An interventional study of Video Conferencing Group and In Person Group in Obesity, Weight Loss and Telemedicine, sponsored by University of New Mexico. Completed. Open to participants aged 18 Years to 65 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2017-09-14.
Sponsored by University of New Mexico · Not applicable, Interventional, and Other
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).
6,570 studies on the registry are indexed under Obesity; 1,718 are open to participants now.
This study's enrollment of 30 is below the median of 77 across 5,084 interventional studies indexed under Obesity.
Browse Obesity studies →University of New Mexico is the lead sponsor of 312 studies on the registry; 28 are open to participants now.
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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:
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.
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.
Behavioral: Video Conferencing Group
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.
Behavioral: In Person Group
Weight loss in (kg)
Investigators examined body weight changes between groups baseline (week 0) and post intervention (week12).
Time frame: Change in weight between baseline (week 0) and post intervention (week 12)
Comparison of daily step average per day by group (n=10 for each group).
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).
Time frame: Average steps per day/week over a 12 week period.
Hba1c pre and post intervention
Investigators measured HbA1c via a blood test which was analyzed by Quest® laboratories.
Time frame: Pre and Post (a 12 week study)
Insulin pre and post intervention
Investigators measured Insulin via a blood test which was analyzed by Quest® laboratories.
Time frame: Pre and Post (a 12 week study)
Blood glucose pre and post intervention
Investigators measured blood glucose via a blood test which was analyzed by Quest® laboratories.
Time frame: Pre and Post (a 12 week study)
Homeostasis Model Assessment Insulin resistance (HOMA-IR)
A Homeostasis Model Assessment was used to estimate insulin resistance (HOMA-IR)
Time frame: Pre and Post (a 12 week study)
No study locations are listed for this record.
Plan to share: Undecided — It is not yet known if there will be a plan to make IPD available.
This study is completed, as verified in Sep 2017. You cannot join it, but the record below documents what was studied.
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