TY - JOUR AU - Paredes, Enrique Pablo AU - Hamdan, Al-Huda Nur AU - Clark, Dav AU - Cai, Carrie AU - Ju, Wendy AU - Landay, A. James PY - 2017/12/04 TI - Evaluating In-Car Movements in the Design of Mindful Commute Interventions: Exploratory Study JO - J Med Internet Res SP - e372 VL - 19 IS - 12 KW - mental health KW - stress KW - stress management KW - mindfulness KW - in-car experience KW - interventions KW - just-in-time interventions KW - autonomous vehicles KW - cars KW - driving KW - breathing KW - mindful movement N2 - Background: The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges. Objective: This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights. Methods: We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete movements (configural or breath-based) while engaged in either simple (highway) or complex (city) simulated urban driving tasks using autonomous and manual driving modes. Then, we performed a matching exercise where participants could experience vibrotactile patterns from the back of the car seat and map them to the prior movements. Results: We report a summary of individual perceptions concerning different movements and vibrotactile patterns. Beside describing situations within a drive when it may be more likely to perform movement-based interventions, we also describe movements that may interfere with driving and those that may complement it well. Furthermore, we identify movements that could be conducive to a more relaxing commute and describe vibrotactile patterns that could guide such movements and exercises. We discuss implications for design such as the influence of driving modality on the adoption of movement, need for personal customization, the influence that social perception has on participants, and the potential role of prior awareness of mindful techniques in the adoption of new movement-based interventions. Conclusions: This exploratory study provides insights into which types of movements could be better suited to design mindful interventions to reduce stress for commuters, when to encourage such movements, and how best to guide them using noninvasive haptic stimuli embedded in the car seat. UR - http://www.jmir.org/2017/12/e372/ UR - http://dx.doi.org/10.2196/jmir.6983 UR - http://www.ncbi.nlm.nih.gov/pubmed/29203458 ID - info:doi/10.2196/jmir.6983 ER - TY - JOUR AU - Brodey, B. Benjamin AU - Gonzalez, L. Nicole AU - Elkin, Ann Kathryn AU - Sasiela, Jordan W. AU - Brodey, S. Inger PY - 2017/09/06 TI - Assessing the Equivalence of Paper, Mobile Phone, and Tablet Survey Responses at a Community Mental Health Center Using Equivalent Halves of a ?Gold-Standard? Depression Item Bank JO - JMIR Ment Health SP - e36 VL - 4 IS - 3 KW - mobile phone KW - tablet KW - PROMIS KW - depression KW - item response theory KW - outcomes tracking KW - PORTAL KW - TeleSage KW - behavioral health KW - special issue on computing and mental health N2 - Background: The computerized administration of self-report psychiatric diagnostic and outcomes assessments has risen in popularity. If results are similar enough across different administration modalities, then new administration technologies can be used interchangeably and the choice of technology can be based on other factors, such as convenience in the study design. An assessment based on item response theory (IRT), such as the Patient-Reported Outcomes Measurement Information System (PROMIS) depression item bank, offers new possibilities for assessing the effect of technology choice upon results. Objective: To create equivalent halves of the PROMIS depression item bank and to use these halves to compare survey responses and user satisfaction among administration modalities?paper, mobile phone, or tablet?with a community mental health care population. Methods: The 28 PROMIS depression items were divided into 2 halves based on content and simulations with an established PROMIS response data set. A total of 129 participants were recruited from an outpatient public sector mental health clinic based in Memphis. All participants took both nonoverlapping halves of the PROMIS IRT-based depression items (Part A and Part B): once using paper and pencil, and once using either a mobile phone or tablet. An 8-cell randomization was done on technology used, order of technologies used, and order of PROMIS Parts A and B. Both Parts A and B were administered as fixed-length assessments and both were scored using published PROMIS IRT parameters and algorithms. Results: All 129 participants received either Part A or B via paper assessment. Participants were also administered the opposite assessment, 63 using a mobile phone and 66 using a tablet. There was no significant difference in item response scores for Part A versus B. All 3 of the technologies yielded essentially identical assessment results and equivalent satisfaction levels. Conclusions: Our findings show that the PROMIS depression assessment can be divided into 2 equivalent halves, with the potential to simplify future experimental methodologies. Among community mental health care recipients, the PROMIS items function similarly whether administered via paper, tablet, or mobile phone. User satisfaction across modalities was also similar. Because paper, tablet, and mobile phone administrations yielded similar results, the choice of technology should be based on factors such as convenience and can even be changed during a study without adversely affecting the comparability of results. UR - http://mental.jmir.org/2017/3/e36/ UR - http://dx.doi.org/10.2196/mental.6805 UR - http://www.ncbi.nlm.nih.gov/pubmed/28877861 ID - info:doi/10.2196/mental.6805 ER - TY - JOUR AU - Hoermann, Simon AU - McCabe, L. Kathryn AU - Milne, N. David AU - Calvo, A. Rafael PY - 2017/7/21 TI - Application of Synchronous Text-Based Dialogue Systems in Mental Health Interventions: Systematic Review JO - J Med Internet Res SP - e267 VL - 19 IS - 8 KW - chat KW - dialog system KW - remote psychotherapy N2 - Background: Synchronous written conversations (or ?chats?) are becoming increasingly popular as Web-based mental health interventions. Therefore, it is of utmost importance to evaluate and summarize the quality of these interventions. Objective: The aim of this study was to review the current evidence for the feasibility and effectiveness of online one-on-one mental health interventions that use text-based synchronous chat. Methods: A systematic search was conducted of the databases relevant to this area of research (Medical Literature Analysis and Retrieval System Online [MEDLINE], PsycINFO, Central, Scopus, EMBASE, Web of Science, IEEE, and ACM). There were no specific selection criteria relating to the participant group. Studies were included if they reported interventions with individual text-based synchronous conversations (ie, chat or text messaging) and a psychological outcome measure. Results: A total of 24 articles were included in this review. Interventions included a wide range of mental health targets (eg, anxiety, distress, depression, eating disorders, and addiction) and intervention design. Overall, compared with the waitlist (WL) condition, studies showed significant and sustained improvements in mental health outcomes following synchronous text-based intervention, and post treatment improvement equivalent but not superior to treatment as usual (TAU) (eg, face-to-face and telephone counseling). Conclusions: Feasibility studies indicate substantial innovation in this area of mental health intervention with studies utilizing trained volunteers and chatbot technologies to deliver interventions. While studies of efficacy show positive post-intervention gains, further research is needed to determine whether time requirements for this mode of intervention are feasible in clinical practice. UR - http://www.jmir.org/2017/8/e267/ UR - http://dx.doi.org/10.2196/jmir.7023 UR - http://www.ncbi.nlm.nih.gov/pubmed/28784594 ID - info:doi/10.2196/jmir.7023 ER - TY - JOUR AU - Kaiser, Tim AU - Laireiter, Rupert Anton PY - 2017/07/20 TI - DynAMo: A Modular Platform for Monitoring Process, Outcome, and Algorithm-Based Treatment Planning in Psychotherapy JO - JMIR Med Inform SP - e20 VL - 5 IS - 3 KW - health information management KW - mental health KW - mental disorders KW - psychotherapeutic processes KW - algorithms N2 - Background: In recent years, the assessment of mental disorders has become more and more personalized. Modern advancements such as Internet-enabled mobile phones and increased computing capacity make it possible to tap sources of information that have long been unavailable to mental health practitioners. Objective: Software packages that combine algorithm-based treatment planning, process monitoring, and outcome monitoring are scarce. The objective of this study was to assess whether the DynAMo Web application can fill this gap by providing a software solution that can be used by both researchers to conduct state-of-the-art psychotherapy process research and clinicians to plan treatments and monitor psychotherapeutic processes. Methods: In this paper, we report on the current state of a Web application that can be used for assessing the temporal structure of mental disorders using information on their temporal and synchronous associations. A treatment planning algorithm automatically interprets the data and delivers priority scores of symptoms to practitioners. The application is also capable of monitoring psychotherapeutic processes during therapy and of monitoring treatment outcomes. This application was developed using the R programming language (R Core Team, Vienna) and the Shiny Web application framework (RStudio, Inc, Boston). It is made entirely from open-source software packages and thus is easily extensible. Results: The capabilities of the proposed application are demonstrated. Case illustrations are provided to exemplify its usefulness in clinical practice. Conclusions: With the broad availability of Internet-enabled mobile phones and similar devices, collecting data on psychopathology and psychotherapeutic processes has become easier than ever. The proposed application is a valuable tool for capturing, processing, and visualizing these data. The combination of dynamic assessment and process- and outcome monitoring has the potential to improve the efficacy and effectiveness of psychotherapy. UR - http://medinform.jmir.org/2017/3/e20/ UR - http://dx.doi.org/10.2196/medinform.6808 UR - http://www.ncbi.nlm.nih.gov/pubmed/28729233 ID - info:doi/10.2196/medinform.6808 ER - TY - JOUR AU - Huang, Hsiao-Ying AU - Bashir, Masooda PY - 2017/06/28 TI - Users? Adoption of Mental Health Apps: Examining the Impact of Information Cues JO - JMIR Mhealth Uhealth SP - e83 VL - 5 IS - 6 KW - user interaction design KW - recommendation system KW - mobile app search KW - mental health KW - anxiety N2 - Background: Numerous mental health apps have been developed and made available to users on the current app market. Users may find it difficult and overwhelming to select apps from the hundreds of choices that are available in the app marketplace. Clarifying what information cues may impact a user?s selection and adoption of mental health apps is now a critical and pressing issue. Objective: The aim of this study was to investigate the impact of information cues on users? adoption of anxiety apps using observational data from the Android app market. Methods: A systematic search of anxiety apps was conducted on the Android app store by using keywords search. The title and metadata information of a total of 274 apps that met our criteria were collected and analyzed. Three trained researchers recorded the app rankings from the search results page on different dates and Web browsers. Results: Our results show that ratings (r=.56, P<.001) and reviews (r=.39, P<.001) have significant positive correlations with the number of installs, and app prices have significant negative correlations with installs (r=?.36). The results also reveal that lower-priced apps have higher ratings (r=?.23, P<.001) and a greater number of app permission requests (r=.18, P=.002) from the device. For app titles, we found that apps with titles related to symptoms have significantly lower installs than apps with titles that are not related to symptoms (P<.001). Conclusions: This study revealed a relationship between information cues and users? adoption of mental health apps by analyzing observational data. As the first of its kind, we found impactful indicators for mental health app adoptions. We also discovered a labeling effect of app titles that could hinder mental health app adoptions and which may provide insight for future designs of mental health apps and their search mechanisms. UR - http://mhealth.jmir.org/2017/6/e83/ UR - http://dx.doi.org/10.2196/mhealth.6827 UR - http://www.ncbi.nlm.nih.gov/pubmed/28659256 ID - info:doi/10.2196/mhealth.6827 ER - TY - JOUR AU - Zhu, Bin AU - Hedman, Anders AU - Feng, Shuo AU - Li, Haibo AU - Osika, Walter PY - 2017/06/14 TI - Designing, Prototyping and Evaluating Digital Mindfulness Applications: A Case Study of Mindful Breathing for Stress Reduction JO - J Med Internet Res SP - e197 VL - 19 IS - 6 KW - respiration KW - biofeedback KW - mindfulness KW - stress KW - device design KW - sound KW - light KW - breathing KW - heart rate KW - relaxation N2 - Background: During the past decade, there has been a rapid increase of interactive apps designed for health and well-being. Yet, little research has been published on developing frameworks for design and evaluation of digital mindfulness facilitating technologies. Moreover, many existing digital mindfulness applications are purely software based. There is room for further exploration and assessment of designs that make more use of physical qualities of artifacts. Objective: The study aimed to develop and test a new physical digital mindfulness prototype designed for stress reduction. Methods: In this case study, we designed, developed, and evaluated HU, a physical digital mindfulness prototype designed for stress reduction. In the first phase, we used vapor and light to support mindful breathing and invited 25 participants through snowball sampling to test HU. In the second phase, we added sonification. We deployed a package of probes such as photos, diaries, and cards to collect data from users who explored HU in their homes. Thereafter, we evaluated our installation using both self-assessed stress levels and heart rate (HR) and heart rate variability (HRV) measures in a pilot study, in order to measure stress resilience effects. After the experiment, we performed a semistructured interview to reflect on HU and investigate the design of digital mindfulness apps for stress reduction. Results: The results of the first phase showed that 22 of 25 participants (88%) claimed vapor and light could be effective ways of promoting mindful breathing. Vapor could potentially support mindful breathing better than light (especially for mindfulness beginners). In addition, a majority of the participants mentioned sound as an alternative medium. In the second phase, we found that participants thought that HU could work well for stress reduction. We compared the effect of silent HU (using light and vapor without sound) and sonified HU on 5 participants. Subjective stress levels were statistically improved with both silent and sonified HU. The mean value of HR using silent HU was significantly lower than resting baseline and sonified HU. The mean value of root mean square of differences (RMSSD) using silent HU was significantly higher than resting baseline. We found that the differences between our objective and subjective assessments were intriguing and prompted us to investigate them further. Conclusions: Our evaluation of HU indicated that HU could facilitate relaxed breathing and stress reduction. There was a difference in outcome between the physiological measures of stress and the subjective reports of stress, as well as a large intervariability among study participants. Our conclusion is that the use of stress reduction tools should be customized and that the design work of mindfulness technology for stress reduction is a complex process, which requires cooperation of designers, HCI (Human-Computer Interaction) experts and clinicians. UR - http://www.jmir.org/2017/6/e197/ UR - http://dx.doi.org/10.2196/jmir.6955 UR - http://www.ncbi.nlm.nih.gov/pubmed/28615157 ID - info:doi/10.2196/jmir.6955 ER - TY - JOUR AU - Aledavood, Talayeh AU - Triana Hoyos, Maria Ana AU - Alakörkkö, Tuomas AU - Kaski, Kimmo AU - Saramäki, Jari AU - Isometsä, Erkki AU - Darst, K. Richard PY - 2017/06/09 TI - Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype JO - JMIR Res Protoc SP - e110 VL - 6 IS - 6 KW - data collection framework KW - mental health KW - digital phenotyping KW - big data N2 - Background: Mental and behavioral disorders are the main cause of disability worldwide. However, their diagnosis is challenging due to a lack of reliable biomarkers; current detection is based on structured clinical interviews which can be biased by the patient?s recall ability, affective state, changing in temporal frames, etc. While digital platforms have been introduced as a possible solution to this complex problem, there is little evidence on the extent of usability and usefulness of these platforms. Therefore, more studies where digital data is collected in larger scales are needed to collect scientific evidence on the capacities of these platforms. Most of the existing platforms for digital psychiatry studies are designed as monolithic systems for a certain type of study; publications from these studies focus on their results, rather than the design features of the data collection platform. Inevitably, more tools and platforms will emerge in the near future to fulfill the need for digital data collection for psychiatry. Currently little knowledge is available from existing digital platforms for future data collection platforms to build upon. Objective: The objective of this work was to identify the most important features for designing a digital platform for data collection for mental health studies, and to demonstrate a prototype platform that we built based on these design features. Methods: We worked closely in a multidisciplinary collaboration with psychiatrists, software developers, and data scientists and identified the key features which could guarantee short-term and long-term stability and usefulness of the platform from the designing stage to data collection and analysis of collected data. Results: The key design features that we identified were flexibility of access control, flexibility of data sources, and first-order privacy protection. We also designed the prototype platform Non-Intrusive Individual Monitoring Architecture (Niima), where we implemented these key design features. We described why each of these features are important for digital data collection for psychiatry, gave examples of projects where Niima was used or is going to be used in the future, and demonstrated how incorporating these design principles opens new possibilities for studies. Conclusions: The new methods of digital psychiatry are still immature and need further research. The design features we suggested are a first step to design platforms which can adapt to the upcoming requirements of digital psychiatry. UR - http://www.researchprotocols.org/2017/6/e110/ UR - http://dx.doi.org/10.2196/resprot.6919 UR - http://www.ncbi.nlm.nih.gov/pubmed/28600276 ID - info:doi/10.2196/resprot.6919 ER - TY - JOUR AU - Boudreaux, D. Edwin AU - Brown, K. Gregory AU - Stanley, Barbara AU - Sadasivam, S. Rajani AU - Camargo, A. Carlos AU - Miller, W. Ivan PY - 2017/05/15 TI - Computer Administered Safety Planning for Individuals at Risk for Suicide: Development and Usability Testing JO - J Med Internet Res SP - e149 VL - 19 IS - 5 KW - technology KW - safety KW - health planning KW - suicide KW - computers KW - telemedicine N2 - Background: Safety planning is a brief intervention that has become an accepted practice in many clinical settings to help prevent suicide. Even though it is quick compared to other approaches, it frequently requires 20 min or more to complete, which can impede adoption. A self-administered, Web-based safety planning application could potentially reduce clinician time, help promote standardization and quality, and provide enhanced ability to share the created plan. Objective: The aim of this study was to design, build, and test the usability of a Web-based, self-administered safety planning application. Methods: We employed a user-centered software design strategy led by a multidisciplinary team. The application was tested for usability with a target sample of suicidal patients. Detailed observations, structured usability ratings, and Think Aloud procedures were used. Suicidal ideation intensity and perceived ability to cope were assessed pre-post engagement with the Web application. Results: A total of 30 participants were enrolled. Usability ratings were generally strong, and all patients successfully built a safety plan. However, the completeness of the safety plan varied. The mean number of steps completed was 5.5 (SD 0.9) out of 6, with 90% (27/30) of participants completing at least 5 steps and 67% (20/30) completing all 6 steps. Some safety planning steps were viewed as inapplicable to some individuals. Some confusion in instructions led to modifications to improve understandability of each step. Ratings of suicide intensity after completion of the application were significantly lower than preratings, pre: mean 5.11 (SD 2.9) versus post: mean 4.46 (SD 3.0), t27=2.49, P=.02. Ratings of ability to cope with suicidal thoughts after completion of the application were higher than preratings, with the difference approaching statistical significance, pre: mean 5.93 (SD 2.9), post: mean 6.64 (SD 2.4), t27=?2.03, P=.05. Conclusions: We have taken the first step toward identifying the components needed to maximize usability of a self-administered, Web-based safety planning application. Results support initial consideration of the application as an adjunct to clinical contact. This allows for the clinician or other personnel to provide clarification, when needed, to help the patient build the plan, and to help review and revise the draft. UR - http://www.jmir.org/2017/5/e149/ UR - http://dx.doi.org/10.2196/jmir.6816 UR - http://www.ncbi.nlm.nih.gov/pubmed/28506957 ID - info:doi/10.2196/jmir.6816 ER - TY - JOUR AU - Aguilera, Adrian AU - Bruehlman-Senecal, Emma AU - Demasi, Orianna AU - Avila, Patricia PY - 2017/05/08 TI - Automated Text Messaging as an Adjunct to Cognitive Behavioral Therapy for Depression: A Clinical Trial JO - J Med Internet Res SP - e148 VL - 19 IS - 5 KW - depression KW - text messaging KW - cognitive behavioral therapy KW - mhealth KW - mental health KW - Latinos N2 - Background: Cognitive Behavioral Therapy (CBT) for depression is efficacious, but effectiveness is limited when implemented in low-income settings due to engagement difficulties including nonadherence with skill-building homework and early discontinuation of treatment. Automated messaging can be used in clinical settings to increase dosage of depression treatment and encourage sustained engagement with psychotherapy. Objectives: The aim of this study was to test whether a text messaging adjunct (mood monitoring text messages, treatment-related text messages, and a clinician dashboard to display patient data) increases engagement and improves clinical outcomes in a group CBT treatment for depression. Specifically, we aim to assess whether the text messaging adjunct led to an increase in group therapy sessions attended, an increase in duration of therapy attended, and reductions in Patient Health Questionnaire-9 item (PHQ-9) symptoms compared with the control condition of standard group CBT in a sample of low-income Spanish speaking Latino patients. Methods: Patients in an outpatient behavioral health clinic were assigned to standard group CBT for depression (control condition; n=40) or the same treatment with the addition of a text messaging adjunct (n=45). The adjunct consisted of a daily mood monitoring message, a daily message reiterating the theme of that week?s content, and medication and appointment reminders. Mood data and qualitative responses were sent to a Web-based platform (HealthySMS) for review by the therapist and displayed in session as a tool for teaching CBT skills. Results: Intent-to-treat analyses on therapy attendance during 16 sessions of weekly therapy found that patients assigned to the text messaging adjunct stayed in therapy significantly longer (median of 13.5 weeks before dropping out) than patients assigned to the control condition (median of 3 weeks before dropping out; Wilcoxon-Mann-Whitney z=?2.21, P=.03). Patients assigned to the text messaging adjunct also generally attended more sessions (median=6 sessions) during this period than patients assigned to the control condition (median =2.5 sessions), but the effect was not significant (Wilcoxon-Mann-Whitney z=?1.65, P=.10). Both patients assigned to the text messaging adjunct (B=?.29, 95% CI ?0.38 to ?0.19, z=?5.80, P<.001) and patients assigned to the control conditions (B=?.20, 95% CI ?0.32 to ?0.07, z=?3.12, P=.002) experienced significant decreases in depressive symptom severity over the course of treatment; however, the conditions did not significantly differ in their degree of symptom reduction. Conclusions: This study provides support for automated text messaging as a tool to sustain engagement in CBT for depression over time. There were no differences in depression outcomes between conditions, but this may be influenced by low follow-up rates of patients who dropped out of treatment. UR - http://www.jmir.org/2017/5/e148/ UR - http://dx.doi.org/10.2196/jmir.6914 UR - http://www.ncbi.nlm.nih.gov/pubmed/28483742 ID - info:doi/10.2196/jmir.6914 ER - TY - JOUR AU - Saha, Koustuv AU - Weber, Ingmar AU - Birnbaum, L. Michael AU - De Choudhury, Munmun PY - 2017/05/08 TI - Characterizing Awareness of Schizophrenia Among Facebook Users by Leveraging Facebook Advertisement Estimates JO - J Med Internet Res SP - e156 VL - 19 IS - 5 KW - schizophrenia KW - psychotic disorders KW - online social networks KW - health awareness KW - mental health KW - public health KW - Facebook N2 - Background: Schizophrenia is a rare but devastating condition, affecting about 1% of the world?s population and resulting in about 2% of the US health care expenditure. Major impediments to appropriate and timely care include misconceptions, high levels of stigma, and lack of public awareness. Facebook offers novel opportunities to understand public awareness and information access related to schizophrenia, and thus can complement survey-based approaches to assessing awareness that are limited in scale, robustness, and temporal and demographic granularity. Objective: The aims of this study were to (1) construct an index that measured the awareness of different demographic groups around schizophrenia-related information on Facebook; (2) study how this index differed across demographic groups and how it correlated with complementary Web-based (Google Trends) and non?Web-based variables about population well-being (mental health indicators and infrastructure), and (3) examine the relationship of Facebook derived schizophrenia index with other types of online activity as well as offline health and mental health outcomes and indicators. Methods: Data from Facebook?s advertising platform was programmatically collected to compute the proportion of users in a target demographic group with an interest related to schizophrenia. On consultation with a clinical expert, several topics were combined to obtain a single index measuring schizophrenia awareness. This index was then analyzed for differences across US states, gender, age, ethnic affinity, and education level. A statistical approach was developed to model a group?s awareness index based on the group?s characteristics. Results: Overall, 1.03% of Facebook users in the United States have a schizophrenia-related interest. The schizophrenia awareness index (SAI) is higher for females than for males (1.06 vs 0.97, P<.001), and it is highest for the people who are aged 25-44 years (1.35 vs 1.03 for all ages, P<.001). The awareness index drops for higher education levels (0.68 for MA or PhD vs 1.92 for no high school degree, P<.001), and Hispanics have the highest level of interest (1.57 vs 1.03 for all ethnic affinities, P<.001). A regression model fit to predict a group?s interest level achieves an adjusted R2=0.55. We also observe a positive association between our SAI and mental health services (or institutions) per 100,000 residents in a US state (Pearson r=.238, P<.001), but a negative association with the state-level human development index (HDI) in United States (Pearson r=?.145, P<.001) and state-level volume of mental health issues in United States (Pearson r=?.145, P<.001). Conclusions: Facebook?s advertising platform can be used to construct a plausible index of population-scale schizophrenia awareness. However, only estimates of awareness can be obtained, and the index provides no information on the quality of the information users receive online. UR - http://www.jmir.org/2017/5/e156/ UR - http://dx.doi.org/10.2196/jmir.6815 UR - http://www.ncbi.nlm.nih.gov/pubmed/28483739 ID - info:doi/10.2196/jmir.6815 ER - TY - JOUR AU - Haskins, L. Brianna AU - Davis-Martin, Rachel AU - Abar, Beau AU - Baumann, M. Brigitte AU - Harralson, Tina AU - Boudreaux, D. Edwin PY - 2017/05/01 TI - Health Evaluation and Referral Assistant: A Randomized Controlled Trial of a Web-Based Screening, Brief Intervention, and Referral to Treatment System to Reduce Risky Alcohol Use Among Emergency Department Patients JO - J Med Internet Res SP - e119 VL - 19 IS - 5 KW - alcohol consumption KW - intervention study KW - emergency medicine KW - referral and consultation N2 - Background: Computer technologies hold promise for implementing alcohol screening, brief intervention, and referral to treatment (SBIRT). Questions concerning the most effective and appropriate SBIRT model remain. Objective: The aim of this study was to evaluate the impact of a computerized SBIRT system called the Health Evaluation and Referral Assistant (HERA) on risky alcohol use treatment initiation. Methods: Alcohol users (N=319) presenting to an emergency department (ED) were considered for enrollment. Those enrolled (n=212) were randomly assigned to the HERA, to complete a patient-administered assessment using a tablet computer, or a minimal-treatment control, and were followed for 3 months. Analyses compared alcohol treatment provider contact, treatment initiation, treatment completion, and alcohol use across condition using univariate comparisons, generalized estimating equations (GEEs), and post hoc chi-square analyses. Results: HERA participants (n=212; control=115; intervention=97) did not differ between conditions on initial contact with an alcohol treatment provider, treatment initiation, treatment completion, or change in risky alcohol use behavior. Subanalyses indicated that HERA participants, who accepted a faxed referral, were more likely to initiate contact with a treatment provider and initiate treatment for risky alcohol use, but were not more likely to continue engaging in treatment, or to complete treatment and change risky alcohol use behavior over the 3-month period following the ED visit. Conclusions: The HERA promoted initial contact with an alcohol treatment provider and initiation of treatment for those who accepted the faxed referral, but it did not lead to reduced risky alcohol use behavior. Factors which may have limited the HERA?s impact include lack of support for the intervention by clinical staff, the low intensity of the brief and stand-alone design of the intervention, and barriers related to patient follow-through, (eg, a lack of transportation or childcare, fees for services, or schedule conflicts). Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): NCT01153373; https://clinicaltrials.gov/ct2/show/NCT01153373 (Archived by WebCite at http://www.webcitation.org/6pHQEpuIF) UR - http://www.jmir.org/2017/5/e119/ UR - http://dx.doi.org/10.2196/jmir.6812 UR - http://www.ncbi.nlm.nih.gov/pubmed/28461283 ID - info:doi/10.2196/jmir.6812 ER - TY - JOUR AU - Saeb, Sohrab AU - Cybulski, R. Thaddeus AU - Schueller, M. Stephen AU - Kording, P. Konrad AU - Mohr, C. David PY - 2017/04/28 TI - Authorship Correction: Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles JO - J Med Internet Res SP - e143 VL - 19 IS - 4 UR - http://www.jmir.org/2017/4/e143/ UR - http://dx.doi.org/10.2196/jmir.7932 UR - http://www.ncbi.nlm.nih.gov/pubmed/30578218 ID - info:doi/10.2196/jmir.7932 ER - TY - JOUR AU - Mandryk, Lee Regan AU - Birk, Valentin Max PY - 2017/04/20 TI - Toward Game-Based Digital Mental Health Interventions: Player Habits and Preferences JO - J Med Internet Res SP - e128 VL - 19 IS - 4 KW - computer games KW - mental health KW - depression KW - anxiety N2 - Background: Designers of digital interventions for mental health often leverage interactions from games because the intrinsic motivation that results from game-based interventions may increase participation and translate into improved treatment efficacy. However, there are outstanding questions about the suitability (eg, are desktop or mobile interventions more appropriate?) and intervention potential (eg, do people with depression activate enough to play?) of games for mental health. Objective: In this paper, we aimed to describe the presently unknown relationship between gaming activity and indicators of well-being so that designers make informed choices when designing game-based interventions for mental health. Methods: We gathered validated scales of well-being (Beck?s Depression Inventory [BDI-II], Patient Health Questionnaire [PHQ-9], trait anxiety [TA], and basic psychological needs satisfaction [BPNS]), play importance (control over game behavior: control; gamer identity: identity), and play behavior (play frequency, platform preferences, and genre preferences) in a Web-based survey (N=491). Results: The majority of our participants played games a few times a week (45.3%, 222/490) or daily (34.3%, 168/490). In terms of depression, play frequency was associated with PHQ-9 (P=.003); PHQ-9 scores were higher for those who played daily than for those who played a few times a week or less. Similarly, for BDI-II (P=.01), scores were higher for those who played daily than for those who played once a week or less. Genre preferences were not associated with PHQ-9 (P=.32) or BDI-II (P=.68); however, platform preference (ie, mobile, desktop, or console) was associated with PHQ-9 (P=.04); desktop-only players had higher PHQ-9 scores than those who used all platforms. Platform preference was not associated with BDI-II (P=.18). In terms of anxiety, TA was not associated with frequency (P=.23), platform preference (P=.07), or genre preference (P=.99). In terms of needs satisfaction, BPNS was not associated with frequency (P=.25) or genre preference (P=.53), but it was associated with platform preference (P=.01); desktop-only players had lower needs satisfaction than those who used all platforms. As expected, play frequency was associated with identity (P<.001) and control (P<.001); those who played more had identified more as a gamer and had less control over their gameplay. Genre preference was associated with identity (P<.001) and control (P<.001); those who played most common genres had higher control over their play and identified most as gamers. Platform preference was not associated with control (P=.80), but was with identity (P=.001); those who played on all devices identified more as a gamer than those who played on mobiles or consoles only. Conclusions: Our results suggest that games are a suitable approach for mental health interventions as they are played broadly by people across a range of indicators of mental health. We further unpack the platform preferences and genre preferences of players with varying levels of well-being. UR - http://www.jmir.org/2017/4/e128/ UR - http://dx.doi.org/10.2196/jmir.6906 UR - http://www.ncbi.nlm.nih.gov/pubmed/28428161 ID - info:doi/10.2196/jmir.6906 ER - TY - JOUR AU - Saeb, Sohrab AU - Cybulski, R. Thaddeus AU - Schueller, M. Stephen AU - Kording, P. Konrad AU - Mohr, C. David PY - 2017/4/18 TI - Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles JO - J Med Internet Res SP - e118 VL - 19 IS - 4 KW - sleep monitoring KW - mobile phones KW - decision trees KW - classification N2 - Background: Sleep is a critical aspect of people?s well-being and as such assessing sleep is an important indicator of a person?s health. Traditional methods of sleep assessment are either time- and resource-intensive or suffer from self-reporting biases. Recently, researchers have started to use mobile phones to passively assess sleep in individuals? daily lives. However, this work remains in its early stages, having only examined relatively small and homogeneous populations in carefully controlled contexts. Thus, it remains an open question as to how well mobile device-based sleep monitoring generalizes to larger populations in typical use cases. Objective: The aim of this study was to assess the ability of machine learning algorithms to detect the sleep start and end times for the main sleep period in a 24-h cycle using mobile devices in a diverse sample. Methods: We collected mobile phone sensor data as well as daily self-reported sleep start and end times from 208 individuals (171 females; 37 males), diverse in age (18?66 years; mean 39.3), education, and employment status, across the United States over 6 weeks. Sensor data consisted of geographic location, motion, light, sound, and in-phone activities. No specific instructions were given to the participants regarding phone placement. We used random forest classifiers to develop both personalized and global predictors of sleep state from the phone sensor data. Results: Using all available sensor features, the average accuracy of classifying whether a 10-min segment was reported as sleep was 88.8%. This is somewhat better than using the time of day alone, which gives an average accuracy of 86.9%. The accuracy of the model considerably varied across the participants, ranging from 65.1% to 97.3%. We found that low accuracy in some participants was due to two main factors: missing sensor data and misreports. After correcting for these, the average accuracy increased to 91.8%, corresponding to an average median absolute deviation (MAD) of 38 min for sleep start time detection and 36 min for sleep end time. These numbers are close to the range reported by previous research in more controlled situations. Conclusions: We find that mobile phones provide adequate sleep monitoring in typical use cases, and that our methods generalize well to a broader population than has previously been studied. However, we also observe several types of data artifacts when collecting data in uncontrolled settings. Some of these can be resolved through corrections, but others likely impose a ceiling on the accuracy of sleep prediction for certain subjects. Future research will need to focus more on the understanding of people?s behavior in their natural settings in order to develop sleep monitoring tools that work reliably in all cases for all people. UR - http://www.jmir.org/2017/4/e118/ UR - http://dx.doi.org/10.2196/jmir.6821 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/jmir.6821 ER - TY - JOUR AU - Peters, Dorian AU - Davis, Sharon AU - Calvo, Alejandro Rafael AU - Sawyer, M. Susan AU - Smith, Lorraine AU - Foster, M. Juliet PY - 2017/04/11 TI - Young People?s Preferences for an Asthma Self-Management App Highlight Psychological Needs: A Participatory Study JO - J Med Internet Res SP - e113 VL - 19 IS - 4 KW - asthma KW - mobile applications KW - quality of life KW - mental health KW - adolescents KW - chronic disease KW - mhealth KW - participatory design N2 - Background: Although the prevalence of mental illness among young people with asthma is known to be twice the rate of the wider population, none of the asthma apps reported have acknowledged or attempted to include psychological support features. This is perhaps because user involvement in the development of asthma apps has been scarce. User involvement, facilitated by participatory design methods, can begin to address these issues while contributing insights to our understanding of the psychological experience associated with asthma and how technology might improve quality of life. Objective: The goal of this participatory user research study was to explore the experience, needs, and ideas of young people with asthma while allowing them to define requirements for an asthma app that would be engaging and effective at improving their well-being. Methods: Young people aged 15-24 years with doctor-diagnosed asthma were invited to participate in a participatory workshop and to complete a workbook designed to elicit their thoughts and ideas about living with asthma, technology use, and the design of an app. Participants generated a number of artifacts (including collages, concept maps, and paper prototypes) designed to reify their ideas, tacit knowledge, and experience. Results: A total of 20 participants (mean age 17.8 years; 60%, 12/20 female) representing a range from inadequately to well-controlled asthma completed a workbook and 13 of these also took part in a workshop (four workshops were held in total), resulting in 102 participant-generated artifacts. Theoretical thematic analysis resulted in a set of personal needs, feature ideas, and app characteristics considered relevant by young people for an asthma support app. The data revealed that psychological factors such as anxiety, and impediments to autonomy, competence, and relatedness (as consistent with self-determination theory [SDT]), were considered major influences on quality of life by young people with asthma. Furthermore, the incorporation of features pertaining to psychological experience was particularly valued by participants. Conclusions: In addition to practical features for asthma management, an app for young people with asthma should include support for the mental health factors associated with lived experience (ie, anxiety, lack of autonomy, and social disconnectedness). We show how support for these factors can be translated into design features of an app for asthma. In addition to informing the development of asthma-support technologies for young people, these findings could have implications for technologies designed to support people with chronic illness more generally. UR - http://www.jmir.org/2017/4/e113/ UR - http://dx.doi.org/10.2196/jmir.6994 UR - http://www.ncbi.nlm.nih.gov/pubmed/28400353 ID - info:doi/10.2196/jmir.6994 ER - TY - JOUR AU - Parra, Federico AU - Miljkovitch, Raphaële AU - Persiaux, Gwenaelle AU - Morales, Michelle AU - Scherer, Stefan PY - 2017/04/06 TI - The Multimodal Assessment of Adult Attachment Security: Developing the Biometric Attachment Test JO - J Med Internet Res SP - e100 VL - 19 IS - 4 KW - psychometrics KW - linguistics KW - heart rate KW - facial expression KW - psychophysiology KW - psychopathology KW - COVAREP KW - attachment N2 - Background: Attachment theory has been proven essential for mental health, including psychopathology, development, and interpersonal relationships. Validated psychometric instruments to measure attachment abound but suffer from shortcomings common to traditional psychometrics. Recent developments in multimodal fusion and machine learning pave the way for new automated and objective psychometric instruments for adult attachment that combine psychophysiological, linguistic, and behavioral analyses in the assessment of the construct. Objective: The aim of this study was to present a new exposure-based, automatic, and objective adult-attachment assessment, the Biometric Attachment Test (BAT), which exposes participants to a short standardized set of visual and music stimuli, whereas their immediate reactions and verbal responses, captured by several computer sense modalities, are automatically analyzed for scoring and classification. We also aimed to empirically validate two of its assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli. Methods: A total of 59 French participants from the general population were assessed using the Adult Attachment Questionnaire (AAQ), the Adult Attachment Projective Picture System (AAP), and the Attachment Multiple Model Interview (AMMI) as ground truth for attachment security. They were then exposed to three different BAT stimuli sets, whereas their faces, voices, heart rate (HR), and electrodermal activity (EDA) were recorded. Psychophysiological features, such as skin-conductance response (SCR) and Bayevsky stress index; behavioral features, such as gaze and facial expressions; as well as linguistic and paralinguistic features, were automatically extracted. An exploratory analysis was conducted using correlation matrices to uncover the features that are most associated with attachment security. A confirmatory analysis was conducted by creating a single composite effects index and by testing it for correlations with attachment security. The stability of the theory-consistent features across three different stimuli sets was explored using repeated measures analysis of variances (ANOVAs). Results: In total, 46 theory-consistent correlations were found during the exploration (out of 65 total significant correlations). For example, attachment security as measured by the AAP was correlated with positive facial expressions (r=.36, P=.01). AMMI?s security with the father was inversely correlated with the low frequency (LF) of HRV (r=?.87, P=.03). Attachment security to partners as measured by the AAQ was inversely correlated with anger facial expression (r=?.43, P=.001). The confirmatory analysis showed that the composite effects index was significantly correlated to security in the AAP (r=.26, P=.05) and the AAQ (r=.30, P=.04) but not in the AMMI. Repeated measures ANOVAs conducted individually on each of the theory-consistent features revealed that only 7 of the 46 (15%) features had significantly different values among responses to three different stimuli sets. Conclusions: We were able to validate two of the instrument?s core assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli. Future validation of other of its dimensions, as well as the ongoing development of its scoring and classification algorithms is discussed. UR - http://www.jmir.org/2017/4/e100/ UR - http://dx.doi.org/10.2196/jmir.6898 UR - http://www.ncbi.nlm.nih.gov/pubmed/28385683 ID - info:doi/10.2196/jmir.6898 ER - TY - JOUR AU - Park, Albert AU - Conway, Mike PY - 2017/03/20 TI - Longitudinal Changes in Psychological States in Online Health Community Members: Understanding the Long-Term Effects of Participating in an Online Depression Community JO - J Med Internet Res SP - e71 VL - 19 IS - 3 KW - mental health KW - depression KW - consumer health information KW - informatics KW - information science KW - social support KW - psychosocial support system KW - community networks KW - self-help groups KW - communications media N2 - Background: Major depression is a serious challenge at both the individual and population levels. Although online health communities have shown the potential to reduce the symptoms of depression, emotional contagion theory suggests that negative emotion can spread within a community, and prolonged interactions with other depressed individuals has potential to worsen the symptoms of depression. Objective: The goals of our study were to investigate longitudinal changes in psychological states that are manifested through linguistic changes in depression community members who are interacting with other depressed individuals. Methods: We examined emotion-related language usages using the Linguistic Inquiry and Word Count (LIWC) program for each member of a depression community from Reddit. To measure the changes, we applied linear least-squares regression to the LIWC scores against the interaction sequence for each member. We measured the differences in linguistic changes against three online health communities focusing on positive emotion, diabetes, and irritable bowel syndrome. Results: On average, members of an online depression community showed improvement in 9 of 10 prespecified linguistic dimensions: ?positive emotion,? ?negative emotion,? ?anxiety,? ?anger,? ?sadness,? ?first person singular,? ?negation,? ?swear words,? and ?death.? Moreover, these members improved either significantly or at least as much as members of other online health communities. Conclusions: We provide new insights into the impact of prolonged participation in an online depression community and highlight the positive emotion change in members. The findings of this study should be interpreted with caution, because participating in an online depression community is not the sole factor for improvement or worsening of depressive symptoms. Still, the consistent statistical results including comparative analyses with different communities could indicate that the emotion-related language usage of depression community members are improving either significantly or at least as much as members of other online communities. On the basis of these findings, we contribute practical suggestions for designing online depression communities to enhance psychosocial benefit gains for members. We consider these results to be an important step toward a better understanding of the impact of prolonged participation in an online depression community, in addition to providing insights into the long-term psychosocial well-being of members. UR - http://www.jmir.org/2017/3/e71/ UR - http://dx.doi.org/10.2196/jmir.6826 UR - http://www.ncbi.nlm.nih.gov/pubmed/28320692 ID - info:doi/10.2196/jmir.6826 ER - TY - JOUR AU - Delgado-Gomez, David AU - Peñuelas-Calvo, Inmaculada AU - Masó-Besga, Eduardo Antonio AU - Vallejo-Oñate, Silvia AU - Baltasar Tello, Itziar AU - Arrua Duarte, Elsa AU - Vera Varela, Constanza María AU - Carballo, Juan AU - Baca-García, Enrique PY - 2017/03/20 TI - Microsoft Kinect-based Continuous Performance Test: An Objective Attention Deficit Hyperactivity Disorder Assessment JO - J Med Internet Res SP - e79 VL - 19 IS - 3 KW - kinect KW - attention deficit hyperactivity disorder KW - continuous performance test KW - impulsivity KW - hyperactivity N2 - Background: One of the major challenges in mental medical care is finding out new instruments for an accurate and objective evaluation of the attention deficit hyperactivity disorder (ADHD). Early ADHD identification, severity assessment, and prompt treatment are essential to avoid the negative effects associated with this mental condition. Objective: The aim of our study was to develop a novel ADHD assessment instrument based on Microsoft Kinect, which identifies ADHD cardinal symptoms in order to provide a more accurate evaluation. Methods: A group of 30 children, aged 8-12 years (10.3 [SD 1.4]; male 70% [21/30]), who were referred to the Child and Adolescent Psychiatry Unit of the Department of Psychiatry at Fundación Jiménez Díaz Hospital (Madrid, Spain), were included in this study. Children were required to meet the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria of ADHD diagnosis. One of the parents or guardians of the children filled the Spanish version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN) rating scale used in clinical practice. Each child conducted a Kinect-based continuous performance test (CPT) in which the reaction time (RT), the commission errors, and the time required to complete the reaction (CT) were calculated. The correlations of the 3 predictors, obtained using Kinect methodology, with respect to the scores of the SWAN scale were calculated. Results: The RT achieved a correlation of -.11, -.29, and -.37 with respect to the inattention, hyperactivity, and impulsivity factors of the SWAN scale. The correlations of the commission error with respect to these 3 factors were -.03, .01, and .24, respectively. Conclusions: Our findings show a relation between the Microsoft Kinect-based version of the CPT and ADHD symptomatology assessed through parental report. Results point out the importance of future research on the development of objective measures for the diagnosis of ADHD among children and adolescents. UR - http://www.jmir.org/2017/3/e79/ UR - http://dx.doi.org/10.2196/jmir.6985 UR - http://www.ncbi.nlm.nih.gov/pubmed/28320691 ID - info:doi/10.2196/jmir.6985 ER - TY - JOUR AU - Chow, I. Philip AU - Fua, Karl AU - Huang, Yu AU - Bonelli, Wesley AU - Xiong, Haoyi AU - Barnes, E. Laura AU - Teachman, A. Bethany PY - 2017/03/03 TI - Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students JO - J Med Internet Res SP - e62 VL - 19 IS - 3 KW - mental health KW - depression KW - social anxiety KW - affect KW - homestay KW - mobile health KW - mHealth N2 - Background: Research in psychology demonstrates a strong link between state affect (moment-to-moment experiences of positive or negative emotionality) and trait affect (eg, relatively enduring depression and social anxiety symptoms), and a tendency to withdraw (eg, spending time at home). However, existing work is based almost exclusively on static, self-reported descriptions of emotions and behavior that limit generalizability. Despite adoption of increasingly sophisticated research designs and technology (eg, mobile sensing using a global positioning system [GPS]), little research has integrated these seemingly disparate forms of data to improve understanding of how emotional experiences in everyday life are associated with time spent at home, and whether this is influenced by depression or social anxiety symptoms. Objective: We hypothesized that more time spent at home would be associated with more negative and less positive affect. Methods: We recruited 72 undergraduate participants from a southeast university in the United States. We assessed depression and social anxiety symptoms using self-report instruments at baseline. An app (Sensus) installed on participants? personal mobile phones repeatedly collected in situ self-reported state affect and GPS location data for up to 2 weeks. Time spent at home was a proxy for social isolation. Results: We tested separate models examining the relations between state affect and time spent at home, with levels of depression and social anxiety as moderators. Models differed only in the temporal links examined. One model focused on associations between changes in affect and time spent at home within short, 4-hour time windows. The other 3 models focused on associations between mean-level affect within a day and time spent at home (1) the same day, (2) the following day, and (3) the previous day. Overall, we obtained many of the expected main effects (although there were some null effects), in which higher social anxiety was associated with more time or greater likelihood of spending time at home, and more negative or less positive affect was linked to longer homestay. Interactions indicated that, among individuals higher in social anxiety, higher negative affect and lower positive affect within a day was associated with greater likelihood of spending time at home the following day. Conclusions: Results demonstrate the feasibility and utility of modeling the relationship between affect and homestay using fine-grained GPS data. Although these findings must be replicated in a larger study and with clinical samples, they suggest that integrating repeated state affect assessments in situ with continuous GPS data can increase understanding of how actual homestay is related to affect in everyday life and to symptoms of anxiety and depression. UR - http://www.jmir.org/2017/3/e62/ UR - http://dx.doi.org/10.2196/jmir.6820 UR - http://www.ncbi.nlm.nih.gov/pubmed/28258049 ID - info:doi/10.2196/jmir.6820 ER - TY - JOUR AU - Nicholas, Jennifer AU - Huckvale, Kit AU - Larsen, Erik Mark AU - Basu, Ashna AU - Batterham, J. Philip AU - Shaw, Frances AU - Sendi, Shahbaz PY - 2017/02/28 TI - Issues for eHealth in Psychiatry: Results of an Expert Survey JO - J Med Internet Res SP - e55 VL - 19 IS - 2 KW - eHealth KW - mental health KW - technology adoption N2 - Background: Technology has changed the landscape in which psychiatry operates. Effective, evidence-based treatments for mental health care are now available at the fingertips of anyone with Internet access. However, technological solutions for mental health are not necessarily sought by consumers nor recommended by clinicians. Objective: The objectives of this study are to identify and discuss the barriers to introducing eHealth technology-supported interventions within mental health. Methods: An interactive polling tool was used to ask ?In this brave new world, what are the key issues that need to be addressed to improve mental health (using technology)?? Respondents were the multidisciplinary attendees of the ?Humans and Machines: A Quest for Better Mental Health? conference, held in Sydney, Australia, in 2016. Responses were categorized into 10 key issues using team-based qualitative analysis. Results: A total of 155 responses to the question were received from 66 audience members. Responses were categorized into 10 issues and ordered by importance: access to care, integration and collaboration, education and awareness, mental health stigma, data privacy, trust, understanding and assessment of mental health, government and policy, optimal design, and engagement. In this paper, each of the 10 issues are outlined, and potential solutions are discussed. Many of the issues were interrelated, having implications for other key areas identified. Conclusions: As many of the issues identified directly related to barriers to care, priority should be given to addressing these issues that are common across mental health delivery. Despite new challenges raised by technology, technology-supported mental health interventions represent a tremendous opportunity to address in a timely way these major concerns and improve the receipt of effective, evidence-based therapy by those in need. UR - http://www.jmir.org/2017/2/e55/ UR - http://dx.doi.org/10.2196/jmir.6957 UR - http://www.ncbi.nlm.nih.gov/pubmed/28246068 ID - info:doi/10.2196/jmir.6957 ER - TY - JOUR AU - Mowery, Danielle AU - Smith, Hilary AU - Cheney, Tyler AU - Stoddard, Greg AU - Coppersmith, Glen AU - Bryan, Craig AU - Conway, Mike PY - 2017/02/28 TI - Understanding Depressive Symptoms and Psychosocial Stressors on Twitter: A Corpus-Based Study JO - J Med Internet Res SP - e48 VL - 19 IS - 2 KW - social media KW - Twitter messaging KW - natural language processing KW - major depressive disorder KW - data annotation KW - machine learning N2 - Background: With a lifetime prevalence of 16.2%, major depressive disorder is the fifth biggest contributor to the disease burden in the United States. Objective: The aim of this study, building on previous work qualitatively analyzing depression-related Twitter data, was to describe the development of a comprehensive annotation scheme (ie, coding scheme) for manually annotating Twitter data with Diagnostic and Statistical Manual of Mental Disorders, Edition 5 (DSM 5) major depressive symptoms (eg, depressed mood, weight change, psychomotor agitation, or retardation) and Diagnostic and Statistical Manual of Mental Disorders, Edition IV (DSM-IV) psychosocial stressors (eg, educational problems, problems with primary support group, housing problems). Methods: Using this annotation scheme, we developed an annotated corpus, Depressive Symptom and Psychosocial Stressors Acquired Depression, the SAD corpus, consisting of 9300 tweets randomly sampled from the Twitter application programming interface (API) using depression-related keywords (eg, depressed, gloomy, grief). An analysis of our annotated corpus yielded several key results. Results: First, 72.09% (6829/9473) of tweets containing relevant keywords were nonindicative of depressive symptoms (eg, ?we?re in for a new economic depression?). Second, the most prevalent symptoms in our dataset were depressed mood and fatigue or loss of energy. Third, less than 2% of tweets contained more than one depression related category (eg, diminished ability to think or concentrate, depressed mood). Finally, we found very high positive correlations between some depression-related symptoms in our annotated dataset (eg, fatigue or loss of energy and educational problems; educational problems and diminished ability to think). Conclusions: We successfully developed an annotation scheme and an annotated corpus, the SAD corpus, consisting of 9300 tweets randomly-selected from the Twitter application programming interface using depression-related keywords. Our analyses suggest that keyword queries alone might not be suitable for public health monitoring because context can change the meaning of keyword in a statement. However, postprocessing approaches could be useful for reducing the noise and improving the signal needed to detect depression symptoms using social media. UR - http://www.jmir.org/2017/2/e48/ UR - http://dx.doi.org/10.2196/jmir.6895 UR - http://www.ncbi.nlm.nih.gov/pubmed/28246066 ID - info:doi/10.2196/jmir.6895 ER - TY - JOUR AU - Yarosh, Svetlana AU - Schueller, Matthew Stephen PY - 2017/01/17 TI - ?Happiness Inventors?: Informing Positive Computing Technologies Through Participatory Design With Children JO - J Med Internet Res SP - e14 VL - 19 IS - 1 KW - positive computing KW - positive psychology KW - participatory design KW - cooperative inquiry KW - children N2 - Background: Positive psychological interventions for children have typically focused on direct adaptations of interventions developed for adults. As the community moves toward designing positive computing technologies to support child well-being, it is important to use a more participatory process that directly engages children?s voices. Objective: Our objectives were, through a participatory design study, to understand children?s interpretations of positive psychology concepts, as well as their perspectives on technologies that are best suited to enhance their engagement with practice of well-being skills. Methods: We addressed these questions through a content analysis of 434 design ideas, 51 sketches, and 8 prototype and videos, which emerged from a 14-session cooperative inquiry study with 12 child ?happiness inventors.? The study was part of a summer learning camp held at the children?s middle school, which focused on teaching the invention process, teaching well-being skills drawn from positive psychology and related areas (gratitude, mindfulness, and problem solving), and iterating design ideas for technologies to support these skills. Results: The children?s ideas and prototypes revealed specific facets of how they interpreted gratitude (as thanking, being positive, and doing good things), mindfulness (as externally representing thought and emotions, controlling those thoughts and emotions, getting through unpleasant things, and avoiding forgetting something), and problem solving (as preventing bad decisions, seeking alternative solutions, and not dwelling on unproductive thoughts). This process also revealed that children emphasized particular technologies in their solutions. While desktop or laptop solutions were notably lacking, other ideas were roughly evenly distributed between mobile apps and embodied computing technologies (toys, wearables, etc). We also report on desired functionalities and approaches to engagement in the children?s ideas, such as a notable emphasis on representing and responding to internal states. Conclusions: Our findings point to promising directions for the design of positive computing technologies targeted at children, with particular emphases on the perspectives, technologies, engagement approaches, and functionalities that appealed to the children in our study. The dual focus of the study on teaching skills while designing technologies is a novel methodology in the design of positive computing technologies intended to increase child well-being. UR - http://www.jmir.org/2017/1/e14/ UR - http://dx.doi.org/10.2196/jmir.6822 UR - http://www.ncbi.nlm.nih.gov/pubmed/28096066 ID - info:doi/10.2196/jmir.6822 ER -