Mobile Behavioral Sensing for Outpatients and Inpatients With Schizophrenia

Ben‐Zeev, Dror; Wang, Rui; Abdullah, Saeed; Brian, Rachel; Scherer, Emily A.; Mistler, Lisa A; Hauser, Marta; Kane, John M.; Campbell, Andrew T.; Choudhury, Tanzeem

doi:10.1176/appi.ps.201500130

Cited by 118 publications

(106 citation statements)

References 15 publications

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“…Data collection software combined pretimed and behaviorally triggered sensor activation (8,10,11). The microphone was activated every two minutes to capture sound.…”

Section: Methodsmentioning

confidence: 99%

Use of Multimodal Technology to Identify Digital Correlates of Violence Among Inpatients With Serious Mental Illness: A Pilot Study

Ben‐Zeev

Scherer

Brian

et al. 2017

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Objective The study examined multimodal technologies to identify correlates of violence among inpatients with serious mental illness. Methods Twenty-eight high-risk inpatients were provided with smartphones adapted for data collection. Participants recorded their thoughts and behaviors by using self-report software. Sensors embedded in each device (microphone and accelerometers) and throughout the inpatient unit (Bluetooth beacons) captured patients’ activity and location. Results Self-reported delusions were associated with violent ideation (odds ratio [OR]=3.08), damaging property (OR=8.24), and physical aggression (OR=12.39). Alcohol and cigarette cravings were associated with violent ideation (OR=5.20 and OR=6.08, respectively), damaging property (OR=3.71 and OR=4.26, respectively), threatening others (OR=3.62 and OR=3.04, respectively), and physical aggression (OR=6.26, and OR=8.02, respectively). Drug cravings were associated with violent ideation (OR=2.76) and damaging property (OR=5.09). Decreased variability in physical activity and noisy ward conditions were associated with violent ideation (OR=.71 and OR=2.82, respectively). Conclusions Identifiable digital correlates may serve as indicators of increased risk of violence.

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“…Data collection software combined pretimed and behaviorally triggered sensor activation (8,10,11). The microphone was activated every two minutes to capture sound.…”

Section: Methodsmentioning

confidence: 99%

Use of Multimodal Technology to Identify Digital Correlates of Violence Among Inpatients With Serious Mental Illness: A Pilot Study

Ben‐Zeev

Scherer

Brian

et al. 2017

Self Cite

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“…For example, working closely with community partners and carefully considering the perspectives of the target population emerged as essential steps towards facilitating the implementation and uptake of a novel mHealth activity tracking system within a low-income African American neighborhood (Yingling et al, 2016). For people with serious mental illness, a recent pilot study showed that a sample of inpatients and outpatients were satisfied and felt comfortable using smartphone sensors for characterizing their daily activity patterns over a 1 to 2 week period (Ben-Zeev et al, 2015). In our prior work, we also observed that popular mHealth technologies appeared feasible for tracking physical activity among a community sample of people with serious mental illness (Aschbrenner, Naslund, Barre, et al, 2015; Naslund, Aschbrenner, Barre, & Bartels, 2015).…”

Section: Introductionmentioning

confidence: 99%

Wearable devices and smartphones for activity tracking among people with serious mental illness

Naslund

Aschbrenner

Bartels

2016

Mental Health and Physical Activity

109

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Introduction People with serious mental illness, including schizophrenia spectrum and mood disorders, are more physically inactive than people from the general population. Emerging wearable devices and smartphone applications afford opportunities for promoting physical activity in this group. This exploratory mixed methods study obtained feedback from participants with serious mental illness to assess the acceptability of using wearable devices and smartphones to support a lifestyle intervention targeting weight loss. Methods Participants with serious mental illness and obesity enrolled in a 6-month lifestyle intervention were given Fitbit activity tracking devices and smartphones to use for the study. Participants completed quantitative post-intervention usability and satisfaction surveys, and provided qualitative feedback regarding acceptability of using these devices and recommendations for improvement through in-depth interviews. Results Eleven participants wore Fitbits for an average of 84.7% (SD=18.1%) of the days enrolled in the study (median=93.8% of the days enrolled, interquartile range=83.6–94.3%). Participants were highly satisfied, stating that the devices encouraged them to be more physically active and were useful for self-monitoring physical activity and reaching daily step goals. Some participants experienced challenges using the companion mobile application on the smartphone, and recommended greater technical support, more detailed training, and group tutorials prior to using the devices. Discussion Participants’ perspectives highlight the feasibility and acceptability of using commercially available mHealth technologies to support health promotion efforts targeting people with serious mental illness. This study offers valuable insights for informing future research to assess the effectiveness of these devices for improving health outcomes in this high-risk group.

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“…Ben-Zeev and colleagues [17] investigated passive mHealth monitoring through sensors in an smartphone app in a sample of 11 inpatients and nine outpatients with schizophrenia for one or two week periods respectively. They observed that approximately 20% of the sample felt upset by monitoring.…”

Section: Discussionmentioning

confidence: 99%

Healthcare in the pocket: A qualitative analysis of patients� perspectives of an mHealth application to foster power in everyday living with schizophrenia (Preprint)

Terp¹,

Jørgensen²,

Laursen³

et al. 2018

Preprint

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BACKGROUND We co-designed a mobile health application (mHealth app) – MindFrame - in partnership with individuals with schizophrenia and healthcare providers. The purpose of MindFrame is to empower patients to confidently manage everyday living when having been recently diagnosed with schizophrenia trough tracking of the mental health state, customized psychoeducation, medication adherence support, illness exacerbation alerts and delivery of time sensitive strategies for relapse prevention and self-management. OBJECTIVE This paper explores how young adults recently diagnosed with schizophrenia, used and perceived MindFrame as a tool to foster power in the daily management of their illness. METHODS From January to December 2016 patients from a first episode psychosis outpatient program in Denmark were invited to use MindFrame as part of their care. Along with MindFrame, they continued their usual care. They customized and used MindFrame based on their needs and preferences while assessing their mental health state on a daily basis. 27 patients used MindFrame and 13 subsequently evaluated it. The evaluation was qualitative and conducted using telephone interviews. Data were analysed using a hermeneutical approach. RESULTS The analysis showed that, for patients, MindFrame served to foster power in the everyday management of living with schizophrenia. When the app was used consistently for more than a month, and with the healthcare providers, it could provide the patients with the power to keep up their medication, to keep a step ahead of their illness and to get fast and timely help. This empowered them to stay on track with the illness, thus in control of it. Also, MindFrame could fuel the fear of restraint and illness exacerbation, thereby disempowering some from feeling certain and secure. CONCLUSIONS The findings demonstrate that MindFrame has the ability to empower young adults to manage their illness in the context of their daily lives. This contributes toward the potential of putting healthcare into the patient’s pocket. The disempowering aspect of MindFrame accentuates a need for further research to clarify the limitations of mHealth apps for patient empowerment in young adults with schizophrenia.

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Mobile Behavioral Sensing for Outpatients and Inpatients With Schizophrenia

Cited by 118 publications

References 15 publications

Use of Multimodal Technology to Identify Digital Correlates of Violence Among Inpatients With Serious Mental Illness: A Pilot Study

Use of Multimodal Technology to Identify Digital Correlates of Violence Among Inpatients With Serious Mental Illness: A Pilot Study

Wearable devices and smartphones for activity tracking among people with serious mental illness

Healthcare in the pocket: A qualitative analysis of patients� perspectives of an mHealth application to foster power in everyday living with schizophrenia (Preprint)

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