Digital technology for health promotion: opportunities to address excess mortality in persons living with severe mental disorders
•,.
...
Abstract
Persons with severe mental disorders (SMDs) experience dramatically reduced life expectancy compared with the general population. We consider the role of digital technologies for addressing this serious public health concern. In this clinical review, we apply the multilevel risk model recently introduced by the WHO to conceptualise how digital technology can support efforts to reduce excess mortality risk at the individual, health system and social determinants of health levels. In particular, digital technologies show promise for targeting preventable physical health conditions in persons with SMDs. However, evidence on the use of these technologies for addressing early mortality risk factors is lacking. At the individual level, digital interventions show promise for managing mental health symptoms, promoting healthy lifestyle behaviours and targeting substance use concerns. At the health system level, digital interventions can support care coordination, clinician training, screening and monitoring health indices and shared decision-making. At the social determinants of health level, digital interventions can facilitate opportunities to engage peers for illness self-management and health promotion and for delivering and/or augmenting supported employment programmes. The time is ripe to capitalise on early evidence to support future development, testing and delivery of effective digital efforts targeting risk factors that contribute to shorter life expectancy in persons with SMDs. Key challenges and opportunities for future research include increasing user engagement, involving users during development and testing of digital interventions, carefully considering risks/harms and rigorously evaluating effectiveness and costs to support the scalability and sustainability of promising digital approaches.
Introduction
Individuals living with severe mental disorders (SMDs), including schizophrenia, schizoaffective disorder, major depressive disorder or bipolar disorder, experience dramatically reduced life expectancy compared with the general population.1 Meta-analyses and epidemiological studies have estimated that this excess mortality disparity ranges from 10 to 30 years earlier than the general population.2–4 Despite growing awareness about this alarming public health concern,1 the response has been limited and progress to date has been lacklustre as reflected by recent studies suggesting that this mortality gap may actually be worsening over time.5 6
With considerable evidence documenting the extent of the mortality gap,1 it is essential that research funding and clinical resources support the development, implementation and sustained delivery of evidence-based interventions targeting a range of modifiable risk factors that account for reduced life expectancy among individuals with SMDs. Excess mortality is largely due to preventable physical health conditions, equating to roughly 70% of deaths in this at-risk group.2 These primarily include cardiovascular and respiratory diseases as well as infectious diseases, diabetes and cancers.1 Unnatural causes of death account for approximately 18% of deaths among individuals with SMDs,2 with rates of suicide, homicide and accidental death all substantially higher when compared with the general population.1
To illustrate the multiple contributors to early mortality among persons with SMDs, Liu and colleagues (2017) from the WHO proposed a multilevel risk model.1 In their model, risks are classified across three levels: (1) individual; (2) health system; and (3) social determinants of health. This model accounts for individual level characteristics such as diagnosis, symptom severity, health behaviours and motivation as well as health system factors including service delivery, knowledge and attitudes of healthcare providers and appropriate use of antipsychotic medications. The social determinants of health level of the model recognises the impact of numerous social and environmental factors that negatively affect mortality risk, including individuals’ socioeconomic position, employment status, social relationships, access to supportive community resources, experiences of stigma and discrimination and effects of public policies. These various factors across each level of the model interact with one another and combine to negatively impact life expectancy. No single factor is responsible for early mortality, and this multilevel model underscores key opportunities to intervene.1
In this clinical review, we apply the WHO multilevel intervention framework to conceptualise how digital technologies could support efforts for health promotion and reducing excess mortality risk due to natural causes among individuals with SMDs. This includes using digital technologies as stand-alone interventions, as tools to complement in person programmes and as approaches for enhancing existing evidence-based practices and clinical services. Digital technologies, ranging from smartphones, mobile applications and web-enabled platforms have emerged as a collection of promising strategies for reaching and supporting intervention delivery, contributing to improved illness management and promoting the adoption of positive health behaviours among persons with SMDs.7 While digital technologies also hold potential for addressing unnatural causes of excess mortality, such as suicide, in this clinical review, we focus on opportunities to address natural causes of excess mortality since they account for the greatest proportion of early deaths in people with SMDs.
Methods
Our literature search was informed by recent systematic reviews describing use of digital technology for persons living with SMDs. These include five reviews: Batra et al (2018);8 Biagianti et al (2017);9 Berry et al (2016);10 Naslund et al (2015)7 and Alvarez-Jimenez et al (2014).11 Initially, we searched lists of included studies from each of these reviews. Then, we searched MEDLINE/PubMed and Google Scholar to determine if there were any additional recent studies published since the searches conducted in these reviews. We specifically searched for studies involving use of digital technology, defined as mobile devices such as cellphones or smartphones, mobile applications, wearable devices and sensors and online platforms, for targeting risk factors for early mortality among individuals with SMDs, including schizophrenia, schizoaffective disorder, major depressive disorder or bipolar disorder. We summarised these studies emphasising how digital technology could support efforts to address early mortality according to the WHO multilevel framework spanning the individual, health system and social determinants of health.
Digital interventions and the multilevel intervention framework
Numerous studies have highlighted the promise of digital technologies for targeting the health needs of individuals with SMDs. This includes digital interventions for supporting illness self-management and relapse prevention among people with schizophrenia11 and for promoting treatment adherence and retention in care among individuals receiving community mental health services.7 Several studies show that access to and use of smartphones and other digital technologies among people with SMDs is comparable to the general population.12 13 Additionally, digital technologies may make it possible to reach those without access to formal healthcare services or who may be reluctant to seek care and for targeting individuals in their own homes or outside formal clinical settings.14 However, use of digital technology for specifically addressing risk of early mortality in this group has received little attention.
In table 1, we have highlighted specific instances where digital interventions may afford opportunities for targeting multiple risk factors for early mortality guided by Liu and colleagues’ (2017) multilevel intervention framework.1 It is important to consider that the multilevel framework offers a roadmap by illustrating key targets for digital interventions, and that at times the interventions identified in this clinical review may not align perfectly with the framework, highlighting areas for further investigation. There may be novel ways to leverage how individuals with SMDs use these technologies to scale efforts targeting treatment and management of psychiatric symptoms, promoting physical health and well-being and addressing multiple modifiable risk factors that contribute to substantially reduced life expectancy, including smoking, obesity, substance use and chronic medical conditions. Digital interventions could target co-occurring mental and physical health concerns, which together are major contributors to early mortality. For instance, a common scenario may require ongoing management of symptoms of schizophrenia while simultaneously managing diabetes, chronic respiratory disease and needing to overcome symptoms of depression to engage in healthy eating and regular exercise. While research supports the use of digital interventions for general patient populations,15–17 these programmes are often not suitable for persons with SMDs. For instance, digital interventions for general patient populations typically lack key design features, such as simplified layout, content at lower reading level and easy to navigate interface, necessary to enhance usability for individuals with SMDs who may experience cognitive deficits, low literacy and persistent symptoms.18–21 Therefore, promising digital interventions for individuals with SMDs must be tailored to meet their needs. In the sections that follow, we draw from published scientific literature demonstrating how digital approaches designed for persons with SMDs can potentially support health promotion and target risk factors for early mortality in this group.
Table 1
•
Multiple levels of risk factors for early mortality and the potential for digital interventions for individuals living with severe mental disorders*
Digital interventions at the individual level
As behavioural health concerns among people with SMDs often involve co-occurring mental and physical health conditions,1 digital technologies such as telehealth devices can be effective for managing co-occurring mental health and chronic medical conditions in this group.22 23 Technology can also support health promotion programming, including telephone-delivered lifestyle coaching for weight reduction associated with antipsychotic medications,24 and wearable activity tracking devices for enhancing community-based lifestyle interventions.25 Digital interventions also show promise for addressing health behaviours such as tobacco use, as demonstrated in a pilot study of the ‘Let’s Talk About Smoking’ interactive, web-based motivational intervention.26 This online programme from the USA contributed to greater smoking abstinence compared with a control condition among young adults with SMDs.26 Recent formative work to develop a smartphone application for smoking cessation emphasised the importance of tailoring the content, design and layout of the digital intervention according to the needs of users with SMDs.27 28
Overall, most digital intervention studies at the individual level have focused on monitoring or managing mental health symptoms for persons with SMDs,7 with well-documented feasibility and acceptability of these interventions.7 29 Therefore, there may be opportunities to extend the impact of existing digital interventions by combining these programmes with evidence-based techniques for self-managing chronic medical conditions or promoting lifestyle behaviours towards addressing individual-level risk factors for early mortality. For example, FOCUS is a smartphone application developed in the USA supplemented by a digital clinician dashboard and mHealth support specialist.29 In a randomised controlled trial, this programme contributed to comparable improvements in clinical outcomes as standard care and resulted in significantly greater likelihood of commencing and engaging in clinical services.30 Similarly, the Actissist smartphone application developed in the UK for early psychosis supports self-management and shared decision making by monitoring symptoms and providing real-time active management strategies.31 In a pilot study, Actissist was associated with superior treatment effects compared with a control condition.31 Another mobile application called PRIME from the USA was designed for young individuals with recent onset schizophrenia to improve motivation and functioning through goal setting and promoting better quality of life.32 In each of these examples, there may be opportunities to incorporate strategies for managing chronic medical conditions, promoting health and wellness and addressing lifestyle behaviours.
Digital interventions at the health system level
At the health system level, digital technology holds promise for supporting detection and monitoring of at-risk patients with SMDs. For example, an electronic screening tool for recording and monitoring metabolic syndrome indices in patients with SMDs was successful at changing clinician practice to screen, monitor and document risk factors such as weight, body mass index, blood pressure and waist circumference.33 In another study, the CommonGround web application implemented in community mental health settings in the USA supports clinical encounters by allowing people with SMDs to participate in shared decision making, to identify their personal treatment goals and to communicate these goals to psychiatric care providers ahead of treatment visits.34 In this approach, individuals emphasised the importance of lifestyle factors, highlighting the potential for CommonGround to support shared decision making related to addressing risk factors for early mortality.34 Further, implementation of an electronic personal health record within community mental health centres allowed patients with SMDs and comorbid medical conditions to access their own health information and showed success in supporting goal setting, monitoring health indicators, accessing preventive services and contributing to greater engagement in care.35
Another study demonstrated that a web-based platform was effective for supporting clinician training in cognitive behavioural therapy for persons in recovery within community mental health settings.36 This approach also showed potential for overcoming challenges such as high staff turnover, difficulties scheduling in-person training sessions and reliance on costly experts to lead in-person trainings.36 Using digital technology for clinician education could be an important strategy for building capacity among community mental health clinicians and primary care clinicians for recognising and addressing risk factors for early mortality among persons with SMDs.
Importantly, digital interventions have been identified as a possible strategy to strengthen health systems by supporting clinicians in coordinating care for patients with mental disorders.37 One promising initiative launched in the USA is the Healthy Technology Program, which targets relapse prevention after hospitalisation using a technology coach who oversees and coordinates different technology components.38 This model of coordinated technology-delivered treatment has demonstrated high acceptance by integrating various digital tools into care processes aimed at improving outcomes and reducing costs for persons with schizophrenia.38 This multicomponent approach could also leverage technology to coordinate with primary care services and allow opportunities to target chronic medical conditions, lifestyle behaviours and other early mortality risk factors.
Digital interventions at the social determinants of health level
Few studies have examined whether digital interventions can specifically target social determinants of early mortality among persons with SMDs, though digital technology affords unique opportunities to leverage an individual’s social networks and personal relationships and facilitate peer-to-peer communication, which can improve participant retention and engagement.9 For instance, recent pilot studies have demonstrated the acceptability of using digital technology including smartphone applications to facilitate peer support for integrated medical and psychiatric self-management39 and text-messaging and social media for facilitating peer-based lifestyle intervention targeting weight loss and improved fitness.40–43 While still targeting individual level risk factors, such as exercise, diet or illness self-management, these initial efforts demonstrate the feasibility of technology for engaging peers and social relationships to support positive health behaviour change. These approaches may be especially appealing for persons with SMDs, as online communities can serve as sources of naturally occurring peer support44 and given increasing interest in using social media to access lifestyle programmes and mental health services.14
Few digital interventions have specifically targeted poverty or homelessness, which are important contributors to shortened life expectancy in persons with SMDs. In one project in the USA, the feasibility and acceptability of the WorkingWell mobile application aimed at supporting employment and providing coping strategies for improving success in the work environment among persons with SMDs is currently being evaluated.45 WorkingWell focuses on key factors such as relationships, mental health concerns, encouraging motivation and managing lifestyle and wellness outside of work, such as sleeping and eating well,46 which are relevant for addressing risk of early mortality. Future research is necessary to determine whether digital technologies can enhance efforts targeting key social determinants of early mortality among individuals with SMDs.
Discussion
In this clinical review, we considered how Liu and colleagues’ multilevel risk model can provide a roadmap for guiding use of digital technology interventions for targeting risk of excess mortality in persons with SMDs.1 Few studies used technology to specifically address early mortality risk factors, yet several recent pilot studies of digital interventions showed promise for targeting lifestyle behaviours, managing co-occurring chronic medical conditions, and facilitating peer support for persons with SMDs. Digital interventions hold promise for strengthening health systems by bridging gaps in coordination between primary care and mental health services, improving information sharing among clinicians and supporting the delivery of integrated care for mental and co-occurring chronic health conditions. Further, digital training programmes could expand the role and competencies of clinicians in primary care or community mental health settings by equipping them with necessary skills and knowledge for recognising and treating risk factors for early mortality among their patients with SMDs and supporting referral to specialists when necessary.
As digital technologies such as smartphones, wearable devices or social media become an increasingly important fixture in the daily lives of individuals living with SMDs, it may be possible to monitor their use of these technologies for detecting risk factors for early mortality and supporting real-time delivery of targeted interventions. Studying patterns of individual technology use as a means to characterise health behaviours and illness symptoms is an emerging research area referred to as ‘digital phenotyping’.47 48 To date, examining patterns of social media use has generated insights about tobacco use, mental health symptoms and suicide among social media users with schizophrenia,49–51 while careful monitoring of smartphone use over time can detect changes in mobility and social behaviour as risk factors for relapse among patients with schizophrenia.52 53 Capturing data from various digital sources could inform a more fine-grained understanding of how mental health and physical health symptoms interact with environmental and social factors to contribute to poorer health and reduced life expectancy among individuals with SMDs. While most of the studies that we summarised in this clinical review focused primarily on persons with schizophrenia spectrum or psychotic disorders, it will be important for digital interventions aimed at addressing early mortality risk factors to be flexible in accommodating the needs of diagnostically heterogeneous groups in order to reflect the typical patient populations served in community mental health organisations. However, digital interventions could also incorporate multiple design features tailored to the unique needs of different mental health diagnoses, while potentially allowing interventions to adapt in response to real-time data to meet an individual’s changing health needs.54
Challenges and limitations
As digital interventions ranging from mobile phones, wearable devices or web-based platforms yield increasingly important opportunities to target early mortality risk factors in persons with SMDs, ensuring security and privacy of these efforts will be critical. Emphasis should be placed on informed consent, data privacy, confidentiality and support for individual autonomy and treatment goals. For example, concerns about privacy and lack of trust may contribute to low rates of engagement in smartphone applications among users with mental illness.55 The immense data collection capacity of digital devices, the potential to extend the reach of services outside traditional clinical settings and new opportunities to engage peers and online networks in intervention delivery can result in unintended consequences and infringe on privacy and confidentiality.56 To guide the development and evaluation of digital interventions for early mortality risk reduction, researchers and clinicians will need to carefully weigh benefits and risks, while fully disclosing any known or plausible risks to patients.57 It will also be important to inform individuals with SMDs about potential risks associated with direct-to-consumer products, such as mobile applications or digital devices for promoting fitness and healthy lifestyle, as these may involve business models that place users at risk through data collection and sharing with third parties.57 There remain considerable gaps in clinical knowledge surrounding the risks of digital interventions for persons with SMDs as well as limited awareness among researchers, clinicians and patients about the potential risks associated with using these devices,56 57 highlighting an important area for further investigation especially in the context of addressing excess mortality in this patient group.
Efforts will also be needed to ensure adequate engagement in digital interventions at each level of the framework. Low engagement is a common challenge for many digital interventions for persons with SMDs55 and may be attributed in part to the failure to integrate the perspectives, goals, interests and needs of the target user group during the design of these digital programmes.58 59 Furthermore, it is important to recognise that barriers to accessing digital technology remain a challenge for those in impoverished settings or rural areas. Development and evaluation of digital interventions typically favours a highly selective group of individuals interested and willing to participate,58 who likely represent a small subset of the greater population of individuals served by mental health systems. To improve engagement and generalisability of digital interventions, it will be necessary to actively involve users throughout the development, evaluation and implementation process. Last, and importantly, across each level of the risk model, we found few effectiveness studies. This highlights the need for rigorous research to evaluate effectiveness and cost-effectiveness of promising digital interventions to fully determine the impact on reducing risk of early mortality. Emphasis is needed on assessing long-term outcomes, the costs of intervention development and delivery to ensure scalability and whether technology-based approaches contribute to greater impact in the form of reduced mortality risk compared with existing services.
Conclusion
The time is ripe to capitalise on this early evidence to support the development, testing and delivery of effective digital efforts targeting risk factors that contribute to shortened life expectancy in persons with SMDs. Digital technologies such as social media may even offer compelling avenues for advocating for access to quality healthcare for persons with SMDs and demanding that this early mortality disparity be recognised as a major public health priority. We must strive to reverse course and look to emerging digital innovations to advance our efforts.
Patient consent for publication: Not required.
Contributors: Wrote the first draft of the manuscript: JAN. Contributed to the writing of the manuscript: KAA. Meet criteria for authorship and agree with manuscript results and decision to publish: JAN, KAA.
Funding: JAN is supported by a grant from the National Institute of Mental Health (U19MH113211). KAA is supported by a grant from the National Institute of Mental Health (1R01MH110965-01).
Disclaimer: The funders had no role in the preparation of the manuscript or decision to publish. There are no additional acknowledgements. This work has not been previously presented at a conference or published as an abstract.
Competing interests: None declared.
Provenance and peer review: Not commissioned; internally peer reviewed.
Data sharing statement: Not applicable.
Liu NH, Daumit GL, Dua T, et al. Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy and research agendas. World Psychiatry2017; 16:30–40.
Walker ER, McGee RE, Druss BG, et al. Mortality in mental disorders and global disease burden implications: a systematic review and meta-analysis. JAMA Psychiatry2015; 72:334–41.
Druss BG, Zhao L, Von Esenwein S, et al. Understanding excess mortality in persons with mental illness: 17-year follow up of a nationally representative US survey. Med Care2011; 49:599–604.
Saha S, Chant D, McGrath J, et al. A systematic review of mortality in schizophrenia: is the differential mortality gap worsening over time? Arch Gen Psychiatry2007; 64:1123–31.
Lee EE, Liu J, Tu X, et al. A widening longevity gap between people with schizophrenia and general population: A literature review and call for action. Schizophr Res2018; 196.
Naslund JA, Marsch LA, McHugo GJ, et al. Emerging mHealth and eHealth interventions for serious mental illness: a review of the literature. J Ment Health2015; 24:321–32.
Batra S, Baker RA, Wang T, et al. Digital health technology for use in patients with serious mental illness: a systematic review of the literature. Med Devices2017; 10:237–51.
Biagianti B, Quraishi SH, Schlosser DA, et al. Potential benefits of incorporating peer-to-peer interactions into digital interventions for psychotic disorders: a systematic review. Psychiatr Serv2018; 69:377–88.
Berry N, Lobban F, Emsley R, et al. Acceptability of interventions delivered online and through mobile phones for people who experience severe mental health problems: a systematic review. J Med Internet Res2016; 18:e121.
Alvarez-Jimenez M, Alcazar-Corcoles MA, González-Blanch C, et al. Online, social media and mobile technologies for psychosis treatment: a systematic review on novel user-led interventions. Schizophr Res2014; 156:96–106.
Firth J, Cotter J, Torous J, et al. Mobile phone ownership and endorsement of "mhealth" among people with psychosis: a meta-analysis of cross-sectional studies. Schizophr Bull2016; 42:448–55.
Naslund JA, Aschbrenner KA, Bartels SJ, et al. How people with serious mental illness use smartphones, mobile apps, and social media. Psychiatr Rehabil J2016; 39:364–7.
Naslund JA, Aschbrenner KA, McHugo GJ, et al. Exploring opportunities to support mental health care using social media: A survey of social media users with mental illness. Early Interv Psychiatry2017;
Free C, Phillips G, Galli L, et al. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med2013; 10:e1001362.
Webb TL, Joseph J, Yardley L, et al. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res2010; 12:e4.
Widmer RJ, Collins NM, Collins CS, et al. Digital health interventions for the prevention of cardiovascular disease: a systematic review and meta-analysis. Mayo Clin Proc2015; 90:469–80.
Brunette MF, Ferron JC, Devitt T, et al. Do smoking cessation websites meet the needs of smokers with severe mental illnesses? Health Educ Res2012; 27:183–90.
Ferron JC, Brunette MF, McHugo GJ, et al. Developing a quit smoking website that is usable by people with severe mental illnesses. Psychiatr Rehabil J2011; 35:111–6.
Rotondi AJ, Sinkule J, Haas GL, et al. Designing websites for persons with cognitive deficits: Design and usability of a psychoeducational intervention for persons with severe mental illness. Psychol Serv2007; 4:202–24.
Ben-Zeev D, Kaiser SM, Brenner CJ, et al. Development and usability testing of FOCUS: a smartphone system for self-management of schizophrenia. Psychiatr Rehabil J2013; 36:289–96.
Pratt SI, Bartels SJ, Mueser KT, et al. Feasibility and effectiveness of an automated telehealth intervention to improve illness self-management in people with serious psychiatric and medical disorders. Psychiatr Rehabil J2013; 36:297–305.
Pratt SI, Naslund JA, Wolfe RS, et al. Automated telehealth for managing psychiatric instability in people with serious mental illness. J Ment Health2015; 24:261–5.
Temmingh H, Claassen A, van Zyl S, et al. The evaluation of a telephonic wellness coaching intervention for weight reduction and wellness improvement in a community-based cohort of persons with serious mental illness. J Nerv Ment Dis2013; 201:977–86.
Naslund JA, Aschbrenner KA, Scherer EA, et al. Wearable devices and mobile technologies for supporting behavioral weight loss among people with serious mental illness. Psychiatry Res2016; 244:139–44.
Brunette MF, Ferron JC, Robinson D, et al. Brief web-based interventions for young adult smokers with severe mental illnesses: a randomized, controlled pilot study. Nicotine Tob Res2018; 20:1206-1214.
Vilardaga R, Rizo J, Kientz JA, et al. User experience evaluation of a smoking cessation app in people with serious mental illness. Nicotine Tob Res2016; 18:1032–8.
Vilardaga R, Rizo J, Zeng E, et al. User-centered design of learn to quit, a smoking cessation smartphone app for people with serious mental illness. JMIR Serious Games2018; 6:e2.
Ben-Zeev D, Brenner CJ, Begale M, et al. Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull2014; 40:1244–53.
Ben-Zeev D, Brian RM, Jonathan G, et al. Mobile health (mhealth) versus clinic-based group intervention for people with serious mental illness: a randomized controlled trial. Psychiatr Serv2018; 69:978–85.
Bucci S, Barrowclough C, Ainsworth J, et al. Actissist: proof-of-concept trial of a theory-driven digital intervention for psychosis. Schizophr Bull2018; 44:1070–80.
Schlosser D, Campellone T, Kim D, et al. Feasibility of prime: a cognitive neuroscience-informed mobile app intervention to enhance motivated behavior and improve quality of life in recent onset schizophrenia. JMIR Res Protoc2016; 5:e77.
Nash K, Ghinassi F, Brar JS, et al. The development and implementation of an electronic health record tool for monitoring metabolic syndrome indices in patients with serious mental illness. Clin Schizophr Relat Psychoses2016; 10:145–53.
Deegan PE, Carpenter-Song E, Drake RE, et al. Enhancing clients' communication regarding goals for using psychiatric medications. Psychiatr Serv2017; 68:771–5.
Druss BG, Ji X, Glick G, et al. Randomized trial of an electronic personal health record for patients with serious mental illnesses. Am J Psychiatry2014; 171:360–8.
German RE, Adler A, Frankel SA, et al. Testing a web-based, trained-peer model to build capacity for evidence-based practices in community mental health systems. Psychiatr Serv2018; 69:286–92.
Baumel A, Correll CU, Hauser M, et al. Health technology intervention after hospitalization for schizophrenia: service utilization and user satisfaction. Psychiatr Serv2016; 67:1035–8.
Fortuna KL, DiMilia PR, Lohman MC, et al. Feasibility, acceptability, and preliminary effectiveness of a peer-delivered and technology supported self-management intervention for older adults with serious mental illness. Psychiatr Q2018; 89:293–305.
Aschbrenner KA, Naslund JA, Shevenell M, et al. Feasibility of behavioral weight loss treatment enhanced with peer support and mobile health technology for individuals with serious mental illness. Psychiatr Q2016; 87:401–15.
Aschbrenner KA, Naslund JA, Shevenell M, et al. A pilot study of a peer-group lifestyle intervention enhanced with mhealth technology and social media for adults with serious mental illness. J Nerv Ment Dis2016; 204:483–6.
Naslund JA, Aschbrenner KA, Marsch LA, et al. Facebook for supporting a lifestyle intervention for people with major depressive disorder, bipolar disorder, and schizophrenia: an exploratory study. Psychiatr Q2018; 89:81–94.
Naslund JA, Aschbrenner KA, Marsch LA, et al. Feasibility and acceptability of Facebook for health promotion among people with serious mental illness. Digit Health2016; 2:205520761665482.
Naslund JA, Grande SW, Aschbrenner KA, et al. Naturally occurring peer support through social media: the experiences of individuals with severe mental illness using YouTube. PLoS One2014; 9.
Nicholson J, Carpenter-Song EA, MacPherson LH, et al. Developing the WorkingWell mobile app to promote job tenure for individuals with serious mental illnesses. Psychiatr Rehabil J2017; 40:276–82.
Nicholson J, Wright SM, Carlisle AM, et al. Pre-post, mixed-methods feasibility study of the WorkingWell mobile support tool for individuals with serious mental illness in the USA: a pilot study protocol. BMJ Open2018; 8.
Hswen Y, Naslund JA, Chandrashekar P, et al. Exploring online communication about cigarette smoking among Twitter users who self-identify as having schizophrenia. Psychiatry Res2017; 257:479–84.
Hswen Y, Naslund JA, Brownstein JS, et al. Online communication about depression and anxiety among twitter users with schizophrenia: preliminary findings to inform a digital phenotype using social media. Psychiatr Q2018; 89:569–80.
Hswen Y, Naslund JA, Brownstein JS, et al. Monitoring online discussions about suicide among Twitter users with schizophrenia. JMIR Mental Health2018; 5:e11483.
Barnett I, Torous J, Staples P, et al. Relapse prediction in schizophrenia through digital phenotyping: a pilot study. Neuropsychopharmacology2018; 43:1660–6.
Torous J, Staples P, Barnett I, et al. Characterizing the clinical relevance of digital phenotyping data quality with applications to a cohort with schizophrenia. NPJ Digit Med2018; 1:15.
Naslund JA, Aschbrenner KA, Kim SJ, et al. Health behavior models for informing digital technology interventions for individuals with mental illness. Psychiatr Rehabil J2017; 40:325–35.
Torous J, Nicholas J, Larsen ME, et al. Clinical review of user engagement with mental health smartphone apps: evidence, theory and improvements. Evid Based Ment Health2018; 21:116–9.
Torous J, Nebeker C. Navigating ethics in the digital age: introducing connected and open research ethics (core), a tool for researchers and institutional review boards. J Med Internet Res2017; 19:e38.
Mohr DC, Weingardt KR, Reddy M, et al. Three problems with current digital mental health research and three things we can do about them. Psychiatr Serv2017; 68:427–9.
Biagianti B, Hidalgo-Mazzei D, Meyer N, et al. Developing digital interventions for people living with serious mental illness: perspectives from three mHealth studies. Evid Based Ment Health2017; 20:98–101.