Objective personality measures potentially eliminate random variation that can result from errors in scoring test items or tallying results. It is usually assumed that the scoring of objective personality tests is error free or nearly so. We checked the accuracy with which trained clinic personnel hand scored one particular objective personality measure, the Personality Diagnostic Questionnaire-Revised (Hyler, Skodol, Oldham, Kellman, & Doidge, 1992), using a computer program that was verified to be error free. We found frequent mistakes: 53% of the inventories showed at least one error, and 19% contained errors sufficient to alter clinical diagnoses. Our results align with other studies suggesting that errors are common in scoring psychological tests and argue for wider use of such methods as computerized scoring to prevent avoidable errors and, hence, increase the accuracy of test interpretation. GREOORY ALLARD received his BS from Carnegie Mellon University in 1988. He is currently pursuing a PhD in clinical psychology from the University of Rhode Island. JULIAN BUTLER is currently pursuing his BS in computer science from the University of Rhode Island. He has developed several computer software applications for the social sciences. DAVID FAUST received his PhD from Ohio University. He is a professor in the Department of Psychology at the University of Rhode Island and has an affiliate appointment in the Department of Psychology and Human Behavior, Brown University Medical School. M. TRACIE SHEA received her PhD from Catholic University in personality psychology in 1981. Her current positions include associate professor in the Department of Psychiatry and Human Behavior at Brown University and a psychologist in the Post-Traumatic Stress Disorder Clinic of the Providence Veterans Affairs Medical Center. WE WOULD LIKE TO THANK the psychologists who participated in the survey, including

Précis: Intraocular pressure (IOP) was found to be significantly correlated with body mass index (BMI), waist circumference, and diastolic blood pressure (DBP) in a farmworker population located in the southeast Georgia, USA. BMI was correlated with IOP, independent of systemic blood pressures. Purpose: Elevated IOP is a known risk factor for glaucomatous optic neuropathy and is believed to be associated with obesity and cardiometabolic diseases. The high prevalence of these conditions in the United States necessitates an evaluation of the relationship among obesity, cardiometabolic risks, and IOP among understudied younger populations. Materials and Methods: Farmworker data were collected from the annual Costa-Layman Health Fair between 2013 and 2017. Correlations of IOP with demographic factors, obesity, and cardiometabolic risks were analyzed using analysis of covariance, partial Pearson correlations, and linear regressions. Results: In the farmworker population (n=346), the mean IOP was 15.5 mm Hg and the prevalence of ocular hypertension (IOP>21 mm Hg) was 5.5%. BMI, waist circumference, and DBP were significantly correlated (r=0.192, P=0.001; r=0.128, P=0.017; r=0.142, P=0.007, respectively) with IOP when adjusted for age, sex, and ethnicity. Each 10 mm Hg increase in DBP corresponded with a 0.51 mm Hg increase in IOP. With adjustment for age, sex, ethnicity, systolic blood pressure, and DBP, BMI remained significantly correlated with IOP (r=0.166, P=0.002). Conclusions: Higher IOP is associated with obesity measures including BMI and waist circumference and is correlated with DBP. These findings suggest that BMI is an independent risk factor for elevated IOP.

Aims and methodA total of 384 incidents of violence against the person (six ‘serious' and 378 ‘mild’), by adult in-patients in general psychiatric units (GPUs) and learning disability units (LDUs) in 10 National Health Service trusts in the Anglia region, were evaluated by Interviews with staff and examination of records.ResultsThe findings, when compared with standards derived from previous recommendations, showed deficiencies in the documentation of incidents (there was no satisfactory written record of physical restraint for 97% of incidents in GPUs and 86% in LDUs), in the training of staff in ‘control and restraint’ procedures (If two or more staff were involved In physical restraint, for 3% of incidents in GPUs and 100% in LDUs, the staff had received no training within the previous 12 months) and in policies for victim support (there was no written policy that included procedures for victim support in relation to 84% of incidents in GPUs and 44% in LDUs).Clinical implicationsTrusts should consider reviewing their policies on the prevention and management of violence, particularly in relation to staff training.

Introduction Prolonged bedrest amongst the elderly causes deconditioning leading to; increased hospital length of stay, additional social costs and decreased quality of life. An audit on an acute geriatric ward in November 2018, found that over a third of patients medically fit (PMF) to sit out remained in bed all day. Therefore, a service development initiative was undertaken, addressing the misconception that keeping elderly patients in bed is safe, when in fact, unintentional harm results. Method In a root cause analysis, four main reasons for bedrest were identified: risk aversion, unknown function, widespread “bed is safe” culture and lack of equipment. The project tasked getting PMF out of bed each day and was audited daily from November 2018 to present, involving all members of the multi-disciplinary team (MDT) and using a “plan, do, study, act” approach. Results Initially, the project showed an increase in percentage of PMF sitting out each day, but this subsequently decreased with winter pressures. However, for a whole year (February 2019–February 2020) a sustained and significant improvement was achieved (64.3%–89.7%). The pre-COVID19 period (February–March 2020) saw fluctuations in PMF sitting out. Data collection halted during the COVID19 peak, although observationally most patients remained in bed. Auditing resumed from June 2020 (COVID19 recovery phase) which showed a steady increase in PMF out of bed, with recent figures surpassing pre-COVID19 levels (97.8%). Conclusion Cultural change takes time to embed and needs persistent reviewing by a dedicated and engaged MDT. Improvements were made through more accessible doctor’s advice, better MDT education and communication, daily feedback of data and sourcing additional equipment. Disruption to working patterns over the COVID19 period made this unachievable and the project lost impetus. In the COVID19 recovery phase, the specialized MDT reformed and worked successfully to restore the cultural change as evidenced by audited data.

No abstract