Purpose: This study aims to capture the complex clinical reasoning process during tailoring of exercise and dietary interventions to adverse effects and comorbidities of patients with ovarian cancer receiving chemotherapy. Methods: Clinical vignettes were presented to expert physical therapists (n = 4) and dietitians (n = 3). Using the think aloud method, these experts were asked to verbalize their clinical reasoning on how they would tailor the intervention to adverse effects of ovarian cancer and its treatment and comorbidities. Clinical reasoning steps were categorized in questions raised to obtain additional information; anticipated answers; and actions to be taken. Questions and actions were labeled according to the evidence-based practice model. Results: Questions to obtain additional information were frequently related to the patients’ capacities, safety or the etiology of health issues. Various hypothetical answers were proposed which led to different actions. Suggested actions by the experts included extensive monitoring of symptoms and parameters, specific adaptations to the exercise protocol and dietary-related patient education. Conclusions: Our study obtained insight into the complex process of clinical reasoning, in which a variety of patient-related variables are used to tailor interventions. This insight can be useful for description and fidelity assessment of interventions and training of healthcare professionals.
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ABSTRACT Background: We investigated if the addition of an inter-professional student-led medication review team (ISP-team) to standard care can increase the number of detected ADRs and reduce the number of ADRs 3 months after an outpatient visit. Research design and methods: In this controlled clinical trial, patients were allocated to standard care (control group) or standard care plus the ISP team (intervention group). The ISP team consisted of medical and pharmacy students and student nurse practitioners. The team performed a structured medication review and adjusted medication to reduce the number of ADRs. Three months after the outpatient visit, a clinical pharmacologist who was blinded for allocation performed a follow-up telephone interview to determine whether patients experienced ADRs. Results: During the outpatient clinic visit, significantly more (p < 0.001) ADRs were detected in the intervention group (n = 48) than in the control group (n = 10). In both groups, 60–63% of all detected ADRs were managed. Three months after the outpatient visit, significantly fewer (predominantly mild and moderately severe) ADRs related to benzodiazepine derivatives and antihypertensive causing dizziness were detected in the patients of the intervention group. Conclusions: An ISP team in addition to standard care increases the detection and management of ADRs in elderly patients resulting in fewer mild and moderately severe ADRs
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The relationship between race and biology is complex. In contemporary medical science, race is a social construct that is measured via self-identification of study participants. But even though race has no biological essence, it is often used as variable in medical guidelines (e.g., treatment recommendations specific for Black people with hypertension). Such recommendations are based on clinical trials in which there was a significant correlation between self-identified race and actual, but often unmeasured, health-related factors such as (pharmaco) genetics, diet, sun exposure, etc. Many teachers are insufficiently aware of this complexity. In their classes, they (unintentionally) portray self-reported race as having a biological essence. This may cause students to see people of shared race as biologically or genetically homogeneous, and believe that race-based recommendations are true for all individuals (rather than reflecting the average of a heterogeneous group). This medicalizes race and reinforces already existing healthcare disparities. Moreover, students may fail to learn that the relation between race and health is easily biased by factors such as socioeconomic status, racism, ancestry, and environment and that this limits the generalizability of race-based recommendations. We observed that the clinical case vignettes that we use in our teaching contain many stereotypes and biases, and do not generally reflect the diversity of actual patients. This guide, written by clinical pharmacology and therapeutics teachers, aims to help our colleagues and teachers in other health professions to reflect on and improve our teaching on race-based medical guidelines and to make our clinical case vignettes more inclusive and diverse.
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Low back pain is the leading cause of disability worldwide and a significant contributor to work incapacity. Although effective therapeutic options are scarce, exercises supervised by a physiotherapist have shown to be effective. However, the effects found in research studies tend to be small, likely due to the heterogeneous nature of patients' complaints and movement limitations. Personalized treatment is necessary as a 'one-size-fits-all' approach is not sufficient. High-tech solutions consisting of motions sensors supported by artificial intelligence will facilitate physiotherapists to achieve this goal. To date, physiotherapists use questionnaires and physical examinations, which provide subjective results and therefore limited support for treatment decisions. Objective measurement data obtained by motion sensors can help to determine abnormal movement patterns. This information may be crucial in evaluating the prognosis and designing the physiotherapy treatment plan. The proposed study is a small cohort study (n=30) that involves low back pain patients visiting a physiotherapist and performing simple movement tasks such as walking and repeated forward bending. The movements will be recorded using sensors that estimate orientation from accelerations, angular velocities and magnetometer data. Participants complete questionnaires about their pain and functioning before and after treatment. Artificial analysis techniques will be used to link the sensor and questionnaire data to identify clinically relevant subgroups based on movement patterns, and to determine if there are differences in prognosis between these subgroups that serve as a starting point of personalized treatments. This pilot study aims to investigate the potential benefits of using motion sensors to personalize the treatment of low back pain. It serves as a foundation for future research into the use of motion sensors in the treatment of low back pain and other musculoskeletal or neurological movement disorders.
