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The objective of the study is to review the literature for studies that assessed the concordance of financial conflicts of interest disclosures with payments’ databases and evaluate their methods. We conducted a systematic survey of the health literature to identify eligible studies. We searched both Medline and EMBASE up to February 2017. We conducted study selection, data abstraction, and methodological quality assessment in duplicate and independently using standardized forms. We subcategorized ‘nonconcordant disclosures’ as either ‘partially nonconcordant’ or ‘completely nonconcordant’. The main outcome was the percentage of authors with ‘nonconcordant’ disclosures. We summarized results by three levels of analysis: authors, companies, and studies. We identified 27 eligible journal articles. The top two types of documents assessed were published articles (n = 13) and published guidelines (n = 9). The most commonly used payment database was the Open Payments Database (n = 16). The median percentage of authors with ‘nonconcordant’ disclosures was 81%; the median percentage was 43% for ‘completely nonconcordant’ disclosures. The percentage of ‘nonconcordant’ conflict of interest (COI) reporting by companies varied between 23% and 85%. The methods of concordance assessment, as well as the labeling and definitions of assessed outcomes varied widely across the included studies. We judged three of the included studies as high-quality studies. Underreporting of health science researchers’ financial COIs is pervasive. Studies assessing COI underreporting suffer from a number of limitations that could have overestimated their findings.

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting Diagnostic Accuracy (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

We examine the relationship between disclosure of nonfinancial information and analyst forecast accuracy using firm-level data from 31 countries. We use the issuance of stand-alone corporate social responsibility (CSR) reports to proxy for disclosure of nonfinancial information. We find that the issuance of stand-alone CSR reports is associated with lower analyst forecast error. This relationship is stronger in countries that are more stakeholder-oriented—i.e., in countries where CSR performance is more likely to affect firm financial performance. The relationship is also stronger for firms and countries with more opaque financial disclosure, suggesting that issuance of stand-alone CSR reports plays a role complementary to financial disclosure. These results hold after we control for various factors related to firm financial transparency and other potentially confounding institutional factors. Collectively, our findings have important implications for academics and practitioners in understanding the function of CSR disclosure in financial markets.

Standalone corporate social responsibility (CSR) reports vary considerably in the content of information released due to their voluntary nature. In this study, we develop a disclosure score based on the tone, readability, length, and the numerical and horizon content of CSR report narratives, and examine the relationship between the CSR disclosure scores and analyst forecasts. We find that CSR reporters with high disclosure scores are associated with more accurate forecasts, whereas low score CSR reporters are not associated with more accurate forecasts than firms who do not issue CSR reports. The findings are robust to controlling for firm characteristics including CSR activity ratings and financial narratives. The findings are driven by experienced CSR reporters rather than first-time CSR reporters. Together, our findings suggest that the content of CSR reports helps to improve analyst forecast accuracy, and this relationship is more pronounced for CSR reports with more substantial content.

Large-scale collection of data could help curb the COVID-19 pandemic, but it should not neglect privacy and public trust. Best practices should be identified to maintain responsible data-collection and data-processing standards at a global scale.

This study examines the association between corporate social responsibility (CSR) and management forecast accuracy. Using data from 1995 to 2009, we find that firms provide more accurate earnings forecasts in the face of CSR activities. We also find that the positive association between CSR and management forecast accuracy is only present for the post-regulation period of 2001-2009, after the introduction of disclosure regulations intended to mitigate managers' opportunistic behavior. These findings are consistent with the notion that managers strive to improve the quality of financial disclosure following superior CSR performance in the recent period.

This study examines the impact of corporate site visits on analysts’ forecast accuracy based on a sample of such visits to Chinese listed firms during 2009–2012. We find that analysts who conduct visits (“visiting analysts”) have a greater increase in forecast accuracy than other analysts. Consistent with the notion that site visits facilitate analysts’ information acquisition through observing firms’ operations, we find that the results are stronger for manufacturing firms, firms with more tangible assets, and firms with more concentrated business lines. Moreover, we find that the effect of a site visit is greater when the site visit is an analyst-only visit, when the current visit is preceded by fewer visits, and when visiting analysts are based far from the visited firms. Furthermore, we find that site visits partially mitigate nonlocal analysts’ information disadvantage. Collectively, these results indicate that site visits are an important information acquisition activity for analysts.

Purpose – The purpose of this paper is to determine the influence and interaction of social networks and personality traits on the self-disclosure behavior of social network site (SNS) users. According to social capital theory and the Big Five personality model, the authors hypothesized that social capital factors would affect the accuracy and amount of self-disclosure behavior and that personality traits would moderate this effect. Design/methodology/approach – A survey was conducted to collect data from 207 SNS users. The questionnaire was administered in university classrooms and libraries and via e-mail. The measurement model and structural model were examined by using LISREL 8.8 and SmartPLS 2.0. Findings – Based on the path analysis, the authors identified several interesting patterns to explain self-disclosure behavior on SNSs. First, the centrality of SNS users has a positive effect on their amount of self-disclosure. Moreover, people who are more extroverted disclose personal information that is more accurate with the level of the cognitive dimension held constant and disclose a greater amount of personal information with the level of the structural dimension held constant. From a practical perspective, the results may provide useful insight for companies operating SNSs. Originality/value – This study analyzed the influence of social capital factors on SNS users’ self-disclosure, as well as the interactions between personality and social capital factors. Specifically, the authors examined six important variables of social capital divided into three dimensions. This research complements current research on SNSs by focusing on SNS users’ motivation to disclose self-related information in addition to information sharing.

Laboratories must validate all assays before they can be used to test patient specimens, but currently there are no evidence-based guidelines regarding validation of immunohistochemical assays. To develop recommendations for initial analytic validation and revalidation of immunohistochemical assays. The College of American Pathologists Pathology and Laboratory Quality Center convened a panel of pathologists and histotechnologists with expertise in immunohistochemistry to develop validation recommendations. A systematic evidence review was conducted to address key questions. Electronic searches identified 1463 publications, of which 126 met inclusion criteria and were extracted. Individual publications were graded for quality, and the key question findings for strength of evidence. Recommendations were derived from strength of evidence, open comment feedback, and expert panel consensus. Fourteen guideline statements were established to help pathology laboratories comply with validation and revalidation requirements for immunohistochemical assays. Laboratories must document successful analytic validation of all immunohistochemical tests before applying to patient specimens. The parameters for cases included in validation sets, including number, expression levels, fixative and processing methods, should take into account intended use and should be sufficient to ensure that the test accurately measures the analyte of interest in specimens tested in that laboratory. Recommendations are also provided for confirming assay performance when there are changes in test methods, reagents, or equipment.