The relationship between text message sentiment and self-reported depression.

BACKGROUND: Personal sensing has shown promise for detecting behavioral correlates of depression, but there is little work examining personal sensing of cognitive and affective states. Digital language, particularly through personal text messages, is one source that can measure these markers. METHODS: We correlated privacy-preserving sentiment analysis of text messages with self-reported depression symptom severity. We enrolled 219 U.S. adults in a 16 week longitudinal observational study. Participants installed a personal sensing app on their phones, which administered self-report PHQ-8 assessments of their depression severity, collected phone sensor data, and computed anonymized language sentiment scores from their text messages. We also trained machine learning models for predicting end-of-study self-reported depression status using on blocks of phone sensor and text features. RESULTS: In correlation analyses, we find that degrees of depression, emotional, and personal pronoun language categories correlate most strongly with self-reported depression, validating prior literature. Our classification models which predict binary depression status achieve a leave-one-out AUC of 0.72 when only considering text features and 0.76 when combining text with other networked smartphone sensors. LIMITATIONS: Participants were recruited from a panel that over-represented women, caucasians, and individuals with self-reported depression at baseline. As language use differs across demographic factors, generalizability beyond this population may be limited. The study period also coincided with the initial COVID-19 outbreak in the United States, which may have affected smartphone sensor data quality. CONCLUSIONS: Effective depression prediction through text message sentiment, especially when combined with other personal sensors, could enable comprehensive mental health monitoring and intervention.

Evaluation of Changes in Depression, Anxiety, and Social Anxiety Using Smartphone Sensor Features: Longitudinal Cohort Study.

BACKGROUND: The assessment of behaviors related to mental health typically relies on self-report data. Networked sensors embedded in smartphones can measure some behaviors objectively and continuously, with no ongoing effort. OBJECTIVE: This study aims to evaluate whether changes in phone sensor-derived behavioral features were associated with subsequent changes in mental health symptoms. METHODS: This longitudinal cohort study examined continuously collected phone sensor data and symptom severity data, collected every 3 weeks, over 16 weeks. The participants were recruited through national research registries. Primary outcomes included depression (8-item Patient Health Questionnaire), generalized anxiety (Generalized Anxiety Disorder 7-item scale), and social anxiety (Social Phobia Inventory) severity. Participants were adults who owned Android smartphones. Participants clustered into 4 groups: multiple comorbidities, depression and generalized anxiety, depression and social anxiety, and minimal symptoms. RESULTS: A total of 282 participants were aged 19-69 years (mean 38.9, SD 11.9 years), and the majority were female (223/282, 79.1%) and White participants (226/282, 80.1%). Among the multiple comorbidities group, depression changes were preceded by changes in GPS features (Time: r=-0.23, P=.02; Locations: r=-0.36, P<.001), exercise duration (r=0.39; P=.03) and use of active apps (r=-0.31; P<.001). Among the depression and anxiety groups, changes in depression were preceded by changes in GPS features for Locations (r=-0.20; P=.03) and Transitions (r=-0.21; P=.03). Depression changes were not related to subsequent sensor-derived features. The minimal symptoms group showed no significant relationships. There were no associations between sensor-based features and anxiety and minimal associations between sensor-based features and social anxiety. CONCLUSIONS: Changes in sensor-derived behavioral features are associated with subsequent depression changes, but not vice versa, suggesting a directional relationship in which changes in sensed behaviors are associated with subsequent changes in symptoms.

Lessons learned from service design of a trial of a digital mental health service: Informing implementation in primary care clinics.

Implementing a digital mental health service in primary care requires integration into clinic workflow. However, without adequate attention to service design, including designing referral pathways to identify and engage patients, implementation will fail. This article reports results from our efforts designing referral pathways for a randomized clinical trial evaluating a digital service for depression and anxiety delivered through primary care clinics. We utilized three referral pathways: direct to consumer (e.g., digital and print media, registry emails), provider referral (i.e., electronic health record [EHR] order and provider recommendation), and other approaches (e.g., presentations, word of mouth). Over the 5-month enrollment, 313 individuals completed the screen and reported how they learned about the study. Penetration was 13%, and direct to consumer techniques, most commonly email, had the highest yield. Providers only referred 16 patients through the EHR, half of whom initiated the screen. There were no differences in referral pathway based on participants' age, depression severity, or anxiety severity at screening. Ongoing discussions with providers revealed that the technologic implementation and workflow design may not have been optimal to fully affect the EHR-based referral process, which potentially limited patient access. Results highlight the importance of designing and evaluating referral pathways within service implementation, which is important for guiding the implementation of digital services into practice. Doing so can ensure that sustained implementation is not left to post-evaluation bridge-building. Future efforts should assess these and other referral pathways implemented in clinical practice outside of a research trial.

Coached Mobile App Platform for the Treatment of Depression and Anxiety Among Primary Care Patients: A Randomized Clinical Trial.

Importance: Depression and anxiety are common and disabling. Primary care is the de facto site for treating these mental health problems but is typically underresourced to meet the burden of these demands. Objective: To evaluate the efficacy of a mobile intervention platform, IntelliCare, for addressing depression and anxiety among primary care patients. Design, Setting, and Participants: Two-arm randomized clinical trial at internal medicine clinics at the University of Arkansas for Medical Sciences. Adult primary care patients (N = 146) who screened positive for depression on the Patient Health Questionnaire-8 (PHQ; score ≥ 10) or anxiety on the Generalized Anxiety Disorder-7 (GAD-7; score ≥ 8) were recruited between July 17, 2018, and December 14, 2018. Interventions: The coach-supported platform composed of a suite of apps, was delivered over 8 weeks. Wait list control participants received treatment as usual for 8 weeks, then the mobile platform. Main Outcomes and Measures: Primary outcomes were changes in depression (PHQ-9) and anxiety (GAD-7) during the intervention period. Secondary outcomes were differences in the proportion of patients who achieved recovery (PHQ-9/GAD-7 <5 or 50% improvement from baseline), sustainment of intervention effects during 2-month follow-up, and app use during the intervention period. Results: One hundred forty-six patients were included (119 of 146 were women [81.5%]; mean [SD] age, 42.3 [13.8] years). Of the 146 patients, 122 (83.6%) were diagnosed as having depression and 131 (89.7%) were diagnosed as having anxiety. A greater proportion of intervention vs wait list control participants achieved recovery from depression (n = 38 of 64 [59%] vs n = 18 of 58 [31%]; odds ratio, 3.25; 95% CI, 1.54-6.86) and anxiety (n = 37 of 65 [57%] vs n = 25 of 66 [38%]; odds ratio, 2.17; 95% CI, 1.08-4.36). Sustained effects were observed for depression (slope, 0.01; 95% CI, -0.09 to 0.10; P = .92) and anxiety scores (slope, 0.02; 95% CI, -0.08 to 0.12; P = .67) during follow-up. App use was high, with a median of 93 and 98 sessions among participants with depression and anxiety, respectively. Conclusions and Relevance: In this trial, a mobile intervention app was effective for depression and anxiety among primary care patients. Findings also support designing digital mental health interventions as platforms containing simple, brief apps that can be bundled by users to meet their needs. Trial Registration: ClinicalTrials.gov Identifier: NCT03500536.

Opportunities for and Tensions Surrounding the Use of Technology-Enabled Mental Health Services in Community Mental Health Care.

Technology-enabled mental health services have the potential to expand the reach of care and reduce clinician demand. While the efficacy of technology-enabled mental health services is well established, there have been few successful implementations of such services into community care settings. Using mixed methods, 89 clinicians and supervisors at a mental health service organization shared attitudes toward and interest in using a variety of technologies in their work. Participants discussed several challenges and opportunities for technology-enabled mental health services. Whilst clinicians saw potential for technology to engage individuals both in and outside the clinical environment, the range of therapeutic techniques used by clinicians presented a challenge in implementing a tool to meet their needs. Client technology access was a concern, and although text messaging would facilitate communication, current HIPAA and payment structures restrict this ability. With these considerations, we offer recommendations for implementing technological services in community mental health organizations.

A randomized noninferiority trial evaluating remotely-delivered stepped care for depression using internet cognitive behavioral therapy (CBT) and telephone CBT.

This trial examined whether a stepped care program for depression, which initiated treatment with internet cognitive behavioral therapy, including telephone and messaging support, and stepped up non-responders to telephone-administered cognitive behavioral therapy (tCBT), was noninferior, less costly to deliver, and as acceptable to patients compared to tCBT alone. Adults with a diagnosis of major depressive episode (MDE) were randomized to receive up to 20 weeks of stepped care or tCBT. Stepped care (n = 134) was noninferior to tCBT (n = 136) with an end-of-treatment effect size of d = 0.03 and a 6-month post-treatment effect size of d = -0.07 [90% CI 0.29 to 0.14]. Therapist time in stepped care was 5.26 (SD = 3.08) hours versus 10.16 (SD 4.01) for tCBT (p < 0.0001), with a delivery cost difference of $-364.32 [95% CI $-423.68 to $-304.96]. There was no significant difference in pre-treatment preferences (p = 0.10) or treatment dropout (39 in stepped care; 27 in tCBT; p = 0.14). tCBT patients were significantly more satisfied than stepped care patients with the treatment they received (p < 0.0001). These findings indicate that stepped care was less costly to deliver, but no less effective than tCBT. There was no significant difference in treatment preference or completion, however satisfaction with treatment was higher in tCBT than stepped care. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01906476.

Comparison of the Effects of Coaching and Receipt of App Recommendations on Depression, Anxiety, and Engagement in the IntelliCare Platform: Factorial Randomized Controlled Trial.

BACKGROUND: IntelliCare is a modular platform that includes 12 simple apps targeting specific psychological strategies for common mental health problems. OBJECTIVE: This study aimed to examine the effect of 2 methods of maintaining engagement with the IntelliCare platform, coaching, and receipt of weekly recommendations to try different apps on depression, anxiety, and app use. METHODS: A total of 301 participants with depression or anxiety were randomized to 1 of 4 treatments lasting 8 weeks and were followed for 6 months posttreatment. The trial used a 2X2 factorial design (coached vs self-guided treatment and weekly app recommendations vs no recommendations) to compare engagement metrics. RESULTS: The median time to last use of any app during treatment was 56 days (interquartile range 54-57), with 253 participants (84.0%, 253/301) continuing to use the apps over a median of 92 days posttreatment. Receipt of weekly recommendations resulted in a significantly higher number of app use sessions during treatment (overall median=216; P=.04) but only marginal effects for time to last use (P=.06) and number of app downloads (P=.08). Coaching resulted in significantly more app downloads (P<.001), but there were no significant effects for time to last download or number of app sessions (P=.36) or time to last download (P=.08). Participants showed significant reductions in the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) across all treatment arms (P s<.001). Coached treatment led to larger GAD-7 reductions than those observed for self-guided treatment (P=.03), but the effects for the PHQ-9 did not reach significance (P=.06). Significant interaction was observed between receiving recommendations and time for the PHQ-9 (P=.04), but there were no significant effects for GAD-7 (P=.58). CONCLUSIONS: IntelliCare produced strong engagement with apps across all treatment arms. Coaching was associated with stronger anxiety outcomes, and receipt of recommendations enhanced depression outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT02801877; https://clinicaltrials.gov/ct2/show/NCT02801877.

A Practical Do-It-Yourself Recruitment Framework for Concurrent eHealth Clinical Trials: Identification of Efficient and Cost-Effective Methods for Decision Making (Part 2).

BACKGROUND: The ability to successfully recruit participants for electronic health (eHealth) clinical trials is largely dependent on the use of efficient and effective recruitment strategies. Determining which types of recruitment strategies to use presents a challenge for many researchers. OBJECTIVE: The aim of this study was to present an analysis of the time-efficiency and cost-effectiveness of recruitment strategies for eHealth clinical trials, and it describes a framework for cost-effective trial recruitment. METHODS: Participants were recruited for one of 5 eHealth trials of interventions for common mental health conditions. A multipronged recruitment approach was used, including digital (eg, social media and Craigslist), research registry-based, print (eg, flyers and posters on public transportation), clinic-based (eg, a general internal medicine clinic within an academic medical center and a large nonprofit health care organization), a market research recruitment firm, and traditional media strategies (eg, newspaper and television coverage in response to press releases). The time costs and fees for each recruitment method were calculated, and the participant yield on recruitment costs was calculated by dividing the number of enrolled participants by the total cost for each method. RESULTS: A total of 777 participants were enrolled across all trials. Digital recruitment strategies yielded the largest number of participants across the 5 clinical trials and represented 34.0% (264/777) of the total enrolled participants. Registry-based recruitment strategies were in second place by enrolling 28.0% (217/777) of the total enrolled participants across trials. Research registry-based recruitment had a relatively high conversion rate from potential participants who contacted our center for being screened to be enrolled, and it was also the most cost-effective for enrolling participants in this set of clinical trials with a total cost per person enrolled at US $8.99. CONCLUSIONS: On the basis of these results, a framework is proposed for participant recruitment. To make decisions on initiating and maintaining different types of recruitment strategies, the resources available and requirements of the research study (or studies) need to be carefully examined.

A Practical Do-It-Yourself Recruitment Framework for Concurrent eHealth Clinical Trials: Simple Architecture (Part 1).

BACKGROUND: The ability to identify, screen, and enroll potential research participants in an efficient and timely manner is crucial to the success of clinical trials. In the age of the internet, researchers can be confronted with large numbers of people contacting the program, overwhelming study staff and frustrating potential participants. OBJECTIVE: This paper describes a "do-it-yourself" recruitment support framework (DIY-RSF) that uses tools readily available in many academic research settings to support remote participant recruitment, prescreening, enrollment, and management across multiple concurrent eHealth clinical trials. METHODS: This work was conducted in an academic research center focused on developing and evaluating behavioral intervention technologies. A needs assessment consisting of unstructured individual and group interviews was conducted to identify barriers to recruitment and important features for the new system. RESULTS: We describe a practical and adaptable recruitment management architecture that used readily available software, such as REDCap (Research Electronic Data Capture) and standard statistical software (eg, SAS, R), to create an automated recruitment framework that supported prescreening potential participants, consent to join a research registry, triaging for management of multiple trials, capture of eligibility information for each phase of a recruitment pipeline, and staff management tools including monitoring of participant flow and task assignment/reassignment features. The DIY-RSF was launched in July 2015. As of July 2017, the DIY-RSF has supported the successful recruitment efforts for eight trials, producing 14,557 participant records in the referral tracking database and 5337 participants in the center research registry. The DIY-RSF has allowed for more efficient use of staff time and more rapid processing of potential applicants. CONCLUSIONS: Using tools already supported at many academic institutions, we describe the architecture and utilization of an adaptable referral management framework to support recruitment for multiple concurrent clinical trials. The DIY-RSF can serve as a guide for leveraging common technologies to improve clinical trial recruitment procedures.

Harnessing Peer Support in an Online Intervention for Older Adults with Depression.

OBJECTIVE: This pilot study evaluated the feasibility and efficacy of two methods of delivering a cognitive behaviorally informed Internet intervention for depression for adults 65 years and older. METHODS: Forty-seven participants were enrolled and assigned to receive one of two versions of the Internet intervention, either delivered individually (III) or with peer support (II+PS), or to a wait list control group (WLC). Primary outcomes included change in depressive symptoms from baseline to post-intervention (week 8), site use, self-reported usability, and coach time. Secondary outcomes included measures of social support and isolation and anxiety. RESULTS: Follow-up data were provided by 85.1% (40 of 47) of enrolled participants. There were significant differences in depression change across groups (F(2,37) = 3.81, p = 0.03). Greater reductions in depressive symptoms were found for the III (p = 0.02) and II+PS (p = 0.03) compared with WLC, and significantly less coach time was required in the II+PS (p = 0.003). CONCLUSIONS: These results highlight the potential of cognitive-behaviorally informed Internet interventions for older adults with depression, and indicate that peer-supported programs are both acceptable and equivalent to individually delivered Internet interventions. Including peer support may be a viable and potentially more cost-effective option for disseminating online treatments for depression for older adults.

IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety.

BACKGROUND: Digital mental health tools have tended to use psychoeducational strategies based on treatment orientations developed and validated outside of digital health. These features do not map well to the brief but frequent ways that people use mobile phones and mobile phone apps today. To address these challenges, we developed a suite of apps for depression and anxiety called IntelliCare, each developed with a focused goal and interactional style. IntelliCare apps prioritize interactive skills training over education and are designed for frequent but short interactions. OBJECTIVE: The overall objective of this study was to pilot a coach-assisted version of IntelliCare and evaluate its use and efficacy at reducing symptoms of depression and anxiety. METHODS: Participants, recruited through a health care system, Web-based and community advertising, and clinical research registries, were included in this single-arm trial if they had elevated symptoms of depression or anxiety. Participants had access to the 14 IntelliCare apps from Google Play and received 8 weeks of coaching on the use of IntelliCare. Coaching included an initial phone call plus 2 or more texts per week over the 8 weeks, with some participants receiving an additional brief phone call. Primary outcomes included the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) for anxiety. Participants were compensated up to US $90 for completing all assessments; compensation was not for app use or treatment engagement. RESULTS: Of the 99 participants who initiated treatment, 90.1% (90/99) completed 8 weeks. Participants showed substantial reductions in the PHQ-9 and GAD-7 (P<.001). Participants used the apps an average of 195.4 (SD 141) times over the 8 weeks. The average length of use was 1.1 (SD 2.1) minutes, and 95% of participants downloaded 5 or more of the IntelliCare apps. CONCLUSIONS: This study supports the IntelliCare framework of providing a suite of skills-focused apps that can be used frequently and briefly to reduce symptoms of depression and anxiety. The IntelliCare system is elemental, allowing individual apps to be used or not used based on their effectiveness and utility, and it is eclectic, viewing treatment strategies as elements that can be applied as needed rather than adhering to a singular, overarching, theoretical model. TRIAL REGISTRATION: Clinicaltrials.gov NCT02176226; http://clinicaltrials.gov/ct2/show/NCT02176226 (Archived by WebCite at http://www.webcitation/6mQZuBGk1).

MedLink: A mobile intervention to improve medication adherence and processes of care for treatment of depression in general medicine.

BACKGROUND: Major depressive disorder is a common psychological problem affecting up to 20% of adults in their lifetime. The majority of people treated for depression receive antidepressant medication through their primary care physician. This commonly results in low rates of recovery. Failure points in the process of care contributing to poor outcomes include patient non-adherence to medications, failure of physicians to optimize dose and absence of communication between patients and physicians. OBJECTIVE: This pilot study evaluated the feasibility of a systemic digital intervention (MedLink) designed to address failure points and improve treatment of depression in primary care among patients during the first eight weeks of initiating a new course of antidepressant therapy. METHODS: Participants were provided with the MedLink mobile app that provided dose reminders, information and surveys of symptoms and side effects. A cellularly enabled pillbox monitored antidepressant medication adherence. Reports were provided to physicians and participants to prompt changes in medication regimen. Study outcomes were assessed via self-report and interview measures at baseline, week 4 and week 8. RESULTS: Medication adherence detected by the MedLink system was 82%. Participants demonstrated significant decreases in depressive symptoms on the patient health questionnaire-9 (PHQ-9) (p = 0.0005) and the Quick Inventory of Depressive Symptomatology (p = 0.0008) over the eight-week trial. Usability was generally rated favorably. CONCLUSIONS: The MedLink system demonstrated promise as an intervention to address failure points in the primary care treatment of major depressive disorder. Current findings support the further development of MedLink through a randomized controlled trial to evaluate the efficacy of improving processes of care, patient adherence and symptoms of depression.

MedLink: A Mobile Intervention to Address Failure Points in the Treatment of Depression in General Medicine.

Major depression is common, and imposes a high burden in terms of cost, morbidity, and suffering. Most people with depression are treated in general medicine using antidepressant medication. Outcomes are poor due to failure points across the care system, including patient non-adherence, failure of physicians to optimize the treatment regimens, and lack of patient-physician communication. This study reports on the 4-week pilot deployment of MedLink, a mobile intervention aimed at systemically addressing each of these failure points. A mobile app provides the patient with information and collects data on symptoms and side-effects. A cellularly enabled pill bottle monitors medication adherence. Data from these are provided to the physician and patient to foster communication and medication adjustments. Usability evaluation was generally favorable. Medication adherence rates in this first deployment were high with no patients discontinuing, and 84% of doses taken. Depressive symptom severity was significantly reduced. This study supports the use of a comprehensive, systemic approach to mHealth solutions to enhance processes of care for depression by general medicine physicians.

Adapting supported employment for emerging adults with serious mental health conditions.

Effective services are needed to assist young people with serious mental health conditions to successfully transition to employment or education, especially among those with intensive adolescent mental health service utilization. To meet these needs, the Individual Placement and Support (IPS) model of supported employment was adapted and its feasibility was tested in a psychiatric treatment program for early-emerging adults. Participants were 17-20 years old (mean age = 18.5 years). Most were African American, under the custody of the state, with a primary mood disorder diagnosis. Adaptations to IPS included adding the following: near age peer mentors, a supported education component, and a career development focus. This open trial feasibility study tracked the model's development, recruitment, and retention and tracked vocational and educational outcomes for 12 months. Model refinement resulted in the development of a separate educational specialist position, greater integration of the peer mentor with the vocational team, and further specification of the role of peer mentor. There was an 80% retention rate in the feasibility evaluation. Of the 35 participants, 49% started a job and/or enrolled in an education program over the 12-month period.

Remote "hovering" with individuals with psychotic disorders and substance use: feasibility, engagement, and therapeutic alliance with a text-messaging mobile interventionist.

OBJECTIVE: People with serious mental illnesses and substance abuse problems (i.e., dual diagnosis) constitute a particularly challenging and costly clinical group. This study evaluated the feasibility and acceptability of a novel model of care in which a mobile interventionist used mobile phone text messaging to remotely monitor and provide daily support to individuals with psychotic disorders and substance use. METHODS: Seventeen participants with dual diagnosis were enrolled in a 12-week single-arm trial. A clinical social worker served as the mobile interventionist and sent daily text messages to participants' privately owned mobile phones to assess their medication adherence and clinical status. The mobile interventionist provided text-message feedback and support and suggested various coping strategies flexibly, in response to participants' replies to prompts. At the end of the trial, participants completed a usability and satisfaction measure and two self-rated measures of therapeutic alliance with their clinicians. In one version, participants rated their relationship with their mobile interventionist; in the second version, they rated their relationship with their community-based treatment team. RESULTS: Participants received an average of 139 text messages (SD = 37.5) each from the mobile interventionist over the 12-week trial. On average, participants responded to 87% of the mobile interventionist's messages that required a reply. More than 90% of participants thought the intervention was useful and rewarding and that it helped them be more effective and productive in their lives. Participants' assessments of their relationship with the mobile interventionist were positive. Paired-sample t-test found that the therapeutic alliance ratings participants provided for their mobile interventionist were significantly higher than those provided for their community-based treatment team clinicians, who they met with regularly. CONCLUSIONS: Our findings suggest that text-message "hovering" can be conducted successfully with individuals with psychotic disorders and substance abuse. Developing a cadre of mobile interventionists who are specifically trained on how to engage patients via mobile devices while adhering to ethical guidelines and regulatory standards may be an effective way to strengthen service delivery models, improve patient outcomes, and reduce costs.

Targeting consumers in the early stages of substance use treatment: a pilot study.

OBJECTIVE: Engaging persons with co-occurring disorders in substance use treatment presents a significant challenge for public mental health service providers. Standardized, user-friendly guidelines may have great benefit for community mental health outreach staff working with individuals with co-occurring disorders. The purpose of this study is to describe the impact of a brief, structured goal development curriculum ("Fresh Start") on clinicians' motivational interviewing skills and to assess clinician and consumer satisfaction with the curriculum. METHOD: Four clinicians, each working with 3-4 consumer participants, were assessed with the Yale Adherence and Competency Scale prior to and during use of Fresh Start to determine improvements in motivational interviewing and goal setting. Consumer participants were assessed in brief qualitative interviews to assess satisfaction. Chart-review of routinely collected substance use data was used to assess reductions in use. RESULTS: Clinicians demonstrated high ratings in relational motivational interviewing skills at baseline which were maintained at study conclusion. Clinicians had lower technical motivational interviewing skills at baseline and made modest improvements in motivational interviewing techniques targeting increasing change talk. Fresh Start participants completed an average of 10 sessions (SD = 2.35). Among the 16 consumers who volunteered to participate in using the Fresh Start curriculum, 12 finished the program and 9 decided to reduce use and composed a sobriety plan. CONCLUSIONS AND IMPLICATION FOR PRACTICE: High rates of completion indicate acceptability of the curriculum and feasibility for implementing the program in a community setting. Short, goal-setting interventions are needed and under proper conditions may be teachable in vivo.

Development and usability testing of FOCUS: a smartphone system for self-management of schizophrenia.

OBJECTIVE: Mobile Health (mHealth) approaches can support the rehabilitation of individuals with psychiatric conditions. In the current article, we describe the development of a smartphone illness self-management system for people with schizophrenia. METHODS: The research was conducted with consumers and practitioners at a community-based rehabilitation agency. Stage 1: 904 individuals with schizophrenia or schizoaffective disorder completed a survey reporting on their current use of mobile devices and interest in mHealth services. Eight practitioners completed a survey examining their attitudes and expectations from an mHealth intervention, and identified needs and potential obstacles. Stage 2: A multidisciplinary team incorporated consumer and practitioner input and employed design principles for the development of e-resources for people with schizophrenia to produce an mHealth intervention. Stage 3: 12 consumers participated in laboratory usability sessions. They performed tasks involved in operating the new system, and provided "think aloud" commentary and post-session usability ratings. RESULTS: 570 (63%) of survey respondents reported owning a mobile device and many expressed interest in receiving mHealth services. Most practitioners believed that consumers could learn to use and would benefit from an mHealth intervention. In response, we developed a smartphone system that targets medication adherence, mood regulation, sleep, social functioning, and coping with symptoms. Usability testing revealed several design vulnerabilities, and the system was adapted to address consumer needs and preferences accordingly. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Through a comprehensive development process, we produced an mHealth illness self-management intervention that is likely to be used successfully, and is ready for deployment and systemic evaluation in real-world conditions.

Partnering with mental health providers: a guide for services researchers.

BACKGROUND: There is a 20-year delay between the development of effective interventions for individuals with severe mental illness and widespread adoption in public mental health care settings. Academic-provider collaborations can shorten this gap, but establishing and maintaining partnerships entail significant challenges. AIMS: This paper identifies potential barriers to academic-provider research collaborations and provides guidelines to overcome these obstacles. METHOD: Authors from an academic institution and community mental health organization outline the components of their long-standing partnership, and discuss the lessons learned that were instrumental in establishing the collaborative model. Results Realistic resource allocation and training, a thorough understanding of the service model and consumer characteristics, systemic and bidirectional communication and concrete plans for post-project continuation are necessary at all project phases. CONCLUSIONS: A shared decision-making framework is essential for effective academic institution and community mental health agency collaborations and can facilitate long-term sustainability of novel interventions.

Applying social and cultural capital frameworks: understanding employment perspectives of transition age youth with serious mental health conditions.

Vulnerable transition age youth, such as those in foster care and with serious mental health conditions, are at increased risk for lower rates of employment. Social capital is empirically linked to employment in the general population, yet little is known about the role of social capital in employment for at-risk transition age youth. Focus groups were conducted with young people with serious mental health conditions and their vocational specialists. Discussions reveal that both social and cultural capital influence employment processes. Those with employment experience value the motivation to work provided through others compared to those with no employment experience. Consistently employed describe strong working relationships with vocational specialists and possession of self-awareness, professionalism, and work-place knowledge as critical for employment success, while inconsistently employed describe worries about controlling emotions or behaviors on the job. Building social and cultural capital are explored as potential service provider goals.

Paxton house: integrating mental health and diabetes care for people with serious mental illnesses in a residential setting.

OBJECTIVE: This report provides a program description of a supported housing residence for individuals with co-occurring diabetes and serious mental illnesses and preliminary health outcome data. METHODS: Weight, blood glucose levels and satisfaction survey data were collected retrospectively on 13 individuals referred to the program. RESULTS: Results indicate that individuals lost weight and fasting glucose readings fell into the ADA recommended range in the first six months of participation. Overall, consumers participating in the program were satisfied with the diabetes education and monitoring services provided. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: While preliminary results suggest that consumers benefit, this study only begins to address how integrated behavioral health and diabetes-specific programming in residential settings meets the needs of persons with severe mental illnesses and diabetes. A more thorough understanding of the impact of these programs on consumers' health outcomes is needed to inform how to deliver diabetes management curricula and support consumers to improve their overall health.