Feasibility study of portable technology for weight loss and HbA1c control in type 2 diabetes

Abstract

BackgroundThe study investigated the feasibility of conducting a future Randomised Controlled Trial (RCT) of a mobile health (mHealth) intervention for weight loss and HbA1c reduction in Type 2 Diabetes Mellitus (T2DM).MethodsThe intervention was a small wearable mHealth device used over 12 weeks by overweight people with T2DM with the intent to lose weight and reduce their HbA1c level. A 4 week maintenance period using the device followed. The device records physical activity level and information about food consumption, and provides motivational feedback based on energy balance. Twenty-seven participants were randomised to receive no intervention; intervention alone; or intervention plus weekly motivational support. All participants received advice on diet and exercise at the start of the study. Weight and HbA1c levels were recorded at baseline and weeks 6, 12, and 16. Qualitative interviews were conducted with participants who received the intervention to explore their experiences of using the device and involvement in the study including the training received.ResultsOverall the device was perceived to be well-liked, acceptable, motivational and easy to use by participants. Some logistical changes were required during the feasibility study, including shortening of the study duration and relaxation of participant inclusion criteria. Descriptive statistics of weight and HbA1c data showed promising trends of weight loss and HbA1c reduction in both intervention groups, although this should be interpreted with caution.ConclusionsA number of methodological recommendations for a future RCT emerged from the current feasibility study. The mHealth device was acceptable and promising for helping individuals with T2DM to reduce their HbA1c and lose weight. Devices with similar features should be tested further in larger studies which follow these methodological recommendations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-016-0331-2) contains supplementary material, which is available to authorized users.

Wearable Technology and Physical Activity Behavior Change in Adults With Chronic Cardiometabolic Disease: A Systematic Review and Meta-Analysis

“…Sample sizes ranged from 24 51 to 808 53 across RCTs with an aggregate total of 4528 participants recruited across 35 studies. Participants were recruited from multiple settings including in-hospital clinics (n ¼ 16, 45.7%), 31,32,[39][40][41][42][43][44]48,49,52,[55][56][57]61,65 primary care or general practice clinics (n ¼ 5, 14.3%), 34,45,50,53,59 public print or electronic advertisements (n ¼ 9, 25.7%), 30,33,35,46,51,58,62,63,66 or medical databases (n ¼ 2, 5.7%). 47,54 Three (8.6%) studies did not clearly specify how participants were recruited.…”

“…Five (38.5%) studies reported PA outcomes solely from a secondary previously validated, blinded accelerometer device [8][9][10][11][12] (eg, Actigraph, ActivPAL), two (15.4%) studies captured objective PA using a secondary sealed/blinded pedometer, 43,57 and six (46.2%) studies reported PA outcome data from the intervention device worn. 33,40,42,44,46,49 The remaining 13 (37.1%) studies used a combination of objective and selfreported PA data. 30,31,39,41,45,47,48,51,[53][54][55][56]59 Of these, six studies employed a validated self-report questionnaire including the International Physical Activity Questionnaire 31,41,53,54,56,59 or Minnesota Leisure-Time Physical Activity Questionnaire 30 in addition to objectively obtaining PA; two studies included a secondary blinded accelerometer in addition to the intervention device 54,59 ; and the remaining six studies varied based on objective and self-report PA outcome measure protocol.…”

“…39,45,47,48,51,55 A total of nine (25.7%) studies relied solely on self-report PA via the administration of diary/logs for participants to complete 34,50,58,63,64 or investigator-developed selfreport questionnaires. 32,35,66,67 Two studies 33,46 failed to report any raw PA outcome data collected from the intervention device.…”

Instrument for assessing mobile technology acceptability in diabetes self-management: a validation and reliability study

“…Many mHealth solutions for DM assistive control were proposed, ranging from technical interventions, 8 web-based applications, 9 clinical decision support systems, 10 online self-management programs, 11 and specific-task mobile applications 12 – 15 to applications promoting behavior change techniques, but the actual use has been demonstrated to be still limited. 16 – 19 However, the acceptance and use of mobile technology for disease management requires positive attitude and openness. 20 , 21 …”

Innovations in energy expenditure assessment

“…They provide information on duration of the exercise, heart rate, speed, distance and altitude covered during a training session, and can also help maintain the patient's motivation to pursue physical activity. They may be useful not only for athletes but also for patients with malnutrition, obesity and diabetes [22]. We will focus on wearable devices relying on accelerometry which measures the body accelerations along reference axes.…”