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Automated virtual reality therapies are being developed to increase access to psychological interventions. We assessed the experience with one such therapy of patients diagnosed with psychosis, including satisfaction, side effects, and positive experiences of access to the technology. We tested whether side effects affected therapy.
Methods
In a clinical trial 122 patients diagnosed with psychosis completed baseline measures of psychiatric symptoms, received gameChange VR therapy, and then completed a satisfaction questionnaire, the Oxford-VR Side Effects Checklist, and outcome measures.
Results
79 (65.8%) patients were very satisfied with VR therapy, 37 (30.8%) were mostly satisfied, 3 (2.5%) were indifferent/mildly dissatisfied, and 1 (0.8%) person was quite dissatisfied. The most common side effects were: difficulties concentrating because of thinking about what might be happening in the room (n = 17, 14.2%); lasting headache (n = 10, 8.3%); and the headset causing feelings of panic (n = 9, 7.4%). Side effects formed three factors: difficulties concentrating when wearing a headset, feelings of panic using VR, and worries following VR. The occurrence of side effects was not associated with number of VR sessions, therapy outcomes, or psychiatric symptoms. Difficulties concentrating in VR were associated with slightly lower satisfaction. VR therapy provision and engagement made patients feel: proud (n = 99, 81.8%); valued (n = 97, 80.2%); and optimistic (n = 96, 79.3%).
Conclusions
Patients with psychosis were generally very positive towards the VR therapy, valued having the opportunity to try the technology, and experienced few adverse effects. Side effects did not significantly impact VR therapy. Patient experience of VR is likely to facilitate widespread adoption.
Many patients with mental health disorders become increasingly isolated at home due to anxiety about going outside. A cognitive perspective on this difficulty is that threat cognitions lead to the safety-seeking behavioural response of agoraphobic avoidance.
Aims:
We sought to develop a brief questionnaire, suitable for research and clinical practice, to assess a wide range of cognitions likely to lead to agoraphobic avoidance. We also included two additional subscales assessing two types of safety-seeking defensive responses: anxious avoidance and within-situation safety behaviours.
Method:
198 patients with psychosis and agoraphobic avoidance and 1947 non-clinical individuals completed the item pool and measures of agoraphobic avoidance, generalised anxiety, social anxiety, depression and paranoia. Factor analyses were used to derive the Oxford Cognitions and Defences Questionnaire (O-CDQ).
Results:
The O-CDQ consists of three subscales: threat cognitions (14 items), anxious avoidance (11 items), and within-situation safety behaviours (8 items). Separate confirmatory factor analyses demonstrated a good model fit for all subscales. The cognitions subscale was significantly associated with agoraphobic avoidance (r = .672, p < .001), social anxiety (r = .617, p < .001), generalized anxiety (r = .746, p < .001), depression (r = .619, p < .001) and paranoia (r = .655, p < .001). Additionally, both the O-CDQ avoidance (r = .867, p < .001) and within-situation safety behaviours (r = .757, p < .001) subscales were highly correlated with agoraphobic avoidance. The O-CDQ demonstrated excellent internal consistency (cognitions Cronbach’s alpha = .93, avoidance Cronbach’s alpha = .94, within-situation Cronbach’s alpha = .93) and test–re-test reliability (cognitions ICC = 0.88, avoidance ICC = 0.92, within-situation ICC = 0.89).
Conclusions:
The O-CDQ, consisting of three separate scales, has excellent psychometric properties and may prove a helpful tool for understanding agoraphobic avoidance across mental health disorders.
Agoraphobic avoidance of everyday situations is a common feature in many mental health disorders. Avoidance can be due to a variety of fears, including concerns about negative social evaluation, panicking, and harm from others. The result is inactivity and isolation. Behavioural avoidance tasks (BATs) provide an objective assessment of avoidance and in situ anxiety but are challenging to administer and lack standardisation. Our aim was to draw on the principles of BATs to develop a self-report measure of agoraphobia symptoms.
Method
The scale was developed with 194 patients with agoraphobia in the context of psychosis, 427 individuals in the general population with high levels of agoraphobia, and 1094 individuals with low levels of agoraphobia. Factor analysis, item response theory, and receiver operating characteristic analyses were used. Validity was assessed against a BAT, actigraphy data, and an existing agoraphobia measure. Test–retest reliability was assessed with 264 participants.
Results
An eight-item questionnaire with avoidance and distress response scales was developed. The avoidance and distress scales each had an excellent model fit and reliably assessed agoraphobic symptoms across the severity spectrum. All items were highly discriminative (avoidance: a = 1.24–5.43; distress: a = 1.60–5.48), indicating that small increases in agoraphobic symptoms led to a high probability of item endorsement. The scale demonstrated good internal reliability, test–retest reliability, and validity.
Conclusions
The Oxford Agoraphobic Avoidance Scale has excellent psychometric properties. Clinical cut-offs and score ranges are provided. This precise assessment tool may help focus attention on the clinically important problem of agoraphobic avoidance.
When vaccination depends on injection, it is plausible that the blood-injection-injury cluster of fears may contribute to hesitancy. Our primary aim was to estimate in the UK adult population the proportion of COVID-19 vaccine hesitancy explained by blood-injection-injury fears.
Methods
In total, 15 014 UK adults, quota sampled to match the population for age, gender, ethnicity, income and region, took part (19 January–5 February 2021) in a non-probability online survey. The Oxford COVID-19 Vaccine Hesitancy Scale assessed intent to be vaccinated. Two scales (Specific Phobia Scale-blood-injection-injury phobia and Medical Fear Survey–injections and blood subscale) assessed blood-injection-injury fears. Four items from these scales were used to create a factor score specifically for injection fears.
Results
In total, 3927 (26.2%) screened positive for blood-injection-injury phobia. Individuals screening positive (22.0%) were more likely to report COVID-19 vaccine hesitancy compared to individuals screening negative (11.5%), odds ratio = 2.18, 95% confidence interval (CI) 1.97–2.40, p < 0.001. The population attributable fraction (PAF) indicated that if blood-injection-injury phobia were absent then this may prevent 11.5% of all instances of vaccine hesitancy, AF = 0.11; 95% CI 0.09–0.14, p < 0.001. COVID-19 vaccine hesitancy was associated with higher scores on the Specific Phobia Scale, r = 0.22, p < 0.001, Medical Fear Survey, r = 0.23, p = <0.001 and injection fears, r = 0.25, p < 0.001. Injection fears were higher in youth and in Black and Asian ethnic groups, and explained a small degree of why vaccine hesitancy is higher in these groups.
Conclusions
Across the adult population, blood-injection-injury fears may explain approximately 10% of cases of COVID-19 vaccine hesitancy. Addressing such fears will likely improve the effectiveness of vaccination programmes.
Cognitive therapies are developed on the principle that specific cognitive appraisals are key determinants in the development and maintenance of mental health disorders. It is likely that particular appraisals of the coronavirus pandemic will have explanatory power for subsequent mental health outcomes in the general public. To enable testing of this hypothesis we developed a questionnaire assessing coronavirus-related cognitions.
Methods
12 285 participants completed online a 46-item pool of cognitions about coronavirus and six measures of different mental health problems. The sample was randomly split into derivation and validation samples. Exploratory factor analyses determined the factor structure, selection of items, and model fit in the derivation sample. Confirmatory factor analysis (CFA) then tested this model in the validation sample. Associations of the questionnaire with mental health outcomes were examined.
Results
The 26-item, seven-factor, Oxford Psychological Investigation of Coronavirus Questionnaire [TOPIC-Q] was developed. CFA demonstrated a good model fit (χ2 = 2108.43, df = 278, p < 0.001, comparative fit index (CFI) = 0.950, Tucker−Lewis index (TLI) = 0.942, root mean square error of approximation (RMSEA) = 0.033, standardized root mean square residual (SRMR) = 0.038). The factors were: cognitions about (1) safety and vulnerability, (2) negative long-term impact, (3) having the virus, (4) spreading the virus, (5) social judgment, (6) negative self, and (7) being targeted. The questionnaire explained significant variance in depression (45.8%), social anxiety (37.3%), agoraphobia (23.2%), paranoia (27.3%), post-traumatic stress disorder (57.1%), and panic disorder (31.4%). Cognitions about negative long-term impact had the greatest explanatory power across disorders.
Conclusions
TOPIC-Q provides a method to assess appraisals of the pandemic, which is likely to prove helpful both in longitudinal studies assessing mental health outcomes and in delivery of psychological therapy.
Our aim was to estimate provisional willingness to receive a coronavirus 2019 (COVID-19) vaccine, identify predictive socio-demographic factors, and, principally, determine potential causes in order to guide information provision.
Methods
A non-probability online survey was conducted (24th September−17th October 2020) with 5,114 UK adults, quota sampled to match the population for age, gender, ethnicity, income, and region. The Oxford COVID-19 vaccine hesitancy scale assessed intent to take an approved vaccine. Structural equation modelling estimated explanatory factor relationships.
Results
71.7% (n=3,667) were willing to be vaccinated, 16.6% (n=849) were very unsure, and 11.7% (n=598) were strongly hesitant. An excellent model fit (RMSEA=0.05/CFI=0.97/TLI=0.97), explaining 86% of variance in hesitancy, was provided by beliefs about the collective importance, efficacy, side-effects, and speed of development of a COVID-19 vaccine. A second model, with reasonable fit (RMSEA=0.03/CFI=0.93/TLI=0.92), explaining 32% of variance, highlighted two higher-order explanatory factors: ‘excessive mistrust’ (r=0.51), including conspiracy beliefs, negative views of doctors, and need for chaos, and ‘positive healthcare experiences’ (r=−0.48), including supportive doctor interactions and good NHS care. Hesitancy was associated with younger age, female gender, lower income, and ethnicity, but socio-demographic information explained little variance (9.8%). Hesitancy was associated with lower adherence to social distancing guidelines.
Conclusions
COVID-19 vaccine hesitancy is relatively evenly spread across the population. Willingness to take a vaccine is closely bound to recognition of the collective importance. Vaccine public information that highlights prosocial benefits may be especially effective. Factors such as conspiracy beliefs that foster mistrust and erode social cohesion will lower vaccine up-take.
An invisible threat has visibly altered the world. Governments and key institutions have had to implement decisive responses to the danger posed by the coronavirus pandemic. Imposed change will increase the likelihood that alternative explanations take hold. In a proportion of the general population there may be strong scepticism, fear of being misled, and false conspiracy theories. Our objectives were to estimate the prevalence of conspiracy thinking about the pandemic and test associations with reduced adherence to government guidelines.
Methods
A non-probability online survey with 2501 adults in England, quota sampled to match the population for age, gender, income, and region.
Results
Approximately 50% of this population showed little evidence of conspiracy thinking, 25% showed a degree of endorsement, 15% showed a consistent pattern of endorsement, and 10% had very high levels of endorsement. Higher levels of coronavirus conspiracy thinking were associated with less adherence to all government guidelines and less willingness to take diagnostic or antibody tests or to be vaccinated. Such ideas were also associated with paranoia, general vaccination conspiracy beliefs, climate change conspiracy belief, a conspiracy mentality, and distrust in institutions and professions. Holding coronavirus conspiracy beliefs was also associated with being more likely to share opinions.
Conclusions
In England there is appreciable endorsement of conspiracy beliefs about coronavirus. Such ideas do not appear confined to the fringes. The conspiracy beliefs connect to other forms of mistrust and are associated with less compliance with government guidelines and greater unwillingness to take up future tests and treatment.
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