The brief window of time comprising a wheelchair transfer confers a significant fracture risk on elderly Americans.

OBJECTIVES: Wheelchairs grant increased mobility to their users but can result in injuries of varying severities, including fractures which are often associated with wheelchair transfers. However, this fracture burden remains poorly characterized in elderly Americans. The purpose of this study was to report demographic and environmental risk factors for these injuries. STUDY DESIGN: We used data from the National Electronic Injury Surveillance System (NEISS) for the years 2007-2017 to perform a retrospective, cross-sectional analysis of wheelchair transfer fractures in patients aged 65 years and older. METHODS: Each yearly sample in the NEISS database was queried between 2007 and 2017 for fractures associated with wheelchair transfers in patients aged 65 years or older. The narrative sections of the database were individually read and reviewed to identify cases in which a patient explicitly transferred into or out of a wheelchair while sustaining said fracture. RESULTS: Between 2007 and 2017, the average number of patients aged 65 years and older presenting to US emergency departments was 3924 (95% confidence interval [CI] = 2792-5055). A significantly higher percentage of fractures (61.8%; 95% CI = 56.7%-66.8%) is associated with transferring out of wheelchairs. Moreover, such fractures were often associated with transferring to and from beds (29.9%; 95% CI = 25.4%-34.3%), with the hip (37.5%; 95% CI = 33.3%-41.6%) being the most commonly fractured anatomical region overall. A majority of patients required admission to the hospital (60.2%; 95%CI = 52.4%-68.0%) and most wheelchair transfer fractures occurred at home (44.1%; 95% CI = 36.7%-51.5%), with women (71.9%; 95% CI = 68.3%-75.6%) comprising the majority of these patients. CONCLUSIONS: Our findings show that wheelchair transfers are associated with significant risk of severe fracture in elderly Americans. As such, wheelchair transfer events merit extra attention from healthcare providers because they comprise a brief window of time relative to the number of occupancy hours in full-time wheelchair users yet can result in significant morbidity and mortality. Preventative measures and patient education should be encouraged to preserve patient mobility and reduce injury.

Self-reference in psychosis and depression: a language marker of illness.

BACKGROUND: Language use is of increasing interest in the study of mental illness. Analytical approaches range from phenomenological and qualitative to formal computational quantitative methods. Practically, the approach may have utility in predicting clinical outcomes. We harnessed a real-world sample (blog entries) from groups with psychosis, strong beliefs, odd beliefs, illness, mental illness and/or social isolation to validate and extend laboratory findings about lexical differences between psychosis and control subjects. METHOD: We describe the results of two experiments using Linguistic Inquiry and Word Count software to assess word category frequencies. In experiment 1, we compared word use in psychosis and control subjects in the laboratory (23 per group), and related results to subject symptoms. In experiment 2, we examined lexical patterns in blog entries written by people with psychosis and eight comparison groups. In addition to between-group comparisons, we used factor analysis followed by clustering to discern the contributions of strong belief, odd belief and illness identity to lexical patterns. RESULTS: Consistent with others' work, we found that first-person pronouns, biological process words and negative emotion words were more frequent in psychosis language. We tested lexical differences between bloggers with psychosis and multiple relevant comparison groups. Clustering analysis revealed that word use frequencies did not group individuals with strong or odd beliefs, but instead grouped individuals with any illness (mental or physical). CONCLUSIONS: Pairing of laboratory and real-world samples reveals that lexical markers previously identified as specific language changes in depression and psychosis are probably markers of illness in general.