Video Conferencing and In-person Health Coaching on Weight Loss, Physical Activity, and Metabolic Control

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT03278951
Recruitment Status : Completed
First Posted : September 12, 2017
Last Update Posted : September 14, 2017
National Institute of General Medical Sciences (NIGMS)
inHealth Medical Services, Inc.
Information provided by (Responsible Party):
University of New Mexico

September 7, 2017
September 12, 2017
September 14, 2017
January 30, 2016
May 20, 2017   (Final data collection date for primary outcome measure)
Weight loss in (kg) [ Time Frame: Change in weight between baseline (week 0) and post intervention (week 12) ]
Investigators examined body weight changes between groups baseline (week 0) and post intervention (week12).
Same as current
Complete list of historical versions of study NCT03278951 on Archive Site
  • Comparison of daily step average per day by group (n=10 for each group). [ Time Frame: Average steps per day/week over a 12 week period. ]
    Investigators examined steps per day and averaged them every week. Each time point (weeks) were then graphed and presented as adjusted least mean square (LMS) and standard error (SE).
  • Hba1c pre and post intervention [ Time Frame: Pre and Post (a 12 week study) ]
    Investigators measured HbA1c via a blood test which was analyzed by Quest® laboratories.
  • Insulin pre and post intervention [ Time Frame: Pre and Post (a 12 week study) ]
    Investigators measured Insulin via a blood test which was analyzed by Quest® laboratories.
  • Blood glucose pre and post intervention [ Time Frame: Pre and Post (a 12 week study) ]
    Investigators measured blood glucose via a blood test which was analyzed by Quest® laboratories.
  • Homeostasis Model Assessment Insulin resistance (HOMA-IR) [ Time Frame: Pre and Post (a 12 week study) ]
    A Homeostasis Model Assessment was used to estimate insulin resistance (HOMA-IR)
Same as current
Not Provided
Not Provided
Video Conferencing and In-person Health Coaching on Weight Loss, Physical Activity, and Metabolic Control
A Comparison of Video Conferencing and In-person Health Coaching Approaches in Combination With mHealth Devices on Weight Loss, Physical Activity, and Glycemic Control
The purpose of this study was to determine how 12 weeks of health coaching with individualized feedback and education in combination with mobile health devices (a digital wireless body weight scale and wireless activity tracker) influences body weight, waist circumference, physical activity levels, and select blood-borne markers of health (fasting blood glucose, hemoglobin A1c, and insulin). The individualized health coaching, education, and feedback was delivered by either video conferencing or direct, in-person consultation. All education materials including (i.e. video modules, exercise manuals, nutrition manuals) were designed and compiled by a team of health professionals from (inHealth Medical Services, Inc.). These materials focused on incorporating behavioral principles of self-monitoring, exercise, nutrition, goal setting, and behavior modification. Each participant was randomly assigned into one of two intervention groups (a video conferencing or in-person group) or a control group.

Telemedicine can be defined as using communication technologies, specifically video conferencing, to support long-distance delivery of clinical health care and patient and professional health-related education. Video conferencing (VC) has been used since the early 1990's as a tool to monitor symptoms (Hubble et al. 1992), and it has also been used in various subspecialties such as heart disease (Winters & Winters, 2007), diabetes prevention/management (Davis et al. 2010), mental health care (O'Reilly et al. 2007), and for providing nutritional advice (Rollo et al. 2015). Evidence regarding the effectiveness of video conferencing is amassing with systematic reviews revealing promising results in the management of various chronic diseases (Pronk et al. 2011). However, to date there are no published studies investigating a fully online, medically monitored, weight loss program utilizing VC.

The application of VC has the potential to shift current clinical practice for medical weight management/weight loss from traditional in-person medical office visits to remote delivery using VC. eClinicalWorks® (ECW)l) is a telemedicine service company providing cost effective medical care solutions to patients through the use of technology.ECW® provides patients with an easy-to-use application that enables face-to-face contact with a healthcare provider through the use of VC on their smart device from any location. The ECW® application which will be utilized in the present study will be fully customized to utilize Bluetooth connectivity to sync with commercially available clinical assessment tools such as body weight scales and physical activity trackers to monitor obesity related health outcomes. Through the integration of tools into a customized smartphone application provided by ECW®, health care professionals in the present study will be able to evaluate a participant's body weight, body composition, and physical activity through one convenient smartphone application.

Within the obesity prevention and management strategies, the use of health coaching is one possible way to improve patient lifestyle behavior change. Health coaching can be defined as the "practice of providing health education within a coaching context to enhance the knowledge of individuals which helps facilitate the achievement in their health-related goals'' (Olson and Nesbitt et al. 2010). A fairly recent study (Ferrante et al. 2009) in which more than 500 physicians were surveyed on their practices and management strategies regarding extreme obesity (BMI ≥40kg/m2) indicated that having a readily available nutrition and exercise therapist would be helpful in improving the quality of care in these patients, thereby highlighting the benefits gained by using health coaches. The majority of health coaching intervention studies investigating behavior change have been personalized and conveyed to the individual participant through several mediums including telephone, (Huber et al. 2015), web-based chatting (Hersey et al. 2012, Bennett et al. 2010), or a combination of in-person and web-based delivery (Appel et al. 2011; Bennett et al. 2005). Additionally, there appears to be great variability between interventions in the type of health care professional utilized as health coaches including: nurses, health counselors, registered dietitians, primary care providers, or diabetes educators (Kivela et al. 2014). However, using a health coaching approach in which a multi-disciplinary team (medical doctor, registered dietitian, and exercise physiologist) is utilized, as in the present study, has yet to be examined. This is especially important as recent evidence has shown that increased collaboration between healthcare professionals may enhance patient adherence, education, and medical monitoring (Jeon & Park, 2015).

In addition to the utilization of both health coaching and VC, health professionals are always seeking ways to objectively monitor and improve their patients' health and fitness, especially between patient visits. A potential way health professionals can monitor a patient's health metrics is through mobile health (mHealth) devices including smartphones and wearable fitness trackers, as well as wireless weight scales, blood pressure cuffs, and glucometers (Shaw et al. 2016). However, to leverage mHealth devices as tools to promote patient self-monitoring, the integrated use of mHealth devices which collect, display, and secure data through a unified system is needed. To date, only one study (Shaw et al. 2016) examined the feasibility of multiple mHealth devices which transmitted data to a secure US Food and Drug Administration (FDA) database. Therefore, The primary aim of this study was to assess changes in physical activity, body weight and metabolic markers (fasting blood glucose, insulin, insulin resistance, and hemoglobin A1c) in obese adults randomized into either a control group or one of two intervention groups (an in-person group or VC group).

Not Applicable
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description:
All participants were randomized in a balanced fashion and stratified by sex into either one of the two intervention groups (VC or in-person group) or a control group.
Masking: Single (Participant)
Masking Description:
Following baseline visits, participants were randomized to a viideo conference (VC(, in person (IP) or control (CG) groups via the website
Primary Purpose: Other
  • Obesity
  • Weight Loss
  • Telemedicine
  • Behavioral: Video Conferencing Group
  • Behavioral: In Person Group
  • No Intervention: Control Group
    The control group received the mHealth devices but no health coaching or feedback. Participants in this group completed the same pre- and post-intervention measurements.
  • Experimental: Video Conferencing Health Coaching
    The video conferencing group participants met via the eClinicalWorks® app using their smartphone, and met 12 times with the registered dietitian (RD) and 12 times with the exercise physiologist to discuss exercise and diet goals.
    Intervention: Behavioral: Video Conferencing Group
  • Experimental: In Person Health Coaching
    The in person group participants met 12 times with the registered dietitian (RD) and 12 times with the exercise physiologist over the course of the study to discuss both diet and exercise regimens.
    Intervention: Behavioral: In Person Group

*   Includes publications given by the data provider as well as publications identified by Identifier (NCT Number) in Medline.
Same as current
May 30, 2017
May 20, 2017   (Final data collection date for primary outcome measure)

Inclusion Criteria:

Fluent in English spoken and written at a high-school level, Non-diabetic Obese according to body mass index (BMI) standards (> 30 kg/m2), Weigh less than 396 pounds, Live a sedentary lifestyle defined as < 7,000 steps per day Had access to an Apple® iPhone or Android® smart phone

Exclusion Criteria:

  • Participants were excluded if they have stated having an Immunodeficiency disorder Kidney disease; Type II diabetes; History of uncontrolled high blood pressure (defined as a systolic blood pressure ≥ 140mmHg and/or diastolic blood pressure ≥90 mmHg confirmed by measurements on two separate occasions); Asthma, COPD, Heart attack or stroke within the past 12 months; Presence of a partial or full artificial limb; Known dementia, brain cancer, eating disorders, history of significant neurological or psychiatric disorder or any other psychological condition; Medications, dietary supplements, or substances advertised to modify metabolism or body weight; Undergone major surgery less than 4 weeks prior to enrollment in the study; or were actively losing weight.
Sexes Eligible for Study: All
18 Years to 65 Years   (Adult, Older Adult)
Contact information is only displayed when the study is recruiting subjects
Not Provided
8UL1GM118979-02 ( U.S. NIH Grant/Contract )
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Plan to Share IPD: Undecided
Plan Description: It is not yet known if there will be a plan to make IPD available.
University of New Mexico
University of New Mexico
  • National Institute of General Medical Sciences (NIGMS)
  • inHealth Medical Services, Inc.
Study Chair: Ann Gibson, PhD University of New Mexico
University of New Mexico
September 2017

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP