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      Daily Collection of Self-Reporting Sleep Disturbance Data via a Smartphone App in Breast Cancer Patients Receiving Chemotherapy: A Feasibility Study

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          Abstract

          Background

          Improvements in mobile telecommunication technologies have enabled clinicians to collect patient-reported outcome (PRO) data more frequently, but there is as yet limited evidence regarding the frequency with which PRO data can be collected via smartphone applications (apps) in breast cancer patients receiving chemotherapy.

          Objective

          The primary objective of this study was to determine the feasibility of an app for sleep disturbance-related data collection from breast cancer patients receiving chemotherapy. A secondary objective was to identify the variables associated with better compliance in order to identify the optimal subgroups to include in future studies of smartphone-based interventions.

          Methods

          Between March 2013 and July 2013, patients who planned to receive neoadjuvant chemotherapy for breast cancer at Asan Medical Center who had access to a smartphone app were enrolled just before the start of their chemotherapy and asked to self-report their sleep patterns, anxiety severity, and mood status via a smartphone app on a daily basis during the 90-day study period. Push notifications were sent to participants daily at 9 am and 7 pm. Data regarding the patients’ demographics, interval from enrollment to first self-report, baseline Beck’s Depression Inventory (BDI) score, and health-related quality of life score (as assessed using the EuroQol Five Dimensional [EQ5D-3L] questionnaire) were collected to ascertain the factors associated with compliance with the self-reporting process.

          Results

          A total of 30 participants (mean age 45 years, SD 6; range 35-65 years) were analyzed in this study. In total, 2700 daily push notifications were sent to these 30 participants over the 90-day study period via their smartphones, resulting in the collection of 1215 self-reporting sleep-disturbance data items (overall compliance rate=45.0%, 1215/2700). The median value of individual patient-level reporting rates was 41.1% (range 6.7-95.6%). The longitudinal day-level compliance curve fell to 50.0% at day 34 and reached a nadir of 13.3% at day 90. The cumulative longitudinal compliance curve exhibited a steady decrease by about 50% at day 70 and continued to fall to 45% on day 90. Women without any form of employment exhibited the higher compliance rate. There was no association between any of the other patient characteristics (ie, demographics, and BDI and EQ5D-3L scores) and compliance. The mean individual patient-level reporting rate was higher for the subgroup with a 1-day lag time, defined as starting to self-report on the day immediately after enrollment, than for those with a lag of 2 or more days (51.6%, SD 24.0 and 29.6%, SD 25.3, respectively; P=.03).

          Conclusions

          The 90-day longitudinal collection of daily self-reporting sleep-disturbance data via a smartphone app was found to be feasible. Further research should focus on how to sustain compliance with this self-reporting for a longer time and select subpopulations with higher rates of compliance for mobile health care.

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          Most cited references14

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          Mapping mHealth Research: A Decade of Evolution

          Background For the last decade, mHealth has constantly expanded as a part of eHealth. Mobile applications for health have the potential to target heterogeneous audiences and address specific needs in different situations, with diverse outcomes, and to complement highly developed health care technologies. The market is rapidly evolving, making countless new mobile technologies potentially available to the health care system; however, systematic research on the impact of these technologies on health outcomes remains scarce. Objective To provide a comprehensive view of the field of mHealth research to date and to understand whether and how the new generation of smartphones has triggered research, since their introduction 5 years ago. Specifically, we focused on studies aiming to evaluate the impact of mobile phones on health, and we sought to identify the main areas of health care delivery where mobile technologies can have an impact. Methods A systematic literature review was conducted on the impact of mobile phones and smartphones in health care. Abstracts and articles were categorized using typologies that were partly adapted from existing literature and partly created inductively from publications included in the review. Results The final sample consisted of 117 articles published between 2002 and 2012. The majority of them were published in the second half of our observation period, with a clear upsurge between 2007 and 2008, when the number of articles almost doubled. The articles were published in 77 different journals, mostly from the field of medicine or technology and medicine. Although the range of health conditions addressed was very wide, a clear focus on chronic conditions was noted. The research methodology of these studies was mostly clinical trials and pilot studies, but new designs were introduced in the second half of our observation period. The size of the samples drawn to test mobile health applications also increased over time. The majority of the studies tested basic mobile phone features (eg, text messaging), while only a few assessed the impact of smartphone apps. Regarding the investigated outcomes, we observed a shift from assessment of the technology itself to assessment of its impact. The outcome measures used in the studies were mostly clinical, including both self-reported and objective measures. Conclusions Research interest in mHealth is growing, together with an increasing complexity in research designs and aim specifications, as well as a diversification of the impact areas. However, new opportunities offered by new mobile technologies do not seem to have been explored thus far. Mapping the evolution of the field allows a better understanding of its strengths and weaknesses and can inform future developments.
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            Patient non-compliance with paper diaries.

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              Patient online self-reporting of toxicity symptoms during chemotherapy.

              Tracking symptoms related to treatment toxicity is standard practice in routine care and during clinical trials. Currently, clinicians collect symptom information via complex and often inefficient mechanisms, but there is growing interest in collecting outcome information directly from patients. The National Cancer Institute Common Terminology Criteria for Adverse Events schema for seven common symptoms was adapted into a Web-based patient-reporting system, accessible from desktop computers in outpatient clinics and from home computers. Eighty patients with gynecologic malignancies beginning standard chemotherapy regimens were enrolled between April and September 2004. During an 8-week observation period, participants were encouraged to log in and report symptoms at each follow-up visit, or alternatively, to access the system from home. All patients completed an initial log in. At each subsequent appointment, most enrollees (80% to 85%) reported symptoms using the online system, with a mean of three follow-up visits per patient during the observation period (range, one to six). Sixty of 80 patients (75%) logged in at least once from home. Use was significantly associated with prior Internet experience. Forty-two severe toxicities (grade 3 to 4) entered from home prompted seven clinician interventions. Most patients (96%) found the system useful and would recommend it to others. Patients are capable of reporting symptoms experienced during chemotherapy using a Web-based interface. Assessment in the clinical trial setting and comparison of direct patient- versus clinician-based approaches for reporting symptoms and their severity are warranted.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications Inc. (Toronto, Canada )
                1439-4456
                1438-8871
                May 2014
                23 May 2014
                : 16
                : 5
                : e135
                Affiliations
                [1] 1Seoul National University College of Nursing SeoulRepublic of Korea
                [2] 2Department of Surgery University of Ulsan College of Medicine Asan Medical Center SeoulRepublic of Korea
                [3] 3Department of Epidemiology School of Public Health and Institute of Health and Environment Seoul National University SeoulRepublic of Korea
                [4] 4Department of Psychiatry University of Ulsan College of Medicine Asan Medical Center SeoulRepublic of Korea
                [5] 5Department of Preventive Medicine University of Ulsan College of Medicine Asan Medical Center SeoulRepublic of Korea
                [6] 6Department of Emergency Medicine University of Ulsan College of Medicine Asan Medical Center SeoulRepublic of Korea
                [7] 7Medical Information Administration Team Asan Medical Center SeoulRepublic of Korea
                [8] 8Department of Oncology University of Ulsan College of Medicine Asan Medical Center SeoulRepublic of Korea
                Author notes
                Corresponding Author: Jong Won Lee jongwonlee116@ 123456gmail.com
                Article
                v16i5e135
                10.2196/jmir.3421
                4051741
                24860070
                f4cae0a2-eeb2-4384-a5ed-1d5ad75a54d6
                ©Yul Ha Min, Jong Won Lee, Yong-Wook Shin, Min-Woo Jo, Guiyun Sohn, Jae-Ho Lee, Guna Lee, Kyung Hae Jung, Joohon Sung, Beom Seok Ko, Jong-Han Yu, Hee Jeong Kim, Byung Ho Son, Sei Hyun Ahn. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 23.05.2014.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 25 March 2014
                : 12 April 2014
                : 14 April 2014
                : 19 May 2014
                Categories
                Original Paper
                Original Paper

                Medicine
                mobile applications,self report,compliance,breast cancer
                Medicine
                mobile applications, self report, compliance, breast cancer

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