Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions

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Abstract

Background

Patient retrospective recollection is a mainstay of assessing symptoms in mental health and psychiatry. However, evidence suggests that these retrospective recollections may not be as accurate as data collection though the experience sampling method (ESM), which captures patient data in “real time” and “real life.” However, the difficulties in practical implementation of ESM data collection have limited its impact in psychiatry and mental health. Smartphones with the capability to run mobile applications may offer a novel method of collecting ESM data that may represent a practical and feasible tool for mental health and psychiatry.

Objective

This paper aims to provide data on psychiatric patients’ prevalence of smartphone ownership, patterns of use, and interest in utilizing mobile applications to monitor their mental health conditions.

Methods

One hundred psychiatric outpatients at a large urban teaching hospital completed a paper-and-pencil survey regarding smartphone ownership, use, and interest in utilizing mobile applications to monitor their mental health condition.

Results

Ninety-seven percent of patients reported owning a phone and 72% reported that their phone was a smartphone. Patients in all age groups indicated greater than 50% interest in using a mobile application on a daily basis to monitor their mental health condition.

Conclusions

Smartphone and mobile applications represent a practical opportunity to explore new modalities of monitoring, treatment, and research of psychiatric and mental health conditions.

Related collections

Most cited references 15

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Harnessing Context Sensing to Develop a Mobile Intervention for Depression

Michelle Burns, Mark Begale, Jennifer Duffecy … (2011)

Background Mobile phone sensors can be used to develop context-aware systems that automatically detect when patients require assistance. Mobile phones can also provide ecological momentary interventions that deliver tailored assistance during problematic situations. However, such approaches have not yet been used to treat major depressive disorder. Objective The purpose of this study was to investigate the technical feasibility, functional reliability, and patient satisfaction with Mobilyze!, a mobile phone- and Internet-based intervention including ecological momentary intervention and context sensing. Methods We developed a mobile phone application and supporting architecture, in which machine learning models (ie, learners) predicted patients’ mood, emotions, cognitive/motivational states, activities, environmental context, and social context based on at least 38 concurrent phone sensor values (eg, global positioning system, ambient light, recent calls). The website included feedback graphs illustrating correlations between patients’ self-reported states, as well as didactics and tools teaching patients behavioral activation concepts. Brief telephone calls and emails with a clinician were used to promote adherence. We enrolled 8 adults with major depressive disorder in a single-arm pilot study to receive Mobilyze! and complete clinical assessments for 8 weeks. Results Promising accuracy rates (60% to 91%) were achieved by learners predicting categorical contextual states (eg, location). For states rated on scales (eg, mood), predictive capability was poor. Participants were satisfied with the phone application and improved significantly on self-reported depressive symptoms (betaweek = –.82, P < .001, per-protocol Cohen d = 3.43) and interview measures of depressive symptoms (betaweek = –.81, P < .001, per-protocol Cohen d = 3.55). Participants also became less likely to meet criteria for major depressive disorder diagnosis (bweek = –.65, P = .03, per-protocol remission rate = 85.71%). Comorbid anxiety symptoms also decreased (betaweek = –.71, P < .001, per-protocol Cohen d = 2.58). Conclusions Mobilyze! is a scalable, feasible intervention with preliminary evidence of efficacy. To our knowledge, it is the first ecological momentary intervention for unipolar depression, as well as one of the first attempts to use context sensing to identify mental health-related states. Several lessons learned regarding technical functionality, data mining, and software development process are discussed. Trial Registration Clinicaltrials.gov NCT01107041; http://clinicaltrials.gov/ct2/show/NCT01107041 (Archived by WebCite at http://www.webcitation.org/60CVjPH0n)

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Experience Sampling: Promises and Pitfalls, Strengths and Weaknesses

Christie Scollon, Chu Kim-Prieto (2003)

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Community Attitudes to the Appropriation of Mobile Phones for Monitoring and Managing Depression, Anxiety, and Stress

Judith Proudfoot, Gordon Parker, Dusan Hadzi-Pavlovic … (2010)

Background The benefits of self-monitoring on symptom severity, coping, and quality of life have been amply demonstrated. However, paper and pencil self-monitoring can be cumbersome and subject to biases associated with retrospective recall, while computer-based monitoring can be inconvenient in that it relies on users being at their computer at scheduled monitoring times. As a result, nonadherence in self-monitoring is common. Mobile phones offer an alternative. Their take-up has reached saturation point in most developed countries and is increasing in developing countries; they are carried on the person, they are usually turned on, and functionality is continually improving. Currently, however, public conceptions of mobile phones focus on their use as tools for communication and social identity. Community attitudes toward using mobile phones for mental health monitoring and self-management are not known. Objective The objective was to explore community attitudes toward the appropriation of mobile phones for mental health monitoring and management. Methods We held community consultations in Australia consisting of an online survey (n = 525), focus group discussions (n = 47), and interviews (n = 20). Results Respondents used their mobile phones daily and predominantly for communication purposes. Of those who completed the online survey, the majority (399/525 or 76%) reported that they would be interested in using their mobile phone for mental health monitoring and self-management if the service were free. Of the 455 participants who owned a mobile phone or PDA, there were no significant differences between those who expressed interest in the use of mobile phones for this purpose and those who did not by gender (χ21, = 0.98, P = .32, phi = .05), age group (χ24, = 1.95, P = .75, phi = .06), employment status (χ22, = 2.74, P = .25, phi = .08) or marital status (χ24, = 4.62, P = .33, phi = .10). However, the presence of current symptoms of depression, anxiety, or stress affected interest in such a program in that those with symptoms were more interested (χ2 1, = 16.67, P < .001, phi = .19). Reasons given for interest in using a mobile phone program were that it would be convenient, counteract isolation, and help identify triggers to mood states. Reasons given for lack of interest included not liking to use a mobile phone or technology, concerns that it would be too intrusive or that privacy would be lacking, and not seeing the need. Design features considered to be key by participants were enhanced privacy and security functions including user name and password, ease of use, the provision of reminders, and the availability of clear feedback. Conclusions Community attitudes toward the appropriation of mobile phones for the monitoring and self-management of depression, anxiety, and stress appear to be positive as long as privacy and security provisions are assured, the program is intuitive and easy to use, and the feedback is clear.

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Author and article information

Contributors

John Torous:

Harvard Longwod Psychiatry Residency Training Prorgam330 Brookline AveBoston, MA, 02215United States1 617 667 46301 617 667 5575jtorous@bidmc.harvard.edu

Journal

Journal ID (nlm-ta): JMIR Mhealth Uhealth

Journal ID (iso-abbrev): JMIR Mhealth Uhealth

Journal ID (publisher-id): JMU

Title: JMIR mHealth and uHealth

Publisher: JMIR Publications Inc. (Toronto, Canada )

ISSN (Electronic): 2291-5222

Publication date Collection: Jan-Mar 2014

Publication date (Electronic): 21 January 2014

Volume: 2

Issue: 1

Electronic Location Identifier: e2

Affiliations

[1] ¹Harvard Longwod Psychiatry Residency Training Prorgam Boston, MAUnited States

[2] ²Beth Israel Deaconess Medical Center Department of Psychiatry Harvard Medical School Boston, MAUnited States

Author notes

Corresponding Author: John Torous jtorous@ 123456bidmc.harvard.edu

Article

Publisher ID: v2i1e2

DOI: 10.2196/mhealth.2994

PMC ID: 4114412

PubMed ID: 25098314

SO-VID: ad9fcc95-10a5-4bc7-a993-80048650b07e

License:

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 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

Date received : 29 September 2013

Date revision requested : 30 October 2013

Date revision received : 11 November 2013

Date accepted : 23 December 2013

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