Enhancement of Self-Monitoring in a Web-Based Weight Loss Program by Extra Individualized Feedback and Reminders: Randomized Trial

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Abstract

Background

Self-monitoring is an essential behavioral strategy for effective weight loss programs. Traditionally, self-monitoring has been achieved using paper-based records. However, technology is now more frequently used to deliver treatment programs to overweight and obese adults. Information technologies, such as the Internet and mobile phones, allow innovative intervention features to be incorporated into treatment that may facilitate greater adherence to self-monitoring processes, provide motivation for behavior change, and ultimately lead to greater weight loss success.

Objective

The objective of our study was to determine whether the consistency of self-monitoring differed between participants randomly assigned to a basic or an enhanced 12-week commercial Web-based weight loss program.

Methods

We randomly assigned a sample of 301 adults (mean age 42.3 years; body mass index 31.3 kg/m2; female 176/301, 58.5%) to the basic or enhanced group. The basic program included tools for self-monitoring (online food and exercise diary, and a weekly weigh-in log) with some feedback and reminders to weigh in (by text or email). The enhanced program included the basic components, as well as extra individualized feedback on self-monitoring entries and reminders (by text, email, or telephone) to engage with self-monitoring tools. We evaluated the level of self-monitoring by examining the consistency of self-monitoring of food, exercise, and weight during the 12 weeks. Consistency was defined as the number of weeks during which participants completed a criterion number of entries (ie, ≥3 days of online food or exercise diary records per week and ≥1 weigh-in per week).

Results

The enhanced group’s consistency of use of self-monitoring tools was significantly greater than that of the basic group throughout the 12 weeks (median consistency for food 8 vs 3 weeks, respectively, P<.001; for exercise 2.5 vs 1 weeks, respectively, P=.003).

Conclusions

Enhanced features, including additional individualized feedback and reminders, are effective in enhancing self-monitoring behaviors in a Web-based weight loss program.

ClinicalTrial

Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12610000197033; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=335159 (Archived by WebCite at http://www.webcitation.org/6gCQdj21G)

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Most cited references 17

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Dropout, Nonusage Attrition, and Pretreatment Predictors of Nonusage Attrition in a Commercial Web-Based Weight Loss Program

Melinda J Neve, Clare Collins, Philip J Morgan (2010)

Background An understanding of the factors that predict retention and website use are critical to the development of effective Web-based weight loss interventions. However, poor retention (dropout attrition) and website utilization (nonusage attrition) are major inhibitors to the effectiveness of Web-based programs. Objective The study aimed to (1) describe the prevalence of dropout and nonusage attrition and (2) examine pretreatment predictors of nonusage attrition in a cohort of commercial Web-based weight loss program participants. Methods Participants enrolled in the online program, The Biggest Loser Club, Australia, from August 15, 2007, to May 31, 2008. Only those who subscribed for 12 or 52 weeks were included in this study. All data were collected by the program proprietors, SP Health Co Pty Ltd (Sydney, Australia), and provided in “deidentified” form. Data collected included responses to a pretreatment survey (sociodemographic and behavioral characteristics), subscription history (date of enrollment and subscription end), and website use (log-ins, food and exercise diary entries, weigh-ins, and forum posts). Participants were classified as a member of the program at 12 or 52 weeks if they held an active subscription plan at that point in time. Participants were classified as nonusers at 12 or 52 weeks if they had stopped using all of the website features and had not returned. Predictors of nonusage attrition were explored using Cox proportional hazards regression analysis. Results Of the 9599 eligible participants, 6943 (72%) subscribed to the program for 12 weeks, and 2656 (28%) subscribed for 52 weeks. Of all participants, 31% (2975/9599) were classified as overweight, 61% (5866/9599) were classified as obese, 86% (8279/9599) were female, and participants’ mean (SD) age was 35.7 (9.5) years. The 12 week and 52 week subscribers’ retention rates were 97% and 77% respectively. Of 12 week subscribers, 35% were classified as program “users” after 12 weeks, and 30% of 52 week subscribers were classified as “users” after 52 weeks. Significant predictors of nonusage attrition among 12 week subscribers included age (hazard ratio for 45 to 55 years of age = 0.83, 95% confidence interval [CI] 0.73 - 0.93, P = .001; hazard ratio for 55 to 65 years of age = 0.80, 95% CI 0.66 - 0.99, P = .04), exercise level (hazard ratio = 0.76, 95% CI 0.72 - 0.81, P < .001), emotional eating (hazard ratio = 1.11, 95% CI 1.04 - 1.18, P = .001), eating breakfast (hazard ratio = 0.88, 95% CI 0.82 - 0.95, P = .001), and skipping meals (hazard ratio = 1.12, 95% CI 1.04 -1.19, P = .001). For 52 week subscribers, eating breakfast (hazard ratio = 0.88, 95% CI 0.79 - 0.99, P = .04) and not drinking tea or coffee with sugar (hazard ratio = 1.23, 95% CI 1.11 - 1.37, P < .001) were the pretreatment characteristics that significantly decreased risk of nonusage attrition. Conclusions The findings demonstrate a high prevalence of nonusage attrition among a cohort of commercial Web-based weight loss program participants. Several sociodemographic and behavioral factors were shown to independently predict nonusage attrition.

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eHealth evaluation and dissemination research.

Russell E. Glasgow (2007)

This paper reviews key challenges in evaluating eHealth intervention and behavior change programs, and makes recommendations for the types of designs, measures, and methods needed to accelerate the integration of proven eHealth programs into practice. Key issues discussed include evaluation approaches that answer questions that consumers, potential adoptees, and policymakers have. These include measures of participation and representativeness at both patient and healthcare setting levels, consistency of outcomes across different subgroups, tendency of an eHealth program to ameliorate versus exacerbate health disparities, implementation and program adaptation, cost, and quality-of-life outcomes. More practical eHealth trials are needed that use rigorous but creative designs compatible with eHealth interventions and theory. These evaluations should address key dissemination issues, such as appeal, use, and robustness of eHealth programs across different subgroups, settings, conditions, outcomes, and time.

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The Impact of Regular Self-weighing on Weight Management: A Systematic Literature Review

Jeffrey VanWormer, Simone French, Mark A. Pereira … (2008)

Background Regular self-weighing has been a focus of attention recently in the obesity literature. It has received conflicting endorsement in that some researchers and practitioners recommend it as a key behavioral strategy for weight management, while others caution against its use due to its potential to cause negative psychological consequences associated with weight management failure. The evidence on frequent self-weighing, however, has not yet been synthesized. The purpose of this paper is to evaluate the evidence regarding the use of regular self-weighing for both weight loss and weight maintenance. Methods A systematic literature review was conducted using the MEDLINE, CINAHL, and PsycINFO online databases. Reviewed studies were broken down by sample characteristics, predictors/conditions, dependent measures, findings, and evidence grade. Results Twelve studies met the inclusion/exclusion criteria, but nearly half received low evidence grades in terms of methodological quality. Findings from 11 of the 12 reviewed studies indicated that more frequent self-weighing was associated with greater weight loss or weight gain prevention. Specifically, individuals who reported self-weighing weekly or daily, typically over a period of several months, held a 1 to 3 kg/m2 (current) advantage over individuals who did not self-weigh frequently. The effects of self-weighing in experimental studies, especially those where self-weighing behaviors could be isolated, were less clear. Conclusion Based on the consistency of the evidence reviewed, frequent self-weighing, at the very least, seems to be a good predictor of moderate weight loss, less weight regain, or the avoidance of initial weight gain in adults. More targeted research is needed in this area to determine the causal role of frequent self-weighing in weight loss/weight gain prevention programs. Other open questions to be pursued include the optimal dose of self-weighing, as well as the risks posed for negative psychological consequences.

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Author and article information

Contributors

Clare Collins:

School of Health SciencesFaculty of Health and MedicineUniversity of NewcastleAdvanced Technology Centre, Level 3University DriveCallaghan, 2308Australia61 2 4921564661 2 4921 7053clare.collins@newcastle.edu.au

ORCID: http://orcid.org/0000-0003-3298-756X

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J. Med. Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications Inc. (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: April 2016

Publication date (Electronic): 12 April 2016

Volume: 18

Issue: 4

Electronic Location Identifier: e82

Affiliations

[1] ¹Priority Research Centre in Physical Activity and Nutrition, School of Health Sciences Faculty of Health and Medicine University of Newcastle CallaghanAustralia

[2] ²School of Education Faculty of Education and Arts University of Newcastle CallaghanAustralia

[3] ³School of Biomedical Sciences and Pharmacy Faculty of Health and Medicine University of Newcastle CallaghanAustralia

[4] ⁴School of Health Sciences Faculty of Health and Medicine University of Newcastle CallaghanAustralia

Author notes

Corresponding Author: Clare Collins clare.collins@ 123456newcastle.edu.au

Author information

Melinda Jane Hutchesson http://orcid.org/0000-0002-1851-0661

Chor Yin Tan http://orcid.org/0000-0002-7327-9044

Philip Morgan http://orcid.org/0000-0002-5632-8529

Robin Callister http://orcid.org/0000-0001-5592-6132

Clare Collins http://orcid.org/0000-0003-3298-756X

Article

Publisher ID: v18i4e82

DOI: 10.2196/jmir.4100

PMC ID: 4846785

PubMed ID: 27072817

SO-VID: b5c0adba-7795-44a8-882b-2065c456c3ed

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 4 December 2014

Date revision requested : 22 February 2015

Date revision received : 31 August 2015

Date accepted : 23 January 2016

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