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Oddi's 24-item Continuing Learning Inventory (OCLI) is an instrument that has been used frequently to measure self-directed learning. Although three previous studies have assessed OCLI's underlying dimensions, the conflicting results of those studies prompted this further investigation that used a series of factor analyses of the 250 responses from University of Toronto undergraduate medical students. Although exploratory factor analyses yielded results consistent with Oddi's empirically derived three-factor model, further analyses of the student responses suggested that OCLI's underlying dimensions are better described by four factors. This four-factor model was also identified through confirmatory factor analyses. These four underlying OCLI dimensions--Learning With Others, Learner Motivation/Self-Efficacy/Autonomy, Ability to be Self-Regulating, and Reading Avidity--provide further specificity and insights for examining and better understanding students' self-directed learning.

Introduction: Effective, sustained collaboration between clinical and public health professionals can lead to improved individual and population health. The concept of clinical public health promotes collaboration between clinical medicine and public health to address complex, real-world health challenges. In this commentary, we describe the concept of clinical public health, the types of complex problems that require collaboration between individual and population health, and the barriers towards and applications of clinical public health that have become evident during the COVID-19 pandemic. Rationale: The focus of clinical medicine on the health of individuals and the aims of public health to promote and protect the health of populations are complementary. Interdisciplinary collaborations at both levels of health interventions are needed to address complex health problems. However, there is a need to address the disciplinary, cultural and financial barriers to achieving greater and sustained collaboration. Recent successes, particularly during the COVID-19 pandemic, provide a model for such collaboration between clinicians and public health practitioners. Conclusion: A public health approach that fosters ongoing collaboration between clinical and public health professionals in the face of complex health threats will have greater impact than the sum of the parts. [ABSTRACT FROM AUTHOR]

While controversies regarding optimal breast cancer screening modalities, screening start and end ages, and screening frequencies continue to exist, additional population-based randomized trials are unlikely to be initiated to examine these concerns. Simulation models have been used to evaluate the efficacy and effectiveness of various breast cancer screening strategies, however these models were all developed using US data. Currently, there is a need to examine the optimal screening and treatment policies in the Canadian context. In this commentary, we discuss the current controversies pertaining to breast cancer screening, and describe the fundamental components of a simulation model, which can be used to inform breast cancer screening and treatment policies. Key words: Breast cancer; screening controversies; screening strategies; simulation; model components Des controverses persistent au sujet des modalites optimales de depistage du cancer du sein, de l'age de debut et de fin du depistage, et de la frequence du depistage, mais on a peu tendance a lancer d'autres essais aleatoires en population pour examiner ces questions. Des modeles de simulation ont ete utilises pour evaluer l'utilite et l'efficacite de diverses strategies de depistage du cancer du sein, mais ces modeles ont tous ete elabores a l'aide de donnees des Etats-Unis. Il faudrait aujourd'hui examiner les politiques de depistage et de traitement optimales dans un contexte canadien. Dans notre commentaire, nous expliquons les controverses actuelles afferentes au depistage du cancer du sein et nous decrivons les composants fondamentaux d'un modele de simulation pouvant servir a eclairer les politiques de depistage et de traitement du cancer du sein. Mots cles: tumeurs du sein; controverses et dissensions (depistage); strategies de depistage; simulation; composants de modele La traduction du resume se trouve a la fin de l'article. Can J Public Health 2012;103(6):417-19., In 2011, an estimated 23,400 Canadian women developed breast cancer and approximately 5,100 women died of the disease, making breast cancer the second most commonly occurring cancer and the second [...]

Clostridium difficile infection (CDI) has emerged as a major health care-associated infection; incidence, hospitalizations, and mortality rates are increasing (1,2). Reported case-fatality rates are 6%-30% and seem to be rising [...]

Abstract Background Evaluating the cost-effectiveness of breast cancer screening requires estimates of the absolute risk of breast cancer, which is modified by various risk factors. Breast cancer incidence, and thus mortality, is altered by the occurrence of competing events. More accurate estimates of competing risks should improve the estimation of absolute risk of breast cancer and benefit from breast cancer screening, leading to more effective preventive, diagnostic, and treatment policies. We have previously described the effect of breast cancer risk factors on breast cancer incidence in the presence of competing risks. In this study, we investigate the association of the same risk factors with mortality as a competing event with breast cancer incidence. Methods We use data from the Canadian National Breast Screening Study, consisting of two randomized controlled trials, which included data on 39 risk factors for breast cancer. The participants were followed up for the incidence of breast cancer and mortality due to breast cancer and other causes. We stratified all-cause mortality into death from other types of cancer and death from non-cancer causes. We conducted separate analyses for cause-specific mortalities. Results We found that “age at entry” is a significant factor for all-cause mortality, and cancer-specific and non-cancer mortality. “Menstruation length” and “number of live births” are significant factors for all-cause mortality, and cancer-specific mortality. “Ever noted lumps in right/left breasts” is a factor associated with all-cause mortality, and non-cancer mortality. Conclusions For proper estimation of absolute risk of the main event of interest common risk factors associated with competing events should be identified and considered.

Abstract Background Improvements in the quality of health care services are often measured using data present in medical records. Electronic Medical Records (EMRs) contain potentially valuable new sources of health data. However, data quality in EMRs may not be optimal and should be assessed. Data reliability (are the same data elements being measured over time?) is a prerequisite for data validity (are the data accurate?). Our objective was to measure the reliability of data for preventive services in primary care EMRs during the transition to EMR. Methods Our data sources were randomly selected eligible patients’ medical records and data obtained from provincial administrative datasets. Eighteen community-based family physicians in Toronto, Ontario that implemented EMRs starting in 2006 participated in this study. We measured the proportion of patients eligible for a service (Pap smear, screening mammogram or influenza vaccination) that received the service. We compared the change in rates of selected preventive services calculated from the medical record audits with the change in administrative datasets. Results In the first year of EMR use (2006) services decreased by 8.7% more (95% CI −11.0%– − 6.4%, p p = 0.05) in the medical record audits during the second year of EMR use (2007). Conclusion There were differences between the change measured through medical record audits and administrative datasets. Problems could include difficulties with organizing new data entry processes as well as continued use of both paper and EMRs. Data extracted from EMRs had limited reliability during the initial phase of EMR implementation. Unreliable data interferes with the ability to measure and improve health care quality

Background. Modeling breast cancer progression and the effect of various risk is helpful in deciding when a woman should start and end screening, and how often the screening should be undertaken. Methods. We modeled the natural progression of breast cancer using a hidden Markov process, and incorporated the effects of covariates. Patients are women aged 50–59 (older) and 40–49 (younger) years from the Canadian National Breast Screening Studies. We included prevalent cancers, estimated the screening sensitivities and rates of over-diagnosis, and validated the models using simulation. Results. We found that older women have a higher rate of transition from a healthy to preclinical state and other causes of death but a lower rate of transition from preclinical to clinical state. Reciprocally, younger women have a lower rate of transition from a healthy to preclinical state and other causes of death but a higher rate of transition from a preclinical to clinical state. Different risk factors were significant for the age groups. The mean sojourn times for older and younger women were 2.53 and 2.96 years, respectively. In the study group, the sensitivities of the initial physical examination and mammography for older and younger women were 0.87 and 0.81, respectively, and the sensitivity of the subsequent screens were 0.78 and 0.53, respectively. In the control groups, the sensitivities of the initial physical examination for older and younger women were 0.769 and 0.671, respectively, and the sensitivity of the subsequent physical examinations for the control group aged 50–59 years was 0.37. The upper-bounds for over-diagnosis in older and younger women were 25% and 27%, respectively. Conclusions. The present work offers a basis for the better modeling of cancer incidence for a population with the inclusion of prevalent cancers. [ABSTRACT FROM AUTHOR]

We thank Corber, (1) Dunkley (2) and Moloughney (3) for their thoughtful responses to our commentary, (4) with each further expanding the understanding and appreciation of public health medicine's past, [...]

The article announces that physician Flo Witte will be recognized with the American Medical Writers Association's 2016 Harold Swanberg Distinguished Service Award.

Oddi's 24-item Continuing Learning Inventory (OCLI) is an instrument that has been used frequently to measure self-directed learning. Although three previous studies have assessed OCLl's underlying dimensions, the conflicting results of those studies prompted this further investigation that used a series of factor analyses of the 250 responses from University of Toronto undergraduate medical students. Although exploratory factor analyses yielded results consistent with Oddi's empirically derived three-factor model, further analyses of the student responses suggested that OCLl's underlying dimensions are better described by four factors. This four-factor model was also identified through confirmatory factor analyses. These four underlying OCLl dimensions—Learning With Others, Learner Motivation/Self-efficacy/Autonomy, Ability to be Self-Regulating, and Reading Avidity—provide further specificity and insights for examining and better understanding students' self-directed learning. [ABSTRACT FROM AUTHOR]

Presents letters to the editor on a number of medical topics as of January 22, 2002. Breast self-examination; Assessment of the quality of clinical practice guidelines; Gaining a history of illness from a patient.

Coronavirus Disease 2019 (COVID-19) is a global pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While detection of SARS-CoV-2 by polymerase chain reaction with reverse transcription (RT-PCR) is currently used to diagnose acute COVID-19 infection, serological assays are needed to study the humoral immune response to SARS-CoV-2. Anti-SARS-CoV-2 immunoglobulin (Ig)G/A/M antibodies against spike (S) protein and its receptor-binding domain (RBD) were characterized in recovered subjects who were RT-PCR-positive (n = 153) and RT-PCR-negative (n = 55) using an enzyme-linked immunosorbent assay (ELISA). These antibodies were also further assessed for their ability to neutralize live SARS-CoV-2 virus. Anti-SARS-CoV-2 antibodies were detected in 90.9% of resolved subjects up to 180 days post-symptom onset. Anti-S protein and anti-RBD IgG titers correlated (r = 0.5157 and r = 0.6010, respectively) with viral neutralization. Of the RT-PCR-positive subjects, 22 (14.3%) did not have anti-SARS-CoV-2 antibodies; and of those, 17 had RT-PCR cycle threshold (Ct) values > 27. These high Ct values raise the possibility that these indeterminate results are from individuals who were not infected or had mild infection that failed to elicit an antibody response. This study highlights the importance of serological surveys to determine population-level immunity based on infection numbers as determined by RT-PCR. [ABSTRACT FROM AUTHOR]