Impact of High-Fidelity E-Learning on Knowledge Acquisition and Satisfaction in Radiation Oncology Trainees

Background e-Learning is an underutilized tool in education for the health professions, and radiation medicine, given its reliance on technology for clinical practice, is well-suited to training simulation in online environments. The purpose of the present study was to evaluate the knowledge impact and user interface satisfaction of high- (hf) compared with low-fidelity (lf) e-learning modules (e-modules) in radiation oncology training. Methods Two versions of an e-module on lung radiotherapy (lf and hf) were developed. Radiation oncology residents and fellows were invited to be randomized to complete either the lf or the hf module through individual online accounts over a 2-week period. A 25-item multiple-choice knowledge assessment was administered before and after module completion, and user interface satisfaction was measured using the Questionnaire for User Interaction Satisfaction (quis) tool. Results Of 18 trainees, 8 were randomized to the lf module, and 10, to the hf module. Overall, knowledge assessment performance increased (11%, p < 0.05), with hf-group participants reporting a 13% improvement (p = 0.02), and senior participants reporting an almost 15% improvement (p < 0.01). Scores on the quis indicated that participants were satisfied with various aspects of the user interface. Conclusions The hf e-module had a greater impact on knowledge acquisition, and users expressed satisfaction with the interface in both the hf and lf situations. The use of e-learning in a competency-based curriculum could have educational advantages; participants expressed benefits and drawbacks. Preferences for e-learning integration in education for the health professions should be explored further

Implementation of a Comprehensive Smoking Cessation Program in Cancer Care

Background: Quitting smoking after a cancer diagnosis maximizes treatment-related effects, improves prognosis, and enhances quality of life. However, smoking cessation (SC) services are not routinely integrated into cancer care. The Princess Margaret Cancer Centre implemented a digitally-based sc program in oncology, leveraging an e-referral system (CEASE) to screen all new ambulatory patients, provide tailored education and advice on quitting, and facilitate referrals. Methods: We adopted the Framework for Managing eHealth Change to guide implementation of the sc program by integrating 6 key elements: governance and leadership, stakeholder engagement, communication, workflow analysis and integration, monitoring and evaluation, and training and education. Results: Incorporating elements of the Framework, we used extensive stakeholder engagement and strategic partnerships to establish a sc program with organizational and provincial accountability. Existing electronic patient-reported assessments were changed to integrate cease. Clinic audits and staff engagement allowed for analysis of workflow, ongoing monitoring and evaluation that aided in establishing a communication strategy, and development of cancer-specific education for patients and health care providers. From April 2016 to March 2018, 22,137 new patients were eligible for screening. Among those new patients, 13,617 (62%) were screened, with 1382 (10%) being current smokers and 532 (4%) having recently quit (within 6 months). Of the current smokers and those who had recently quit, all were advised to quit or to stay smoke-free, and 380 (20%) accepted referral to a sc counselling service. Conclusions: Here, we provide a comprehensive practice blueprint for the implementation of digitally based sc programs as a standard of care within comprehensive cancer centres with high patient volumes

Reporting of tobacco use and tobacco-related analyses in cancer cooperative group clinical trials: a systematic scoping review.

BACKGROUND: Continued smoking after a diagnosis of cancer negatively impacts cancer outcomes, but the impact of tobacco on newer treatments options is not well established. Collecting and evaluating tobacco use in clinical trials may advance understanding of the consequences of tobacco use on treatment modalities, but little is known about the frequency of reporting and analysis of tobacco use in cancer cooperative clinical trial groups. PATIENTS AND METHODS: A comprehensive literature search was conducted to identify cancer cooperative group clinical trials published from January 2017-October 2019. Eligible studies evaluated either systemic and/or radiation therapies, included ≥100 adult patients, and reported on at least one of: overall survival, disease/progression-free survival, response rates, toxicities/adverse events, or quality-of-life. RESULTS: A total of 91 studies representing 90 trials met inclusion criteria with trial start dates ranging from 1995 to 2015 with 14% involving lung and 5% head and neck cancer patients. A total of 19 studies reported baseline tobacco use; 2 reported collecting follow-up tobacco use. Seven studies reported analysis of the impact of baseline tobacco use on clinical outcomes. There was significant heterogeneity in the reporting of baseline tobacco use: 7 reported never/ever status, 10 reported never/ex-smoker/current smoker status, and 4 reported measuring smoking intensity. None reported verifying smoking status or second-hand smoke exposure. Trials of lung and head and neck cancers were more likely to report baseline tobacco use than other disease sites (83% versus 6%, P < 0.001). CONCLUSIONS: Few cancer cooperative group clinical trials report and analyze trial participants' tobacco use. Significant heterogeneity exists in reporting tobacco use. Routine standardized collection and reporting of tobacco use at baseline and follow-up in clinical trials should be implemented to enable investigators to evaluate the impact of tobacco use on new cancer therapies

Contribution of Patient and Physician Factors to Cardiac Rehabilitation Referral: A Prospective Multi-Level Study

Introduction: Cardiac rehabilitation (CR) is a proven means of reducing mortality, yet is grossly under-utilized. This is due to both health system and patient-level factors, issues which have yet to be investigated concurrently. This study utilized a hierarchical design to examine physician and patient-level factors affecting verified CR referral. Methods: This was a prospective study using a multi-level design of 1490 CAD outpatients nested within 97 cardiology practices. Cardiologists completed a survey regarding CR attitudes. Outpatients were surveyed prospectively to assess sociodemographic, clinical, behavioral, psychosocial and health system factors affecting CR referral. CR referral was verified 9 months later with 40 sites. Results: 550 (43.4%) outpatients were referred to CR. Factors affecting verified referral in mixed logistic regression analyses were positive physician perceptions of CR (p=.03), shorter patient distance to the closest CR site (p=.003), fewer perceived CR barriers (p<.001) and personal control (p=.001). Conclusions: Both physician and patient factors play a role in CR referral. Not only is referral to CR affected by physician perceptions of such programs, including quality and perceived benefit, but is affected by patient’s perceived CR barriers which they may convey during CR discussions. Distance to CR was related to physician referral practice, despite the availability of home-based services