Evaluating the Effects of Holidays on Road Crash Injuries in the United Kingdom.

BACKGROUND: Research suggests that drivers tend to engage in risk-taking behaviours on public holidays. Studies that examined the association between holidays (or other special days) and fatal injuries are inconsistent. This study used UK STATS19 data to investigate the associations of nine public holidays on road crash casualties. METHODS: This retrospective study assessed UK STATS19 crash data for 1990-2017. All casualties from two vehicle crashes were initially considered; subsequently, casualties with missing data were excluded. Multiple logistic regression was estimated to explore the associations of potential risk factors with the likelihood of killed or seriously injured (KSI) casualties and to calculate adjusted odds ratios (AORs). RESULTS: In total, 3,751,998 casualties from traffic accidents in the United Kingdom during 1990-2017 were included in the final data set; among these, 410,299 (10.9%) were KSI casualties, and 3,341,699 (89.1%) were slight injuries. Crashes on public holidays were 16% (AOR = 1.16; 95% confidence interval [CI] = 1.13-1.19) more likely to involve KSI casualties than were crashes on non-holidays. With other factors controlled for, crashes during the Queen's 2002 Golden Jubilee and on New Year's Day were 48% (AOR = 1.48; 95% CI = 1.06-2.07) and 36% (AOR = 1.36; 1.26-1.48) more likely to lead to KSIs, respectively. CONCLUSIONS: The proportion of crashes resulting in KSI casualties on public holidays was higher than that on non-holidays. Furthermore, crashes during the Queen's 2002 Golden Jubilee had the highest risk of KSI casualties followed by New Year's Day.

Patient Transfer Decision Difficulty Scale: Development and psychometric testing of emergency department visits by long-term care residents.

BACKGROUND AND OBJECTIVES: Nurses serve as gatekeepers of the health of long-term care facility (LTCF) residents and are key members deciding whether residents should visit an emergency department (ED). Inappropriate decisions as to ED visits may result in ED overcrowding, excessive medical expenses, and nosocomial infections. Currently, there is a lack of effective tools for assessing the barriers and level of difficulty experienced by LTCF nurses. The purposes of this study were to develop a Patient Transfer Decision Difficulty Scale (PTDDS) and test its effectiveness. METHODS: This study randomly sampled LTCFs in Taiwan and surveyed two or three nurses in every institution selected. Registered return envelopes were provided for participants to return self-completed questionnaires. Three steps were used to develop the scale and items: in step I, the instrument was developed; in step II, psychometric testing was conducted, which entailed performing an exploratory factor analysis (EFA) to verify the construct validity and reliability of the developed items; and in step III, a confirmation study was conducted using a confirmatory factor analysis (CFA) and structural equation modeling to cross-validate the factors and items. RESULTS: The cumulative sum of variance explained by the measurement models of the three factors in the PTDDS was 63.54%.When deciding whether to transfer LTCF residents to EDs, the most pronounced barrier experienced by nurses were for judging the severity of "clinical episodes", which had an explanatory power of 37.49%. The second and third pronounced barriers and decision difficulty experienced by nurses were "communication and information" and "timing of the residents' emergency visits," which explained 16.81% and 9.24% of the variance, respectively. CONCLUSIONS: The cross-validation results obtained using the EFA and CFA showed favorable reliability and validity of the PTDDS. For future studies, this study recommends performing large-scale investigations of the level of decision difficulty and related factors experienced by nurses in LTCFs of varying levels and types.