Autonomy Preference Index - Uroonkologie (API-Uro) : API Fragebogen - Fallbeispiele Uroonkologie

Dieser Vignetten-basierte Fragebogen dient der Erfassung der Beteiligungspräferenz von Patient:innen an Behandlungsentscheidungen in der Uroonkologie (Büdenbender et al., eingereicht). Es werden sieben typische Entscheidungen bei der Diagnose, Behandlung und Nachsorge uroonkologischer Erkrankungen (z.B. Harnblasenkarzinom oder Prostatakarzinom) geschildert. Die Patient:innen beantworten, wer die Entscheidung treffen soll auf einer 5-stufigen Likert-Skala von 1 „Der Arzt alleine“ bis 5 „Der Patient alleine“. Die Vignetten wurden in Anlehnung an die Vignetten des Autonomy Preference Index (Ende et al., 1989) gemeinsam mit uroonokologischen Expert:innen des Universitätsklinikums Mannheim in einem Konsensverfahren erstellt und anschließend mit den Rückmeldungen von Patient:innen verbessert

What's in a face: Automatic facial coding of untraines study participants compared to standardized inventories

Automatic facial coding (AFC) is a novel research tool to automatically analyze emotional facial expressions. AFC can classify emotional expressions with high accuracy in standardized picture inventories of intensively posed and prototypical expressions. However, classification of facial expressions of untrained study participants is more error prone. This discrepancy requires a direct comparison between these two sources of facial expressions. To this end, 70 untrained participants were asked to express joy, anger, surprise, sadness, disgust, and fear in a typical laboratory setting. Recorded videos were scored with a well-established AFC software (FaceReader, Noldus Information Technology). These were compared with AFC measures of standardized pictures from 70 trained actors (i.e., standardized inventories). We report the probability estimates of specific emotion categories and, in addition, Action Unit (AU) profiles for each emotion. Based on this, we used a novel machine learning approach to determine the relevant AUs for each emotion, separately for both datasets. First, misclassification was more frequent for some emotions of untrained participants. Second, AU intensities were generally lower in pictures of untrained participants compared to standardized pictures for all emotions. Third, although profiles of relevant AU overlapped substantially across the two data sets, there were also substantial differences in their AU profiles. This research provides evidence that the application of AFC is not limited to standardized facial expression inventories but can also be used to code facial expressions of untrained participants in a typical laboratory setting

Predicting decisional conflict - anxiety and depression in shared decision making

Emotional distress can be a potential barrier to shared decision making (SDM), yet affect is typically not systematically assessed in medical consultation. We examined whether urological patients report anxiety or depression prior to a consultation and if emotional distress predicts decisional conflict thereafter. We recruited a large sample of urological outpatients (N = 397) with a range of different diagnoses (42% oncological). Prior to a medical consultation, patients filled in questionnaires, including the Hospital Anxiety and Depression Scale. After the consultation, patients completed the Decisional Conflict Scale. We scored the rate of anxiety and depression in our sample and conducted multiple regression analysis to examine if emotional distress before the consultation predicts decisional conflict thereafter. About a quarter of patients reported values at or above cut-off for clinically relevant emotional distress. Emotional distress significantly predicted a higher degree of decisional conflict. There were no differences in emotional distress between patients with and without uro-oncological diagnosis. Emotional distress is common in urology patients – oncological as well as non-oncological. It predicts decisional conflict after physician consultation. Emotional distress should be systematically assessed in clinical consultations. This may improve the process and outcome of SDM

Вибір та обґрунтування параметрів технології підтримки стінок стовбура свердловини в осадових породах

Практичне значення роботи полягає в досліджені широкого кола властивостей різних хімічних сполук, покликаних збільшити ступінь стійкості осадових порід в стінках стовбура свердловини; застосування досліджених речовин приведе до істотного підвищення продуктивності бурових робіт, скорочення часу на роботи, пов’язані із ліквідацією ускладнень і аварій в свердловині, або повного виключення останніх, загального зростання ефективності і економічності процесу спорудження свердловин.Мета дипломної роботи: встановлення закономірностей фізико-хімічних процесів, що протікають в стовбурі свердловини, споруджуваної в товщі осадових гірських порід, при циркуляції промивальних рідин і формулюванні на їх основі адекватних технологічних заходів гідравлічної програми промивання свердловини, реалізація якої дозволить надати процесу спорудження свердловин достатньо високу міру продуктивності і економічності

Different patients, different preferences: A multicenter assessment of patients' personality traits and anxiety in shared decision making

OBJECTIVE: Patient‐centered care and shared decision making (SDM) are generally recognized as the gold standard for medical consultations, especially for preference‐sensitive decisions. However, little is known about psychological patient characteristics that influence patient‐reported preferences. We set out to explore the role of personality and anxiety for a preference‐sensitive decision in bladder cancer patients (choice of urinary diversion, UD) and to determine if anxiety predicts patients' participation preferences. METHODS: We recruited a sample of bladder cancer patients (N = 180, primarily male, retired) who awaited a medical consultation on radical cystectomy and their choice of UD. We asked patients to fill in a set of self‐report questionnaires before this consultation, including measures of treatment preference, personality (BFI‐10), anxiety (STAI), and participation preference (API and API‐Uro), as well as sociodemographic characteristics. RESULTS: Most patients (79%) indicated a clear preference for one of the treatment options (44% continent UD, 34% incontinent UD). Patients who reported more conscientiousness were more likely to prefer more complex methods (continent UD). The majority (62%) preferred to delegate decision making to healthcare professionals. A substantial number of patients reported elevated anxiety (32%), and more anxiety was predictive of higher participation preference, specifically for uro‐oncological decisions (β = 0.207, p < 0.01). CONCLUSIONS: Our findings provide insight into the role of psychological patient characteristics for SDM. Aspects of personality such as conscientiousness influence treatment preferences. Anxiety contributes to patients' motivation to be involved in pertinent decisions. Thus, personality and negative affect should be considered to improve SDM