Anguera Joaquin A, Jordan Joshua T, Castaneda Diego, Gazzaley Adam, Areán Patricia A
Departments of Neurology and Psychiatry , University of California , San Francisco, California , USA.
Department of Psychiatry and Behavioral Sciences , University of Washington , Seattle, Washington , USA.
BMJ Innov. 2016 Jan;2(1):14-21. doi: 10.1136/bmjinnov-2015-000098.
Advances in mobile technology have resulted in federal and industry-level initiatives to facilitate large-scale clinical research using smart devices. Although the benefits of technology to expand data collection are obvious, assumptions about the reach of mobile research methods (), participant willingness to engage in mobile research protocols (), and the cost of this research () remain untested.
To assess the feasibility of a fully mobile randomised controlled trial using assessments and treatments delivered entirely through mobile devices to depressed individuals.
Using a web-based research portal, adult participants with depression who also owned a smart device were screened, consented and randomised to 1 of 3 mental health apps for treatment. Assessments of self-reported mood and cognitive function were conducted at baseline, 4, 8 and 12 weeks. Physical and social activity was monitored daily using passively collected phone use data. All treatment and assessment tools were housed on each participant's smart phone or tablet.
A cognitive training application, an application based on problem-solving therapy, and a mobile-sensing application promoting daily activities.
: We screened 2923 people and enrolled 1098 participants in 5 months. The sample characteristics were comparable to the 2013 US census data. Recruitment via Craigslist.org yielded the largest sample. : Study engagement was high during the first 2 weeks of treatment, falling to 44% adherence by the 4th week. : The total amount spent on for this project, including staff costs and β testing, was $314 264 over 2 years.
These findings suggest that mobile randomised control trials can recruit large numbers of participants in a short period of time and with minimal cost, but study engagement remains challenging.
NCT00540865.
移动技术的进步促使联邦政府和行业层面采取举措，以推动利用智能设备开展大规模临床研究。尽管技术在扩大数据收集方面的益处显而易见，但关于移动研究方法的覆盖范围（）、参与者参与移动研究方案的意愿（）以及此项研究的成本（）的假设仍未得到验证。
评估一项完全通过移动设备对抑郁症患者进行评估和治疗的全移动随机对照试验的可行性。
利用基于网络的研究平台，对患有抑郁症且拥有智能设备的成年参与者进行筛查、征得同意并随机分配至三款心理健康应用程序中的一款进行治疗。在基线、第4、8和12周对自我报告的情绪和认知功能进行评估。使用被动收集的手机使用数据每日监测身体和社交活动。所有治疗和评估工具均存储在每位参与者的智能手机或平板电脑上。
一款认知训练应用程序、一款基于解决问题疗法的应用程序以及一款促进日常活动的移动传感应用程序。
：我们在5个月内筛查了2923人并招募了1098名参与者。样本特征与2013年美国人口普查数据相当。通过Craigslist.org招募的样本量最大。：治疗的前两周研究参与度较高，到第4周依从率降至44%。：该项目在两年内的总花费，包括人员成本和β测试，为314,264美元。
这些发现表明，移动随机对照试验能够在短时间内以最低成本招募大量参与者，但研究参与度仍然具有挑战性。
NCT00540865。
