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      Utilizing a Personal Smartphone Custom App to Assess the Patient Health Questionnaire-9 (PHQ-9) Depressive Symptoms in Patients With Major Depressive Disorder


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          Accurate reporting of patient symptoms is critical for diagnosis and therapeutic monitoring in psychiatry. Smartphones offer an accessible, low-cost means to collect patient symptoms in real time and aid in care.


          To investigate adherence among psychiatric outpatients diagnosed with major depressive disorder in utilizing their personal smartphones to run a custom app to monitor Patient Health Questionnaire-9 (PHQ-9) depression symptoms, as well as to examine the correlation of these scores to traditionally administered (paper-and-pencil) PHQ-9 scores.


          A total of 13 patients with major depressive disorder, referred by their clinicians, received standard outpatient treatment and, in addition, utilized their personal smartphones to run the study app to monitor their symptoms. Subjects downloaded and used the Mindful Moods app on their personal smartphone to complete up to three survey sessions per day, during which a randomized subset of PHQ-9 symptoms of major depressive disorder were assessed on a Likert scale. The study lasted 29 or 30 days without additional follow-up. Outcome measures included adherence, measured by the percentage of completed survey sessions, and estimates of daily PHQ-9 scores collected from the smartphone app, as well as from the traditionally administered PHQ-9.


          Overall adherence was 77.78% (903/1161) and varied with time of day. PHQ-9 estimates collected from the app strongly correlated ( r=.84) with traditionally administered PHQ-9 scores, but app-collected scores were 3.02 (SD 2.25) points higher on average. More subjects reported suicidal ideation using the app than they did on the traditionally administered PHQ-9.


          Patients with major depressive disorder are able to utilize an app on their personal smartphones to self-assess their symptoms of major depressive disorder with high levels of adherence. These app-collected results correlate with the traditionally administered PHQ-9. Scores recorded from the app may potentially be more sensitive and better able to capture suicidality than the traditional PHQ-9.

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          Harnessing Context Sensing to Develop a Mobile Intervention for Depression

          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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            Assessing depression in primary care with the PHQ-9: can it be carried out over the telephone?

            Telephone assessment of depression for research purposes is increasingly being used. The Patient Health Questionnaire 9-item depression module (PHQ-9) is a well-validated, brief, self-reported, diagnostic, and severity measure of depression designed for use in primary care (PC). To our knowledge, there are no available data regarding its validity when administered over the telephone. The aims of the present study were to evaluate agreement between self-administered and telephone-administered PHQ-9, to investigate possible systematic bias, and to evaluate the internal consistency of the telephone-administered PHQ-9. Three hundred and forty-six participants from two PC centers were assessed twice with the PHQ-9. Participants were divided into 4 groups according to administration procedure order and administration procedure of the PHQ-9: Self-administered/Telephone-administered; Telephone-administered/Self-administered; Telephone-administered/Telephone-administered; and Self-administered/Self-administered. The first 2 groups served for analyzing the procedural validity of telephone-administered PHQ-9. The last 2 allowed a test-retest reliability analysis of both self- and telephone-administered PHQ-9. Intraclass correlation coefficient (ICC) and weighted kappa (for each item) were calculated as measures of concordance. Additionally, Pearson's correlation coefficient, Student's t-test, and Cronbach's alpha were analyzed. Intraclass correlation coefficient and weighted kappa between both administration procedures were excellent, revealing a strong concordance between telephone- and self-administered PHQ-9. A small and clinically nonsignificant tendency was observed toward lower scores for the telephone-administered PHQ-9. The internal consistency of the telephone-administered PHQ-9 was high and close to the self-administered one. Telephone and in-person assessments by means of the PHQ-9 yield similar results. Thus, telephone administration of the PHQ-9 seems to be a reliable procedure for assessing depression in PC.
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              Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions

              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.

                Author and article information

                JMIR Ment Health
                JMIR Ment Health
                JMIR Mental Health
                JMIR Publications Inc. (Toronto, Canada )
                Jan-Mar 2015
                24 March 2015
                : 2
                : 1
                : e8
                [1] 1Harvard Longwood Psychiatry Residency Training Prorgam Boston, MAUnited States
                [2] 2Beth Israel Deaconess Medical Center Department of Psychiatry Harvard Medical School Boston, MAUnited States
                [3] 3Department of Biostatistics Harvard School of Public Health Harvard University Boston, MAUnited States
                [4] 4Pocket Gems Palo Alto, CAUnited States
                Author notes
                Corresponding Author: John Torous jtorous@ 123456bidmc.harvard.edu
                Author information
                ©John Torous, Patrick Staples, Meghan Shanahan, Charlie Lin, Pamela Peck, Matcheri Keshavan, Jukka-Pekka Onnela. Originally published in JMIR Mental Health (http://mental.jmir.org), 24.03.2015.

                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 Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included.

                : 24 September 2014
                : 30 December 2014
                : 12 January 2015
                : 22 January 2015
                Original Paper
                Original Paper

                medical informatics,mobile health,depression
                medical informatics, mobile health, depression


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