Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Mar 13;20(3):e92.
doi: 10.2196/jmir.9738.

Expert Coaching in Weight Loss: Retrospective Analysis

Affiliations

Expert Coaching in Weight Loss: Retrospective Analysis

Stefanie Lynn Painter et al. J Med Internet Res. .

Abstract

Background: Providing coaches as part of a weight management program is a common practice to increase participant engagement and weight loss success. Understanding coach and participant interactions and how these interactions impact weight loss success needs to be further explored for coaching best practices.

Objective: The purpose of this study was to analyze the coach and participant interaction in a 6-month weight loss intervention administered by Retrofit, a personalized weight management and Web-based disease prevention solution. The study specifically examined the association between different methods of coach-participant interaction and weight loss and tried to understand the level of coaching impact on weight loss outcome.

Methods: A retrospective analysis was performed using 1432 participants enrolled from 2011 to 2016 in the Retrofit weight loss program. Participants were males and females aged 18 years or older with a baseline body mass index of ≥25 kg/m², who also provided at least one weight measurement beyond baseline. First, a detailed analysis of different coach-participant interaction was performed using both intent-to-treat and completer populations. Next, a multiple regression analysis was performed using all measures associated with coach-participant interactions involving expert coaching sessions, live weekly expert-led Web-based classes, and electronic messaging and feedback. Finally, 3 significant predictors (P<.001) were analyzed in depth to reveal the impact on weight loss outcome.

Results: Participants in the Retrofit weight loss program lost a mean 5.14% (SE 0.14) of their baseline weight, with 44% (SE 0.01) of participants losing at least 5% of their baseline weight. Multiple regression model (R2=.158, P<.001) identified the following top 3 measures as significant predictors of weight loss at 6 months: expert coaching session attendance (P<.001), live weekly Web-based class attendance (P<.001), and food log feedback days per week (P<.001). Attending 80% of expert coaching sessions, attending 60% of live weekly Web-based classes, and receiving a minimum of 1 food log feedback day per week were associated with clinically significant weight loss.

Conclusions: Participant's one-on-one expert coaching session attendance, live weekly expert-led interactive Web-based class attendance, and the number of food log feedback days per week from expert coach were significant predictors of weight loss in a 6-month intervention.

Keywords: body mass index; coaching; feedback; obesity; overweight; weight loss; weight reduction program.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: SP, RA, SB, and AM are employees of Retrofit, Inc, with equity in the company. JH, RK, and RL are active members of the Retrofit, Inc Advisory Board, with equity in the company.

Figures

Figure 1
Figure 1
Weight loss outcomes for different levels of coach-participant interaction.
Figure 2
Figure 2
Interaction levels of participants with different levels of outcome.

Similar articles

Cited by

References

    1. World Health Organization. Obesity and overweight http://www.who.int/mediacentre/factsheets/fs311/en/ 6wjWaAWcr
    1. Waters H, DeVol R. Milken Institute. Weighing Down America: The Health and Economic Impact of Obesity http://www.milkeninstitute.org/publications/view/833 6vfARXaLA.
    1. Gates DM, Succop P, Brehm BJ, Gillespie GL, Sommers BD. Obesity and presenteeism: the impact of body mass index on workplace productivity. J Occup Environ Med. 2008 Jan;50(1):39–45. doi: 10.1097/JOM.0b013e31815d8db2. - DOI - PubMed
    1. Van Nuys K, Globe D, Ng-Mak D, Cheung H, Sullivan J, Goldman D. The association between employee obesity and employer costs: evidence from a panel of U.S. employers. Am J Health Promot. 2014;28(5):277–85. doi: 10.4278/ajhp.120905-QUAN-428. - DOI - PubMed
    1. National Center for Health Statistics. Health, United States, 2016 https://www.cdc.gov/nchs/hus/index.htm 6vdJUOX2i.
  NODES
admin 1
Association 2
INTERN 10
twitter 2
USERS 1