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Full-Text Articles in Medicine and Health Sciences
Internalized And Anticipated Stigmatization In Patients With Gout, Maria Kleinstäuber, Leonie Wolf, Annie S. K. Jones, Nicola Dalberth, Keith J. Petrie
Internalized And Anticipated Stigmatization In Patients With Gout, Maria Kleinstäuber, Leonie Wolf, Annie S. K. Jones, Nicola Dalberth, Keith J. Petrie
Psychology Faculty Publications
Objective: To investigate the relationship between stigma perception and demographic, clinical, and psychosocial variables. Methods: A sample of 50 patients with gout and prescribed urate-lowering medication (84% were males, mean serum urate 0.34 mmol/l) completed questionnaires on internalized and anticipated stigma, demographics, clinical gout-related variables, and psychosocial variables (illness perceptions, illness-related disability, illness-related body satisfaction, intentional nonadherence). Serum urate level was obtained from the most recent blood test. Results: In this sample, 26% experienced internalized stigma, 26% expected to be stigmatized by friends or family members, and 14% by health care workers. Univariate regression analyses showed that younger age, ethnicity …
Evaluating Commonalities Between Different Medically Unexplained Symptoms, Dan Guo, Maria Kleinstäuber, Malcolm Henry Johnson, Frederick Sundram
Evaluating Commonalities Between Different Medically Unexplained Symptoms, Dan Guo, Maria Kleinstäuber, Malcolm Henry Johnson, Frederick Sundram
Psychology Faculty Publications
This commentary presents commonalities in medically unexplained symptoms (MUS) across multiple organ systems, including symptoms, aetiological mechanisms, comorbidity with mental health disorders, symptom burden and impact on quality of life. Further, treatment outcomes and barriers in the clinician–patient relationship, and cross-cultural experiences are highlighted. This discussion is necessary in aiding an improved understanding and management of MUS due to the interconnectedness underlying MUS presentations across the spectrum of medical specialties.
Autoscore: An Open-Source Automated Tool For Scoring Listener Perception Of Speech, Stephanie A. Borrie, Tyson S. Barrett, Sarah E. Yoho Leopold
Autoscore: An Open-Source Automated Tool For Scoring Listener Perception Of Speech, Stephanie A. Borrie, Tyson S. Barrett, Sarah E. Yoho Leopold
Psychology Faculty Publications
Speech perception studies typically rely on trained research assistants to score orthographic listener transcripts for words correctly identified. While the accuracy of the human scoring protocol has been validated with strong intra- and inter-rater reliability, the process of hand-scoring the transcripts is time-consuming and resource intensive. Here, an open-source computer-based tool for automated scoring of listener transcripts is built (Autoscore) and validated on three different human-scored data sets. Results show that not only is Autoscore highly accurate, achieving approximately 99% accuracy, but extremely efficient. Thus, Autoscore affords a practical research tool, with clinical application, for scoring listener intelligibility of speech.