BACKGROUND: Shared decision-making (SDM) has been linked to important health care quality outcomes. However, to the authors' knowledge, the value of SDM has not been thoroughly evaluated in the field of radiation oncology. The objective of the current study was to determine the association between SDM and patient satisfaction during radiotherapy (RT). The authors also explored patient desire for and perception of control during RT, and how these factors relate to patient satisfaction, anxiety, depression, and fatigue. METHODS: A cross-sectional survey of 305 patients undergoing definitive RT was conducted. Patients self-reported measured variables during the last week of RT. Relationships between variables were evaluated using chi-square analyses. RESULTS: Among study participants, 31.3% of patients experienced SDM, 32.3% perceived control in treatment decisions, and 76.2% reported feeling very satisfied with their care. Patient satisfaction was associated with perceived SDM (84.4% vs 71.4%; P <.02) and patient-perceived control (89.7% vs 69.2%; P <.001). Furthermore, the perception of having control in treatment decisions was associated with increased satisfaction regardless of whether the patient desired control. Increased anxiety (44.0% vs 20.0%; P <.02), depression (44.0% vs 15.0%; P <.01), and fatigue (68.0% vs 32.9%; P <.01) were reported in patients who desired but did not perceive control over their treatments, compared with those who both desired and perceived control. CONCLUSIONS: The findings of the current study emphasize the value of SDM and patient-perceived control during RT, particularly as it relates to patient satisfaction and psychological distress. Regardless of a patient's desire for control, it is important to engage patients in the decision-making process.

An integrative Reiki volunteer program shows promise as a component of supportive care for cancer patients. More research is needed to evaluate and understand the impact that Reiki may have for patients, caregivers, and staff whose lives have been affected by cancer.

Methods: This study compares CAM usage between baby boomers (n ‫؍‬ 7734) and the silent generation (n ‫؍‬ 4682) through secondary analyses of the 2007 National Health Interview Survey data. The analysis also compares chronic disease and pain status. Multivariate logistic regression models were developed to identify generational differences.Results: Although the silent generation reported twice as many chronic disease (51.3% vs 26.1%; P < .001) and more painful conditions (56.1% vs 52.2%; P < .001), baby boomers were more likely to use CAM within the past year (43.1% vs 35.4%; P < .001). Adjusting for covariates, baby boomers with heart disease, cancer, and diabetes were more likely to use CAM than adults from the silent generation. Chronic pain status was independently associated with greater CAM use (adjusted odds ratio, 2.26; 95% confidence interval, 2.03-2.52).Conclusions: Baby boomers reported significantly higher rates of CAM use than the silent generation for both chronic diseases and painful conditions. Family physicians caring for the aging population must use patient-centered communication about the risks/benefits of CAM, which is necessary to promote effective coping with chronic illnesses and pain. (J Am Board Fam Med 2014;27:465-473.)

CAM approaches have broad appeal within this inner city cohort of veterans, particularly among African Americans, those that experience pain and those that expect greater benefit from CAM. These findings may inform the development of patient-centered integrative pain management for veterans.

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Mobile electrocardiograms (ECGs) (mECGs) using smartphone applications are an emerging technology. In the coronavirus disease 2019 (COVID-19) era, minimizing patient contact has gained increasing importance. Additionally, increased QT/corrected QT (QTc) monitoring has concurrently been required. The KardiaMobile 6L ECG device, cleared by the United States Food and Drug Administration (FDA) for recording ECGs, along with the KardiaStation tablet application is a platform (AliveCor, Mountain View, CA, USA) that addresses these two issues. A team of residents, fellows, hospitalists, and cardiologists identified inpatients in need of QT/QTc interval monitoring to pilot the adoption of a system composed of a KardiaMobile 6L ECG device with the accompanying KardiaStation tablet application. Concurrent standard ECGs provided validation. Adoption and performance issues were recorded. Four patients agreed to participate in QT/QTc interval monitoring, three of whom were positive for severe acute respiratory syndrome coronavirus 2 viral infection. After basic instructions were given to the patients and their clinical nurses, all patients recorded mECGs successfully. Patients were able to record their own mECG tracings at least once without any assistance. The 12-lead ECGs and mECGs each showed the correct rhythm, and the measured QTc intervals on each modality were consistently acceptable (< 500 ms). Contactless ECGs were successfully uploaded to KardiaStation for QT/QTc interval measurement and archiving. In this study, we showed that an FDA-cleared product, KardiaMobile 6L, has the ability to provide high-quality contactless ECGs for reliable QT/QTc interval measurements. Hospitalized patients were able to perform recordings when requested after receiving simple instructions at the time of first use. This technology has applications during the COVID-19 pandemic and beyond.

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ObjectiveCavo-tricuspid isthmus atrial flutter (CTI-AFL) is an important arrhythmia to recognise because there is a highly effective and relatively low-risk ablation strategy. However, clinical experience has demonstrated that providers often have difficulty distinguishing AFL from atrial fibrillation.MethodsWe developed a novel ECG-based three-step algorithm to identify CTI-AFL based on established CTI flutter characteristics and verified on consecutive ablation cases of typical flutter, atypical flutter and atrial fibrillation. The algorithm assesses V1/inferior lead F-wave concordance, consistency of P-wave morphology and the presence of isoelectric intervals in the inferior leads. In this observation study, the algorithm was validated on a cohort of 50 second-year medical students. Students were paired in a control and experimental group, and each pair received 10 randomly selected ECGs (from a pool of 50 intracardiac electrogram-proven CTI-AFL and 50 AF or atypical AFL cases). The experimental group received a cover sheet with the CTI algorithm, and the control group received no additional guidance.ResultsThere was a statistically significant difference in the mean number of correctly identified ECGs among the students in the experimental and control groups (8.12 vs 5.68, p<0.001). Students who used the algorithm correctly identified 2.44 more ECGs as being CTI-AFL or not CTI-AFL. Using the electrophysiology study as the gold standard, the algorithm had an accuracy of 81%, sensitivity of 81%, specificity of 82%, positive predictive value of 78% and negative predictive value of 84% in identifying CTI-AFL.ConclusionWe developed a three-step ECG algorithm that provides a simple, sensitive, specific and accurate tool to identify CTI-AFL.