G-estimation of causal pathways in vocational rehabilitation for adults with psychotic disorders – a secondary analysis of a randomized trial

Abstract Background Vocational rehabilitation (VR) has increasingly become an important intervention targeting poor occupational functioning in schizophrenia. The Norwegian Job Management Program (JUMP), sought to enhance occupational outcomes by augmenting VR with either cognitive behavioral therapy (CBT) techniques aiming to improve psychotic symptoms or cognitive remediation (CR) aiming to improve cognition. CBT is standard treatment in schizophrenia, but recent meta-analyses question the effect of CBT on negative psychotic symptoms. It is of interest to study the causal role of psychotic symptoms and cognitive functioning on occupational functioning. Methods Data from the JUMP VR – program, was reanalyzed with a causal inference method to assess the causal effects of reduced symptoms / improved neurocognitive functioning on occupational functioning measured by number of working hours per week. Participants (N = 131) had been randomized to either VR + CBT (N = 68) or VR + CR (N = 63). Large improvements in number of working hours were demonstrated in both intervention groups (nonsignificant group difference). G-estimation was used to assess the strength and nature of the causal effects, adjusted for time-varying confounding and selection – bias from loss to follow-up. Results Significant causal effects of reduction in each of four dimensions of symptoms and improved neurocognition respectively, on number of working hours were found (separate models). The effect of negative symptoms was the strongest and increased in magnitude during the whole observation period, while the effect of two other symptoms and neurocognition was constant. Adjusted for confounding (including potential feedback), the causal effect of a hypothetical change in negative symptoms equal to the average improvement in the CBT group corresponded to an increase in working hours of 3.2 h per week (95% CI: 1.11, 5.35). Conclusion High performance of g-estimation in a small psychiatric data set with few repeated measures and time-varying confounding and effects, was demonstrated. Augmented vocational rehabilitation showed causal effects of intervention targets with the strongest and increasing effect from negative symptoms on number of working hours. Combination of therapy and activation (indirect and direct approach) might explain improvement in both cognition and negative symptoms, and shed some light on effective ingredients for improved treatment of negative symptoms.

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G-Estimation of Causal Pathways in Vocational Rehabilitation For Adults With Psychotic Disorders – A Secondary Analysis of A Randomized Trial

10.21203/rs.3.rs-279135/v1 ◽

2021 ◽

Author(s):

Ole Klungsøyr ◽

June Ullevoldsæter Lystad ◽

Helen Bull ◽

Stig Evensen ◽

Torill Ueland ◽

...

Keyword(s):

Vocational Rehabilitation ◽

Negative Symptoms ◽

Causal Effect ◽

Working Hours ◽

Causal Effects ◽

Psychotic Symptoms ◽

Time Varying ◽

Occupational Functioning ◽

Data Set ◽

Causal Pathways

Abstract Background: Vocational rehabilitation (VR) has increasingly become an important intervention targeting poor occupational functioning in schizophrenia. The Norwegian Job Management Program (JUMP), sought to enhance occupational outcomes by augmenting VR with either cognitive behavioral therapy (CBT) techniques aiming to improve psychotic symptoms or cognitive remediation (CR) aiming to improve cognition. CBT is standard treatment in schizophrenia, but recent meta-analyses question the effect of CBT on negative psychotic symptoms. It is of interest to study the causal role of psychotic symptoms and cognitive functioning on occupational functioning. Methods: Data from the JUMP VR – program, was reanalyzed with a causal inference method to assess the causal effects of reduced symptoms / improved neurocognitive functioning on occupational functioning measured by number of working hours per week. Participants (N=131) had been randomized to either VR + CBT (N=68) or VR + CR (N=63). Large improvements in number of working hours were demonstrated in both intervention groups (nonsignificant group difference). G-estimation was used to assess the strength and nature of the causal effects, adjusted for time-varying confounding and selection – bias from loss to follow-up. Results: Significant causal effects of reduction in each of four dimensions of symptoms and improved neurocognition respectively, on number of working hours were found (separate models). The effect of negative symptoms was the strongest and increased in magnitude during the whole observation period, while the effect of the other symptoms and neurocognition was constant. Adjusted for confounding (including potential feedback), the causal effect of a hypothetical change in negative symptoms equal to the average improvement in the CBT group corresponded to an increase in working hours of 3.2 hours per week (95% CI: 1.11, 5.35).Conclusion: High performance of g-estimation in a small psychiatric data set with few repeated measures and time-varying confounding and effects, was demonstrated. Augmented vocational rehabilitation showed causal effects of intervention targets with the strongest and increasing effect from negative symptoms on number of working hours.Combination of therapy and activation (indirect and direct approach) might explain improvement in both cognition and negative symptoms, and shed some light on effective ingredients for improved treatment of negative symptoms.

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The Impact of US Monetary Growth on Bitcoin Trading Volume in the Current Economic Uncertainty

Advances in Marketing, Customer Relationship Management, and E-Services - Handbook of Research on Decision-Making Techniques in Financial Marketing ◽

10.4018/978-1-7998-2559-3.ch023 ◽

2020 ◽

pp. 493-509

Author(s):

İsmail Canöz

Keyword(s):

Causal Relationship ◽

Trading Volume ◽

Causal Effect ◽

Study Data ◽

Time Interval ◽

Time Varying ◽

Economic Uncertainty ◽

Causality Test ◽

Data Set ◽

The Impact

This study examines the effect of US monetary growth on Bitcoin trading volume. To achieve this purpose, firstly, the symmetric causality test is used. Following this test, another symmetric causality test is used to reveal a time-varying causal effect between variables. The data set covers the period from July 2010 to July 2019. The results of the first symmetric causality test, which considers the time interval of the study data as a whole, show that there is no causal relationship between variables. According to the results of the second causality test, these support the previous results substantially. However, an interesting detail is the causal relationship between variables for the period between April 2019 and July 2019. The reason for this relationship could be that investors who are indecisive during the current economic uncertainty add Bitcoin to their portfolios in response to the Federal Reserve's decisions.

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Estimating the causal effects of treatment

Epidemiologia e Psichiatria Sociale ◽

10.1017/s1121189x0000573x ◽

2002 ◽

Vol 11 (3) ◽

pp. 206-215 ◽

Cited By ~ 9

Author(s):

Graham Dunn

Keyword(s):

Causal Effect ◽

Randomised Trial ◽

Outcome Data ◽

Causal Effects ◽

Estimation Methods ◽

Random Allocation ◽

Statistical Research ◽

Data Set ◽

The One ◽

Randomised Controlled

SUMMARYObjective – To provide a relatively non-technical review of recent statistical research on the analysis and interpretation of the results of randomised controlled trials in which there are possibly all three of the following types of protocol violation: non-adherence to allocated treatment, contamination (that is, patients receiving treatments other than the one to which they were allocated) and attrition (missing outcome data). Methods – The estimation methods involve the use of potential outcomes (counterfactuals) in the definition of a causal effect of treatment and in drawing valid inferences concerning its size. Results – The methods are explained through the use of simple arithmetical expressions involving the counts from three-way contingency tables (Outcome by Treatment Received by Random Allocation). Illustration is provided through the use of a hypothetical data set. Conclusions – Recent advances in statistical methodology enable one to estimate treatment effects from the results of randomised trials in which the treatment actually received is not necessarily the one to which the patient was allocated. These methods allow one to make adjustments to allow for both non-compliance and loss to follow-up. Even for such a 'broken' randomised trial, inference concerning causal effects is safer than that from data arising from an observational study that never involved random allocation in the first place.

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11. Identification and Estimation of Causal Effects with Time-Varying Treatments and Time-Varying Outcomes

Sociological Methodology ◽

10.1111/j.1467-9531.2007.00185.x ◽

2007 ◽

Vol 37 (1) ◽

pp. 393-434 ◽

Cited By ~ 19

Author(s):

Jennie E. Brand ◽

Yu Xie

Keyword(s):

Employment Status ◽

Causal Effect ◽

Causal Effects ◽

Potential Outcomes ◽

Time Varying ◽

Potential Outcome ◽

Units Of Analysis ◽

Wisconsin Longitudinal Study ◽

Time Periods ◽

Causal Variable

We develop an approach to identifying and estimating causal effects in longitudinal settings with time-varying treatments and time-varying outcomes. The classic potential outcome approach to causal inference generally involves two time periods: units of analysis are exposed to one of two possible values of the causal variable, treatment or control, at a given point in time, and values for an outcome are assessed some time subsequent to exposure. In this paper, we develop a potential outcome approach for longitudinal situations in which both exposure to treatment and the effects of treatment are time-varying. In this longitudinal setting, the research interest centers not on only two potential outcomes, but on a whole matrix of potential outcomes, requiring a complicated conceptualization of many potential counterfactuals. Motivated by sociological applications, we develop a simplification scheme—a weighted composite causal effect that allows identification and estimation of effects with a number of possible solutions. Our approach is illustrated via an analysis of the effects of disability on subsequent employment status using panel data from the Wisconsin Longitudinal Study.

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Causal inference under over-simplified longitudinal causal models

The International Journal of Biostatistics ◽

10.1515/ijb-2020-0081 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Lola Étiévant ◽

Vivian Viallon

Keyword(s):

Causal Inference ◽

Causal Effect ◽

Sufficient Conditions ◽

Repeated Measurements ◽

Causal Models ◽

Causal Effects ◽

Sensitivity Analyses ◽

Time Varying ◽

Weighted Averages

Abstract Many causal models of interest in epidemiology involve longitudinal exposures, confounders and mediators. However, repeated measurements are not always available or used in practice, leading analysts to overlook the time-varying nature of exposures and work under over-simplified causal models. Our objective is to assess whether – and how – causal effects identified under such misspecified causal models relates to true causal effects of interest. We derive sufficient conditions ensuring that the quantities estimated in practice under over-simplified causal models can be expressed as weighted averages of longitudinal causal effects of interest. Unsurprisingly, these sufficient conditions are very restrictive, and our results state that the quantities estimated in practice should be interpreted with caution in general, as they usually do not relate to any longitudinal causal effect of interest. Our simulations further illustrate that the bias between the quantities estimated in practice and the weighted averages of longitudinal causal effects of interest can be substantial. Overall, our results confirm the need for repeated measurements to conduct proper analyses and/or the development of sensitivity analyses when they are not available.

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Gformula: Estimating Causal Effects in the Presence of Time-Varying Confounding or Mediation using the G-Computation Formula

The Stata Journal Promoting communications on statistics and Stata ◽

10.1177/1536867x1201100401 ◽

2011 ◽

Vol 11 (4) ◽

pp. 479-517 ◽

Cited By ~ 61

Author(s):

Rhian M. Daniel ◽

Bianca L. De Stavola ◽

Simon N. Cousens

Keyword(s):

Indirect Effects ◽

A generalized theory of separable effects in competing event settings

Lifetime Data Analysis ◽

10.1007/s10985-021-09530-8 ◽

2021 ◽

Cited By ~ 2

Author(s):

Mats J. Stensrud ◽

Miguel A. Hernán ◽

Eric J Tchetgen Tchetgen ◽

James M. Robins ◽

Vanessa Didelez ◽

...

Keyword(s):

Indirect Effects ◽

Causal Effect ◽

Time Varying ◽

Direct And Indirect Effects ◽

Loss To Follow Up ◽

Causal Pathways ◽

Common Causes ◽

Competing Events ◽

Definition Of ◽

Weaker Conditions

AbstractIn competing event settings, a counterfactual contrast of cause-specific cumulative incidences quantifies the total causal effect of a treatment on the event of interest. However, effects of treatment on the competing event may indirectly contribute to this total effect, complicating its interpretation. We previously proposed the separable effects to define direct and indirect effects of the treatment on the event of interest. This definition was given in a simple setting, where the treatment was decomposed into two components acting along two separate causal pathways. Here we generalize the notion of separable effects, allowing for interpretation, identification and estimation in a wide variety of settings. We propose and discuss a definition of separable effects that is applicable to general time-varying structures, where the separable effects can still be meaningfully interpreted as effects of modified treatments, even when they cannot be regarded as direct and indirect effects. For these settings we derive weaker conditions for identification of separable effects in studies where decomposed, or otherwise modified, treatments are not yet available; in particular, these conditions allow for time-varying common causes of the event of interest, the competing events and loss to follow-up. We also propose semi-parametric weighted estimators that are straightforward to implement. We stress that unlike previous definitions of direct and indirect effects, the separable effects can be subject to empirical scrutiny in future studies.

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Metacognitive awareness of cognitive problems in schizophrenia: exploring the role of symptoms and self-esteem

Psychological Medicine ◽

10.1017/s0033291713001189 ◽

2013 ◽

Vol 44 (3) ◽

pp. 469-476 ◽

Cited By ~ 24

Author(s):

M. Cella ◽

S. Swan ◽

E. Medin ◽

C. Reeder ◽

T. Wykes

Keyword(s):

Social Functioning ◽

Negative Symptoms ◽

Self Esteem ◽

Metacognitive Awareness ◽

Psychotic Symptoms ◽

Cognitive Assessments ◽

Cognitive Problem ◽

Causal Pathways ◽

Problem Reporting ◽

Cognitive Problems

BackgroundPeople with a diagnosis of schizophrenia have limited metacognitive awareness of their symptoms. This is also evident for cognitive difficulties when neuropsychological assessments and self-reports are compared. Unlike for delusions and hallucinations, little attention has been given to factors that may influence the mismatch between objective and subjectively reported cognitive problems. Symptom severity, and also self-esteem and social functioning, can have an impact on cognitive problem perception and help to explain the gap between objective and subjective cognitive assessments in psychosis.MethodOne-hundred participants with a diagnosis of schizophrenia were recruited and assessed with a comprehensive neuropsychological battery, a measure of awareness of cognitive problems and measures of psychotic symptoms, social and behavioural functioning and self-esteem. Regression was used to investigate the influence of symptoms, social functioning and self-esteem, and patients with different levels of cognitive problem awareness were contrasted.ResultsSimple correlation analysis replicated the lack of association between objective cognitive measures and metacognitive awareness of cognitive problems. However, the results of the regression analyses highlight that self-esteem and negative symptoms predict metacognitive awareness. When significant predictors were controlled, individuals with better awareness had more impaired working memory but higher IQ.ConclusionsPoor self-esteem and high negative symptoms are negatively associated with metacognitive awareness in people with schizophrenia. Interventions that aim to improve cognition should consider that cognitive problem reporting in people with schizophrenia correlates poorly with objective measures and is biased not only by symptoms but also by self-esteem. Future studies should explore the causal pathways using longitudinal designs.

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Understanding the nature of association between anxiety phenotypes and anorexia nervosa: a triangulation approach

BMC Psychiatry ◽

10.1186/s12888-020-02883-8 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

E. Caitlin Lloyd ◽

Hannah M. Sallis ◽

Bas Verplanken ◽

Anne M. Haase ◽

Marcus R. Munafò

Keyword(s):

Anorexia Nervosa ◽

Longitudinal Study ◽

Anxiety Disorder ◽

Anxiety Disorders ◽

Causal Effect ◽

Causal Effects ◽

Observational Research ◽

Genome Wide Association Studies ◽

Genetic Liability ◽

Depressed Affect

Abstract Background Evidence from observational studies suggests an association between anxiety disorders and anorexia nervosa (AN), but causal inference is complicated by the potential for confounding in these studies. We triangulate evidence across a longitudinal study and a Mendelian randomization (MR) study, to evaluate whether there is support for anxiety disorder phenotypes exerting a causal effect on AN risk. Methods Study One assessed longitudinal associations of childhood worry and anxiety disorders with lifetime AN in the Avon Longitudinal Study of Parents and Children cohort. Study Two used two-sample MR to evaluate: causal effects of worry, and genetic liability to anxiety disorders, on AN risk; causal effects of genetic liability to AN on anxiety outcomes; and the causal influence of worry on anxiety disorder development. The independence of effects of worry, relative to depressed affect, on AN and anxiety disorder outcomes, was explored using multivariable MR. Analyses were completed using summary statistics from recent genome-wide association studies. Results Study One did not support an association between worry and subsequent AN, but there was strong evidence for anxiety disorders predicting increased risk of AN. Study Two outcomes supported worry causally increasing AN risk, but did not support a causal effect of anxiety disorders on AN development, or of AN on anxiety disorders/worry. Findings also indicated that worry causally influences anxiety disorder development. Multivariable analysis estimates suggested the influence of worry on both AN and anxiety disorders was independent of depressed affect. Conclusions Overall our results provide mixed evidence regarding the causal role of anxiety exposures in AN aetiology. The inconsistency between outcomes of Studies One and Two may be explained by limitations surrounding worry assessment in Study One, confounding of the anxiety disorder and AN association in observational research, and low power in MR analyses probing causal effects of genetic liability to anxiety disorders. The evidence for worry acting as a causal risk factor for anxiety disorders and AN supports targeting worry for prevention of both outcomes. Further research should clarify how a tendency to worry translates into AN risk, and whether anxiety disorder pathology exerts any causal effect on AN.

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Evaluation of positive and negative symptoms in schizophrenia

Psychiatry and Psychobiology ◽

10.1017/s0767399x00003199 ◽

1986 ◽

Vol 1 (2) ◽

pp. 108-122 ◽

Cited By ~ 29

Author(s):

Nancy C. Andreasen ◽

William M. Grove

Keyword(s):

Negative Symptoms ◽

The United States ◽

Psychotic Symptoms ◽

Positive Symptoms ◽

University Of Iowa ◽

Normal Functions ◽

Subsequent Investigation ◽

The University ◽

The Relationship ◽

Positive And Negative Symptoms

SummaryMost investigators concur that schizophrenia is probably a heterogeneous group of disorders that share the common features of psychotic symptoms, partial response to neuroleptics, and a relatively poor outcome. The subdivision of schizophrenia into two subtypes, positive versus negative, has achieved wide acceptance throughout the world during recent years. This distinction has heuristic and theoretical appeal because it unites phenomenology, pathophysiology, and etiology into a single comprehensive hypothesis.In spite of its wide appeal, the distinction has a number of problems. These include the failure to distinguish between symptom syndromes and diseases; failure to deal with the mixed patient; failure to take longitudinal course into account; and failure to address conceptually and methodologically the distinction between positive and negative symptoms.This paper focuses primarily on the conceptual basis for two instruments designed to measure positive and negative symptoms, the Scale for the Assessment of Negative Symptoms (SANS) and the Scale for the Assessment of Positive Symptoms (SAPS), originally described in 1982. Since their description, these scales have been used in a variety of other centers. These scales are based on the hypothesis that negative symptoms represent a deficit or diminution in normal psychological functions wliile positive symptoms represent an excess or distortion of normal functions. Reliability data are now available from Italy, Spain, and Japan which suggest that these scales can be used reliably in cultural settings outside the United States. The results of these studies are summarized in this paper. In addition, a replication study involving a new sample of 117 schizophrenics collected at the University of Iowa is described. In this second study of the SANS and SAPS, internal consistency is found to be quite high in the SANS. Thus negative symptoms appear to be more internally correlated with one another than are positive symptoms. The implications of this result are discussed. A principal components analysis is used to explore the relationship between positive and negative symptoms. While the study reported in 1982 suggested that positive and negative symptoms are negatively correlated, in the present study they appear to be uncorrelated. Overall, the results suggest that the SANS and SAPS are useful comprehensive instruments for the evaluation of positive and negative symptoms. The relationship between these symptoms and external validators such as cognitive functioning or CT scan abnormalities will be reported in a subsequent investigation.

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