
Weight Loss Interventions

BACKGROUND Maintaining weight after weight loss is a major health challenge, and eHealth (electronic health) solutions may be a way to meet this challenge. Application of behavior change techniques (BCTs) and persuasive system design (PSD) principles in eHealth development may contribute to the design of technologies that positively influence behavior and motivation to support the sustainable health behavior change needed. OBJECTIVE This review aimed to identify BCTs and PSD principles applied in eHealth interventions to support weight loss and weight loss maintenance, as well as techniques and principles applied to stimulate motivation and adherence for long-term weight loss maintenance. METHODS A systematic literature search was conducted in PsycINFO, Ovid MEDLINE (including PubMed), EMBASE, Scopus, Web of Science, and AMED, from January 1, 2007 to June 30, 2018. Arksey and O’Malley’s scoping review methodology was applied. Publications on eHealth interventions were included if focusing on weight loss or weight loss maintenance, in combination with motivation or adherence and behavior change. RESULTS The search identified 317 publications, of which 45 met the inclusion criteria. Of the 45 publications, 11 (24%) focused on weight loss maintenance, and 34 (76%) focused on weight loss. Mobile phones were the most frequently used technology (28/45, 62%). Frequently used wearables were activity trackers (14/45, 31%), as well as other monitoring technologies such as wireless or digital scales (8/45, 18%). All included publications were anchored in behavior change theories. Feedback and monitoring and goals and planning were core behavior change technique clusters applied in the majority of included publications. Social support and associations through prompts and cues to support and maintain new habits were more frequently used in weight loss maintenance than weight loss interventions. In both types of interventions, frequently applied persuasive principles were self-monitoring, goal setting, and feedback. Tailoring, reminders, personalization, and rewards were additional principles frequently applied in weight loss maintenance interventions. Results did not reveal an ideal combination of techniques or principles to stimulate motivation, adherence, and weight loss maintenance. However, the most frequently mentioned individual techniques and principles applied to stimulate motivation were, personalization, simulation, praise, and feedback, whereas associations were frequently mentioned to stimulate adherence. eHealth interventions that found significant effects for weight loss maintenance all applied self-monitoring, feedback, goal setting, and shaping knowledge, combined with a human social support component to support healthy behaviors. CONCLUSIONS To our knowledge, this is the first review examining key BCTs and PSD principles applied in weight loss maintenance interventions compared with those of weight loss interventions. This review identified several techniques and principles applied to stimulate motivation and adherence. Future research should aim to examine which eHealth design combinations can be the most effective in support of long-term behavior change and weight loss maintenance.

Mobile Applications for Health Management of Older Adults: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Nurul Asilah Ahmad ◽  
Shahrul Azman Mohd Noah ◽  
Arimi Fitri Mat Ludin ◽  
Suzana Shahar ◽  
Noorlaili Mohd Tohit
Keyword(s):  
Older Adults ◽  
Goal Setting ◽  
Mobile Applications ◽  
Health Management ◽  
Mobile Apps ◽  
Personalized Feedback ◽  
Self Monitoring ◽  
App Store ◽  
Evidenced Based ◽  
Google Play

BACKGROUND Currently, the use of smartphones to deliver health-related content has experienced a rapid growth, with more than 165,000 mobile health (mHealth) applications currently available in the digital marketplace such as iOS store and Google Play. Among these, there are several mobile applications (mobile apps) that offer tools for disease prevention and management among older generations. These mobile apps could potentially promote health behaviors which will reduce or delay the onset of disease. However, no review to date that has focused on the app marketplace specific for older adults and little is known regarding its evidence-based quality towards the health of older adults. OBJECTIVE The aim of this review was to characterize and critically appraise the content and functionality of mobile apps that focuses on health management and/or healthy lifestyle among older adults. METHODS An electronic search was conducted between May 2019 to December 2019 of the official app store for two major smartphone operating systems: iPhone operating system (iTunes App Store) and Android (Google Play Store). Stores were searched separately using predetermined search terms. Two authors screened apps based on information provided in the app description. Metadata from all included apps were abstracted into a standard assessment criteria form. Evidenced based strategies and health care expert involvement of included apps was assessed. Evidenced based strategies included: self-monitoring, goal setting, physical activity support, healthy eating support, weight and/or health assessment, personalized feedback, motivational strategies, cognitive training and social support. Two authors verified the data with reference to the apps and downloaded app themselves. RESULTS A total of 16 apps met the inclusion criteria. Six out of 16 (37.5%) apps were designed exclusively for the iOS platform while ten out of 16 (62.5%) were designed for Android platform exclusively. Physical activity component was the most common feature offered in all the apps (9/16, 56.3%) and followed by cognitive training (8/16, 50.0%). Diet/nutrition (0/16, 0%) feature, however, was not offered on all reviewed mobile apps. Of reviewed apps, 56.3% (9/16) provide education, 37.5% (6/16) provide self-monitoring features, 18.8% (3/16) provide goal setting features, 18.5% (3/16) provide personalized feedback, 6.3% (1/16) provide social support and none of the reviewed apps offers heart rate monitoring and reminder features to the users. CONCLUSIONS All reviewed mobile apps for older adults in managing health did not focused on diet/nutrition component, lack of functional components and lack of health care professional involvement in their development process. There is also a need to carry out scientific testing prior to the development of the app to ensure cost effective and its health benefits to older adults. Collaborative efforts between developers, researchers, health professionals and patients are needed in developing evidence-based, high quality mobile apps in managing health prior they are made available in the app store.

scholarly journals The Potential Contribution of Current Health Care Zeitgeists to the Success of Health and Wellness Coaches

2018 ◽  
Vol 12 (6) ◽  
pp. 456-458
Author(s):  
Jon P. Gray ◽  
Katherine R. Arlinghaus ◽  
Craig A. Johnston
Keyword(s):  
Health Care ◽  
Chronic Disease ◽  
Goal Setting ◽  
Behavioral Changes ◽  
Behavior Changes ◽  
Potential Contribution ◽  
Health And Wellness ◽  
Self Monitoring ◽  
Current Health ◽  
Extended Care

Chronic disease is challenging to treat because treatment often requires lifestyle behavior changes. In recent years the use of health and wellness coaches (HWC) has emerged as a way to support patients making behavioral changes. The use of HWCs has resulted in improved management of chronic disease for many patients. The success of HWCs is often thought to be due to the extended care they provide and the behavioral modification techniques they promote such as goal setting and self-monitoring. This article describes how HWC’s conformity to the current health care zeitgeist of personalized, holistic care may be another reason for their success.

Effect of Case Management With Goal-Setting on Diet Scores and Weight Loss in Cardiac Rehabilitation Patients

2018 ◽  
pp. 1
Author(s):  
Karen Aspry ◽  
Shira Dunsiger ◽  
Christopher Breault ◽  
Loren Stabile ◽  
Julianne DeAngelis ◽  
...  
Keyword(s):  
Weight Loss ◽  
Case Management ◽  
Cardiac Rehabilitation ◽  
Goal Setting

scholarly journals Long-Term Evaluation of Counselor Efficiency at Providing Feedback in a Technology-Based Behavioral Weight Loss Intervention (Preprint)

2020 ◽  
Author(s):  
Margaret Fahey ◽  
Robert C. Klesges ◽  
Mehmet Kocak ◽  
Leslie Gladney ◽  
Gerald W. Talcott ◽  
...  
Keyword(s):  
Weight Loss ◽  
Electronic Mail ◽  
Detailed Examination ◽  
Monitoring Data ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Future Technology ◽  
Study Implementation ◽  
Weight Loss Interventions

BACKGROUND Feedback for participants’ self-monitoring is a crucial, and costly, component of technology-based weight loss interventions. Detailed examination of interventionist time when reviewing and providing feedback for online self-monitoring data is unknown. OBJECTIVE Study purpose was to longitudinally examine time counselors spent providing feedback on participant self-monitoring data (i.e., diet, physical activity, weight) in a 12-month technology-based weight loss intervention. We hypothesized that counselors would deliver feedback to participants more quickly over time. METHODS Time counselors (N=10) spent reviewing and providing feedback to participants via electronic mail (e-email) was longitudinally examined for all counselors across the three years of study implementation. Descriptives were observed for counselor feedback duration across counselors by 12 annual quarters (i.e., three-month periods). Differences in overall duration times by each consecutive annual quarter were analyzed using Wilcoxon-Mann-Whitney tests. RESULTS There was a decrease in counselor feedback duration from first to second quarter [Mean (M) = 53 to 46 minutes], and from second to third (M= 46 to 30). A trend suggested a decrease from third to fourth quarters (M = 30 to 26), but no changes were found in subsequent quarters. Consistent with hypothesis, counselors increased their efficiency in providing feedback. Across 12-months, mean time counselors needed to review participant self-monitoring and provide feedback decreased from 53 to 26 minutes. CONCLUSIONS Counselors needed increasingly less time to review online self-monitoring data and provide feedback after the initial nine months of study implementation. Results inform counselor costs for future technology-based behavioral weight loss interventions. For example, regardless of increasing counselor efficiency, 25-30 minutes per feedback message is a high cost for interventions. One possibility for reducing costs would be generating computer-automated feedback. CLINICALTRIAL NCT02063178

scholarly journals Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study (Preprint)

2018 ◽  
Author(s):  
Sherry Pagoto ◽  
Bengisu Tulu ◽  
Emmanuel Agu ◽  
Molly E Waring ◽  
Jessica L Oleski ◽  
...  
Keyword(s):  
Weight Loss ◽  
Problem Solving ◽  
Mobile Apps ◽  
Mobile App ◽  
Behavioral Weight Loss ◽  
Problem Solving Therapy ◽  
Pilot Studies ◽  
Self Monitoring ◽  
Problem Solving Skills ◽  
Automated Delivery

BACKGROUND Reviews of weight loss mobile apps have revealed they include very few evidence-based features, relying mostly on self-monitoring. Unfortunately, adherence to self-monitoring is often low, especially among patients with motivational challenges. One behavioral strategy that is leveraged in virtually every visit of behavioral weight loss interventions and is specifically used to deal with adherence and motivational issues is problem solving. Problem solving has been successfully implemented in depression mobile apps, but not yet in weight loss apps. OBJECTIVE This study describes the development and feasibility testing of the Habit app, which was designed to automate problem-solving therapy for weight loss. METHODS Two iterative single-arm pilot studies were conducted to evaluate the feasibility and acceptability of the Habit app. In each pilot study, adults who were overweight or obese were enrolled in an 8-week intervention that included the Habit app plus support via a private Facebook group. Feasibility outcomes included retention, app usage, usability, and acceptability. Changes in problem-solving skills and weight over 8 weeks are described, as well as app usage and weight change at 16 weeks. RESULTS Results from both pilots show acceptable use of the Habit app over 8 weeks with on average two to three uses per week, the recommended rate of use. Acceptability ratings were mixed such that 54% (13/24) and 73% (11/15) of participants found the diet solutions helpful and 71% (17/24) and 80% (12/15) found setting reminders for habits helpful in pilots 1 and 2, respectively. In both pilots, participants lost significant weight (P=.005 and P=.03, respectively). In neither pilot was an effect on problem-solving skills observed (P=.62 and P=.27, respectively). CONCLUSIONS Problem-solving therapy for weight loss is feasible to implement in a mobile app environment; however, automated delivery may not impact problem-solving skills as has been observed previously via human delivery. CLINICALTRIAL ClinicalTrials.gov NCT02192905; https://clinicaltrials.gov/ct2/show/NCT02192905 (Archived by WebCite at http://www.webcitation.org/6zPQmvOF2)

scholarly journals Understanding self-guided online educational platforms for patients with chronic health conditions: A systematic review of platforms’ features and adherence (Preprint)

2020 ◽  
Author(s):  
Li Feng Xie ◽  
Alexandra Itzkovitz ◽  
Amelie Roy-Fleming ◽  
Deborah Da Costa ◽  
Anne-Sophie Brazeau
Keyword(s):  
Systematic Review ◽  
Online Education ◽  
Clinical Outcomes ◽  
Chronic Diseases ◽  
Goal Setting ◽  
Cochrane Library ◽  
Self Monitoring ◽  
Chronic Respiratory Diseases ◽  
Online Platforms ◽  
Cochrane Reviews

BACKGROUND Chronic diseases contribute to 71% of deaths worldwide every year and an estimated 15 million people between the ages of 30 to 69 years die mainly due to cardiovascular disease, cancer, chronic respiratory diseases, or diabetes. Online education platforms may offer numerous health benefits on disease management and on related health consequences. It is also considered to be a flexible, lower cost method to deliver tailored information to patients. Previous studies concluded that the implementation of different features and degree of adherence to the platform are key factors in determining the success of the intervention. However, limited research has been done to understand the level of acceptability of the specific features and user adherence to self-guided online platforms. OBJECTIVE The aims of this systematic review are to understand how online platforms features are evaluated, to investigate which features have the greatest and lowest level of acceptability and to describe how adherence to online self-guided platforms is defined and measured. METHODS Studies published on self-guided online education platforms for people (≥14 years old) with chronic diseases published between January 2005 to June 2019 were reviewed following the PRISMA Statement protocol. The search was done using the databases of PubMed and Cochrane Library: Cochrane Reviews. The comparison of the interventions and analysis of the features were based on the published content from the selected articles. RESULTS A total of fifteen studies were included. Seven principal features were identified with goal setting, self-monitoring, and feedback being the most frequently used. The level of acceptability of the different features was measured based on the comments collected from users, their association with clinical outcomes and/or device adherence. The use of quizzes was positively reported by participants. Self-monitoring, goal setting, feedback, and discussion forums had mixed results. The negative acceptability was mainly related to the choice of the discussion topic, lack of face-to-face contact, and technical issues. This review also showed that evaluation of adherence to educational platform was inconsistent among the studies therefore limiting comparison. A clear definition of adherence to the platform is lacking. CONCLUSIONS This review suggests that features related to interaction and personalization provide better clinical outcomes and positive users’ experience. The negatively reported features were mainly related to not targeting the population’s needs, low human involvement within the platform, and technical barriers. Only six studies reported the level of acceptability of their features on users’ experience, clinical outcomes or device adherence, which highlights the needs for further studies. There is a lack of consensus on the method used for measuring the level of adherence to the platform, therefore we suggest to use a standardized framework to measure adherence.

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