Reasoning, Emotions, and Delusional Conviction in Psychosis

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1 Journal of Abnormal Psychology Copyright 2005 by the American Psychological Association 2005, Vol. 114, No. 3, X/05/$12.00 DOI: / X Reasoning, Emotions, and Delusional Conviction in Psychosis Philippa A. Garety, Daniel Freeman, and Suzanne Jolley King s College London Paul E. Bebbington University College London Elizabeth Kuipers King s College London Graham Dunn University of Manchester David G. Fowler University of East Anglia Robert Dudley University of Newcastle Upon Tyne The aim of the study was to elucidate the factors contributing to the severity and persistence of delusional conviction. One hundred participants with current delusions, recruited for a treatment trial of psychological therapy (PRP trial), were assessed at baseline on measures of reasoning, emotions, and dimensions of delusional experience. Reasoning biases (belief inflexibility, jumping to conclusions, and extreme responding) were found to be present in one half of the sample. The hypothesis was confirmed that reasoning biases would be related to delusional conviction. There was evidence that belief inflexibility mediated the relationship between jumping to conclusions and delusional conviction. Emotional states were not associated with the reasoning processes investigated. Anxiety, but not depression, made an independent contribution to delusional conviction. Keywords: delusions, reasoning, psychosis, schizophrenia Contemporary cognitive models of the positive symptoms of psychosis propose that biased reasoning processes contribute to the development and maintenance of delusions (Bentall, Corcoran, Howard, Blackwood, & Kinderman, 2001; Garety, Kuipers, Fowler, Freeman, & Bebbington, 2001; Kapur, 2003; Rector & Beck, 2001). Delusions are conceptualized as explanations of experiences, particularly aberrant or anomalous perceptions or events, for which an explanation is not evident (Maher, 1988). We have argued that the acceptance of the relatively implausible delusional explanation for these anomalous events or experiences occurs in the context of the person s Philippa A. Garety, Daniel Freeman, Suzanne Jolley, and Elizabeth Kuipers, Department of Psychology, Institute of Psychiatry, King s College London, London, England; Graham Dunn, Biostatistics Group, School of Epidemiology and Health Sciences, University of Manchester, Manchester, England; Paul E. Bebbington, Department of Mental Health Sciences, Royal Free and University College Medical School, University College London, London, England; David G. Fowler, School of Medicine, Health Policy and Practice, University of East Anglia, Norwich, England; Robert Dudley, Newcastle Cognitive and Behavioural Therapies Centre, University of Newcastle Upon Tyne, Newcastle Upon Tyne, England. This work was supported by a program grant from the Wellcome Trust (No ). We thank the patients taking part in the trial and the participating teams in the four NHS Trusts. Correspondence concerning this article should be addressed to Philippa A. Garety, Department of Psychology, P.O. Box 77, Institute of Psychiatry, Denmark Hill, London SE5 8AF, United Kingdom. p.garety@ iop.kcl.ac.uk idiosyncratic culturally conditioned beliefs. However, it is also facilitated in many cases by biased cognitive processes concerned with reasoning (Freeman et al., 2004; Garety et al., 2001). Better understanding of these cognitive processes should lead to improvements in cognitive behavioral therapy for psychosis, which is now becoming established as effective in improving outcomes in people with schizophrenia (National Institute for Clinical Excellence, 2002; Pilling et al., 2002). Although reasoning processes are important to understand in relation to delusions, they are complex. There is no single model of reasoning, and distinctions are made in the literature between formal models of rationality and the way that people actually reason in specific situations (e.g., Evans & Over, 1996; Johnson-Laird, 1982). Evidence that people in the general population do not invariably use formal logic has led psychologists to consider the rules by which people do form and maintain judgments, with resultant models for understanding inferential performance (Fischhoff & Beyth-Marom, 1983; Garety & Hemsley, 1994). Furthermore, it is important to distinguish between belief formation and the reasoning that maintains or alters a belief, which is of particular relevance to clinical interventions. Confirmatory and disconfirmatory reasoning processes become apparent (e.g., Fischhoff & Beyth-Marom, 1983; Wason, 1960). It is also plausible that reasoning that leads to change in delusions is affected by the emotional state of the person. In summary, the psychological literature has identified many different reasoning processes; these may apply differentially to delusion formation and to the aspects of thinking about delusions that may lead to change. 373

2 374 GARETY ET AL. General Reasoning: Jumping to Conclusions People with delusions show several characteristic cognitive biases. These have been demonstrated with particular consistency in tasks assessing probabilistic reasoning based on a Bayesian model (see Garety & Freeman, 1999, for a review). On a typical probabilistic reasoning task (the beads task), people with delusions have been shown to jump to conclusions, requesting less information to reach a decision than controls. It has been argued that this is a data-gathering bias rather than a deficit in probabilistic reasoning. This bias has been replicated widely, using various modifications of the basic paradigm, not only in people with current delusions but also more recently in people who have recovered from delusions (Peters, Day, & Garety, 1999), in people with delusion proneness in the general population (Colbert & Peters, 2002), and in people at high risk for developing a psychotic disorder (Broome et al., 2003). The jumping to conclusions bias has been found to be greater with emotionally salient task material (Dudley, John, Young, & Over, 1997a; Young & Bentall, 1997). It has been found in people with delusional disorder (e.g., Conway et al., 2002) and in groups of people with schizophrenia, independently of the current severity or presence of delusions (Menon, Pomarol-Clotet, McCarthy, & McKenna, 2002; Mortimer et al., 1996). In contrast, a recent study found the jumping to conclusions bias more pronounced in currently deluded patients, albeit still present in nondeluded patients with schizophrenia; Moritz & Woodward, 2005). Most studies conducted with this paradigm have used neutral rather than delusional material. A notable exception is a study by McGuire, Junginger, Adams, Burright, and Donovick, (2001), which assessed the probabilities assigned to delusional narratives, finding that people with delusions assigned higher probabilities to delusion narratives than nondelusional participants. Taken together, the findings suggest that this thinking style is a trait that may contribute to both delusion formation and persistence. General Reasoning: Extreme Responding Absolutist, dichotomous reasoning ( all-or-nothing thinking) is sometimes said to be characteristic of people with delusions and has long been reported clinically (Cameron, 1951; Fowler, Garety, & Kuipers, 1995). However, it has not been studied systematically in this population. It has been described in other clinical populations, notably people with depression (e.g., Beck, Rush, Shaw, & Emery, 1979). Teasdale et al. (2001) have recently developed an operational measure of this thinking style. They found extreme responding to be a key predictor of relapse in a group of people with residual depression. Furthermore, they found in a trial of cognitive therapy that the therapy worked by reducing dichotomous thinking style. In other words, change in response to therapy was mediated by changing the way that people think, specifically reducing the tendency to make extreme judgments. Thinking About Delusions: Belief Flexibility The research reviewed above has examined the cognitive processing style of people with delusions or depression rather than the way that people think about their own delusions. Most of these studies have used task materials or questionnaire items that bear no direct relevance to the content of a given individual s delusions or psychosis. They are intended precisely to test hypotheses about how a more general cognitive processing style may lead to or maintain delusions. In contrast, the Maudsley Assessment of Delusions Schedule (MADS; Wessely et al., 1993) is an interviewbased assessment of delusions. One of its subscales, the Belief Maintenance Scale, assesses items related to belief flexibility. By belief flexibility, we mean the metacognitive capacity of reflecting on one s own beliefs, changing them in the light of reflection and evidence, and generating and considering alternatives. The scale employs questions about the reasons held to support a delusion (e.g., the events and experiences given as grounds for the belief) and whether it is at all possible that the person may be in any way mistaken (possibility of being mistaken). Interviewees are also asked how they would react to a plausible, but hypothetical contradiction to the delusion (reaction to hypothetical contradiction). Given the strong conviction with which delusions are typically held and the definitional criterion of fixity, it is interesting that studies have shown considerable variability in response to these MADS items. About 50% of currently deluded participants give a positive response to the possibility of being mistaken item (e.g., Garety et al., 1997). In studies of psychosis, the two variables possibility of being mistaken and reaction to hypothetical contradiction have been found to predict change in delusions (Brett- Jones, Garety, & Hemsley, 1987) and to predict a positive response to cognitive therapy (Chadwick & Lowe, 1990; Garety et al., 1997; Sharp et al., 1996). In one study, reaction to hypothetical contradiction was found to be unrelated to measures of conviction (Hurn, Gray, & Hughes, 2002). A strong association between the possibility of being mistaken and the generation of alternative explanations for current delusions has been found: People who were able to report alternative explanations for their delusional beliefs were significantly more likely to respond positively to the possibility of being mistaken (Freeman at al., 2004). We have argued that belief flexibility measured in this way may be an important reasoning process in delusional belief persistence and change (Garety et al., 2001). There has been no study of how belief flexibility in delusions relates to more general reasoning processes, such as jumping to conclusions. Emotional States In a multifactorial model of psychosis, we propose that emotional processes, specifically anxiety and depression, make a distinct contribution to the development and persistence of positive symptoms (Freeman & Garety, 2003; Garety et al., 2001). Barrowclough et al. (2003) have recently found support for this: In a group of people with schizophrenia, greater negative selfevaluation was associated with more severe positive symptoms. Similarly, Lysaker, Lancaster, Nees, and Davis, (2003) have found an association between emotional distress and severity of delusions. There is evidence that the biases associated with the Attributional Style Questionnaire are often partially accounted for by levels of depression in deluded populations (Garety & Freeman, 1999). However, few studies have investigated the role of emotional processes in reasoning biases in people with delusions, and there is no direct evidence to suggest that the reasoning processes investigated in the present study are particularly influenced by emotional distress. At present, therefore, it is an open question

3 REASONING AND DELUSIONS 375 whether the contributions of reasoning and emotional processes to delusional severity are independent or act in combination. Studying Delusions Multidimensionally Most empirical studies of reasoning and delusions have taken a unidimensional approach to the measurement of delusions (scoring delusions as present vs. absent or on a single severity scale). However, it has been increasingly acknowledged that delusions can best be characterized multidimensionally, with factor-analytic studies reporting three or four dimensions, most usually conviction, preoccupation, distress, and disruption to behavior (e.g., Garety & Hemsley, 1987; Harrow, Rattenbury, & Stoll, 1988; Kendler, Glazer, & Morgenstern, 1983). Accordingly, Haddock, McCarron, Tarrier, and Faragher (1999) have developed a multidimensional assessment tool the Psychotic Symptoms Rating Scales (PSYRATS). This scale measures delusions on these key dimensions. Investigations that take a multidimensional approach suggest that different cognitive and emotional processes contribute to these different dimensions such that delusional conviction and distress result from different processes (Freeman, Garety, & Kuipers, 2001). Study Aims The aim of the present study is to elucidate the factors that contribute to the severity and persistence of delusional conviction. In a cross-sectional study of 100 individuals with current delusions, we first tested the associations between the general cognitive processing styles of jumping to conclusions and extreme responding and the metacognitive process of belief flexibility: We predicted that jumping to conclusions on the probabilistic reasoning task and more frequent endorsement of extreme responses would be associated with less belief flexibility on the MADS item, possibility of being mistaken. Second, we investigated the associations between belief flexibility, reasoning styles (jumping to conclusions and extreme responding) and current delusional symptom severity and dimensions of delusions: conviction, preoccupation, disruption, and distress. We predicted that lower belief flexibility, higher jumping to conclusions, and more extreme responding would be associated with increased delusional severity, especially on the dimension of conviction. We also conducted an exploratory analysis to examine whether belief flexibility or general cognitive biases make the greater contribution to severity of current delusional conviction. Third, we undertook an exploratory analysis of the relationships between belief flexibility, general reasoning, and current depression and anxiety. Finally, in a further exploratory analysis, we examined the contributions of reasoning processes and emotional distress to current delusional conviction. We predicted that cognitive reasoning processes contribute more strongly to delusional conviction than emotions. Method Participants Individuals with current delusions participated in the present study, drawn from the first cohort recruited for the Psychological Prevention of Relapse in Psychosis (PRP) Trial (ISRCTN ). The PRP Trial is a United Kingdom multicenter randomized controlled trial of cognitive behavior therapy and family intervention for psychosis. It is based in four National Health Service Trusts in London and East Anglia. It was designed to answer questions both about outcome and the psychological processes associated with psychosis. Planned studies of psychological processes in psychosis are incorporated into the baseline assessment of participating patients before randomization into the trial takes place. We aimed to recruit a representative sample of individuals with psychosis at the time of relapse in positive symptoms, either from a previously recovered state or from a state of persisting symptoms. The inclusion criteria are the following: a current diagnosis of nonaffective psychosis (schizophrenia, schizoaffective psychosis, delusional disorder), age between 18 and 65 years, a second or subsequent episode starting not more than 3 months before consent to enter the trial, and a rating of at least 4 (moderate severity) on the Positive and Negative Syndrome Scale (PANSS) on at least one positive psychotic symptom at first time of meeting. The following exclusionary criteria were employed: primary diagnosis of alcohol or substance dependency, organic syndrome or learning disability, inadequate command of English to engage in psychological therapy with an English-speaking therapist, unstable residential arrangements. The participants were the first cohort of 100 individuals with current delusions during the baseline assessment (4 or above on the PANSS delusions item). They consented to complete the MADS and probabilistic reasoning measures for the current study in addition to the key trial outcome measures (symptoms and functioning). This was 60% of those eligible (100/167). The sample who participated in this study was compared with those who did not: There were no significant differences on any demographic variables (age, sex, length of illness, ethnicity, employment, marital status, inpatient status) or on symptoms (PANSS positive, negative, or general psychopathology; p.05). The use of this initial cohort was decided a priori A more elaborated model of reasoning processes on the basis of the results of the current study will be tested longitudinally in the rest of the sample. Measures The measures for the study were clinical and demographic data taken from medical notes (age, sex, ethnicity, inpatient/outpatient, illness length, number of admissions); symptom identification derived from a clinical diagnostic interview, the Schedules for Clinical Assessment in Neuropsychiatry (SCAN; World Health Organization, 1992), undertaken by trained research assessors; measures of symptoms (positive symptoms of psychosis and emotional states); IQ (Ammons & Ammons, 1962); the Maudsley Assessment of Delusions Scale used to elicit thinking about the delusion (belief flexibility); and measures of cognitive processes (probabilistic reasoning and extreme responding). Symptom and Emotion Measures Positive and Negative Syndrome Scale. The PANSS (Kay, 1991) is a 30-item rating instrument developed for the assessment of phenomena associated with schizophrenia. Each item is rated on a 7-point scale ranging from 1 (absent) to 7 (extreme), with a total scale range of Symptoms over the past 72 hr are rated. Higher scores indicate the greater presence of a symptom. Assessors trained to a high level of interrater reliability conducted the assessments (for a sample of 16 tapes, pairs of raters achieved intraclass correlation coefficients of.92,.98 and.92 for PANSS positive symptoms score). Psychotic Symptoms Rating Scale. The PSYRATS (Haddock et al., 1999) is a 17-item multidimensional measure of delusions and hallucinations on which each item is measured on a 5-point scale ranging from 0 (not endorsing item) to4(fully endorsing item). The instrument assesses the conviction, preoccupation, disruption, and distress associated with delusions and the presence, distress, and disruption associated with hallu-

4 376 GARETY ET AL. cinations. Symptoms over the past week are rated, with higher scores representing greater severity. Interrater reliability for the scale is very good (intraclass correlation coefficients for the items range from.79 to 1.00), but test retest statistics have not been reported. Beck Depression Inventory-II (BDI-II). The BDI-II (Beck, Steer, & Brown, 1996) is a self-report, 21-item scale, with items rated on a 4-point scale ranging from 0 to 3 for the assessment of depression. Depression is assessed over the past fortnight. Higher scores indicate higher depression. Beck Anxiety Inventory (BAI). The BAI (Beck, Epstein, Brown, & Steer, 1988) is a self-report, 21-item scale, with items rated on a 4-point scale ranging from 0 to 3 for the assessment of anxiety. Anxiety is assessed over the past week. Higher scores indicate higher levels of anxiety. Reasoning Measures Belief Flexibility Maudsley Assessment of Delusions scale (MADS). The MADS (Wessely et al., 1993) is a standardized interview assessment of delusions, which inquires about the evidence for the delusion and divides the types of evidence cited into internal experiences (e.g., mood, anomalous experience) and external events (e.g., the actions of others). The evidence for the delusion generated by the patient during this interview was used as the basis for the consideration of whether the patient might possibly be mistaken. In the reaction to hypothetical contradiction, the interviewer offers a hypothetical but plausible piece of evidence, which, if true, would be proof against the delusion; whether the patient reports that this would reduce conviction in the delusion is recorded. The scale has good interrater reliability (mean kappa.82; Taylor et al., 1994), and the interrater reliability for the possibility of being mistaken item is reported as 0.91 (Wessely et al., 1993). For the possibility of being mistaken item, we found test retest reliability over 3 months to be good in a subsample of the current study s population; n 53,.66, p.01. IQ Quick Test. The Quick Test (Ammons & Ammons, 1962) provides a rapid estimation of Full Scale IQ. The procedure relies on verbal knowledge and is well tolerated by patients. Patients are shown four line drawings and given 50 test words, each of which they must relate to one of the pictures. Form 1 of the Quick Test was administered. Because the test is rapid and relies on verbal skills, the IQ obtained is only an approximate estimate. Jumping to conclusions Probabilistic reasoning task. The probabilistic reasoning task (Dudley, John, Young, & Over, 1997a, 1997b; Garety, Hemsley, & Wessely, 1991) assesses data-gathering reasoning style. In the original task (Garety et al., 1991) participants are asked to request as many pieces of evidence (colored beads) as they would like before making a decision (from which of two jars the beads are drawn). The two jars have beads of two different colors (e.g., yellow and black) in the ratio 85:15. The key variable used here is number of items requested before making a decision, with two items or fewer classified as jumping to conclusions. Participants completed a computerized or identical paper version of the 85:15 beads task and two more difficult versions developed by Dudley et al. (1997a, 1997b), presented in a set order. In the second version of the task, the ratio of the colored beads was 60:40. In the third, salient version, the beads were replaced by emotion words that the participant was told had been generated by a survey of the opinions of two groups of 100 about an individual; one group made more positive comments (e.g., reliable, cheerful) and the other, more negative comments (e.g., selfish, unfriendly) in the ratio of 60:40, and participants had to decide which survey the words had been selected from. In order to reduce the task demands on working memory and prevent any confound with memory function, the tasks included a memory aid, in which the previous beads or words drawn are shown (as in Dudley et al., 1997b). Extreme Responding Following Teasdale et al. (2001), we developed the measure of extreme responding in two stages. First we selected a questionnaire, with a range of response options, to score people with delusions on use of extreme points of the scale. For this purpose, the precise content of the measure is not important. We used the Illness Perception Questionnaire (IPQ) (Weinman, Petrie, Moss-Morris, & Horne, 1996). The IPQ is a questionnaire measure of the appraisal of an illness, in this case psychosis, comprising five dimensions identity, causes, consequences, timeline and treatment/cure. There are 27 items for the latter four dimensions, scored on a 5-point Likert scale ranging from 1 (strongly agree) to 5(strongly disagree) and 18 identity items, scored on a 4-point frequency scale. The items involve thinking about psychosis. Extreme responding was scored by summing the total number of items on the IPQ questionnaire (27 items, excluding identity items not suitable for this purpose) on which a participant endorsed the most extreme response, whether positively or negatively valenced. Teasdale et al. (2001) validated extreme responding using selected questionnaires, having first generated the hypothesis of a general tendency to extreme responding from one scale, the Attributional Style Questionnaire (ASQ; Peterson et al., 1982). The authors demonstrated that there was a general tendency to respond in extreme absolute terms across different measures of varying content. We undertook a similar exercise, using the ASQ and the Need For Closure Questionnaire (NFC; Kruglanski, Webster, & Klem, 1993) for the purposes of validation. The ASQ presents scenarios with six positive and six negative outcomes. Participants infer the causes of the outcomes and rate those causes on three 7-point scales: external internal, unstable stable, and specific global. The NFC scale consists of 42 items across five subscales measuring desire for predictability, preference for order and structure, discomfort with ambiguity, decisiveness, and closed-mindedness. Participants indicate how much they agree with a statement by responding on a 6-point scale ranging from 1(strongly disagree) to 6( strongly agree). The scale has good test retest reliability (r.86) and construct validity (Webster & Kruglanski, 1994). In addition to the IPQ measure, 41 participants completed the ASQ and 92 completed the NFC. Extreme responding was calculated for all three measures as the number of responses scored at the extreme of the available options, whether positively or negatively valenced. We found that all three measures of extreme responding from these scales were highly correlated: ASQ and IPQ, r.57, n 41, p.01; NFC and IPQ, r.54, n 92, p.01; ASQ and NFC, r.45, n 39, p.01. The total scores of the measures (not extreme responses) for the same individuals yielded much lower, nonsignificant correlations: ASQ and IPQ, r.17, n 41, p.28; NFC and IPQ, r.13, n 92, p.23; ASQ and NFC, r.13, n 39, p.45. This confirms that in a sample with nonaffective psychosis there is a tendency to show absolutist, extreme responding across a range of measures with different contents, which are themselves unrelated. For the purposes of the present study, to compensate for a small number of participants missing odd items during the completion of the IPQ, a percentage extreme responding score was calculated (number of extreme responses expressed as a percentage of the number of items completed). Statistical Analysis Routine data management and production of summary statistics were carried out using SPSS for Windows (Version 11.0; SPSS, 2001). Multiple regression and multiple logistic regression models were fitted using Stata Version 7.0 (StataCorp, 2002). After initial tests showed that the three jumping to conclusions measures (Beads 85:15, Beads 60:40, and Words 60:40) were strongly associated with each other (all chi-square tests p.01), the three measures were treated as if they were multiple indicators of jumping to conclusions, and their common association with other variables was estimated from a marginal model, as described in Dunn (2000). Robust standard errors, two-tailed p values, and two-sided 95% confidence intervals (CIs) for the effects estimated on the marginal models were produced by Stata, after allowing for the patients identity as a clustering variable. Testing of the belief inflexibility mediational hypothesis followed Baron and Kenny s (1986) analytic strategy, which involved conducting repeated

5 REASONING AND DELUSIONS 377 multiple regression analyses, regressing the dependent variable on the independent variable, and regressing the dependent variable on both the independent variable and the hypothesized mediator. Results Participants Clinical and Demographic Data The group consisted of 100 people with current delusions. Sixty-six percent (n 66) were male, and 34% (n 34) were female. The mean age of the group was 39.6 years (SD 11.6; range 20 65). The clinical diagnoses of the patients were schizophrenia (n 79), schizoaffective disorder (n 20), and delusional disorder (n 1). The mean length of illness was 11.1 years (SD 8.9); the mean number of hospital admissions was 5.0 (SD 6.1). Sixty-two percent were inpatients at the time of the current relapse. The sample was drawn from the following ethnic groups: White (n 75), Black African (n 6), Black Caribbean (n 6), Black other (n 1), Asian Indian (n 2), and other (n 10). Among the sample, 70% were single, 20% were divorced or separated, and only 10% were married or in a stable relationship. Only 5% of the group was employed full-time; 81% were currently unemployed and not engaged in part-time, voluntary, or home-based work. The mean IQ of the sample on the Quick Test was 95.6 (SD 12.5, n 74; this reduced completion rate was largely due to the IQ assessment only being made if English was the participant s first language, as the Quick Test is based on verbal knowledge). Clinical data on the PANSS, the PSYRATS delusions dimension scores, and scores from the measures of emotional states (BDI and BAI) are presented in Table 1. The mean scores on the PANSS indicate that the present sample had moderately high levels of positive symptoms, similar to levels found in a hospitalized group with long-term schizophrenia (Kay, Fiszbein, & Opler, 1987), as would be expected of a group recruited following an acute relapse. They also had moderate levels of depression and anxiety. Table 1 Symptom Levels in the Total Sample Measure n Mean score (SD) PANSS Total score (13.7) Positive (4.3) Negative (6.3) General (7.1) PSYRATS Delusion conviction (0.8) Delusion preoccupation (1.1) Delusion distress (1.4) Delusion disruption (1.1) Current affective state BDI-II (depression) (12.3) BAI (anxiety) (13.7) Note. PANSS Positive and Negative Symptom Scales; PSYRATS Psychotic Symptom Rating Scales; BDI-II Beck Depression Inventory; BAI Beck Anxiety Inventory. What Proportion of the Sample Show Belief Flexibility (MADS), Jumping to Conclusions, and Extreme Responding? The possibility of being mistaken question was answered by 99 patients. Of the sample, 46% considered that they might possibly be mistaken about their delusional belief, whereas 53% did not consider this at all possible. The validity of this item for assessing belief flexibility was checked by testing its association with the MADS reaction to hypothetical contradiction. Those who considered they might be mistaken were much more likely to reduce their conviction in their belief in response to the hypothetical contradiction than those who did not consider they might be mistaken, 2 (1, N 94) 34.8, p.01, odds ratio (CI) 0.04 (0.01 to 0.14). Only 3 of 51 people who did not think that they were mistaken said that they would reduce their delusion conviction in response to a contradiction. In contrast, 27 of 43 people who thought that they could be mistaken said they would reduce their delusion conviction in response to a contradiction. In the probabilistic reasoning task, completed by 100 people, 53% of the sample showed jumping to conclusions (defined as two or fewer items) on the 85:15 Beads task, 41% on the 60:40 Beads task, and 37% on the 60:40 Words task. The mean percentage of extreme responses endorsed was 38.2% (SD 29.3, range 0% to 96%, n 91). Of the 91 people, 33 (36%) answered extremely on more than 50% of the questionnaire items. There were no significant differences ( ps.10) in gender, age, ethnicity, or length of illness in responses on the reasoning measures: belief flexibility, jumping to conclusions, and extreme responding. Furthermore, none of the reasoning measures was significantly associated with IQ ( ps.10). Analysis 1. Are Jumping to Conclusions and Extreme Responding Associated With Belief Flexibility? The associations between the three probabilistic reasoning measures and belief flexibility are shown in Table 2. As predicted, jumping to conclusions was associated with belief inflexibility (no possibility that one could be mistaken): the common odds ratio for the association of the three probabilistic reasoning measures with belief flexibility was significant, odds ratio 1.97, robust standard error 0.65, z 2.05, p.04, CI 1.03 to As predicted, extreme responding was significantly greater in the group that showed belief inflexibility; the mean extreme response score was 43.8% (SD 30.9) in the low belief flexibility group compared with mean extreme response score 30.8% (SD 24.8) in the high belief flexibility group, t(86.8) 2.20, p.03, mean difference (CI) 13.0% (1.20 to 24.9). There was no significant association between extreme responding and jumping to conclusions, 1.97, robust standard error 4.9, t 0.40, p.69, CI 11.8 to 7.8. Analysis 2. How Do Belief Flexibility, Jumping to Conclusions, and Extreme Responding Relate to Current Delusional Symptomatology and Dimensional Assessments of Delusions? Are They Related to Other Symptoms? Belief flexibility was strongly associated in the predicted direction (more flexibility, lower delusion scores) with delusional

6 378 GARETY ET AL. Table 2 Probabilistic Reasoning and Belief Flexibility Probabilistic reasoning task No possibility of being mistaken n (%) Possibly of being mistaken n (%) Beads 85:15 Jumping to conclusions 33 (62.3%) 20 (37.7%) Not jumping to conclusions 20 (43.5%) 26 (56.5%) Beads 60:40 Jumping to conclusions 24 (58.5%) 17 (41.5%) Not jumping to conclusions 28 (50.0%) 28 (50.0%) Words 60:40 Jumping to conclusions 25 (67.6%) 12 (32.4%) Not jumping to conclusions 26 (44.8%) 32 (55.2%) symptomatology, when assessed unidimensionally on the PANSS and also on the PSYRATS dimensional assessments of delusions (delusional conviction, preoccupation, and disruption to life), but it was not associated with delusional distress. Belief flexibility was not associated with PANSS negative or general symptomatology and showed one significant association with a measure of hallucination: It was significantly associated with PANSS hallucinatory behavior, but it was not significantly related to any PSYRATS dimensional assessment of hallucinations (frequency, distress, or disruption). It was not associated with the PANSS measure of thought disorder (conceptual disorganization; see Table 3). Jumping to conclusions was associated with delusions but not with other symptoms. It was significantly associated with higher PSYRATS delusion conviction scores, 0.28, robust standard error 0.13, t 2.20, p.03, CI 0.53 to There was a trend for jumping to conclusions to be associated with higher PANSS Delusion scores, 0.30, robust standard error 0.15, t 1.90, p.06, CI 0.60 to 0.01, and with higher PANSS positive symptoms score, 1.30, robust standard error 0.70, t 1.90, p.06, CI 2.70 to There were no significant associations with: PANSS hallucinatory behavior, 0.17, robust standard error 0.28, t 0.61, p.54, CI 0.73 to 0.39; PSYRATS hallucinations (frequency), 0.21, robust standard error 0.25, t 0.84, p.40, CI 0.28 to 0.69; PANSS negative symptoms score, 0.46, robust standard error 0.85, t 0.54, p.59, CI 1.20 to 2.20; PANSS general symptoms score, 1.15, robust standard error 1.14, t 1.01, p.32, CI 1.10 to 3.40; PSYRATS delusion preoccupation, 0.10, robust standard error 0.18, t 0.54, p.59, CI 0.45 to 0.25; PSYRATS delusion disruption, 0.27, robust standard error 0.18, t 1.50, p.13, CI 0.08 to 0.62; and PSYRATS delusion distress, 0.06, robust standard error 0.21, t 0.29, p.77, CI 0.35 to 0.48 (see Table 4). Contrary to our hypotheses, extreme responding showed no significant association with delusions, nor was it associated with other symptoms: PANSS positive symptoms score, r.03, p.78; PANSS negative symptoms score, r.07, p.51; PANSS general symptoms score, r.05, p.66; PANSS delusion score, r.14, p.18; PANSS hallucination score, r.01, p.89; PSYRATS delusional conviction, r.06, p.57; PSYRATS delusional preoccupation, r.16, p.13; or PSYRATS delusional disruption to life, r.03, p 81. There was only a significant negative correlation of extreme responding with PSYRATS delusional distress, r.29, p.01. In a multiple regression examining the contribution of belief flexibility and jumping to conclusions to delusional conviction, using PSYRATS conviction as the dependent variable and MADS belief flexibility and jumping to conclusions as the independent variables, the model was significant, F(4, 96) 10.00, p.01, R Only belief flexibility remained significant, 0.84, robust standard error 0.15, t 5.66, p.01, CI 1.13 to 0.54, whereas jumping to conclusions did not, 0.14, robust standard error 0.10, t 1.40, p.18, CI 0.35 to Analysis 3. What Are the Relationships Between Reasoning Processes and Emotional Processes? An exploratory analysis found that there were no significant relationships ( p.05) between reasoning processes and current emotional disturbance, as measured by the BDI Inventory or the BAI. First, belief flexibility showed no significant association with scores on the BDI ( p.99) or the BAI ( p.09; see Table 3). Second, there were no significant associations between jumping to conclusions and BDI scores, 3.36, robust standard error 1.92, t 1.80, p.08, CI 0.45 to 7.17, or BAI scores, 0.39, robust standard error 2.32, t 0.17, p.87, CI 4.21 to Finally, extreme responding showed no significant association with BDI, r.00, p.97, or the BAI, r.11, p.23. Analysis 4. What Are the Contributions of Reasoning Processes and Emotional Processes to Current Delusional Conviction? In the final stage of analysis, we carried out two regression analyses, both with delusion conviction as the dependent variable. In the first regression the independent variables were the reasoning measures (belief flexibility, jumping to conclusions, extreme responding) and emotion measures (depression, anxiety). The model was significant, F(7, 84) 5.87, p.01, R Three variables remained significant: belief flexibility, 0.80, robust standard error 0.15, t 5.40, p.01, CI 1.09 to 0.50; anxiety, 0.02, robust standard error 0.01, t 3.20, p.01, CI 0.03 to 0.01; and jumping to conclusions, 0.21, robust standard error 0.10, t 2.00, p.05, CI 0.41 to Lower belief flexibility, higher jumping to conclusions, and higher anxiety contributed to higher delusional conviction. In the second regression we removed belief flexibility as a predictive variable to investigate whether jumping to conclusions or extreme responding would then have a stronger association with delusion conviction (i.e., whether belief flexibility mediates the relationship between general reasoning and delusions). The model was now nonsignificant, F(6, 85) 1.91, p.09, R In this model, jumping to conclusions was the only significant predictor, 0.35, robust standard error 0.13, t 2.60, p.01, CI 0.61 to This analysis, in which there is a higher coefficient and increased level of significance for jumping to conclusions once belief flexibility is removed, is consistent with the earlier regression involving both belief flexibility and jumping to conclusions, in which only belief flexibility remained signifi-

7 REASONING AND DELUSIONS 379 Table 3 Belief Flexibility and Symptoms Measure/possibility of being mistaken n M (SD) t df p PANSS Mean difference CI Positive No (3.7) , 5.28 Yes (4.1) Negative No (7.2) , 3.51 Yes (5.2) General No (7.1) , 4.63 Yes (7.0) Delusion No (0.7) , 1.30 Yes (1.1) Hallucination No (1.8) , 1.42 Yes (1.7) Conceptual disorganization No (1.6) , 0.92 Yes (1.3) PSYRATS delusions Conviction No (0.45) , 1.13 Yes (0.9) Preoccupation No (0.9) , 1.05 Yes (1.1) Distress No (1.4) , 0.58 Yes (1.3) Disruption No (1.0) , 0.89 Yes (1.1) PSYRATS auditory hallucinations Frequency No (1.6) , 0.98 Yes (1.3) Distress No (1.7) , 0.50 Yes (1.6) Disruption No (1.5) , 0.84 Yes (1.2) Current affective state BDI No (12.3) , 5.04 Yes (12.5) BAI No (13.7) , Yes (13.1) Note. PANSS Positive and Negative Symptom Scales; PSYRATS Psychotic Symptom Rating Scales; BDI Beck Depression Inventory; BAI Beck Anxiety Inventory.

8 380 GARETY ET AL. Table 4 Probabilistic Reasoning and Symptoms Symptom measure/ jumping to conclusions 85:15 Beads task 60:40 Beads task 60:40 Words task n M (SD) n M (SD) n M (SD) PANSS Positive Yes (4.7) (4.8) (4.3) No (3.7) (3.9) (4.4) Negative Yes (7.2) (4.3) (5.8) No (5.1) (6.8) (6.5) General Yes (7.4) (7.0) (7.3) No (6.7) (6.7) (6.6) Delusion Yes (1.0) (1.0) (0.8) No (1.0) (1.0) (1.1) Hallucination Yes (1.9) (1.7) (1.8) No (1.7) (1.9) (1.8) PSYRATS delusion Conviction Yes (0.8) (0.9) (0.6) No (0.9) (0.8) (0.9) Preoccupation Yes (1.1) (1.1) (0.9) No (1.1) (1.1) (1.2) Distress Yes (1.4) (1.2) (1.3) No (1.3) (1.5) (1.4) Disruption Yes (1.0) (1.0) (1.0) No (1.1) (1.0) (1.1) Current affective state BDI-II Yes (11.7) (11.6) (12.6) No (12.4) (12.4) (12.1) BAI Yes (13.4) (13.4) (13.0) No (13.8) (14.0) (14.2) Note. PANSS Positive and Negative Symptom Scales; PSYRATS Psychotic Symptom Rating Scales; BDI-II Beck Depression Inventory II; BAI Beck Anxiety Inventory. cant; taken together, these analyses indicate that belief flexibility largely mediates the relationship of jumping to conclusions with delusional conviction (Baron & Kenny, 1986). Discussion In this study, we confirmed our hypothesis, based on cognitive models of psychosis (Bentall et al., 2001; Garety et al., 2001), that reasoning processes would be associated with the severity of current delusional conviction. Belief flexibility, a metacognitive process of thinking about one s own delusional beliefs and previously found to be a marker of change in delusions, was found to have clear relationships to delusional severity and to the two other more general reasoning processes investigated. We draw the testable inference from this that delusional persistence or change results partially from style of reasoning. About 50% of this sample of individuals with a recent relapse of psychosis demonstrated belief flexibility in that they indicated on the MADS (Wessely et al., 1993) a willingness to consider that they might possibly be mistaken in their delusional belief. This finding is at odds with the traditional view of delusional inflexibility, or incorrigibility, but is consistent with previous research (Brett-Jones et al., 1987; Garety et al., 1997; Sharp et al., 1996). We predicted, and found, that belief flexibility would be associated with lower delusional conviction. Belief flexibility might, therefore, be considered simply a measure of less severe psychosis

9 REASONING AND DELUSIONS 381 or delusions. We would argue that it is not. It is not an indicator of less severe general or negative symptomatology. However, it was associated with lower positive symptom scores, with delusions, and with hallucinations, though not with thought disorder. Using a dimensional measure of delusions, we found that it was associated with less severe conviction and with less severe preoccupation and disruption, but not with less severe distress. In contrast, it was not associated with any dimensions of hallucinations, including frequency. It has been previously found that belief flexibility predicts future change in delusions and responsiveness to cognitive therapy, in contrast to symptom severity or levels of conviction, which do not predict change (Garety et al., 1997). In keeping with this, the possibility of being mistaken variable was found in this study to be associated with reduced conviction in response to a hypothetical contradiction. Furthermore, it shows clear relationships with other measures of general reasoning, not themselves in any way concerned with delusional content. Therefore, we suggest that the importance of belief flexibility is a marker of future change in delusions, rather than simply of current symptom levels. However, it should be acknowledged that, in this study, belief flexibility was not demonstrated to be a process entirely distinct from belief strength. Belief flexibility seems to reflect an ability to reflect on one s own beliefs and to consider alternative ideas, and was, as expected, found to be related to more general reasoning biases, tapping absolute, dichotomous thinking (extreme responding) and restricted data gathering (jumping to conclusions). These latter two processes were not related to each other. A cross-sectional study of associations clearly cannot demonstrate causal relationships. However, it is possible that the more general processes of dichotomous thinking and jumping to conclusions each feed into the way individuals think about their delusions. Thus, they contribute to a lack of belief flexibility, in turn, leading to higher conviction and lower potential for change in delusions. In Figure 1 we offer a hypothesized framework of the relationships between these processes and delusions. To explain this framework, we consider first how we understand extreme responding and jumping to conclusions and then discuss the role of anxiety in the framework. First, our prediction was confirmed that people with delusions would show a general tendency to think in an extreme, all-or-nothing style. In the process, we replicated Teasdale et al. s (2001) finding with a different clinical population. Extreme responding was measured by a pattern of extreme endorsement of questionnaire items, on three questionnaires with different contents. Although the total scores were not correlated, extreme responding scores were highly intercorrelated. Additionally, we found, for the first time, that this style of responding is related to a reasoning process of known relevance to delusional thinking and change, belief flexibility. Teasdale et al. (2001) suggested that extreme responding, reflecting dichotomous, all-ornothing thinking, is a marker of uncontrolled automatic processing. It gives rapid access to precomputed schematic representations without the benefit of a second stage of more controlled reappraisals that might lead to more moderate thinking patterns. It is readily apparent, therefore, how this type of rapid, automatic processing might contribute to the ways in which people think about their delusional beliefs favoring the immediate acceptance of the delusion with a lack of a second-stage reappraisal of the delusion as only possibly correct. Figure 1. Hypothesized framework of reasoning processes in delusion conviction and change. JTC jumping to conclusions; ER extreme responding; PM possibility of being mistaken. Significant associations were found between jumping to conclusions and severity of delusional conviction. Together with the recent finding of Moritz and Woodward (2005), who reported that higher delusion scores on the Brief Psychiatric Rating Scale are associated with jumping to conclusions, the absence of any associations of jumping to conclusions with other symptoms, including hallucinations, adds to the literature suggesting that jumping to conclusions, a reasoning process unrelated to delusional content, is specifically implicated in delusional severity. However, the multiple regressions suggested that the contribution of jumping to conclusions was largely mediated by belief flexibility, and we therefore represent this relationship in our model in Figure 1. The jumping to conclusions bias is thought to reflect a data-gathering bias, specifically, the rapid acceptance of a proposition in the absence of much information (Garety & Freeman, 1999). It has also been suggested that this is consistent with the hypothesis that people with psychosis make less use of past information when forming judgments and are overinfluenced by current stimuli at the expense of context or previous learning (Gray, Feldon, Rawlins, Hemsley & Smith, 1991; Hemsley, 1988; Kapur, 2003). Therefore, this process also has a plausible relationship with belief flexibility by facilitating acceptance of the most salient current hypothesis and precluding reflection on past learning to consider whether the information fits with previous knowledge, with the result that the possibility that one might be mistaken is not considered. Although

10 382 GARETY ET AL. there have been some reports of an association of jumping to conclusions with lower IQ, this was not found in the present study, nor was IQ associated with any of the reasoning processes investigated. Perhaps most striking in our results is the divergence of cognitive and emotional processes. In our predictions for the study, we left open the possible relationships between reasoning processes and emotional states. We found that mood states did not show clear associations with these cognitive processes; in general, jumping to conclusions, extreme responding, and belief inflexibility did not appear to be influenced by levels of current emotional disturbance, at least as assessed by questionnaire measures of depression and anxiety. It would be instructive to examine this further by examining concurrent assessment and systematic manipulation of mood with, for example, experimental designs encompassing moodinduction techniques. The findings, therefore, do not at present suggest that emotional processes contribute substantially to these reasoning biases. However, this is not to suggest that emotion is irrelevant. Anxiety, but not depression, did show a clear contribution, independent of the reasoning processes under investigation, to severity of delusional conviction, and we have therefore represented this in our hypothesized framework (see Figure 1). There has been growing recognition of the importance of emotional processes in understanding psychosis, and it has been argued that depression and anxiety may contribute directly to both the development and the persistence of positive symptoms as well as being a consequence of the experience of psychosis (e.g., Birchwood, 2003; Garety et al., 2001). In a review, Freeman and Garety (2003), argued that anxiety is especially likely to contribute to delusional conviction; they reported that empirical studies of persecutory delusions have found that processes typically associated with anxiety and likely to maintain belief conviction are present in individuals with persecutory delusions. In this study, the preponderance of the delusions (over 80%) was persecutory in content. We suggest that anxiety makes an independent additional contribution to delusional conviction, through such emotion-associated processes. The study has a number of limitations. First, a cross-sectional study, as we have noted, is not ideal for testing causal relationships or showing direction of effects but can demonstrate associations. However, it has provided the basis for generating testable new hypotheses, which we plan to investigate longitudinally, in the context of our current trial of cognitive behavioral therapy. A second limitation is that the study, in selecting participants for a therapy trial, had a heterogeneous sample, with a wide range of different delusional subtypes. Many patients had more than one type of delusion (and other symptoms). Analyses by delusional subtype would be of interest in future research. Third, the trial recruitment may have introduced selection biases, particularly by recruiting only those willing to have psychological therapy. These findings may not be generalizable to an unselected group of people with delusions and recent relapses. Fourth, we focused in this study on selected reasoning processes, which we speculated would be especially relevant to delusional severity, persistence, and change. Inevitably, there are omissions. We did not include measures of attributional style or social cognition (e.g., Bentall, Kinderman, & Kaney, 1994; Frith & Corcoran, 1996; Garety & Freeman, 1999). Furthermore, we investigated only belief flexibility in relation to thinking about delusions and not more general cognitive flexibility, as measured by tests of executive functioning. It has been proposed that delusions are related to executive functioning (e.g., Benson & Struss, 1990), but empirical results have been inconclusive, (e.g., Basso, Nasrallah, Olson, & Bornstein, 1998; Mortimer et al., 1996). Finally, it is likely that social processes are likely to be important in belief change, such as the potential benefit of a supportive relationship for discussing ideas and experiences or, conversely, the negative effect of critical comments (Barrowclough et al., 2003; Bebbington & Kuipers, 1994; Garety et al., 2001). We have not investigated social factors in this particular study. This research has clinical implications for psychological therapy for psychosis. From the results of this study, we believe that reducing the conviction (and preoccupation and disruption) with which delusions are held, and protecting against future relapse, should be assisted by targeting the metacognitive processes of reflection on delusions, thus, eliciting ways of opening up new possibilities in thinking. This will involve attention to all-ornothing thinking, data gathering, and the careful consideration and generation of alternative explanations. Ideas such as this are implicit in manuals of cognitive therapy for psychosis, but the reasoning processes to target in therapy have not previously been clearly specified (e.g., Chadwick, Birchwood, & Trower, 1996; Fowler et al., 1995; Kingdon & Turkington, 1994). This study also suggests that direct work on anxiety, and the processes associated with it, might have a beneficial impact on delusional belief persistence and change. This would provide the clinician with another route to working with the delusional belief, drawing on the established methods of therapy for the anxiety disorder, but modified for work with people with psychosis (Freeman et al., 2001; Key, Craske, & Reno, 2003; Morrison, 1998). In conclusion, we have found evidence for associations in reasoning processes that are consistent with current models of delusions. Although the current data are cross-sectional, we offer a new framework for testing hypothesized relationships between these reasoning processes, anxiety, and the severity of delusional conviction and change. This has the potential for improving the effectiveness of cognitive therapy in resolving delusions and in protecting against relapse. We plan to test these hypotheses longitudinally in our current trial. References Ammons, R. B., & Ammons, C. H. (1962). Quick Test. Missoula, MT: Psychological Test Specialists. Baron, R., & Kenny, D. A. (1986). The moderator mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, Barrowclough, C., Tarrier, N., Humphreys, L., Ward, J., & Gregg, L., & Andrews, B. (2003). Self-esteem in schizophrenia: Relationships between self-evaluation, family attitudes, and symptomatology. Journal of Abnormal Psychology, 112, Basso, M. R., Nasrallah, H., Olson, S. C., & Bornstein, R. A. (1998). Neuropsychological correlates of negative, disorganized and psychotic symptoms in schizophrenia. Schizophrenia Research, 31, Bebbington, P. E., & Kuipers, E. (1994). The predictive utility of expressed emotion in schizophrenia: An aggregate analysis. Psychological Medicine, 24, Beck, A. T., Epstein, N., Brown, G., & Steer, R. (1988). An inventory for

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