Social anxiety and paranoia are connected by a shared suspicion framework. Based on cognitive-behavioural approaches, there is evidence for treating social anxiety and psychosis. However, mechanisms underlying the relationship between social anxiety and paranoia remain unclear.

To investigate mediators between social anxiety and paranoia in schizophrenia such as negative social appraisals (i.e. stigma or shame; Hypothesis 1), and safety behaviours (i.e. anxious avoidance or in situ safety behaviours; Hypothesis 2).

A cross-sectional study was conducted among Asian out-patients with schizophrenia (January–April 2020). Data on social anxiety, paranoia, depression, shame, stigma, anxious avoidance, and in situ behaviours were collected. Associations between social anxiety and paranoia were investigated using linear regressions. Mediation analysis via 10,000 bias-corrected bootstrap samples with 95% confidence intervals (CI) was used to test the indirect effects (ab) of mediators.

Participants (n=113, 59.3% male) with a mean age of 44.2 years were recruited. A linear relationship between social anxiety and paranoia was found. In multiple mediation analyses (co-varying for depression), stigma and shame (Hypothesis 1) did not show any significant indirect effects with ab=.004 (95%CI=–.013, .031) and –.003 (–.023, .017), respectively, whereas in situ behaviours (Hypothesis 2) showed a significant effect with ab=.110 (.038, .201) through the social anxiety–paranoia relationship.

Social anxiety and paranoia are positively correlated. In situ safety behaviours fully mediated the social anxiety and paranoia relationship. Targeted interventions focusing on safety behaviours could help reduce paranoia in psychosis. Symptom severity should be measured to help characterise the participants’ characteristics.

Forensic patients with psychosis often engage in violent behaviour. There has been significant progress in understanding risk factors for violence, but identification of causal mechanisms of violence is limited.

To develop a testable psychological framework explaining violence in psychosis – grounded in patient experience – to guide targeted treatment development.

We conducted in-depth interviews with 20 patients with psychosis using forensic psychiatric services across three regions in England. Interviews were analysed using reflexive thematic analysis. People with lived experience contributed to the analysis.

Analysis of interviews identified several psychological processes involved in the occurrence of violence. Violence was the dominant response mode to difficulties that was both habitual and underpinned by rules that engaged and justified an attack. Violence was triggered by a trio of sensitivities to other people: sensitivity to physical threat, from which violence protected; sensitivity to social disrespect, by which violence increased status; and sensitivity to unfairness, by which violence delivered revenge. Violence was an attempt to regulate difficult internal states: intense emotions were released through aggression and violence was an attempt to escape being overwhelmed by voices, visions or paranoia. There were different patterns of emphasis across these processes when explaining an individual participant's offending behaviour.

The seven-factor model of violence derived from our analysis of patient accounts highlights multiple modifiable psychological processes that can plausibly lead to violence. The model can guide the research and development of targeted treatments to reduce violence by individuals with psychosis.

Healthcare workers (HCWs) have faced considerable pressures during the COVID-19 pandemic. For some, this has resulted in mental health distress and disorder. Although interventions have sought to support HCWs, few have been evaluated.

We aimed to determine the effectiveness of the ‘Foundations’ application (app) on general (non-psychotic) psychiatric morbidity.

We conducted a multicentre randomised controlled trial of HCWs at 16 NHS trusts (trial registration number: EudraCT: 2021-001279-18). Participants were randomly assigned to the app or wait-list control group. Measures were assessed at baseline, after 4 and 8 weeks. The primary outcome was general psychiatric morbidity (using the General Health Questionnaire). Secondary outcomes included: well-being; presenteeism; anxiety; depression and insomnia. The primary analysis used mixed-effects multivariable regression, presented as adjusted mean differences (aMD).

Between 22 March and 3 June 2021, 1002 participants were randomised (500:502), and 894 (89.2%) followed-up. The sample was predominately women (754/894, 84.3%), with a mean age of 44⋅3 years (interquartile range (IQR) 34–53). Participants randomised to the app had a reduction in psychiatric morbidity symptoms (aMD = −1.39, 95% CI −2.05 to −0.74), improvement in well-being (aMD = 0⋅54, 95% CI 0⋅20 to 0⋅89) and reduction in insomnia (adjusted odds ratio (aOR) = 0⋅36, 95% CI 0⋅21 to 0⋅60). No other significant findings were found, or adverse events reported.

The app had an effect in reducing psychiatric morbidity symptoms in a sample of HCWs. Given it is scalable with no adverse effects, the app may be used as part of an organisation's tiered staff support package. Further evidence is needed on long-term effectiveness and cost-effectiveness.

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.

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.

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%).

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.

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.

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).

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).

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.

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.

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.

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.

In the UK, acute mental healthcare is provided by in-patient wards and crisis resolution teams. Readmission to acute care following discharge is common. Acute day units (ADUs) are also provided in some areas.

To assess predictors of readmission to acute mental healthcare following discharge in England, including availability of ADUs.

We enrolled a national cohort of adults discharged from acute mental healthcare in the English National Health Service (NHS) between 2013 and 2015, determined the risk of readmission to either in-patient or crisis teams, and used multivariable, multilevel logistic models to evaluate predictors of readmission.

Of a total of 231 998 eligible individuals discharged from acute mental healthcare, 49 547 (21.4%) were readmitted within 6 months, with a median time to readmission of 34 days (interquartile range 10–88 days). Most variation in readmission (98%) was attributable to individual patient-level rather than provider (trust)-level effects (2.0%). Risk of readmission was not associated with local availability of ADUs (adjusted odds ratio 0.96, 95% CI 0.80–1.15). Statistically significant elevated risks were identified for participants who were female, older, single, from Black or mixed ethnic groups, or from more deprived areas. Clinical predictors included shorter index admission, psychosis and being an in-patient at baseline.

Relapse and readmission to acute mental healthcare are common following discharge and occur early. Readmission was not influenced significantly by trust-level variables including availability of ADUs. More support for relapse prevention and symptom management may be required following discharge from acute mental healthcare.

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.

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.

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.

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.

For people in mental health crisis, acute day units (ADUs) provide daily structured sessions and peer support in non-residential settings, often as an addition or alternative to crisis resolution teams (CRTs). There is little recent evidence about outcomes for those using ADUs, particularly compared with those receiving CRT care alone.

We aimed to investigate readmission rates, satisfaction and well-being outcomes for people using ADUs and CRTs.

We conducted a cohort study comparing readmission to acute mental healthcare during a 6-month period for ADU and CRT participants. Secondary outcomes included satisfaction (Client Satisfaction Questionnaire), well-being (Short Warwick–Edinburgh Mental Well-being Scale) and depression (Center for Epidemiologic Studies Depression Scale).

We recruited 744 participants (ADU: n = 431, 58%; CRT: n = 312, 42%) across four National Health Service trusts/health regions. There was no statistically significant overall difference in readmissions: 21% of ADU participants and 23% of CRT participants were readmitted over 6 months (adjusted hazard ratio 0.78, 95% CI 0.54–1.14). However, readmission results varied substantially by setting. At follow-up, ADU participants had significantly higher Client Satisfaction Questionnaire scores (2.5, 95% CI 1.4–3.5, P < 0.001) and well-being scores (1.3, 95% CI 0.4–2.1, P = 0.004), and lower depression scores (−1.7, 95% CI −2.7 to −0.8, P < 0.001), than CRT participants.

Patients who accessed ADUs demonstrated better outcomes for satisfaction, well-being and depression, and no significant differences in risk of readmission, compared with those who only used CRTs. Given the positive outcomes for patients, and the fact that ADUs are inconsistently provided in the National Health Service, their value and place in the acute care pathway needs further consideration and research.

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.

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.

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.

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.

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.

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.

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.

A non-probability online survey with 2501 adults in England, quota sampled to match the population for age, gender, income, and region.

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.

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.

Crisis resolution teams (CRTs) offer brief, intensive home treatment for people experiencing mental health crisis. CRT implementation is highly variable; positive trial outcomes have not been reproduced in scaled-up CRT care.

To evaluate a 1-year programme to improve CRTs’ model fidelity in a non-masked, cluster-randomised trial (part of the Crisis team Optimisation and RElapse prevention (CORE) research programme, trial registration number: ISRCTN47185233).

Fifteen CRTs in England received an intervention, informed by the US Implementing Evidence-Based Practice project, involving support from a CRT facilitator, online implementation resources and regular team fidelity reviews. Ten control CRTs received no additional support. The primary outcome was patient satisfaction, measured by the Client Satisfaction Questionnaire (CSQ-8), completed by 15 patients per team at CRT discharge (n = 375). Secondary outcomes: CRT model fidelity, continuity of care, staff well-being, in-patient admissions and bed use and CRT readmissions were also evaluated.

All CRTs were retained in the trial. Median follow-up CSQ-8 score was 28 in each group: the adjusted average in the intervention group was higher than in the control group by 0.97 (95% CI −1.02 to 2.97) but this was not significant (P = 0.34). There were fewer in-patient admissions, lower in-patient bed use and better staff psychological health in intervention teams. Model fidelity rose in most intervention teams and was significantly higher than in control teams at follow-up. There were no significant effects for other outcomes.

The CRT service improvement programme did not achieve its primary aim of improving patient satisfaction. It showed some promise in improving CRT model fidelity and reducing acute in-patient admissions.