Dataset Information

Predictors of Self-Stigma in Schizophrenia: New Insights Using Mobile Technologies.

ABSTRACT: Self-stigma has significant negative impact on the recovery of individuals with severe mental illness, but its varying course is not well understood. Individual levels of self-stigma may vary over time and fluctuate in response to both external/contextual (i.e., location, activity, social company) and internal (i.e., psychiatric symptoms, mood) factors. The aim of this study was to examine the relationship between self-stigmatizing beliefs and these factors, as they occur in the daily life of individuals with schizophrenia.Mobile technologies were used to longitudinally track momentary levels of self-stigma, psychotic symptoms, negative affect, positive affect, activity, and immediate social and physical environment in twenty-four individuals with schizophrenia, multiple times daily, over a one-week period.Multilevel modeling showed that participants' current activity was associated with changes in self-stigma (?(2)= 10.53, p <0.05), but immediate location and social company were not. Time-lagged analyses found that increases in negative affect (?=0.11, p<0.01) and psychotic symptom severity (?=0.16, p<0.01) predicted increases in the intensity of self-stigmatizing beliefs. Psychotic symptoms were found to be both an antecedent and a consequence (?=0.08, p<0.01) of increased self-stigma.Our findings support a framework for understanding self-stigma as an experience that changes based on alterations in internal states and external circumstances. Mobile technologies are an effective methodology to study self-stigma and have potential to be used to deliver clinical interventions.

SUBMITTER: Ben-Zeev D

PROVIDER: S-EPMC3584451 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Predictors of Self-Stigma in Schizophrenia: New Insights Using Mobile Technologies.

Ben-Zeev Dror D Frounfelker Rochelle R Morris Scott B SB Corrigan Patrick W PW

Journal of dual diagnosis 20120910 4

<h4>Objective</h4>Self-stigma has significant negative impact on the recovery of individuals with severe mental illness, but its varying course is not well understood. Individual levels of self-stigma may vary over time and fluctuate in response to both external/contextual (i.e., location, activity, social company) and internal (i.e., psychiatric symptoms, mood) factors. The aim of this study was to examine the relationship between self-stigmatizing beliefs and these factors, as they occur in th ...[more]

PMID: 23459025

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Project description:Despite the boom in new technologically based interventions for people with psychosis, recent studies suggest medium to low rates of adherence to these types of interventions. The benefits will be limited if only a minority of service users adhere and engage; if specific predictors of adherence can be identified then technologies can be adapted to increase the service user benefits.The study aimed to present a systematic review of rates of adherence, dropout, and approaches to analyzing adherence to newly developed mobile and Web-based interventions for people with psychosis. Specific predictors of adherence were also explored.Using keywords (Internet or online or Web-based or website or mobile) AND (bipolar disorder or manic depression or manic depressive illness or manic-depressive psychosis or psychosis or schizophr* or psychotic), the following databases were searched: OVID including MedLine, EMBASE and PsychInfo, Pubmed and Web of Science. The objectives and inclusion criteria for suitable studies were defined following PICOS (population: people with psychosis; intervention: mobile or Internet-based technology; comparison group: no comparison group specified; outcomes: measures of adherence; study design: randomized controlled trials (RCT), feasibility studies, and observational studies) criteria. In addition to measurement and analysis of adherence, two theoretically proposed predictors of adherence were examined: (1) level of support from a clinician or researcher throughout the study, and (2) level of service user involvement in the app or intervention development. We provide a narrative synthesis of the findings and followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for reporting systematic reviews.Of the 20 studies that reported a measure of adherence and a rate of dropout, 5 of these conducted statistical analyses to determine predictors of dropout, 6 analyzed the effects of specific adherence predictors (eg, symptom severity or type of technological interface) on the effects of the intervention, 4 administered poststudy feedback questionnaires to assess continued use of the intervention, and 2 studies evaluated the effects of different types of interventions on adherence. Overall, the percentage of participants adhering to interventions ranged from 28-100% with a mean of 83%. Adherence was greater in studies with higher levels of social support and service user involvement in the development of the intervention. Studies of shorter duration also had higher rates of adherence.Adherence to mobile and Web-based interventions was robust across most studies. Although 2 studies found specific predictors of nonadherence (male gender and younger age), most did not specifically analyze predictors. The duration of the study may be an important predictor of adherence. Future studies should consider reporting a universal measure of adherence and aim to conduct complex analyses on predictors of adherence such as level of social presence and service user involvement.

Project description:BackgroundThere is growing interest in the potential for wearable and mobile devices to deliver clinically relevant information in real-world contexts. However, there is limited information on their acceptability and barriers to long-term use in people living with psychosis.ObjectiveThis study aimed to describe the development, implementation, feasibility, acceptability, and user experiences of the Sleepsight platform, which harnesses consumer wearable devices and smartphones for the passive and unobtrusive capture of sleep and rest-activity profiles in people with schizophrenia living in their homes.MethodsA total of 15 outpatients with a diagnosis of schizophrenia used a consumer wrist-worn device and smartphone to continuously and remotely gather rest-activity profiles over 2 months. Once-daily sleep and self-rated symptom diaries were also collected via a smartphone app. Adherence with the devices and smartphone app, end-of-study user experiences, and agreement between subjective and objective sleep measures were analyzed. Thresholds for acceptability were set at a wear time or diary response rate of 70% or greater.ResultsOverall, 14 out of 15 participants completed the study. In individuals with a mild to moderate symptom severity at baseline (mean total Positive and Negative Syndrome Scale score 58.4 [SD 14.4]), we demonstrated high rates of engagement with the wearable device (all participants meeting acceptability criteria), sleep diary, and symptom diary (93% and 86% meeting criteria, respectively), with negative symptoms being associated with lower diary completion rate. The end-of-study usability and acceptability questionnaire and qualitative analysis identified facilitators and barriers to long-term use, and paranoia with study devices was not a significant barrier to engagement. Comparison between sleep diary and wearable estimated sleep times showed good correspondence (?=0.50, P<.001).ConclusionsExtended use of wearable and mobile technologies are acceptable to people with schizophrenia living in a community setting. In the future, these technologies may allow predictive, objective markers of clinical status, including early markers of impending relapse.

Dataset Information

Predictors of Self-Stigma in Schizophrenia: New Insights Using Mobile Technologies.

Publications

Predictors of Self-Stigma in Schizophrenia: New Insights Using Mobile Technologies.

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