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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.
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.
Monoclonal antibody therapeutics to treat coronavirus disease (COVID-19) have been authorized by the US Food and Drug Administration under Emergency Use Authorization (EUA). Many barriers exist when deploying a novel therapeutic during an ongoing pandemic, and it is critical to assess the needs of incorporating monoclonal antibody infusions into pandemic response activities. We examined the monoclonal antibody infusion site process during the COVID-19 pandemic and conducted a descriptive analysis using data from 3 sites at medical centers in the United States supported by the National Disaster Medical System. Monoclonal antibody implementation success factors included engagement with local medical providers, therapy batch preparation, placing the infusion center in proximity to emergency services, and creating procedures resilient to EUA changes. Infusion process challenges included confirming patient severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity, strained staff, scheduling, and pharmacy coordination. Infusion sites are effective when integrated into pre-existing pandemic response ecosystems and can be implemented with limited staff and physical resources.
Disasters of all varieties have been steadily increasing in frequency. Simultaneously, “big data” has seen explosive growth as a tool in business and private industries while opportunities for robust implementation in disaster management remain nascent. To more explicitly ascertain the current status of big data as applied to disaster recovery, we conducted an integrative literature review.
Eleven databases were searched using iteratively developed keywords to target big data in a disaster recovery context. All studies were dual-screened by title and abstract followed by dual full-text review to determine if they met inclusion criteria. Articles were included if they focused on big data in a disaster recovery setting and were published in the English-language peer-reviewed literature.
After removing duplicates, 25,417 articles were originally identified. Following dual title/abstract review and full-text review, 18 studies were included in the final analysis. Among those, 44% were United States-based and 39% focused on hurricane recovery. Qualitative themes emerged surrounding geographic information systems (GIS), social media, and mental health.
Big data is an evolving tool for recovery from disasters. More research, particularly in real-time applied disaster recovery settings, is needed to further expand the knowledge base for future applications.
This study aimed to explore the impact of the coronavirus disease 2019 pandemic and postponement of elective surgical procedures for profoundly deaf patients awaiting cochlear implantation.
Open-ended questionnaires were sent to all adult patients awaiting cochlear implantation surgery. Qualitative analysis was performed using a grounded theory approach.
Participants described a primarily negative impact on wellbeing from the surgery delay, expressing feelings of isolation or loneliness. Low mood, depression or hopelessness were commonly expressed by elderly participants; frustration and anxiety were described by young adults. Participants described a negative impact on their general daily life, describing difficulties communicating with facemasks and struggles with reliance on telephone communication because of social distancing. Despite these significant psychosocial challenges, only a minority described adaptive coping strategies.
Profoundly deaf patients may be at greater psychosocial risk because of unique challenges from their hearing disability. Our findings can be used to develop evidence-driven strategies to improve communication, wellbeing and quality of life.
Mr. C, a 75-year-old man, noticed difficulty remembering names and adding numbers after wakening while on vacation. Although these problems were quite subtle, his wife was puzzled because he seemed to have no difficulty the day before. One week later, he noted that “something was wrong” but could not describe the changes in detail. He felt that his balance was “not right” and experienced difficulty keeping track of his golf scores. Over the next few months, he developed word-finding problems and had difficulty expressing himself. He was very forgetful, had trouble problem solving, was distractible, and was unable to do simple calculations. Whereas he had previously been very reserved, he started talking with others in a more open way than he would normally have done. He continued to complain of balance problems and started to notice changes in his handwriting.
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.
Implementation of clinically useful research discoveries in the academic environment is challenged by limited funding for early phase proof-of-concept studies and inadequate expertise in product development and commercialization. To address these limitations, the National Institutes of Health (NIH) established the National Centers for Accelerated Innovations (NCAI) program in 2013. Three centers competed successfully for awards through this mechanism. Here, we present the experience of one such center, the Boston Biomedical Innovation Center (B-BIC), and demonstrate its remarkable success at the translation of innovations to clinical application and commercialization, as well as skills development and education.
The availability of large healthcare datasets offers the opportunity for researchers to navigate the traditional clinical and translational science research stages in a nonlinear manner. In particular, data scientists can harness the power of large healthcare datasets to bridge from preclinical discoveries (T0) directly to assessing population-level health impact (T4). A successful bridge from T0 to T4 does not bypass the other stages entirely; rather, effective team science makes a direct progression from T0 to T4 impactful by incorporating the perspectives of researchers from every stage of the clinical and translational science research spectrum. In this exemplar, we demonstrate how effective team science overcame challenges and, ultimately, ensured success when a diverse team of researchers worked together, using healthcare big data to test population-level substance use disorder (SUD) hypotheses generated from preclinical rodent studies. This project, called Advancing Substance use disorder Knowledge using Big Data (ASK Big Data), highlights the critical roles that data science expertise and effective team science play in quickly translating preclinical research into public health impact.
First episode psychosis (FEP) patients who use cannabis experience more frequent psychotic and euphoric intoxication experiences compared to controls. It is not clear whether this is consequent to patients being more vulnerable to the effects of cannabis use or to their heavier pattern of use. We aimed to determine whether extent of use predicted psychotic-like and euphoric intoxication experiences in patients and controls and whether this differs between groups.
We analysed data on patients who had ever used cannabis (n = 655) and controls who had ever used cannabis (n = 654) across 15 sites from six countries in the EU-GEI study (2010–2015). We used multiple regression to model predictors of cannabis-induced experiences and to determine if there was an interaction between caseness and extent of use.
Caseness, frequency of cannabis use and money spent on cannabis predicted psychotic-like and euphoric experiences (p ⩽ 0.001). For psychotic-like experiences (PEs) there was a significant interaction for caseness × frequency of use (p < 0.001) and caseness × money spent on cannabis (p = 0.001) such that FEP patients had increased experiences at increased levels of use compared to controls. There was no significant interaction for euphoric experiences (p > 0.5).
FEP patients are particularly sensitive to increased psychotic-like, but not euphoric experiences, at higher levels of cannabis use compared to controls. This suggests a specific psychotomimetic response in FEP patients related to heavy cannabis use. Clinicians should enquire regarding cannabis related PEs and advise that lower levels of cannabis use are associated with less frequent PEs.
We used British national survey data to test specific hypotheses that mood instability 1) is associated with psychosis and individual psychotic phenomena, 2) predicts the later emergence of auditory hallucinations and paranoid ideation, and 3) mediates the link between child sexual abuse and psychosis.
We analysed data from the 2000 and 2007 UK national surveys of psychiatric morbidity (N=8580 and 7403 respectively). The 2000 survey included an 18-month follow-up of a subsample (N=2406). Mood instability was assessed from the Structured Clinical Interview for DSMIV Axis II (SCID-II) questionnaire. Our dependent variables comprised auditory hallucinations, paranoid ideation, the presence of psychosis overall, and a 15-item paranoia scale
Mood Instability was strongly associated in cross-sectional analyses with psychosis (2000 OR: 7.5; 95% CI: I 4.1–13.8; 2007: OR 21.4; CI 9.7–41.2), paranoid ideation (2000: OR: 4.7; CI 4.1–5.4; 2007: OR 5.7; CI 4.9–6.7), auditory hallucinations (2000: OR: 3.4; CI 2.6–4.4; 2007: OR 3.5; CI 2.7–4.7) and paranoia total score (2000: Coefficient: 3.6;CI 3.3–3.9), remaining so after adjustment for current mood state. Baseline mood instability significantly predicted 18-month inceptions of paranoid ideation (OR: 2.3;CI 1.6–3.3) and of auditory hallucinations (OR: 2.6;CI 1.5–4.4). Finally it mediated a third of the total association of child sexual abuse with psychosis and persecutory ideation, and a quarter of that with auditory hallucinations.
Mood instability is a prominent feature of psychotic experience, and may have a role in its genesis. Targeting mood instability could lead to innovative treatments for psychosis.
Over the past two decades, numerous methodologies have been developed with the specific goal of reducing the placebo effect in CNS trials. This presentation will discuss how three of these strategies, Central Ratings, use of the SAFER interview, and use of Sequential Parallel Comparison Design (SPCD), in combination, may offer a’triple safety’ net that ensures maximum reduction of the risk of a failed trial. Central Ratings have been shown to reduce variability in ratings by limiting the pool of raters for a given trial, ensuring consistent high reliability and calibration of raters, and reduction of expectation bias due to blinding and independence from the site. Novel study designs such as SPCD have been shown to significantly reduce the overall placebo response rate of the trial by pooling data from both phases of the trial, given the marked reduction in placebo response in the placebo non-responders of phase 2 of these trials. Finally, the use of highly experienced, independent remote interviewers to administer diagnostic and treatment history checks such as the SAFER interview and to perform unbiased assessment of baseline symptom severity improves the quality of subject selection, preventing the randomization of subjects with inadequate severity of illness or without the appropriate diagnosis or treatment history. This presentation will review the evidence in support of the utility of combining these three common methodological approaches to reduce the placebo response in CNS trials, providing a’triple safety’ net for CNS trials and the opportunity to enhance signal detection.
Psychosis and adult Attention Deficit Hyperactivity Disorder (ADHD) have shared attributes, but evidence that they are associated is sparse and inconsistent.
We tested hypotheses that 1] adult ADHD symptoms are associated with psychosis and individual psychotic symptoms 2] links between ADHD symptoms and psychosis are mediated by prescribed ADHD medications, use of illicit drugs, and dysphoric mood (depression and anxiety).
The Adult Psychiatric Morbidity Survey 2007 (N=7403) provided data for regression and multiple mediation analyses. ADHD symptoms were coded from the ADHD Self-Report Scale (ASRS). Dependent variables comprised auditory hallucinations, paranoid ideation, and identified psychosis.
Higher ASRS total score was significantly associated with psychosis (O.R: 1.11; 95% CI 1.02-1.20; p = 0.013), paranoid ideation (O.R:1.12; CI 1.09-1.14; p<0.001) and auditory hallucinations (O.R 1.11; CI 1.08-1.15; p<0.001) even after controlling for socio-demographic variables, verbal IQ, autism spectrum disorder traits, childhood conduct problems, hypomanic mood and dysphoric mood. The link between higher ADHD symptoms and psychosis variables was significantly mediated by dysphoric mood (psychosis, 21%; paranoid ideation, 23%; auditory hallucination, 11%), but not by prescribed ADHD medication or use of amphetamine, cocaine or cannabis.
Higher levels of adult ADHD symptoms and psychosis are linked, and dysphoric mood may form part of the mechanism. Those with greater levels of ADHD symptoms in adulthood may be at higher risk of psychosis. Our analyses contradict the clinical view that the main explanation for people with ADHD symptoms developing psychosis is abuse of illicit drugs or ADHD medications.
Daily use of high-potency cannabis has been reported to carry a high risk for developing a psychotic disorder. However, the evidence is mixed on whether any pattern of cannabis use is associated with a particular symptomatology in first-episode psychosis (FEP) patients.
We analysed data from 901 FEP patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. We used item response modelling to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use were evaluated using linear mixed-effects models analyses.
In patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high-potency cannabis having the highest score (B = 0.35; 95% CI 0.14–0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B = −0.22; 95% CI −0.37 to −0.07). In controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use. Neither patients nor controls presented differences in depressive dimension related to cannabis use.
Our findings provide the first large-scale evidence that FEP patients with a history of daily use of high-potency cannabis present with more positive and less negative symptoms, compared with those who never used cannabis or used low-potency types.
There are high rates of obesity and low self-esteem in patients with psychosis. The occurrence of negative voice content directly about appearance is therefore plausible. Derogatory comments about appearance are likely to be distressing, increase depression and contribute to social withdrawal.
To systematically assess the occurrence of voice content regarding appearance and identify correlates.
Sixty patients experiencing verbal auditory hallucinations at least once a week in the context of non-affective psychosis completed a measure assessing positive and negative voice content about appearance. They also completed assessments about body image, self-esteem, psychiatric symptoms and well-being.
Fifty-five (91.7%) participants reported hearing voices comment on their appearance. A total of 54 (90%) patients reported negative voice content about their appearance with 30 (50%) patients experienced negative appearance comments on a daily basis. The most common negative comment was ‘the voices tell me that I am ugly’ (n = 48, 80%). There were 39 (65%) patients who reported positive voice content on appearance. The most frequent positive comment was ‘I look as nice as other people’ (n = 26, 43.3%). Negative voice content about appearance was associated with body image concerns, paranoia, voice hearing severity, depression, worry, negative self-beliefs and safety-seeking behaviours. Positive appearance voice content was associated with greater body esteem and well-being and lower levels of depression and insomnia.
Voice content about appearance is very common for patients seen in clinical services. Negative voice content may reflect – and subsequently reinforce – negative beliefs about one's appearance, low self-esteem, worry and paranoia.
The period before the formation of a persecutory delusion may provide causal insights. Patient accounts are invaluable in informing this understanding.
To inform the understanding of delusion formation, we asked patients about the occurrence of potential causal factors – identified from a cognitive model – before delusion onset.
A total of 100 patients with persecutory delusions completed a checklist about their subjective experiences in the weeks before belief onset. The checklist included items concerning worry, images, low self-esteem, poor sleep, mood dysregulation, dissociation, manic-type symptoms, aberrant salience, hallucinations, substance use and stressors. Time to reach certainty in the delusion was also assessed.
Most commonly it took patients several months to reach delusion certainty (n = 30), although other patients took a few weeks (n = 24), years (n = 21), knew instantly (n = 17) or took a few days (n = 6). The most frequent experiences occurring before delusion onset were: low self-confidence (n = 84); excessive worry (n = 80); not feeling like normal self (n = 77); difficulties concentrating (n = 77); going over problems again and again (n = 75); being very negative about the self (n = 75); images of bad things happening (n = 75); and sleep problems (n = 75). The average number of experiences occurring was high (mean 23.5, s.d. = 8.7). The experiences clustered into six main types, with patients reporting an average of 5.4 (s.d. = 1.0) different types.
Patients report numerous different experiences in the period before full persecutory delusion onset that could be contributory causal factors, consistent with a complex multifactorial view of delusion occurrence. This study, however, relied on retrospective self-report and could not determine causality.
The diurnal feeding patterns of dairy cows affects the 24 h robot utilisation of pasture-based automatic milking systems (AMS). A decline in robot utilisation between 2400 and 0600 h currently occurs in pasture-based AMS, as cow feeding activity is greatly reduced during this time. Here, we investigate the effect of a temporal variation in feed quality and quantity on cow feeding behaviour between 2400 and 0600 h as a potential tool to increase voluntary cow trafficking in an AMS at night. The day was allocated into four equal feeding periods (0600 to 1200, 1200 to 1800, 1800 to 2400 and 2400 to 0600 h). Lucerne hay cubes (CP = 19.1%, water soluble carbohydrate = 3.8%) and oat, ryegrass and clover hay cubes with 20% molasses (CP = 11.8%, water soluble carbohydrate = 10.7%) were offered as the ‘standard’ and ‘preferred’ (preference determined previously) feed types, respectively. The four treatments were (1) standard feed offered ad libitum (AL) throughout 24 h; (2) as per AL, with preferred feed replacing standard feed between 2400 and 0600 h (AL + P); (3) standard feed offered at a restricted rate, with quantity varying between each feeding period (20:10:30:60%, respectively) as a proportion of the (previously) measured daily ad libitum intake (VA); (4) as per VA, with preferred feed replacing standard feed between 2400 and 0600 h (VA + P). Eight non-lactating dairy cows were used in a 4 × 4 Latin square design. During each experimental period, treatment cows were fed for 7 days, including 3 days habituation and 4 days data collection. Total daily intake was approximately 8% greater (P < 0.001) for the AL and AL + P treatments (23.1 and 22.9 kg DM/cow) as compared with the VA and VA + P treatments (21.6 and 20.9 kg DM/cow). The AL + P and VA treatments had 21% and 90% greater (P < 0.001) dry matter intake (DMI) between 2400 and 0600 h, respectively, compared with the AL treatment. In contrast, the VA + P treatment had similar DMI to the VA treatment. Our experiment shows ability to increase cow feeding activity at night by varying feed type and quantity, though it is possible that a penalty to total DMI may occur using VA. Further research is required to determine if the implementation of variable feed allocation on pasture-based AMS farms is likely to improve milking robot utilisation by increasing cow feeding activity at night.
Open dialogue is an integrative approach to the organisation of specialist mental health services and therapeutic meetings.
This qualitative study sought to explore service users' and clinicians’ experiences of network meetings during the implementation of open dialogue in a modified version, for a UK-based mental health service.
In total 19 participants were interviewed (8 service users and 11 clinicians) and an inductive thematic analysis of the data was conducted.
Four dominant themes were identified: (1) open dialogue delivery, (2) the impact of open dialogue principles; (3) intense interactions and enhanced communication, and (4) organisational challenges. Clinicians considered open dialogue as a preferred, but challenging way of working, while being therapeutic. The data indicated that service users' experiences of network meetings were mixed. There was a wide variety of service user views as to what the purpose of a network meeting was and for some witnessing reflective conversations felt strange. However, the majority described feeling listened to and understood, excluding one service user who described their experience as distressing. Clinicians expressed an authentic self in their interactions with service users and both service users and clinicians described network meetings as emotionally expressive, although this was described as overwhelming at times.
The results of this thematic analysis indicate that service users' and clinicians’ experiences of open dialogue warrant further investigation. The intensity of interactions in network meetings should be carefully considered with service users before gaining consent to commence treatment. Implementation of open dialogue should be monitored to assess clinician- and service-level adherence to the principles of the approach.
Introduction: Endotracheal intubation (ETI) is a lifesaving procedure commonly performed by emergency department (ED) physicians that may lead to patient discomfort or adverse events (e.g., unintended extubation) if sedation is inadequate. No ED-based sedation guidelines currently exist, so individual practice varies widely. This study's objective was to describe the self-reported post-ETI sedation practice of Canadian adult ED physicians. Methods: An anonymous, cross-sectional, web-based survey featuring 7 common ED scenarios requiring ETI was distributed to adult ED physician members of the Canadian Association of Emergency Physicians (CAEP). Scenarios included post-cardiac arrest, hypercapnic and hypoxic respiratory failure, status epilepticus, polytrauma, traumatic brain injury, and toxicology. Participants indicated first and second choice of sedative medication following ETI, as well as bolus vs. infusion administration in each scenario. Data was presented by descriptive statistics. Results: 207 (response rate 16.8%) ED physicians responded to the survey. Emergency medicine training of respondents included CCFP-EM (47.0%), FRCPC (35.8%), and CCFP (13.9%). 51.0% of respondents work primarily in academic/teaching hospitals and 40.4% work in community teaching hospitals. On average, responding physicians report providing care for 4.9 ± 6.8 (mean ± SD) intubated adult patients per month for varying durations (39.2% for 1–2 hours, 27.8% for 2–4 hours, and 22.7% for ≤1 hour). Combining all clinical scenarios, propofol was the most frequently used medication for post-ETI sedation (38.0% of all responses) and was the most frequently used agent except for the post-cardiac arrest, polytrauma, and hypercapnic respiratory failure scenarios. Ketamine was used second most frequently (28.2%), with midazolam being third most common (14.5%). Post-ETI sedation was provided by > 98% of physicians in all situations except the post-cardiac arrest (26.1% indicating no sedation) and toxicology (15.5% indicating no sedation) scenarios. Sedation was provided by infusion in 74.6% of cases and bolus in 25.4%. Conclusion: Significant practice variability with respect to post-ETI sedation exists amongst Canadian emergency physicians. Future quality improvement studies should examine sedation provided in real clinical scenarios with a goal of establishing best sedation practices to improve patient safety and quality of care.
The cognitive process of worry, which keeps negative thoughts in mind and elaborates the content, contributes to the occurrence of many mental health disorders. Our principal aim was to develop a straightforward measure of general problematic worry suitable for research and clinical treatment. Our secondary aim was to develop a measure of problematic worry specifically concerning paranoid fears.
An item pool concerning worry in the past month was evaluated in 250 non-clinical individuals and 50 patients with psychosis in a worry treatment trial. Exploratory factor analysis and item response theory (IRT) informed the selection of scale items. IRT analyses were repeated with the scales administered to 273 non-clinical individuals, 79 patients with psychosis and 93 patients with social anxiety disorder. Other clinical measures were administered to assess concurrent validity. Test-retest reliability was assessed with 75 participants. Sensitivity to change was assessed with 43 patients with psychosis.
A 10-item general worry scale (Dunn Worry Questionnaire; DWQ) and a five-item paranoia worry scale (Paranoia Worries Questionnaire; PWQ) were developed. All items were highly discriminative (DWQ a = 1.98–5.03; PWQ a = 4.10–10.7), indicating small increases in latent worry lead to a high probability of item endorsement. The DWQ was highly informative across a wide range of the worry distribution, whilst the PWQ had greatest precision at clinical levels of paranoia worry. The scales demonstrated excellent internal reliability, test-retest reliability, concurrent validity and sensitivity to change.
The new measures of general problematic worry and worry about paranoid fears have excellent psychometric properties.