Kamber Loren Hart

Objective Authorship and number of publications are important criteria used for making decisions about promotions and research funding awards. Given the increase in the number of author positions over the last few decades, this study sought to determine if there had been a shift in the distribution of authorship among those publishing in high-impact academic medical journals over the last 12 years. Design This study analysed the distribution of authorship across 312 222 original articles published in 134 medium-impact to high-impact academic medical journals between 1 January 2008 and 31 December 2019. Additionally, this study compared the trends in author distributions across nine medical specialties and a collection of cross-specialty high-impact journal articles. Primary outcome measures The distribution of authorship was assessed using the Gini coefficient (GC), a widely used measure of economic inequality. Results The overall GC for all articles sampled across the 12-year study period was 0.49, and the GCs for the first and last authorship positions were 0.30 and 0.44, respectively. Since 2008, there was a significant positive correlation between year and GC for the overall authorship position (r=0.99, pConclusion Overall, these data suggest a growing inequality in authorship across authors publishing in high-impact academic medical journals, especially among the highest impact journals. These findings may have implications for processes such as promotions and allocation of research funding that use authorship metrics as key criteria for making decisions.

Background: Although some health care market reforms seek to better engage consumers in purchasing health care services, health consumer behavior remains poorly understood. Objective: This study aimed to characterize the behaviors and sentiment of consumers who attempt to shop for health care services. Methods: We used a semistructured interview guide based on grounded theory and standard qualitative research methods to examine components of a typical shopping process in a sample size of 54 insured adults. All interviews were systematically coded to capture consumer behaviors, barriers to shopping behavior, and sentiments associated with these experiences. Results: Participants most commonly described determining and evaluating options, seeking value, and assessing or evaluating value. In total, 83% (45/54) of participants described engaging in negotiations regarding health care purchasing. The degree of positive sentiment expressed in the interview was positively correlated with identifying and determining the health plan, provider, or treatment options; making the decision to purchase; and evaluating the decision to purchase. Conversely, negative sentiment was correlated with seeking value and making the decision to buy. Conclusions: Consumer shopping behaviors are prevalent in health care purchasing and can be mapped to established consumer behavior models.

Women remain underrepresented in academic medicine, especially among senior faculty.¹ We examined trends in women’s representation as authors of medical journal articles, one key measure of academic success.²

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Although some health care market reforms seek to better engage consumers in purchasing health care services, health consumer behavior remains poorly understood. Objective: This study aimed to characterize the behaviors and sentiment of consumers who attempt to shop for health care services. Methods: We used a semistructured interview guide based on grounded theory and standard qualitative research methods to examine components of a typical shopping process in a sample size of 54 insured adults. All interviews were systematically coded to capture consumer behaviors, barriers to shopping behavior, and sentiments associated with these experiences. Results: Participants most commonly described determining and evaluating options, seeking value, and assessing or evaluating value. In total, 83% (45/54) of participants described engaging in negotiations regarding health care purchasing. The degree of positive sentiment expressed in the interview was positively correlated with identifying and determining the health plan, provider, or treatment options; making the decision to purchase; and evaluating the decision to purchase. Conversely, negative sentiment was correlated with seeking value and making the decision to buy. Conclusions: Consumer shopping behaviors are prevalent in health care purchasing and can be mapped to established consumer behavior models.

Change in risk tolerance is a feature of multiple psychiatric disorders and may contribute to adverse outcomes. We used a probability discounting (PD) task to measure risk-taking behavior among individuals with bipolar disorder (BPAD), major depressive disorder (MDD), schizoaffective disorder (SCAD), and schizophrenia (SCZ). A PD task was administered to 117 patients and 88 healthy controls (HCs), along with a cognitive battery using the Cambridge Neuropsychological Test Automated Battery, and relevant symptomatology scales. We examined differences in PD rates between diagnostic groups, and compared with HCs, while controlling for potential confounding factors including measures of cognitive functioning. Individuals with a diagnosis of BPAD or SCAD/SCZ prefer smaller, more guaranteed rewards rather than larger, less likely rewards as compared with healthy controls (p = .002 and p = .034, respectively). There was no effect of performance on cognitive tasks, antipsychotic treatment, or symptomatology on the rate of probability discounting. This study supports the transdiagnostic measurement of risk-taking behaviors, even when such behaviors are not the primary area of psychopathology. Quantifying risk-taking may enable targeted therapeutic strategies across disorders. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Patients with schizophrenia (SCZ) experience chronic cognitive deficits. Histone deacetylases (HDACs) are enzymes that regulate cognitive circuitry; however, the role of HDACs in cognitive disorders, including SCZ, remains unknown in humans. We previously determined that HDAC2 mRNA levels were lower in dorsolateral prefrontal cortex (DLPFC) tissue from donors with SCZ compared with controls. Here we investigated the relationship between in vivo HDAC expression and cognitive impairment in patients with SCZ and matched healthy controls using [11C]Martinostat positron emission tomography (PET). In a case-control study, relative [11C]Martinostat uptake was compared between 14 patients with SCZ or schizoaffective disorder (SCZ/SAD) and 17 controls using hypothesis-driven region-of-interest analysis and unbiased whole brain voxel-wise approaches. Clinical measures, including the MATRICS consensus cognitive battery, were administered. Relative HDAC expression was lower in the DLPFC of patients with SCZ/SAD compared with controls, and HDAC expression positively correlated with cognitive performance scores across groups. Patients with SCZ/SAD also showed lower relative HDAC expression in the dorsomedial prefrontal cortex and orbitofrontal gyrus, and higher relative HDAC expression in the cerebral white matter, pons, and cerebellum compared with controls. These findings provide in vivo evidence of HDAC dysregulation in patients with SCZ and suggest that altered HDAC expression may impact cognitive function in humans. National Institute of Mental Health (NIMH), Brain and Behavior Foundation, Massachusetts General Hospital (MGH), Athinoula A. Martinos Center for Biomedical Imaging, National Institute of Biomedical Imaging and Bioengineering (NIBIB), NIH Shared Instrumentation Grant Program.