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      Efficacy and Safety of an mHealth App and Wearable Device in Physical Performance for Patients With Hepatocellular Carcinoma: Development and Usability Study

      research-article
      , MD, MMSc 1 , , BPTh 2 , , MPT 3 , , MD, PhD 4 , , MD, PhD 1 ,
      (Reviewer), (Reviewer)
      JMIR mHealth and uHealth
      JMIR Publications
      mHealth, hepatocellular carcinoma, rehabilitation, exercise, physical fitness, physical activity

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          Abstract

          Background

          Exercise is predicted to have a positive effect among hepatocellular carcinoma (HCC) patients. However, these patients are hesitant to start and build up an exercise program for one major reason: the vague fear of developing hepatic decompensation, a potentially fatal condition that can lead to death. Integrating mobile health (mHealth) with individualized exercise programs could be a possible option for promoting physical capacity among HCC patients.

          Objective

          The aim of this study was to evaluate the efficacy and safety of rehabilitation exercises, which have been individually prescribed via an mHealth app, on physical fitness, body composition, biochemical profile, and quality of life among HCC patients.

          Methods

          A total of 37 HCC patients were enrolled in a 12-week course with an mHealth app program targeted to HCC patients. The wearable wristband device Neofit (Partron Co) was provided to participants, and recorded daily physical data, such as the number of steps, calorie expenditure, exercise time, and heart rate. Each participant was given an individualized rehabilitation exercise program that was prescribed and adjusted at the 6-week midintervention period based on the assessment results. At baseline, 6-week, and 12-week sessions, participants’ physical fitness levels (ie, 6-minute walk test, grip strength test, and 30-second chair stand test) were measured. Physical activity levels, as measured by the International Physical Activity Questionnaire-Short Form (IPAQ-SF); body composition (ie, body mass index, body fat percentage, and muscle mass); biochemical profiles; and quality of life, as measured by the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire C30, were assessed at baseline and at the end point. At the 6-week midpoint, exercise intensity was individually adjusted.

          Results

          Of the 37 patients, 31 (84%) completed the 12-week intervention. Grip strength improved significantly after 12 weeks of the intervention. The 30-second chair stand test and the 6-minute walk test showed significant improvement from 0 to 6 weeks, from 0 to 12 weeks, and from 6 to 12 weeks. Muscle mass and the IPAQ-SF score increased significantly after 12 weeks of the intervention without biochemical deterioration.

          Conclusions

          Following 12 weeks of mHealth care, including an individually prescribed rehabilitation exercise program, we saw significant improvements in physical fitness, body composition, and physical activity without any complication or biochemical deterioration among compensated HCC patients who had completed therapy.

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          Most cited references31

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          Physical activity, sedentary behaviour, diet, and cancer: an update and emerging new evidence.

          The lifestyle factors of physical activity, sedentary behaviour, and diet are increasingly being studied for their associations with cancer. Physical activity is inversely associated with and sedentary behaviour is positively (and independently) associated with an increased risk of more than ten types of cancer, including colorectal cancer (and advanced adenomas), endometrial cancers, and breast cancer. The most consistent dietary risk factor for premalignant and invasive breast cancer is alcohol, whether consumed during early or late adult life, even at low levels. Epidemiological studies show that the inclusion of wholegrain, fibre, fruits, and vegetables within diets are associated with reduced cancer risk, with diet during early life (age <8 years) having the strongest apparent association with cancer incidence. However, randomised controlled trials of diet-related factors have not yet shown any conclusive associations between diet and cancer incidence. Obesity is a key contributory factor associated with cancer risk and mortality, including in dose-response associations in endometrial and post-menopausal breast cancer, and in degree and duration of fatty liver disease-related hepatocellular carcinoma. Obesity produces an inflammatory state, characterised by macrophages clustered around enlarged hypertrophied, dead, and dying adipocytes, forming crown-like structures. Increased concentrations of aromatase and interleukin 6 in inflamed breast tissue and an increased number of macrophages, compared with healthy tissue, are also observed in women with normal body mass index, suggesting a metabolic obesity state. Emerging randomised controlled trials of physical activity and dietary factors and mechanistic studies of immunity, inflammation, extracellular matrix mechanics, epigenetic or transcriptional regulation, protein translation, circadian disruption, and interactions of the multibiome with lifestyle factors will be crucial to advance this field.
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            Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis

            Background Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. Objective The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Methods Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. Results All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Conclusions Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings.
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              Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation

              Background Physical inactivity and sedentary behavior increase the risk of chronic illness and death. The newest generation of “wearable” activity trackers offers potential as a multifaceted intervention to help people become more active. Objective To examine the usability and usefulness of wearable activity trackers for older adults living with chronic illness. Methods We recruited a purposive sample of 32 participants over the age of 50, who had been previously diagnosed with a chronic illness, including vascular disease, diabetes, arthritis, and osteoporosis. Participants were between 52 and 84 years of age (mean 64); among the study participants, 23 (72%) were women and the mean body mass index was 31 kg/m2. Participants tested 5 trackers, including a simple pedometer (Sportline or Mio) followed by 4 wearable activity trackers (Fitbit Zip, Misfit Shine, Jawbone Up 24, and Withings Pulse) in random order. Selected devices represented the range of wearable products and features available on the Canadian market in 2014. Participants wore each device for at least 3 days and evaluated it using a questionnaire developed from the Technology Acceptance Model. We used focus groups to explore participant experiences and a thematic analysis approach to data collection and analysis. Results Our study resulted in 4 themes: (1) adoption within a comfort zone; (2) self-awareness and goal setting; (3) purposes of data tracking; and (4) future of wearable activity trackers as health care devices. Prior to enrolling, few participants were aware of wearable activity trackers. Most also had been asked by a physician to exercise more and cited this as a motivation for testing the devices. None of the participants planned to purchase the simple pedometer after the study, citing poor accuracy and data loss, whereas 73% (N=32) planned to purchase a wearable activity tracker. Preferences varied but 50% felt they would buy a Fitbit and 42% felt they would buy a Misfit, Jawbone, or Withings. The simple pedometer had a mean acceptance score of 56/95 compared with 63 for the Withings, 65 for the Misfit and Jawbone, and 68 for the Fitbit. To improve usability, older users may benefit from devices that have better compatibility with personal computers or less-expensive Android mobile phones and tablets, and have comprehensive paper-based user manuals and apps that interpret user data. Conclusions For older adults living with chronic illness, wearable activity trackers are perceived as useful and acceptable. New users may need support to both set up the device and learn how to interpret their data.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                March 2020
                11 March 2020
                : 8
                : 3
                : e14435
                Affiliations
                [1 ] Department of Physical and Rehabilitation Medicine Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea
                [2 ] Department of Rehabilitation Medicine Incheon St. Mary's Hospital The Catholic University of Korea Incheon Republic of Korea
                [3 ] Department of Health Science Korea University Graduate School Korea University Seoul Republic of Korea
                [4 ] Department of Internal Medicine Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea
                Author notes
                Corresponding Author: Ji Hye Hwang jhlee.hwang@ 123456samsung.com
                Author information
                https://orcid.org/0000-0002-7404-8432
                https://orcid.org/0000-0002-7039-3183
                https://orcid.org/0000-0001-9110-9738
                https://orcid.org/0000-0002-7126-5554
                https://orcid.org/0000-0002-8176-3354
                Article
                v8i3e14435
                10.2196/14435
                7097723
                32159517
                bf3bbb6e-4590-4db7-8a9b-93ea21338d69
                ©Yoon Kim, Jinserk Seo, So-Yeon An, Dong Hyun Sinn, Ji Hye Hwang. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 11.03.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 18 April 2019
                : 3 October 2019
                : 1 November 2019
                : 19 December 2019
                Categories
                Original Paper
                Original Paper

                mhealth,hepatocellular carcinoma,rehabilitation,exercise,physical fitness,physical activity

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