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

Obesity Clinical Trial

Official title:

A Comparison of Video Conferencing and In-person Health Coaching Approaches in Combination With mHealth Devices on Weight Loss, Physical Activity, and Glycemic Control

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03278951
• Other study ID #: 965182-6
• Secondary ID: 8UL1GM118979-02
• Status: Completed
• Phase: N/A
• First received: September 7, 2017
• Last updated: September 13, 2017
• Start date: January 30, 2016
• Est. completion date: May 30, 2017

Study information

• Verified date: September 2017
• Source: University of New Mexico
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

Description:

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).

Recruitment information / eligibility

• Status: Completed
• Enrollment: 30
• Est. completion date: May 30, 2017
• Est. primary completion date: May 20, 2017
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 65 Years

Eligibility

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.

Related Conditions & MeSH terms

• Body Weight
• Obesity
• Telemedicine
• Weight Loss

Intervention

Behavioral:
• Video Conferencing Group

• In Person Group

Locations

Country	Name	City	State
n/a

Sponsors (3)

Lead Sponsor	Collaborator
University of New Mexico	inHealth Medical Services, Inc., National Institute of General Medical Sciences (NIGMS)

References & Publications (12)

American Heart Association; American College of Cardiology; Obesity Society. Reprint: 2013 AHA/ACC/TOS Guideline for the Management of Overweight and Obesity in Adults. J Am Pharm Assoc (2003). 2014 Jan-Feb;54(1):e3. doi: 10.1331/JAPhA.2014.14502. Review. — View Citation

Bennett JA, Perrin NA, Hanson G, Bennett D, Gaynor W, Flaherty-Robb M, Joseph C, Butterworth S, Potempa K. Healthy aging demonstration project: nurse coaching for behavior change in older adults. Res Nurs Health. 2005 Jun;28(3):187-97. — View Citation

Davis RM, Hitch AD, Salaam MM, Herman WH, Zimmer-Galler IE, Mayer-Davis EJ. TeleHealth improves diabetes self-management in an underserved community: diabetes TeleCare. Diabetes Care. 2010 Aug;33(8):1712-7. doi: 10.2337/dc09-1919. Epub 2010 May 18. — View Citation

Ferrante JM, Piasecki AK, Ohman-Strickland PA, Crabtree BF. Family physicians' practices and attitudes regarding care of extremely obese patients. Obesity (Silver Spring). 2009 Sep;17(9):1710-6. doi: 10.1038/oby.2009.62. Epub 2009 Mar 12. — View Citation

Hersey JC, Khavjou O, Strange LB, Atkinson RL, Blair SN, Campbell S, Hobbs CL, Kelly B, Fitzgerald TM, Kish-Doto J, Koch MA, Munoz B, Peele E, Stockdale J, Augustine C, Mitchell G, Arday D, Kugler J, Dorn P, Ellzy J, Julian R, Grissom J, Britt M. The efficacy and cost-effectiveness of a community weight management intervention: a randomized controlled trial of the health weight management demonstration. Prev Med. 2012 Jan;54(1):42-9. doi: 10.1016/j.ypmed.2011.09.018. Epub 2011 Oct 6. — View Citation

Hubble JP, Pahwa R, Michalek DK, Thomas C, Koller WC. Interactive video conferencing: a means of providing interim care to Parkinson's disease patients. Mov Disord. 1993 Jul;8(3):380-2. — View Citation

Huber JM, Shapiro JS, Wieland ML, Croghan IT, Vickers Douglas KS, Schroeder DR, Hathaway JC, Ebbert JO. Telecoaching plus a portion control plate for weight care management: a randomized trial. Trials. 2015 Jul 30;16:323. doi: 10.1186/s13063-015-0880-1. — View Citation

Jeon E, Park HA. Development of a smartphone application for clinical-guideline-based obesity management. Healthc Inform Res. 2015 Jan;21(1):10-20. doi: 10.4258/hir.2015.21.1.10. Epub 2015 Jan 31. — View Citation

Kivelä K, Elo S, Kyngäs H, Kääriäinen M. The effects of health coaching on adult patients with chronic diseases: a systematic review. Patient Educ Couns. 2014 Nov;97(2):147-57. doi: 10.1016/j.pec.2014.07.026. Epub 2014 Aug 1. Review. — View Citation

Olsen JM, Nesbitt BJ. Health coaching to improve healthy lifestyle behaviors: an integrative review. Am J Health Promot. 2010 Sep-Oct;25(1):e1-e12. doi: 10.4278/ajhp.090313-LIT-101. Review. — View Citation

Rollo ME, Hutchesson MJ, Burrows TL, Krukowski RA, Harvey JR, Hoggle LB, Collins CE. Video Consultations and Virtual Nutrition Care for Weight Management. J Acad Nutr Diet. 2015 Aug;115(8):1213-25. doi: 10.1016/j.jand.2015.03.016. Epub 2015 May 16. — View Citation

Shaw RJ, Steinberg DM, Bonnet J, Modarai F, George A, Cunningham T, Mason M, Shahsahebi M, Grambow SC, Bennett GG, Bosworth HB. Mobile health devices: will patients actually use them? J Am Med Inform Assoc. 2016 May;23(3):462-6. doi: 10.1093/jamia/ocv186. Epub 2016 Jan 17. — View Citation

* Note: There are 12 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Weight loss in (kg)	Investigators examined body weight changes between groups baseline (week 0) and post intervention (week12).	Change in weight between baseline (week 0) and post intervention (week 12)
Secondary	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).	Average steps per day/week over a 12 week period.
Secondary	Hba1c pre and post intervention	Investigators measured HbA1c via a blood test which was analyzed by Quest® laboratories.	Pre and Post (a 12 week study)
Secondary	Insulin pre and post intervention	Investigators measured Insulin via a blood test which was analyzed by Quest® laboratories.	Pre and Post (a 12 week study)
Secondary	Blood glucose pre and post intervention	Investigators measured blood glucose via a blood test which was analyzed by Quest® laboratories.	Pre and Post (a 12 week study)
Secondary	Homeostasis Model Assessment Insulin resistance (HOMA-IR)	A Homeostasis Model Assessment was used to estimate insulin resistance (HOMA-IR)	Pre and Post (a 12 week study)