Daily life evidence of environment-incongruent emotion in schizophrenia

Sanchez, Amy H.; Lavaysse, Lindsey M.; Starr, Jessica; Gard, David E.

doi:10.1016/j.psychres.2014.07.041

Cited by 28 publications

(30 citation statements)

References 43 publications

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“…Previous studies indicated that patients with schizophrenia showed abnormal emotional experience and facial expression recognition (Sanchez et al, 2014 ; Zhu et al, 2016 ); they experienced more negative and less positive emotion than did healthy individuals. Meanwhile, the ability of recognizing positive expressions was weaker in male patients with schizophrenia than in healthy individuals, while the ability of recognizing both positive and negative emotions was similar in female patients with schizophrenia and in healthy individuals.…”

Section: Discussionmentioning

confidence: 93%

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Zhu

Zhang

Zhiying

et al. 2017

Front. Behav. Neurosci.

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Previous studies have focused on the characteristics of ordinary facial expressions in patients with depression, and have not investigated the processing characteristics of ecological micro-expressions (MEs, i.e., MEs that presented in different background expressions) in these patients. Based on this, adopting the ecological MEs recognition paradigm, this study aimed to comparatively evaluate facial ME recognition in depressed and healthy individuals. The findings of the study are as follows: (1) background expression: the accuracy (ACC) in the neutral background condition tended to be higher than that in the fear background condition, and the reaction time (RT) in the neutral background condition was significantly longer than that in other backgrounds. The type of ME and its interaction with the type of background expression could affect participants’ ecological MEs recognition ACC and speed. Depression type: there was no significant difference between the ecological MEs recognition ACC of patients with depression and healthy individuals, but the patients’ RT was significantly longer than that of healthy individuals; and (2) patients with depression judged happy MEs that were presented against different backgrounds as neutral and judged neutral MEs that were presented against sad backgrounds as sad. The present study suggested the following: (1) ecological MEs recognition was influenced by background expressions. The ACC of happy MEs was the highest, of neutral ME moderate and of sadness and fear the lowest. The response to the happy MEs was significantly shorter than that of identifying other MEs. It is necessary to conduct research on ecological MEs recognition; (2) the speed of patients with depression in identifying ecological MEs was slower than of healthy individuals; indicating that the patients’ cognitive function was impaired; and (3) the patients with depression showed negative bias in the ecological MEs recognition task, reflecting the lack of happy ME recognition ability and the generalized identification of sad MEs in those patients.

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Section: Discussionmentioning

confidence: 93%

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Zhu

Zhang

Zhiying

et al. 2017

Front. Behav. Neurosci.

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“…Hartley et al [ 41 ] and So et al [ 42 ] did not find a relationship between symptom severity and dropout; however, Palmier-Claus et al [ 29 ] (also reported in the original study [ 30 ]) found that higher severity on the positive and negative syndrome scale’ (PANSS) positive symptom subscale predicted dropout. Finally, Sanchez et al, [ 43 ] found that the level of cognitive functioning did not predict completion of the study. See Table 10 for a summary.…”

Section: Resultsmentioning

confidence: 99%

Improving Adherence to Web-Based and Mobile Technologies for People With Psychosis: Systematic Review of New Potential Predictors of Adherence

Killikelly¹,

He²,

Reeder³

et al. 2017

JMIR Mhealth Uhealth

101

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BackgroundDespite 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.ObjectiveThe 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.MethodsUsing 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.ResultsOf 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.ConclusionsAdherence 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 so...

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“…[27][28][29][30][31][32][33] Findings from these studies suggest that, surprisingly, deficits in expression and blunted affect in individuals with psychotic disorder are not associated with a reduced intensity of emotional experience in daily life. 30,31,33 However, individuals with schizophrenia and high negative symptoms have been found to show a stronger preference for being alone when in company and more social withdrawal in daily life. 27 Similarly, there is evidence of a greater preference for solitude, increased time alone, and lower positive affect in the daily life of individuals with subclinical social anhedonia.…”

Section: Ecological Interventionist Causal Models In Psychosis Putatimentioning

confidence: 99%

Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life

Reininghaus

Depp

Myin-Germeys

2015

SCHBUL

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Integrated models of psychotic disorders have posited a number of putative psychological mechanisms that may contribute to the development of psychotic symptoms, but it is only recently that a modest amount of experience sampling research has provided evidence on their role in daily life, outside the research laboratory. A number of methodological challenges remain in evaluating specificity of potential causal links between a given psychological mechanism and psychosis outcomes in a systematic fashion, capitalizing on longitudinal data to investigate temporal ordering. In this article, we argue for testing ecological interventionist causal models that draw on real world and real-time delivered, ecological momentary interventions for generating evidence on several causal criteria (association, time order, and direction/sole plausibility) under real-world conditions, while maximizing generalizability to social contexts and experiences in heterogeneous populations. Specifically, this approach tests whether ecological momentary interventions can (1) modify a putative mechanism and (2) produce changes in the mechanism that lead to sustainable changes in intended psychosis outcomes in individuals' daily lives. Future research using this approach will provide translational evidence on the active ingredients of mobile health and in-person interventions that promote sustained effectiveness of ecological momentary interventions and, thereby, contribute to ongoing efforts that seek to enhance effectiveness of psychological interventions under real-world conditions.

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Daily life evidence of environment-incongruent emotion in schizophrenia

Cited by 28 publications

References 43 publications

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Improving Adherence to Web-Based and Mobile Technologies for People With Psychosis: Systematic Review of New Potential Predictors of Adherence

Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life

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