Venita DePuy

Measuring trust in medical researchers.

Background:Concern is widespread that the public’s and participants’ trust in medical research is threatened, but few empirical measures of research trust exist. This project aims to enable more rigorous study of researcher trust by developing and testing appropriate survey measures. Methods:Survey items were developed based on a conceptual model of the primary domains of researcher trust (safety, fidelity, honesty, global trust). Pilot testing was conducted on a regional convenience sample of adults (n = 124). Exploratory factor analyses of the data were performed, and an item selection procedure reduced the number of survey questions. A final set of 12 items was validated, and a 4-item short version of the researcher trust scale was selected and tested in a national web-based survey of asthma and diabetes patients (n = 3623). Further factor analysis and validation were performed on this larger sample. Results:Both the full and short scales have a single-factor structure with acceptable internal reliability (alphas of 0.87 [12 items] and 0.72 [4 items]). Trust in physician researchers and trust in medical researchers generally were found not to be separate constructs. In the national sample, the short scale was positively associated with better health status, prior participation in medical research, and willingness to participate in a hypothetical medical research study, and negatively associated with African-American race and higher education. Conclusions:Trust in medical researchers is a measurable single-factor construct including trust in safety, researcher fidelity, and honesty. This new scale provides an empirical tool for informing the ethics and public policy of medical research.

Effects of disclosing financial interests on attitudes toward clinical research.

BackgroundThe effects of disclosing financial interests to potential research participants are not well understood.ObjectiveTo examine the effects of financial interest disclosures on potential research participants’ attitudes toward clinical research.Design and ParticipantsComputerized experiment conducted with 3,623 adults in the United States with either diabetes mellitus or asthma, grouped by lesser and greater severity. Respondents read a description of a hypothetical clinical trial relevant to their diagnosis that included a financial disclosure statement. Respondents received 1 of 5 disclosure statements.MeasurementsWillingness to participate in the hypothetical clinical trial, relative importance of information about the financial interest, change in trust after reading the disclosure statement, surprise regarding the financial interest, and perceived effect of the financial interest on the quality of the clinical trial.ResultsWillingness to participate in the hypothetical clinical trial did not differ substantially among the types of financial disclosures. Respondents viewed the disclosed information as less important than other factors in deciding to participate. Disclosures were associated with some respondents trusting the researchers less, although trust among some respondents increased. Most respondents were not surprised to learn of financial interests. Researchers owning equity were viewed as more troubling than researchers who were compensated for the costs of research through per capita payments.ConclusionsAside from a researcher holding an equity interest, the disclosure to potential research participants of financial interests in research, as recommended in recent policies, is unlikely to affect willingness to participate in research.

Understanding of an aggregate probability statement by patients who are offered participation in Phase I clinical trials.

There is concern that patients with poor numeracy may have difficulty understanding the information necessary to make informed treatment decisions. The authors sought to characterize a special form of numeracy among patients with advanced cancer who were offered participation in Phase I oncology clinical trials.

Racial differences in pain during 1 year among women with metastatic breast cancer: a hazards analysis of interval-censored data.

Longitudinal tumor‐specific studies of cancer pain across the disease trajectory provide insight into the course of pain. Information on pain predictors refines our understanding of patients with greatest distress and need.

A confirmatory factor analytic study of the Posttraumatic Growth Inventory among a sample of racially diverse college students

Aims: The primary aim of the study was to confirm the five-factor structure of Tedeschi and Calhouns () Posttraumatic Growth Inventory (PTGI). A secondary aim of this study was to explore the potential usefulness of the PTGI among populations that experience parentification – a common form of childhood neglect and adversity. Method: The PTGI was administered to a sample of 143 college students with a history of various levels of parentification. Results: The resulting data were subjected to confirmatory factor analysis. The goodness-of-fit indices for the five-factor model indicated a moderate fit with the current sample. However, a five-factor, 18-item model produced a more optimal fit than Tedeschi and Calhouns five-factor, 21-item PTGI. Conclusions: The studys findings suggest that the PTGI appears to be a useful assessment inventory for mental health practitioners in measuring globally the resources an individual might have following the adversity of parentification.

An Exploration of Relative Health Stock in Advanced Cancer Patients

Objective. The authors sought to empirically test whether relative health stock, a measure of patients’ sense of loss in their health due to illness, influences the treatment decisions of patients facing life-threatening conditions. Specifically, they estimated the effect of relative health stock on advanced cancer patients’ decisions to participate in phase I clinical trials. Method. A multicenter study was conducted to survey 328 advanced cancer patients who were offered the opportunity to participate in phase I trials. The authors asked patients to estimate the probabilities of therapeutic benefits and toxicity, their relative health stock, risk preference, and the importance of quality of life. Results. Controlling for health-related quality of life, an increase in relative health stock by 10 percentage points reduced the odds of choosing to participate in a phase I trial by 16% (odds ratio = 0.84, 95% confidence interval = 0.72, 0.97). Conclusion. Relative health stock affects advanced cancer patients’ treatment decisions.

Primary Care Physicians' Evaluation and Treatment of Depression Results of an Experimental Study Using Video Vignettes

Little is known about how patient and primary care physician characteristics are associated with quality of depression care. The authors conducted structured interviews of 404 randomly selected primary care physicians after their interaction with CD-ROM vignettes of actors portraying depressed patients. Vignettes varied along the dimensions of medical comorbidity, attributions regarding the cause of depression, style, race/ethnicity, and gender. Results show that physicians showed wide variation in treatment decisions; for example, most did not inquire about suicidal ideation, and most did not state that they would inform the patient that there can be a delay before an antidepressant is therapeutic. Several physician characteristics were significantly associated with management decisions. Notably, physician age was inversely correlated with a number of quality-of-care measures. In conclusion, quality of care varies among primary care physicians and appears to be associated with physician characteristics to a greater extent than patient characteristics.

Mediating and Moderating Effects of Differentiation of Self on Depression Symptomatology in a Rural Community Sample

Differentiation of self—a core construct of Bowen’s family systems theory, which represents psychological health and healthy functioning—was examined as a possible predictor of depression and as a mediator and moderator of the relation between family conflict (F-CON) and depression symptomatology (DEP). A total of 60 racially diverse adults (M = 41.20, SD = 8.53) from a rural community participated. All data were obtained from standardized self-report questionnaires measuring family variables (F-CON and differentiation of self) and psychological outcome (DEP). F-CON and differentiation of self were correlated with and predictive of DEP. A multivariate, multiple regression model revealed that differentiation of self partially mediated the effects of F-CON on DEP. However, results from a hierarchical regression model showed that differentiation of self did not moderate the relation between F-CON and DEP. Taken together, these preliminary findings provide evidence of the importance of the associations between family systemic factors (F-CON and differentiation of self) and DEP. Implications and directions for future research and family counseling are put forward.

Evidence-Based Therapies and Mortality in Patients Hospitalized in December with Acute Myocardial Infarction

Context In the United States, the outcomes of patients who have myocardial infarctions (MIs) in December are worse than the outcomes during other months. Some attribute this result to less use of evidence-based therapies during the holiday season. Contribution From January 1994 through February 1996, Medicare beneficiaries hospitalized with acute MI in December received evidence-based therapies at the same rate as patients hospitalized in other months but had slightly higher 30-day mortality rates (21.7% vs. 20.1%; P< 0.001). Implications Worse outcomes in patients with MI during December are not attributable to less frequent use of evidence-based therapies. The Editors The incidence of acute myocardial infarction (MI) in the United States is higher during the winter months (1), and patients hospitalized with acute MI in the winter, particularly during the December holiday season, have higher mortality (2). The cause of this increase in mortality is not understood. In addition, a recent study documented an increase in daily mortality (after adjustment for trends and seasonal factors) for patients with cardiac and noncardiac diseases who were hospitalized during the Christmas and New Years holiday season (3). To our knowledge, there has been no analysis of the level of care provided to patients hospitalized during the winter holidays and its relationship to mortality. Therefore, we examined the use of evidence-based therapies and 30-day mortality rates in patients hospitalized in December with acute MI. Methods Source of Data Data were from the Cooperative Cardiovascular Project, a program of the Centers for Medicare & Medicaid Services to improve quality of care for Medicare beneficiaries hospitalized with acute MI. The data set contains records for patients discharged between January 1994 and February 1996 from nonfederal, acute care hospitals in the United States with a primary diagnosis of acute MI (International Classification of Diseases, Ninth Revision, Clinical Modification code 410). Prespecified demographic, clinical, and treatment variables were abstracted from hospital discharge records. Charts were reabstracted randomly to confirm the validity of the database, resulting in overall variable agreement of 95% (4). Quality indicators for processes of care for acute MI were developed by the Centers for Medicare & Medicaid Services as reported by Marciniak and associates (4). These indicators include use of aspirin, -blockers, and reperfusion therapy (that is, thrombolytic treatment or primary percutaneous coronary intervention). The indicators have been validated and incorporated into national guidelines of care (5, 6). The institutional review board of Duke University Medical Center approved this study. Study Sample We limited our analysis to patients 65 years of age and older with a confirmed diagnosis of MI. Myocardial infarction was defined as elevation of creatine kinaseMB level greater than 5%, elevation of lactate dehydrogenase levels with isoenzyme reversal, or 2 of the following: chest pain in the previous 48 hours, 2-fold elevation in creatine kinase level, or electrocardiographic changes (ST-segment elevation or new Q waves) (4). For patients with multiple admissions for MI or readmissions during the study period, only data from the first admission were used. We also excluded patients with invalid ZIP codes, patients hospitalized outside the 50 states or the District of Columbia, patients transferred to another acute care facility, and patients in hospitals with fewer than 10 admissions during any calendar year. The 4 states that participated in the original Cooperative Cardiovascular Project quality improvement project were excluded from the analysis. Statistical Analysis We defined the month of December as the period of interest and compared the care and outcomes of patients hospitalized in December with the care and outcomes of patients hospitalized during the remainder of the year. To test for differences between patients hospitalized in December and those hospitalized during other months, we developed bivariate regression models using generalized estimating equations to account for the clustered structure of the sample (that is, patients clustered within hospitals). To test for differences in Killip class at admission, we used the Wilcoxon rank-sum test. We developed multivariable logistic regression models using generalized estimating equations to examine associations between admission during December and both the use of evidence-based therapies and 30-day mortality. We controlled for demographic characteristics, socioeconomic status, clinical characteristics, ideal patient status (that is, no documented contradictions to each of the evidence-based therapies), hospital characteristics, and physician characteristics, and accounted for the clustering of patients within hospitals (7, 8). To control confounding by center, we divided the time-of-year variable into within-center and among-center components (9). A binary variable indicating hospitalization during December measured the within-center component, and a variable measuring the proportion of all patients hospitalized in December for each center represented the among-center component. For the logistical regression model examining 30-day mortality, we also controlled for the use of evidence-based therapies at admission. We also developed a multivariable logistic regression model using generalized estimating equations to examine the association between admission during the month of December and 30-day mortality, controlling for demographic characteristics, socioeconomic status, clinical characteristics, ideal patient status (that is, no documented contradictions to each of the evidence-based therapies), hospital characteristics, and physician characteristics, and accounting for the clustered structure of the sample (7, 8). In addition, we controlled for confounding by center (9) and the use of evidence-based therapies at admission. We report adjusted and unadjusted use of evidence-based therapies and 30-day mortality. Role of the Funding Source No funding was received for this study. Results The study involved 127959 Medicare beneficiaries. Table 1 gives baseline characteristics of patients hospitalized in December and patients hospitalized during the rest of the year. Although patients hospitalized in December were older, the 2 groups were similar in sex, socioeconomic status, history of hypertension, systolic blood pressure at admission, and rates of anterior infarctions. Table 1 also shows hospital and physician characteristics. Patients hospitalized in December were as likely as other patients to be cared for by board-certified physicians, were more likely to be cared for by an internist, and were more likely to be admitted to a teaching hospital. However, patients hospitalized in December were less likely than other patients to be admitted to a hospital with cardiac catheterization facilities or to be cared for by a cardiologist. Table 1. Patient, Hospital, and Physician Characteristics Table 2 compares the use of evidence-based therapies among patients hospitalized in December and patients hospitalized during the rest of the year. Patients hospitalized in December were less likely than other patients to receive aspirin at admission (77.5% vs. 78.9%; P< 0.001) and to have primary percutaneous coronary intervention (14.2% vs. 16.1%; P< 0.001). When we controlled for patient, physician, and hospital characteristics, patient clustering within hospitals, and confounding by center, the use of evidence-based therapy was not statistically significantly different for patients hospitalized in December as compared with those hospitalized during the rest of the year. Finally, unadjusted 30-day mortality was higher in patients hospitalized in December than in other patients (21.7% vs. 20.1%; P< 0.001). After adjustment for patient, hospital, and physician characteristics, patient clustering within hospitals, and confounding by center, 30-day mortality remained statistically significantly higher in patients hospitalized in December than in patients hospitalized during the rest of the year (Table 3). Table 2. Use of Evidence-Based Therapy according to Month of Admission Table 3. Thirty-Day Mortality according to Month of Admission Discussion Patients hospitalized in December with acute MI had higher 30-day mortality, even after adjustment for patient, physician, and hospital characteristics; for clustering of patients within hospitals; for confounding by hospital; and for the use of evidence-based therapies. A previous study reported increased rates of MI and mortality during winter months (1). This relationship was independent of geographic region, suggesting that the increase in the incidence of MI could not be explained by climate-related factors alone. Another study has raised the possibility that the increase in winter mortality rates is related to the December holiday season. Kloner and colleagues (2) found that cardiovascular deaths in Los Angeles County, California, peaked during the November and December holidays. They suggested that this increase in mortality may have been related to emotional stresses or behavioral changes associated with the holidays. However, because they lacked descriptors of patient care and illness severity, they could not further examine the cause of the increase in mortality (2). To our knowledge, no previous study has examined the use of evidence-based therapies as a potential mechanism for mortality differences during December, a month of decreased staffing at most hospitals (10). However, several studies have found associations between the level of hospital staffing and patient outcomes (11-14). Bell and Redelmeier (11) found that patients with various medical conditions were more likely to die in the hospital if they had been admitted on a weekend rather than on a weekday. They attributed some of this inc