Correlates of frequent gambling and gambling-related chasing behaviors in individuals with schizophrenia-spectrum disorders

Background and aims Published research on the relationship between disordered gambling and schizophrenia is limited. However, existing data suggest that individuals with schizophrenia/schizoaffective disorder may have a high prevalence of co-occurring disordered gambling. As such, effective strategies for screening and assessing gambling-related problems in individuals with psychosis are needed. The goal of this study was to explore the correlates of increased gambling frequency and chasing behavior, a hallmark feature of gambling disorder, in a sample of individuals with schizophrenia and schizoaffective disorders. Methods Data from 336 participants who met DSM-IV criteria for schizophrenia or schizoaffective disorder were used to examine differences between non-gamblers, infrequent gamblers, frequent gamblers who do not report chasing, and frequent gamblers who report chasing on a variety of associated features and symptoms of schizophrenia and disordered gambling. Results and discussion The results of the study support the conclusion that chasing behavior in individuals with schizophrenia/schizoaffective disorder lies on a continuum of severity, with more frequent gamblers endorsing greater chasing. Chasing was also associated with indicators of lower functioning across co-occurring disorders, such as greater problems with alcohol and drugs, greater gambling involvement, and a family history of gambling problems. The findings from the study suggest the utility of screening for chasing behavior as a brief and efficient strategy for assessing risk of gambling problems in individuals with psychotic-spectrum disorders

Cerebrospinal fluid microglia and neurodegenerative markers in twins concordant and discordant for psychotic disorders

International audienceThe jacket type offshore wind turbine transfers efficiently the horizontal load applied on the wind turbine to an axial load on the four piles of its foundation. The axial behaviour of one single pile of the foundation is investigated in a geotechnical centrifuge. The model pile, tested under a 100 g centrifuge acceleration, is designed to represent a cast-in-place pile with a 1.8 m diameter and a 40 m embedded length. The pile, installed in dense Fontainebleau sand, is instrumented with a load sensor at its end to measure the tip resistance. By subtracting the total load applied on the pile, its shaft capacity is also calculated. Different axial loading paths are applied: i) monotonic loadings in compression and tension to obtain ultimate capacities and ii) cyclic loadings which represent a more realistic loading path applied by the jacket during its life time in order to observe the tip and shaft capacities reductions

Perseverant Cognitive Effort and Disengagement

Willingness to expend effort has received increased attention over the past decade, and for good reason – effort is crucial to life's successes, and many of us wish we could harness and control it more optimally. In particular, cognitive effort is central to academic and vocational achievements. Though effort is important, it is also costly. If it were not, no projects would be left unfinished, and no treadmills would be abandoned early. Because it is costly, self-control is often required to exert and maintain effort. Reduced willingness to expend effort has also come into focus as a clinically relevant variable related to amotivation, most notably in schizophrenia. Additionally, both incentive motivation (immediate monetary reward availability) and effort have been linked with cognitive performance, suggesting that our measures of cognitive ability are inexorably linked to and to some degree confounded by cognitive effort. In this dissertation, I present a novel paradigm developed for the assessment of perseverant cognitive effort in the absence of monetary incentive. The Cognitive Effort and DisEngagement (CEDE) task is a cognitive test that increases in difficulty and measures perseverant effort disengagement in a simple but novel way: participants are permitted to skip trials without penalty. The present work introduces the task, situates it within a framework of self-control divided into inhibitory and actuating mechanisms, and provides evidence of its association with stable traits, context, and psychosis. The first set of studies (Chapter 1) tests the reliability and validity of the CEDE task in an undergraduate sample and a community sample. We find evidence of high internal consistency using a split-half method. We also find that skips on the CEDE show convergent validity in terms of correlation with self-reported perseverance and work ethic, as well as discriminant validity, showing lack of significant relationships with several theoretically distinct aspects of self-control. We also show evidence of tolerability of the paradigm and of face validity of skipping as an index of effort disengagement. In Chapter 2, we test the effect of observation on perseverant effort on the CEDE task. We find that participants skip significantly more trials when they are observed by an experimenter with access to information about their performance via sound effects, compared with than when they have privacy (when the experimenter leaves the room, or when the participant wears headphones). We also find that self-reported internal motivational style predicts more perseverant effort when in private, whereas external motivational style predicts more effort when observed, suggesting that motivational styles exert influence differentially depending on features of the context. We also show that self-reported stress during the task negatively predicts performance, and that this relationship is fully mediated by skips. These results suggest that observation has a potent effect on cognitive task effort, affecting people differently according to motivational style, and that test anxiety also promotes effort disengagement. In Chapter 3, we test for group differences in skips between individuals with first episode psychosis (FEP) and community controls, as schizophrenia is associated with both a cognitive and a motivational impairment. We show reduced perseverant cognitive effort on the CEDE in FEP. We find that this group difference specifically emerges during difficult trials, suggesting specifically a deficit in perseverance in reaction to difficulty rather than continuous attention throughout the test. We also show that reduction of effort in the form of skips is correlated with self-reported amotivation among patients. These results suggest clinical relevance of perseverant cognitive effort in schizophrenia as a component or reflection of motivational impairments. Together, these findings provide novel insight into cognitive effort perseverance, its relationship to non-monetary motivations in terms of motivational style and observational context, and its reduction in psychosis. Our findings also highlight the relevance of cognitive effort perseverance to cognitive testing. Willingness to expend cognitive effort appears to be sensitive to numerous factors in the context of difficulty, when the demands on effort are higher, whereas it is relatively steadfast during easier tasks

Mathematical and Computational Modeling of Suicide as a Complex Dynamical System

Background: Despite decades of research, the current suicide rate is nearly identical to what it was 100 years ago. This slow progress is due, at least in part, to a lack of formal theories of suicide. Existing suicide theories are instantiated verbally, omitting details required for precise explanation and prediction, rendering them difficult to effectively evaluate and difficult to improve. By contrast, formal theories are instantiated mathematically and computationally, allowing researchers to precisely deduce theory predictions, rigorously evaluate what the theory can and cannot explain, and thereby, inform how the theory can be improved. This paper takes the first step toward addressing the need for formal theories in suicide research by formalizing an initial, general theory of suicide and evaluating its ability to explain suicide-related phenomena. Methods: First, we formalized a General Escape Theory of Suicide as a system of stochastic and ordinary differential equations. Second, we used these equations to simulate behavior of the system over time. Third, we evaluated if the formal theory produced robust suicide-related phenomena including rapid onset and brief duration of suicidal thoughts, and zero-inflation of suicidal thinking in time series data. Results: Simulations successfully produced the proposed suicidal phenomena (i.e., rapid onset, short duration, and high zero-inflation of suicidal thoughts in time series data). Notably, these simulations also produced theorized phenomena following from the General Escape Theory of Suicide: that suicidal thoughts emerge when alternative escape behaviors failed to effectively regulate aversive internal states, and that effective use of long-term strategies may prevent the emergence of suicidal thoughts. Conclusions: To our knowledge, the model developed here is the first formal theory of suicide, which was able to produce – and, thus, explain – well-established phenomena documented in the suicide literature. We discuss the next steps in a research program dedicated to studying suicide as a complex dynamical system, and describe how the integration of formal theories and empirical research may advance our understanding, prediction, and prevention of suicide

Mapping the Timescale of Suicidal Thinking

Suicide is one of the most devastating aspects of human nature and has puzzled scholars for thousands of years. Most suicide research to date has focused on establishing the prevalence and predictors of the presence or severity of suicidal thoughts/behaviors. Surprisingly little research has documented the fundamental properties of suicidal thoughts/behaviors, such as: when someone has a suicidal thought, how long do such thoughts last? Documenting the basic properties of a phenomenon is necessary to understand, study, and treat it. This study aims to identify the timescale of suicidal thinking, leveraging novel real-time monitoring data and a number of different novel analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-day real-time monitoring study (total number of observations=20,255). Participants completed two forms of real time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 minutes apart over one hour). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-Switching models indicated that that elevated states of suicidal thinking lasted on average 1 to 3 hours. Individuals exhibited considerable heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 hours, while current suicidal desire predictive of future suicidal desire levels for 20 hours. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, our ability to capture within-person dynamics of suicidal thinking was improved using high-frequency sampling. For example, traditional real-time assessments alone estimated the duration of severe suicidal states of suicidal desire as 9.5 hours, whereas, the high-frequency assessments shifted the estimated duration to 1.4 hours. The high-frequency assessments identified 19% more participants with a high-risk response than the traditional real-time assessment, and high frequency measurements were shown to capture considerable levels of variation across consecutive measurement occasions. These results provide the most detailed characterization to date of the temporal dynamics of suicidal thinking. Furthermore, these findings highlight the importance of sampling frequency in capturing the dynamics of a phenomenon

Emotion Regulation in Daily Life among Adults with Suicidal Thoughts

Background. Emotion regulation difficulties are highlighted as a risk factor for suicidal thoughts. However, little is known on how people with suicidal thoughts regulate emotions in daily life using ecologically valid methods. Prior research also rarely differentiated between emotion regulation deficits that are specifically associated with suicidal thoughts, and deficits that characterize high levels of psychopathology, regardless of suicidality. Methods. We conducted two Ecological Momentary Assessment studies (EMA; N1=396; N2=195). We compared adults with current suicidal thoughts to adults with and without a history of suicidal thoughts (Study 1), and to adults with low or high levels of psychiatric symptoms (Study 2). Participants completed a week-long EMA period with 6 surveys per day, assessing emotion regulation attempts, strategies, perceived regulatory success and effort. Results. Participants with suicidal thoughts differed from participants with high psychiatric symptoms only in their regulatory effort and in their use of alcohol or drugs to regulate emotions. Elevated use of distraction, rumination, and self-injury did not differentiate between participants with suicidal thoughts and participants with high psychiatric symptoms but no suicidality. Among participants with suicidal thoughts, self-injury and the use of substances were the only emotion regulation strategies that predicted momentary suicidal thinking. Conclusions. Suicidal thoughts are associated with the use of less effective emotion regulation strategies and difficulties in implementing strategies in daily life. However, many difficulties are not specific to suicidal thoughts. The use of substances to regulate emotions and heightened regulatory effort may be unique to suicidal populations

Frequent Assessment of Suicidal Thinking does not Increase Suicidal Thinking: Evidence from a High-Resolution Real-Time Monitoring Study

Researchers, clinicians, and patients are increasingly using real-time monitoring methods to understand and predict suicidal thoughts and behaviors. These methods involve frequently assessing suicidal thoughts, but it is unknown if asking about suicide repeatedly is iatrogenic. We tested two questions about this approach: (1) does repeatedly assessing suicidal thinking over short periods of time increase suicidal thinking? (2) is more frequent assessment of suicidal thinking associated with more severe suicidal thinking? In a real-time monitoring study (N = 81, number of surveys = 9,819), we found no evidence to support the notion that repeated assessment of suicidal thoughts is iatrogenic

Implementing machine learning algorithms for suicide risk prediction in clinical practice: A focus group study

Background: Interest in developing machine learning algorithms that use electronic health record data to predict patients’ risk of suicidal behavior has recently proliferated. Whether and how such models might be implemented and useful in clinical practice, however, remains unknown. In order to ultimately make automated suicide risk prediction algorithms useful in practice, and thus better prevent patient suicides, it is critical to partner with key stakeholders (including the frontline providers who will be using such tools) at each stage of the implementation process. Objective: The aim of this focus group study was to inform ongoing and future efforts to deploy suicide risk prediction models in clinical practice. The specific goals were to better understand hospital providers’ current practices for assessing and managing suicide risk; determine providers’ perspectives on using automated suicide risk prediction algorithms; and identify barriers, facilitators, recommendations, and factors to consider for initiatives in this area. Methods: We conducted 10 two-hour focus groups with a total of 40 providers from psychiatry, internal medicine and primary care, emergency medicine, and obstetrics and gynecology departments within an urban academic medical center. Audio recordings of open-ended group discussions were transcribed and coded for relevant and recurrent themes by two independent study staff members. All coded text was reviewed and discrepancies resolved in consensus meetings with doctoral-level staff. Results: Though most providers reported using standardized suicide risk assessment tools in their clinical practices, existing tools were commonly described as unhelpful and providers indicated dissatisfaction with current suicide risk assessment methods. Overall, providers’ general attitudes toward the practical use of automated suicide risk prediction models and corresponding clinical decision support tools were positive. Providers were especially interested in the potential to identify high-risk patients who might be missed by traditional screening methods. Some expressed skepticism about the potential usefulness of these models in routine care; specific barriers included concerns about liability, alert fatigue, and increased demand on the healthcare system. Key facilitators included presenting specific patient-level features contributing to risk scores, emphasizing changes in risk over time, and developing systematic clinical workflows and provider trainings. Participants also recommended considering risk-prediction windows, timing of alerts, who will have access to model predictions, and variability across treatment settings. Conclusions: Providers were dissatisfied with current suicide risk assessment methods and open to the use of a machine learning-based risk prediction system to inform clinical decision-making. They also raised multiple concerns about potential barriers to the usefulness of this approach and suggested several possible facilitators. Future efforts in this area will benefit from incorporating systematic qualitative feedback from providers, patients, administrators, and payers on the use of new methods in routine care, especially given the complex, sensitive, and unfortunately still stigmatized nature of suicide risk