Psychology Expert Needed

EBSCO Publishing Citation Format: APA (American Psychological Assoc.):

NOTE: Review the instructions at http://support.ebsco.com.library.capella.edu/help/?int=ehost&lang=&feature_id=APA and

make any necessary corrections before using. Pay special attention to personal names, capitalization, and dates.

Always consult your library resources for the exact formatting and punctuation guidelines.

References

Freeman, D., Pugh, K., Vorontsova, N., Antley, A., & Slater, M. (2010). Testing the continuum of delusional beliefs:

An experimental study using virtual reality. Journal of Abnormal Psychology, 119(1), 83–92. https://doi-

org.library.capella.edu/10.1037/a0017514

<!--Additional Information:

Persistent link to this record (Permalink): http://library.capella.edu/login?url=http://search.ebscohost.com

/login.aspx?direct=true&db=pdh&AN=2010-02209-024&site=ehost-live&scope=site

End of citation-->

Testing the Continuum of Delusional Beliefs: An Experimental Study Using Virtual Reality

By: Daniel Freeman

Department of Psychology, Institute of Psychiatry, King’s College London, England;

Katherine Pugh

Department of Psychology, Institute of Psychiatry, King’s College London, England

Natasha Vorontsova

Department of Psychology, Institute of Psychiatry, King’s College London, England

Angus Antley

Department of Computer Science, University College London, England

Mel Slater

Department of Computer Science, University College London, England;

Institució Catalana de Recerca i Estudis Avançats (ICREA), University of Barcelona, Barcelona, Spain

Acknowledgement: This work was funded by a Wellcome Trust Fellowship awarded to Daniel Freeman.

An emerging literature focuses on the clinically important experience of persecutory delusions (see

Freeman, Bentall, & Garety, 2008). Similar to the occurrence of emotional disorders, the delusions seen in

psychiatric services are likely to be at the severe end of a spectrum of such phenomena in the general

population (e.g., Chapman & Chapman, 1980; Claridge, 1997; van Os, Linscott, Myin-Germeys, Delespaul,

& Krabbendam, 2009); mistrust, suspiciousness, worries about threats from others, persecutory ideas, and

persecutory delusions may be related. However, there is an underlying difficulty to work in this area:

knowing that the ideation is unfounded. Such judgments can seem easier in clinical cases where the

content is (sometimes) implausible but they become much more difficult lower down the spectrum; for

instance, it is difficult to know whether fears about hostility from the neighbors are unrealistic or when

mistrust of work colleagues is excessive. In this unique article the experience of persecutory ideation was

validated in an experimental test.

The solution developed for determining the occurrence of unfounded persecutory ideation is exposure to

neutral virtual reality social environments (see review by Freeman, 2008). Virtual reality is an interactive

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

1 of 17 2/23/2019, 4:17 PM

computer-generated environment. Its attraction lies in the tendency for individuals to react in virtual reality

as they would in the real-life situation (Sanchez-Vives & Slater, 2005). Paranoid responses in the virtual

reality social environments must be unfounded, as the computer characters are programmed to behave

neutrally. No matter what a person does, the characters will remain neutral in their responses. It is

therefore an excellent laboratory test of paranoid ideation. In the first studies the occurrence of persecutory

ideation in virtual reality was established with students (Freeman et al., 2003, 2005), individuals at high risk

of psychosis (Valmaggia et al., 2007), and individuals with persecutory delusions (Fornells-Ambrojo et al.,

2008). The potential of the methodology to advance theoretical understanding was then demonstrated by

the identification in a large general population sample of psychological factors predictive of paranoia

(Freeman, Gittins, et al., 2008; Freeman, Pugh, et al., 2008). In this new study we set out to test three

groups varying along the paranoia continuum: individuals with low levels of paranoia, individuals with high

nonclinical paranoia, and individuals with persecutory delusions. It was predicted that individuals with

clinical delusions would have a higher level of persecutory ideation in virtual reality than individuals with

nonclinical paranoia, who, in turn, would be more suspicious than individuals low in paranoia. Potential

adverse effects (e.g., nausea) of spending time in virtual reality were also monitored for each group.

Epidemiological studies indicated the presence of a psychosis continuum by establishing that delusions

and hallucinations are not confined to psychotic groups (e.g., Eaton, Romanoski, Anthony, & Nestadt,

1991; van Os, Hanssen, Bijl, & Ravelli, 2000) and that the risk of clinical disorder is raised by the earlier

occurrence of low-level symptoms (Chapman, Chapman, Kwapil, Eckbald, & Zinser, 1994; Dominguez,

Wichers, Lieb, Wittchen, & van Os, 2009; Poulton et al., 2000). The continuum perspective also leads to an

important prediction: Low-level psychotic-like experiences and clinical symptoms should be

understandable in terms of similar factors. This has been termed etiological continuity (Myin-Germeys,

Krabbendam, & van Os, 2003). The epidemiological studies, consistent with this prediction, find that

clinical and nonclinical psychotic experiences have similar associations with demographic and social

variables such as age, sex, urbanicity, and cannabis use (see review by van Os et al., 2009). Researchers

in the Netherlands have also examined single psychological variables, such as theory of mind and

attributional style, across a hypothesized positive symptom continuum (e.g., Janssen et al., 2006;

Vermissen et al., 2008). Typically a dose–response relationship is shown between a putative causal factor

and position along the psychosis continuum. In the current study the focus is on paranoid experiences: A

cognitive model of persecutory delusions was used to test potential similarities in causal factors across the

paranoia spectrum.

The threat anticipation model (Freeman, 2007; Freeman & Freeman, 2008; Freeman, Garety, Kuipers,

Fowlers, & Bebbington, 2002) identifies multiple causes of paranoid thinking (see Figure 1), but the

following are particularly important: affective processes, especially anxiety, worry, and interpersonal

sensitivity; anomalous experiences, such as hallucinations and perceptual anomalies; reasoning biases,

particularly jumping to conclusions and belief inflexibility; and social factors, such as adverse events and

environments. It is hypothesized that at a time of stress the individual experiences a changed (and

confusing) anomalous internal state (e.g., perceptual disturbances occur). In essence, the person feels

different and this needs an explanation. A negative affective state makes a threatening interpretation likely:

Anxiety leads to the anticipation of danger; interpersonal sensitivity highlights the potential threat from

other people; and engagement in worry results in more negative, implausible ideas. Paranoid explanations

are particularly likely in the context of previous experience of adverse events such as victimization. The

fears reach a delusional level of conviction when reasoning biases, such as “jumping to conclusions,” are

present. In the current study each of these model components was examined in the groups assessed in

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

2 of 17 2/23/2019, 4:17 PM

virtual reality. It was predicted that dose–response relationships would be found across the three groups for

the presence of anomalous internal experiences, jumping to conclusions, anxiety, interpersonal sensitivity,

worry, and history of trauma. These putative causal factors would be increasingly present as paranoia

levels increase.

Figure 1. Outline of factors involved in persecutory delusion development.

Method

Participants

A low nonclinical paranoia group (n = 30), a high nonclinical paranoia group (n = 30), and a persecutory

delusions group (n = 30) were tested. All participants were required to be within the ages of 18 to 65 and to

be able to read and write in English. For the nonclinical groups there was a screening stage to identify

members of the general public high and low in paranoid thinking. Sixty thousand leaflets advertising the

study were distributed to local postcodes. The text of the leaflet headed “Virtual Reality Research at King’s

College London” was as follows:

Virtual reality is a computer-generated world that you can walk around in. In research taking place in

Denmark Hill, we are studying people’s reactions in virtual reality. We are looking for adult volunteers.

Participation in the research would take 90 minutes for which you would be paid £20. The research has

been approved by an ethics committee. If you are interested in taking part then find out more by

telephoning or e-mailing.

A total of 291 individuals made contact. Thirteen individuals could not be recontacted, 6 people changed

their minds about participating, 10 individuals were excluded for having a history of treatment for severe

mental illness (e.g., schizophrenia, bipolar disorder), and 4 other individuals did not meet entry criteria. The

258 eligible respondents were then asked to complete several questionnaires (so that the focus on

paranoia was not easily discernible). A total of 202 people returned fully completed questionnaires. The

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

3 of 17 2/23/2019, 4:17 PM

participants were selected on the basis of their level of persecutory thinking in the past month as assessed

by the 16-item Green et al. (2008) Paranoid Thought Scale (G-PTS)—Part B, which can have scores

ranging between 16 and 80. The 202 participants had a mean score of 20.1 (SD = 8.6, range 57, mode =

16, median = 17). Almost half of the sample (49%) scored at the bottom of this scale, indicating the

absence of persecutory thinking in the past month. The low paranoia group were required to score 16 on

this measure, indicating the absence of persecutory thinking. The high nonclinical paranoia group were

required to score 21 or above; this cutoff selects the top 20% of the study respondents on the measure

(and the top half of those endorsing paranoia items). We aimed to match the nonclinical groups with the

clinical group for age and sex. The clinical group were recruited from adult psychiatric services at the

South London and Maudsley National Health Service (NHS) Foundation Trust. The entry criteria were the

presence of a current persecutory delusion, which met the criteria of Freeman and Garety (2000), and a

clinical diagnosis of schizophrenia, schizoaffective disorder, or delusional disorder. The presence of a

persecutory delusion was established using the Present State Examination—10 (World Health

Organization, 1992). The case-note diagnoses of those recruited were schizophrenia (n = 24),

schizoaffective disorder (n = 4), and delusional disorder (n = 2). Antipsychotic medication data were

converted into chlorpromazine equivalents grouped into low (0–200 mg), medium (200–400 mg), and high

(≥400 mg); 1 person was not taking any medication, 11 were on a low dose, 14 were on a medium dose,

and 4 were on a high dose. As would be expected, the three groups clearly differed on the self-report

G-PTS (see Table 1). There were significant differences for ideas of reference, F(2, 97) = 77.39, p < .001,

and persecutory ideation, F(2, 87) = 194.33, p < .001. The groups significantly differed from each other on

each of the scales (p < .001).

Levels of Paranoia Across the Groups

Virtual Reality

The equipment, environment, and procedure were identical to that reported by Freeman, Pugh, et al.

(2008). The head-mounted display was a Virtual Research VR1280 (Virtual Research Systems, Aptos,

CA), which has a resolution of 1280 × 1024 pixels in each eye, a 60° diagonal field of view, and a refresh

rate of 60 Hz. The tracking system used was the InterSense IS900 (InterSense Inc., Billerica, MA). The

tracker uses a hybrid of inertial and ultrasonic sensors to determine the orientation and position of the user

during the simulation. The sensors were laid out in a ceiling constellation grid above the user. The tracker

data were accessed by a Virtual Reality Peripheral Network (VRPN) IS900 server (Taylor et al., 2001).

The virtual reality environment comprised a 4-min journey between two stops on a visual and auditory

simulation of a London Underground train which was populated by computer characters (see Figure 2).

The Distributed Immersive Virtual Environment (DIVE) software platform was used to create the overall

scenario (Frecon, Smith, Steed, Stenius, & Stahl, 2001). Both the train shell and the computer characters

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

4 of 17 2/23/2019, 4:17 PM

(avatars) were created using 3D Studio Max (Autodesk, San Rafael, CA). The avatar motions were made

using an optical motion capture system. Each avatar had its own background motion that repeated

throughout the scenario. Each avatar had one motion that approximated their breath and another motion

that randomized the direction of their gaze. In addition, several of the avatars responded to participants’

gaze by looking in their direction, which was enabled through head tracking of the participants. When

looked at, one particular avatar would occasionally smile at the user. The audio for the scene, comprising

background tube noise and low-level snippets of conversation, was rendered in stereo, without

spatialization, using a Creative sound card.

Figure 2. The virtual reality equipment (top panel) and scenario (bottom panel).

Measures

All measures were completed before entering the virtual reality environment. The exceptions were the

State Social Paranoia Scale (Freeman et al., 2007) and the Visual Analogue Scales, which assess

paranoid thinking in virtual reality, and were therefore administered directly after the headset was removed.

The Simulator Sickness Questionnaire (Kennedy, Lane, Berbaum, & Lilienthal, 1993) was repeated after

the virtual train ride.

Paranoia

Green et al. Paranoid Thought Scales (G-PTS; Green et al., 2008)

The G-PTS is a 32-item measure of paranoid thinking over the past month. Part A assesses ideas of

reference (e.g., “It was hard to stop thinking about people talking about me behind my back”) and Part B

assesses ideas of persecution (e.g., “I was convinced there was a conspiracy against me”). Each item is

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

5 of 17 2/23/2019, 4:17 PM

rated on a 5-point scale. Higher scores indicate greater levels of paranoid thinking. The internal

consistency of the scale and test–retest reliability are good. Convergent validity has been shown with the

Paranoia Scale (Fenigstein & Vanable, 1992).

State Social Paranoia Scale (SSPS; Freeman et al., 2007)

The SSPS was designed to assess paranoia in virtual reality. It has 10 persecutory items each rated on a

5-point scale (e.g., “Someone stared at me in order to upset me,” “Someone was trying to isolate me,”

“Someone was trying to make me distressed”). The SSPS has excellent internal reliability, adequate test–

retest reliability, convergent validity with both independent interviewer ratings and self-report measures,

and divergent validity in regards to measures of positive and neutral thinking. Higher scores on the SSPS

indicate greater levels of persecutory thinking. In order to reduce skew, the responses were grouped into

six ordinal categories (corresponding to scores of 10, 11–15, 16–20, 21–25, 26–30, and ≤30; as previously

carried out by Freeman, Pugh, et al., 2008).

Visual Analogue Rating Scales

Participants marked on separate 10-cm lines the degree to which the people on the virtual reality train

were hostile and whether they had felt paranoid on the train. Higher ratings indicate greater endorsement

of the characteristic.

Affective Processes

Depression Anxiety Stress Scales (DASS; Lovibond & Lovibond, 1995)

The DASS is a 42-item instrument with three subscales measuring current symptoms of depression,

anxiety, and stress. Each of the subscales consists of 14 items with a 0–3 scale (0 = did not apply to me at

all, 3 = applied to me very much). Higher scores indicate higher levels of emotional distress. The scale has

been shown to be reliable and valid in large clinical and nonclinical populations (Brown, Chorpita,

Korotitsch, & Barlow, 1997; Crawford & Henry, 2003; Page, Hooke, & Morrison, 2007). The Anxiety and

Depression subscales were used in the current study.

Penn State Worry Questionnaire (PSWQ; Meyer, Miller, Metzger, & Borkovec, 1990)

The PSWQ is the most established measure of trait worry style and has been used in nonclinical and

clinical populations (see review by Startup & Erickson, 2006). Each of the 16 items are rated on a 5-point

scale. Higher scores indicate a greater tendency to worry.

Interpersonal sensitivity measure (Boyce & Parker, 1989)

This is a 36-item scale designed to assess interpersonal sensitivity, defined as undue and excessive

awareness of, and sensitivity to, the behavior and feelings of others. Statements are rated on a 4-point

scale (1 = very unlike self, 2 = moderately unlike self, 3 = moderately like self, 4 = very like self). High

scores indicate greater interpersonal sensitivity. The psychometric properties of the scale have been tested

in nonclinical individuals, general practice attenders, and psychiatric patients.

Reasoning

Beads task (Garety et al., 2005)

Data gathering was assessed with a probabilistic reasoning task that has been extensively used with

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

6 of 17 2/23/2019, 4:17 PM

people who experience delusions (see reviews by Fine, Gardner, Craigie, & Gold, 2007; Freeman, 2007;

Garety & Freeman, 1999). Participants are asked to request as many pieces of evidence (colored beads)

as they would like before making a decision (from which of two hidden jars the beads are drawn). The two

jars have beads of two different colors (orange and black) in opposite ratios of 60:40. The key variable is

the number of beads requested before making a decision (and a lower number has been associated with

delusions).

Anomalous Experience

Cardiff Anomalous Perceptions Scale (Bell, Halligan, & Ellis, 2006)

This 32-item questionnaire assesses perceptual anomalies. It comprises nine subscales including sensory

intensity, distortion of the external world, sensory experience from an unexplained source, sensory

flooding, and hallucinations. A higher score represents the reporting of a greater number of perceptual

anomalies. The scale also has three factor scores. The first factor, Temporal Lobe Experience, contains

items such as “Do you ever see shapes, lights, or colors even though there is nothing really there?” The

second factor, Chemosensation, contains items such as “Do you ever notice that food or drink seems to

have an unusual taste?” The third factor, Clinical Psychosis, contains items such as “Do you ever hear

voices commenting on what you are thinking or doing?” The questionnaire was developed with clinical and

nonclinical groups and displayed good internal reliability, test–retest reliability, and construct and criterion

validity.

Social

Life Stressor Checklist (Wolfe & Kimerling, 1997)

The checklist asks respondents about the occurrence of a range of severe life events (e.g., serious

accident, physical attack, and sexual abuse). If the respondent reports the occurrence of an event,

subsequent questions ask when the event happened, whether the person thought at the time that serious

harm or death could result, and whether feelings of intense helplessness, fear, or horror occurred. Only

checklist items that referred to Criterion A events as defined in the Diagnostic and Statistical Manual of

Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000) were used. Only events that

reached the severity criterion related to posttraumatic stress disorder diagnosis were scored as occurring.

The total number of traumatic events was recorded. McHugo et al. (2005) reported adequate test–retest

reliability of the measure in a sample of 200 women.

Side Effects

Simulator Sickness Questionnaire (Kennedy et al., 1993)

Particularly in the past, virtual reality was known to cause side effects similar to motion sickness. Possible

causes may have been flicker, visual distortion, and the slow response of earlier systems to participants’

movements. The 16-item Simulator Sickness Questionnaire, derived from a large factor analysis, assesses

three symptom clusters: oculomotor (e.g., blurred vision), disorientation (e.g., dizziness), and nausea (e.g.,

vomiting). Each item is assessed on a 4-point scale (from none to very strong). The total score is weighted.

Higher scores indicate a higher level of symptoms.

Intellectual Functioning

Wechsler Test of Adult Reading (Wechsler, 2001)

The Wechsler Test of Adult Reading provides an estimate of premorbid intellectual functioning by asking

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

7 of 17 2/23/2019, 4:17 PM

participants to read a list of 50 words with irregular pronunciations.

Analysis

Analyses were carried out using SPSS Version 15.0 (SPSS, 2006) and Stata Version 10.0 (StataCorp,

2008). Group differences for demographic variables were tested using one-way analysis of variance

(ANOVA) and, when appropriate, least significant difference planned comparisons. Ordinal logistic

regressions (using the Stata ologit command) were used to test differences in paranoia in virtual reality.

The main procedure for testing overall group differences on the cognitive model measures was one-way

ANOVA; when significant these were then followed by least significant difference pairwise comparisons

(i.e., there was no correction applied for multiple testing). Covariates were not used (Miller & Chapman,

2001). There were no missing data for the main analyses.

Results

Basic demographic information for the three groups is displayed in Table 2. It can be seen that the groups

were matched for sex and marital status. There was a significant group difference in age, F(2, 87) = 4.97, p

= .009; the high nonclinical paranoia group was younger than the two other groups (p < .01). The clinical

group had fewer individuals of White ethnicity compared with the low paranoia group, χ (1) = 6.24, p =

.012, and the high nonclinical paranoia group, χ (1) = 3.59, p = .058. There was also a significant

difference in intellectual functioning, F(2, 84) = 4.31, p = .017; the clinical group scored significantly lower

than the low paranoia group (p = .005) and tended to score lower than the high nonclinical paranoia group

(p = .057). The scores on the intellectual functioning measure are consistent with the lower levels of

educational qualifications of the clinical group. The clinical group were more likely to be unemployed than

the low paranoia group, χ (1) = 12.38, p < .001, and the high nonclinical paranoia group, χ (1) = 19.81, p <

.001. For computer game playing the low paranoia group did not differ from either the clinical group, χ (1) =

0.64, p = .426, or the high nonclinical paranoia group, χ (1) = 1.11, p = .292.

2

2

2 2

2

2

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

8 of 17 2/23/2019, 4:17 PM

Demographic Information

Validation of the Groups

Group differences in persecutory ideation in virtual reality as assessed by the SSPS were tested using

ordinal logistic regression. The persecutory delusions group was 12.51 times more likely than the low

paranoia group to be in a higher category of persecutory ideation in virtual reality, p < .001, CI [4.20,

37.22]. This means, for instance, that the delusions group was approximately 12 times more likely to report

paranoid ideation in virtual reality. The high nonclinical paranoia group were 2.86 times more likely than the

low paranoia group to be in a higher category of persecutory ideation in virtual reality, p = .044, CI [1.03,

7.96]. This means, for instance, that the high nonclinical group were approximately 3 times more likely to

report paranoid ideation in virtual reality. When the ordinal regression for paranoia in virtual reality was

repeated with the high nonparanoia group as the reference category, the clinical paranoia group were 4.37

times more likely to be in a higher SSPS category, p = .003, CI [1.63, 11.71]. Therefore the groups

significantly differed from each other in levels of unfounded persecutory ideation.

Side Effects: Simulator Sickness

Total weighted simulator sickness scores indicated that there were no changes from pre- to postvirtual

reality for the persecutory delusions group (Time 1 M = 67.34, SD = 65.40; Time 2 M = 61.71, SD = 65.20),

the high nonclinical paranoia group (Time 1 M = 17.45, SD = 17.74; Time 2 M = 22.19, SD = 24.75), or the

low paranoia group (Time 1 M = 5.24, SD = 11.05; Time 2 M = 5.98, SD = 13.77). A mixed-design ANOVA,

with time as a within-subjects factor and group as a between-subjects factor, confirmed no significant main

effect of time, F(1, 87) < 0.01, p = .984, or significant interaction between time and group, F(2, 87) = 1.58,

p = .212. There was, however, a main effect of group, F(2, 87) = 18.93, p < .001. The persecutory

delusions group scored higher on the Simulator Sickness Questionnaire than both of the nonclinical groups

(p < .001). This higher reporting by the psychiatric group of symptoms such as headache, nausea, and

dizziness—which was independent of being in virtual reality—may reflect their generally higher levels of

affective disturbance or side effects of antipsychotic medication.

Cognitive Model Variables

Comparisons on the model measures, using one-way ANOVA and least significant difference testing, are

displayed in Table 3. Increasing levels of paranoia across the three groups are clearly associated with

increases in anxiety, depression, interpersonal sensitivity, anomalies of experience, and number of

traumatic events. (The difference in number of traumatic events between the low paranoia and high

nonclinical paranoia approached significance, p = .052.) Only reduced data gathering is specific to the

clinical group.

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

9 of 17 2/23/2019, 4:17 PM

Mean Scores and Group Comparisons for the Model Measures

The anomalous experiences questionnaire was examined further because of the variety in types of

perceptual anomalies. The three factor scores and two of the subscales (one concerning hallucinatory

experiences, the other concerning much milder anomalies) were analyzed. There is a clear increase in the

temporal lobe factor score across the groups (see Table 3). A similar pattern is found for the Clinical

Psychosis factor, which was dichotomized because of its skew. Ten (33%) individuals in the low paranoia

group, 20 (67%) individuals in the high nonclinical paranoia group, and 26 (87%) individuals in the clinical

group had at least one clinical psychosis anomaly. The high nonclinical paranoia group, χ (1) = 6.67, p =

.010, and the clinical group, χ (1) = 17.78, p < .001, were more likely to have clinical psychosis anomalies

than the low paranoia group. The high nonclinical paranoia group tended to have a lower likelihood to

experience such anomalies when compared with the clinical group, χ (1) = 3.35, p = .067. A similar pattern

of results was found for the subscale concerning sensory experience from an unexplained source. The

relationships for the Chemosensation factor and the Sensory Intensity subscale scores were slightly

different; the general pattern here was that the high nonclinical paranoia group had the highest scores,

which were similar to the clinical group but significantly different from the low paranoia group.

Finally, all the variables (anxiety, worry, interpersonal sensitivity, depression, total number of anomalous

experiences, beads drawn, number of traumatic events) were considered together in an ordinal logistic

regression with group as the dependent variable; the only significant predictors of the paranoia spectrum

were anxiety, odds ratio = 1.21, p = .008, CI [1.05, 1.40], and number of anomalous experiences, odds

ratio = 1.16, p = .006, CI [1.04, 1.29].

Discussion

Virtual reality proved to be a safe method of studying paranoia. It was used to identify three groups:

individuals with low levels of persecutory ideation, individuals with nonclinical persecutory ideation, and

individuals with clinical persecutory delusions. This provided the opportunity to examine the cognitive

correlates of persecutory delusions and the intriguing issue of whether the persecutory ideation common in

the general population is the counterpart of the clinical phenomena. This process was informed by theory:

The groups were assessed on measures related to a cognitive model of persecutory delusions. There was

a consistency in the results. Across the groups there was a step change in levels of anxiety, worry,

interpersonal sensitivity, depression, anomalies of experience, and trauma history. This pattern of results is

expected if nonclinical and clinical paranoia are related experiences.

The particular associations across the groups are consistent with the existing literature testing the cognitive

model. A number of studies have reported an association of paranoia with anxiety, worry, and interpersonal

sensitivity (e.g., Bassett, Sperlinger, & Freeman, 2009; Freeman & Garety, 1999; Martin & Penn, 2001;

Startup, Freeman, & Garety, 2007). Paranoia may even be a type of anxious fear (Freeman & Freeman,

2008). However, experimental research indicates that anomalies of experience differentiate persecutory

ideation from anxiety (Freeman et al., 2005; Freeman, Gittins, et al., 2008). In the current study anomalies

of experience were the second key factor associated with paranoia. It should be recognized, however, that

2

2

2

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

10 of 17 2/23/2019, 4:17 PM

perceptual anomalies vary greatly in severity. The milder anomalies, such as changes in levels of sensory

intensity (e.g., “Do you ever notice that sounds are much louder than they normally would be?”), were

associated with paranoia, but their presence did not distinguish between clinical and nonclinical instances.

In contrast, the presence of more severe anomalies, such as hallucinations, did discriminate between the

two paranoia groups. It is plausible that there is a qualitative shift in the types of anomalous experiences

associated with severe instances of paranoia.

Indeed, even though the study provides further support for the view that complete discontinuity between

clinical and nonclinical experiences is unlikely, the exact nature of a paranoia spectrum remains to be

established. Van Os and Verdoux (2003) described how the shape of a delusion continuum in the general

population would depend on the number of causal factors, the differences in their effect sizes, the degree

to which they interact, and their prevalence but argued that if there are a number of interacting factors then

it is unlikely that the distribution will be normal. Instead the distribution in the general population is likely to

be skewed, with many people not having any delusional experiences (i.e., quasicontinuous). Such

skewness in the occurrence of persecutory thinking was found in the current study’s screening sample. It is

of interest that in large epidemiological studies new statistical methods are now being applied to

understanding distributions of psychological problems (e.g., Krueger, Markon, Patrick, Benning, & Kramer,

2007). At an individual level there may be nonlinear shifts into clinical disorder. Detailed analysis of

potential differences in the content of clinical and nonclinical paranoia is also required. Specific aspects of

the content of persecutory thoughts (e.g., beliefs about the power of the persecutor) relate to emotional

distress but have not been examined across the spectrum (Freeman, Garety, & Kuipers, 2001). Put simply,

there may be differences between clinical and nonclinical groups other than in levels of belief conviction,

preoccupation, and distress.

One of the assessments did not show a dose–response relationship to level of paranoia; limited data

gathering in the reasoning task was apparent only in individuals with persecutory delusions. The data-

gathering bias (“jumping to conclusions”) has been found in studies with clinical and nonclinical groups to

be specifically associated with levels of delusional conviction (Freeman, Pugh, & Garety, 2008; Garety et

al., 2005). Delusional conviction was not the focus of the current study, but the nonclinical paranoia group

will have had higher levels of belief conviction than the low paranoia group on the screening measure of

persecutory ideation. Therefore a difference in data gathering would be expected, similar to that reported

by Freeman, Pugh, and Garety (2008). Van Dael et al. (2006) also did not find an association of the

reasoning bias with nonclinical delusional ideation. Given the occasional failure to replicate the jumping to

conclusions finding in nonclinical groups, it may well be that a range of more subtle and taxing reasoning

tasks are required to separate reliably nonclinical groups high and low in delusional ideation. Alternatively,

anxiety, worry, and anomalous experiences may be enough on their own to create moderately held

thoughts of a paranoid content, and the extreme data-gathering bias only operates to produce very high

degrees of belief conviction—an account which does not assume a simple correlation between the

continuum of paranoia and reasoning biases. In the high nonclinical paranoia group the absence of a hasty

reasoning style is likely to be protective against the development of severe paranoia by allowing doubt and

the consideration of alternative explanations for events.

The research study could have been strengthened in a number of ways. The recruitment of a nonclinical

group having comparable levels of paranoia to the delusions group would have provided a stronger test of

differences between clinical and nonclinical experiences. This would have entailed recruiting the top 5% of

scorers on the paranoia scale from the general population. Having four groups varying in paranoia levels

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

11 of 17 2/23/2019, 4:17 PM

(i.e., sampling the putative spectrum at more points) would have been informative. Improved matching on

age and intellectual functioning would have been desirable. It is also of note that the initial leafleting had a

very low response rate and therefore the representativeness of the participant sample is unknown. A

central weakness is that the data collected in the current study do not establish that the cognitive factors

are linked to the occurrence of persecutory ideation or rule out the possibility that they are secondary

consequences. Moving beyond a cross-sectional design in future research would be particularly valuable;

for instance, incorporating a longitudinal element could have addressed the issue of whether the factors

from the cognitive model maintain persecutory ideation across the spectrum. Manipulating key factors in

each of the groups would enable stronger causal inference (Kendler & Campbell, 2009; Shadish, Cook, &

Campbell, 2002).

What are the broader implications of the continuum approach for clinicians and researchers? More

information, written with less reference to diagnosis, is needed for those on the paranoia spectrum

(Freeman, Freeman, & Garety, 2008). It is often helpful for individuals with distressing persecutory

thoughts to know that their experiences are commoner than they had realized. The large affective

component to paranoid experience can be valuable to recognize. Clinicians should be aware that paranoia

is not inevitably a sign of severe mental illness; a debate has already begun concerning the introduction of

a dimensional approach to psychosis in the fifth edition of the Diagnostic and Statistical Manual of Mental

Disorders (Allardyce, Gaebel, Zielasek, & van Os, 2007; Dutta et al., 2007). Importantly for researchers,

the understanding of persecutory delusions can be informed by studying milder variants. Studying

nonclinical variants has the advantages of facilitating the recruitment of large sample sizes in order to test

complex models, obviating complicating issues such as the prescription of medication and appraisals of

illness, and enabling manipulationist experiments where putative causal factors are increased. The

continuum approach also implies that delusional ideas can often be understood in terms of normal

processes gone awry rather than substantial deficits. Overall a focus is needed on the individual

experiences, the symptoms, which have hitherto made up diagnoses such as schizophrenia.

References

Allardyce, J., Gaebel, W., Zielasek, J., & van Os, J. (2007). Deconstructing Psychosis Conference

February 2006: The validity of schizophrenia and alternative approaches to the classification of psychosis.

Schizophrenia Bulletin, 33, 863–867.

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.,

text rev.). Washington, DC: Author.

Bassett, M., Sperlinger, D., & Freeman, D. (2009). Fear of madness and persecutory delusions. Psychosis,

1, 39–50.

Bell, V., Halligan, P. W., & Ellis, H. D. (2006). The Cardiff Anomalous Perceptions Scale (CAPS).

Schizophrenia Bulletin, 32, 366–377.

Boyce, P., & Parker, G. (1989). Development of a scale to measure interpersonal sensitivity. Australian and

New Zealand Journal of Psychiatry, 23, 341–351.

Brown, T. A., Chorpita, B. F., Korotitsch, W., & Barlow, D. H. (1997). Psychometric properties of the

Depression Anxiety Stress Scales (DASS) in clinical samples. Behaviour Research and Therapy, 35,

79–89.

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

12 of 17 2/23/2019, 4:17 PM

Chapman, L. J., & Chapman, J. P. (1980). Scales for rating psychotic and psychotic-like experiences as

continua. Schizophrenia Bulletin, 6, 476–489.

Chapman, L. J., Chapman, J. P., Kwapil, T. R., Eckbald, M., & Zinser, M. C. (1994). Putatively psychosis-

prone subjects 10 years later. Journal of Abnormal Psychology, 103, 171–183.

Claridge, G. (1997). Schizotypy: Implications for illness and health. Oxford, England: Oxford University

Press.

Crawford, J. R., & Henry, J. D. (2003). The Depression Anxiety Stress Scales (DASS): Normative data and

latent structure in a large non-clinical sample. British Journal of Clinical Psychology, 42, 111–131.

Dominguez, M., Wichers, M., Lieb, R., Wittchen, H., & van Os, J. (2009). Evidence that onset of clinical

psychosis is an outcome of progressively more persistent subclinical psychotic experiences: An 8-year

cohort study. Schizophrenia Bulletin. Advance online publication. doi:10.1093/schbul/sbp022

Dutta, R., Greene, T., Addington, J., McKenzie, K., Phillips, M., & Murray, R. M. (2007). Biological, life

course, and cross-cultural studies all point toward the value of dimensional and developmental ratings in

the classification of psychosis. Schizophrenia Bulletin, 33, 868–876.

Eaton, W. W., Romanoski, A., Anthony, J. C., & Nestadt, G. (1991). Screening for psychosis in the general

population with a self-report interview. Journal of Nervous and Mental Disease, 179, 689–693.

Fenigstein, A., & Vanable, P. A. (1992). Paranoia and self-consciousness. Journal of Personality and Social

Psychology, 62, 129–138.

Fine, C., Gardner, M., Craigie, J., & Gold, I. (2007). Hopping, skipping or jumping to conclusions?

Clarifying the role of the JTC bias in delusions. Cognitive Neuropsychiatry, 12, 46–77.

Fornells-Ambrojo, M., Barker, C., Swapp, D., Slater, M., Antley, A., & Freeman, D. (2008). Virtual reality

and persecutory delusions: Safety and feasibility. Schizophrenia Research, 104, 228–236.

Frecon, E., Smith, G., Steed, A., Stenius, M., & Stahl, O. (2001). An overview of the COVEN platform.

Presence-Teleoperators and Virtual Environments, 10, 109–127.

Freeman, D. (2007). Suspicious minds: The psychology of persecutory delusions. Clinical Psychology

Review, 27, 425–457.

Freeman, D. (2008). Studying and treating schizophrenia using virtual reality (VR): A new paradigm.

Schizophrenia Bulletin, 34, 605–610.

Freeman, D., Bentall, R., & Garety, P. A. (Eds.). (2008). Persecutory delusions: Assessment, theory and

treatment. Oxford, England: Oxford University Press.

Freeman, D., & Freeman, J. (2008). Paranoia: The 21st century fear. Oxford, England: Oxford University

Press.

Freeman, D., Freeman, J., & Garety, P. (2008). Overcoming paranoid and suspicious thoughts. New York,

NY: Basic Books.

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

13 of 17 2/23/2019, 4:17 PM

Freeman, D., & Garety, P. A. (1999). Worry, worry processes and dimensions of delusions: An exploratory

investigation of a role for anxiety processes in the maintenance of delusional distress. Behavioural &

Cognitive Psychotherapy, 27, 47–62.

Freeman, D., & Garety, P. A. (2000). Comments on the content of persecutory delusions: Does the

definition need clarification?British Journal of Clinical Psychology, 39, 407–414.

Freeman, D., Garety, P. A., Bebbington, P., Slater, M., Kuipers, E., Fowler, D., . . . & Dunn, G. (2005). The

psychology of persecutory ideation: II. A virtual reality experimental study. Journal of Nervous and Mental

Disease, 193, 309–315.

Freeman, D., Garety, P. A., & Kuipers, E. (2001). Persecutory delusions: Developing the understanding of

belief maintenance and emotional distress. Psychological Medicine, 31, 1293–1306.

Freeman, D., Garety, P. A., Kuipers, E., Fowler, D., & Bebbington, P. E. (2002). A cognitive model of

persecutory delusions. British Journal of Clinical Psychology, 41, 331–347.

Freeman, D., Gittins, M., Pugh, K., Antley, A., Slater, M., & Dunn, G. (2008). What makes one person

paranoid and another person anxious? The differential prediction of social anxiety and persecutory ideation

in an experimental situation. Psychological Medicine, 38, 1121–1132.

Freeman, D., Pugh, K., Antley, A., Slater, M., Bebbington, P., Gittins, M., . . . & Garety, P. A. (2008). A

virtual reality study of paranoid thinking in the general population. British Journal of Psychiatry, 192,

258–263.

Freeman, D., Pugh, K., & Garety, P. (2008). Jumping to conclusions and paranoid ideation in the general

population. Schizophrenia Research, 102, 254–260.

Freeman, D., Pugh, K., Green, C., Valmaggia, L., Dunn, G., & Garety, P. (2007). A measure of state

persecutory ideation for experimental studies. Journal of Nervous and Mental Disease, 195, 781–784.

Freeman, D., Slater, M., Bebbington, P. E., Garety, P. A., Kuipers, E., Fowler, D., . . . & Vinayagamoorthy,

V. (2003). Can virtual reality be used to investigate persecutory ideation?Journal of Nervous and Mental

Disease, 191, 509–514.

Garety, P. A., & Freeman, D. (1999). Cognitive approaches to delusions: A critical review of theories and

evidence. British Journal of Clinical Psychology, 38, 113–154.

Garety, P. A., Freeman, D., Jolley, S., Dunn, G., Bebbington, P. E., Fowler, D., . . . & Dudley, R. (2005).

Reasoning, emotions, and delusional conviction in psychosis. Journal of Abnormal Psychology, 114,

373–384.

Green, C., Freeman, D., Kuipers, E., Bebbington, P., Fowler, D., Dunn, G., & Garety, P. A. (2008).

Measuring ideas of persecution and reference: The Green et al. Paranoid Thought Scales (G-PTS).

Psychological Medicine, 38, 101–111.

Janssen, I., Versmissen, D., Campo, J. A., Myin-Germeys, I., van Os, J., & Krabbendam, L. (2006).

Attribution style and psychosis. Psychological Medicine, 36, 771–778.

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

14 of 17 2/23/2019, 4:17 PM

Kendler, K. S., & Campbell, J. (2009). Interventionist causal models in psychiatry. Psychological Medicine,

39, 881–887.

Kennedy, R. S., Lane, N. E., Berbaum, K. S., & Lilienthal, M. G. (1993). Simulator Sickness Questionnaire:

An enhanced method for quantifying simulator sickness. International Journal of Aviation Psychology, 3,

203–220.

Krueger, R. F., Markon, K. E., Patrick, C. J., Benning, S. D., & Kramer, M. D. (2007). Linking antisocial

behavior, substance use, and personality: An integrative quantitative model of the adult externalizing

spectrum. Journal of Abnormal Psychology, 116, 645–666.

Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states: Comparison of the

Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behaviour

Research and Therapy, 33, 335–343.

Martin, J. A., & Penn, D. L. (2001). Brief report: Social cognition and subclinical paranoid ideation. British

Journal of Clinical Psychology, 40, 261–265.

McHugo, G. J., Caspi, Y., Kammerer, N., Mazelis, R., Jackson, E. W., Russell, L., . . . & Kimerling, R.

(2005). The assessment of trauma history in women with co-occurring substance abuse and mental

disorders and a history of interpersonal violence. Journal of Behavioural Health Services and Research,

32, 113–127.

Meyer, T. J., Miller, M. L., Metzger, R. L., & Borkovec, T. D. (1990). Development and validation of the Penn

State Worry Questionnaire. Behaviour Research & Therapy, 28, 487–495.

Miller, G. A., & Chapman, J. P. (2001). Misunderstanding analysis of covariance. Journal of Abnormal

Psychology, 110, 40–48.

Myin-Germeys, I., Krabbendam, L., & van Os, J. (2003). Continuity of psychotic symptoms in the

community. Current Opinion in Psychiatry, 16, 443–449.

Page, A. C., Hooke, G. R., & Morrison, D. L. (2007). Psychometric properties of the Depression Anxiety

Stress Scales (DASS) in depressed clinical samples. British Journal of Clinical Psychology, 46, 283–297.

Poulton, R., Caspi, A., Moffitt, T. E., Cannon, M., Murray, R., & Harrington, H. (2000). Children’s self-

reported psychotic symptoms and adult schizophreniform disorder. Archives of General Psychiatry, 57,

1053–1058.

Sanchez-Vives, M. V., & Slater, M. (2005). From presence to consciousness through virtual reality. Nature

Reviews Neuroscience, 6, 332–339.

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for

generalized causal inference. Boston, MA: Houghton Mifflin.

SPSS. (2006). SPSS base 15.0 user’s guide. Chicago, IL: Author.

Startup, H. M., & Erickson, T. M. (2006). The Penn State Worry Questionnaire. In G.Davey & A.Wells

(Eds.), Worry and its psychological disorders (pp. 101–120). Chichester, England: Wiley.

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

15 of 17 2/23/2019, 4:17 PM

Startup, H., Freeman, D., & Garety, P. A. (2007). Persecutory delusions and catastrophic worry in

psychosis: Developing the understanding of delusion distress and persistence. Behaviour Research and

Therapy, 45, 523–537.

StataCorp. (2008). Stata statistical software: Release 10.0. College Station, TX: Stata Corporation.

Taylor, R. M., II, Hudson, T. C., Seeger, A., Weber, H., Juliano, J., & Helser, A. T. (2001). VRPN: A device-

independent, network-transparent VR peripheral system. In Proceedings of the ACM Symposium on Virtual

Reality Software and Technology (pp. 55–61). New York, New York: ACM. doi:10.1145/505008.505019

Valmaggia, L., Freeman, D., Green, C., Garety, P., Swapp, D., Antley, A., . . . & McGuire, P. (2007). Virtual

reality and paranoid ideations in people with an ’at risk mental state’ for psychosis. British Journal of

Psychiatry, 191, s63–s68.

Van Dael, F., Versmissen, D., Janssen, I., Myin-Germeys, I., van Os, J., & Krabbendam, L. (2006). Data

gathering: Biased in psychosis?Schizophrenia Bulletin, 32, 341–351.

van Os, J., Hanssen, M., Bijl, R. V., & Ravelli, A. (2000). Strauss (1969) revisited: A psychosis continuum

in the general population. Schizophrenia Research, 45, 11–20.

van Os, J., Linscott, R. J., Myin-Germeys, I., Delespaul, P., & Krabbendam, L. (2009). A systematic review

and meta-analysis of the psychosis continuum. Psychological Medicine, 39, 179–195.

van Os, J., & Verdoux, H. (2003). Diagnosis and classification of schizophrenia: Categories versus

dimensions, distributions versus disease. In R. M.Murray, P. B.Jones, E.Susser, J.van Os, & M.Cannon

(Eds.), The epidemiology of schizophrenia (pp. 364–410). Cambridge, England: Cambridge University

Press.

Vermissen, D., Janssen, I., Myin-Germeys, I., Mengelers, R., Campo, J. A., van Os, J., & Krabbendam, L.

(2008). Evidence for a relationship between mentalising deficits and paranoia over the psychosis

continuum. Schizophrenia Research, 99, 103–110.

Wechsler, D. (2001). Wechsler Test of Adult Reading: Manual. San Antonio, TX: Harcourt Assessment.

Wolfe, J., & Kimerling, R. (1997). Gender issues in the assessment of posttraumatic stress disorder. In

J.Wilson & T.Keane (Eds.), Assessing psychological trauma and PTSD (pp. 192–238). New York, NY:

Guilford Press.

World Health Organization. (1992). SCAN: Schedules for Clinical Assessment in Neuropsychiatry. Geneva,

Switzerland: Author.

Submitted: February 16, 2009 Revised: July 23, 2009 Accepted: July 28, 2009

This publication is protected by US and international copyright laws and its content may not be copied

without the copyright holders express written permission except for the print or download capabilities of the

retrieval software used for access. This content is intended solely for the use of the individual user.

Source: Journal of Abnormal Psychology. Vol. 119. (1), Feb, 2010 pp. 83-92)

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

16 of 17 2/23/2019, 4:17 PM

Accession Number: 2010-02209-024

Digital Object Identifier: 10.1037/a0017514

EBSCOhost http://web.a.ebscohost.com.library.capella.edu/ehost/delivery?sid=a1494...

17 of 17 2/23/2019, 4:17 PM