The implications of unconfounding multisource performance ratings.

The multifaceted structure of multisource job performance ratings has been a subject of research and debate for over 30 years. However, progress in the field has been hampered by the confounding of effects relevant to the measurement design of multisource ratings and, as a consequence, the impact of ratee-, rater-, source-, and dimension-related effects on the reliability of multisource ratings remains unclear. In separate samples obtained from 2 different applications and measurement designs (N1 [ratees] = 392, N1 [raters] = 1,495; N2 [ratees] = 342, N2 [raters] = 2,636), we, for the first time, unconfounded all systematic effects commonly cited as being relevant to multisource ratings using a Bayesian generalizability theory approach. Our results suggest that the main contributors to the reliability of multisource ratings are source-related and general performance effects that are independent of dimension-related effects. In light of our findings, we discuss the interpretation and application of multisource ratings in organizational contexts. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Everything that you have ever been told about assessment center ratings is confounded.

Despite a substantial research literature on the influence of dimensions and exercises in assessment centers (ACs), the relative impact of these 2 sources of variance continues to raise uncertainties because of confounding. With confounded effects, it is not possible to establish the degree to which any 1 effect, including those related to exercises and dimensions, influences AC ratings. In the current study (N = 698) we used Bayesian generalizability theory to unconfound all of the possible effects contributing to variance in AC ratings. Our results show that ≤1.11% of the variance in AC ratings was directly attributable to behavioral dimensions, suggesting that dimension-related effects have no practical impact on the reliability of ACs. Even when taking aggregation level into consideration, effects related to general performance and exercises accounted for almost all of the reliable variance in AC ratings. The implications of these findings for recent dimension- and exercise-based perspectives on ACs are discussed. (PsycINFO Database Record

Pig farmers' perceptions, attitudes, influences and management of information in the decision-making process for disease control.

The objectives of this study were (1) to explore the factors involved in the decision-making process used by pig farmers for disease control and (2) to investigate pig farmers' attitudes and perceptions about different information sources relating to disease control. In 2011 a qualitative study involving 20 face-to-face interviews with English pig farmers was conducted. The questionnaire was composed of three parts. The first part required farmers to identify two diseases they had experienced and which were difficult to recognize and/or control. They were asked to report how the disease problem was recognized, how the need for control was decided, and what affected the choice of control approach. For the latter, a structure related to the Theory of Planned Behaviour was used. Their verbal responses were classified as associated with: (1) attitude and beliefs, (2) subjective norms, or (3) perceived behavioural control (PBC). In the second part, five key sources of information for disease control (Defra, BPEX, research from academia, internet and veterinarians) and the factors related to barriers to knowledge were investigated. Interviews were recorded and transcribed. A qualitative analysis of the text of the interview transcripts was carried out using templates. Drivers for disease control were 'pig mortality', 'feeling of entering in an economically critical situation', 'animal welfare' and 'feeling of despair'. Veterinarians were perceived by several participating farmers as the most trusted information source on disease control. However, in particular non-sustainable situations, other producers, and especially experiences from abroad, seemed to considerably influence the farmers' decision-making. 'Lack of knowledge', 'farm structure and management barriers' and 'economic constrains' were identified in relation to PBC. Several negative themes, such as 'lack of communication', 'not knowing where to look', and 'information bias' were associated with research from academia. This study identified a range of factors influencing the decision-making process for disease control by pig farmers. In addition, it highlighted the lack of awareness and difficult access of producers to current scientific research outputs. The factors identified should be considered when developing communication strategies to disseminate research findings and advice for disease control.

The Academic Backbone: longitudinal continuities in educational achievement from secondary school and medical school to MRCP(UK) and the specialist register in UK medical students and doctors.

BACKGROUND: Selection of medical students in the UK is still largely based on prior academic achievement, although doubts have been expressed as to whether performance in earlier life is predictive of outcomes later in medical school or post-graduate education. This study analyses data from five longitudinal studies of UK medical students and doctors from the early 1970s until the early 2000s. Two of the studies used the AH5, a group test of general intelligence (that is, intellectual aptitude). Sex and ethnic differences were also analyzed in light of the changing demographics of medical students over the past decades. METHODS: Data from five cohort studies were available: the Westminster Study (began clinical studies from 1975 to 1982), the 1980, 1985, and 1990 cohort studies (entered medical school in 1981, 1986, and 1991), and the University College London Medical School (UCLMS) Cohort Study (entered clinical studies in 2005 and 2006). Different studies had different outcome measures, but most had performance on basic medical sciences and clinical examinations at medical school, performance in Membership of the Royal Colleges of Physicians (MRCP(UK)) examinations, and being on the General Medical Council Specialist Register. RESULTS: Correlation matrices and path analyses are presented. There were robust correlations across different years at medical school, and medical school performance also predicted MRCP(UK) performance and being on the GMC Specialist Register. A-levels correlated somewhat less with undergraduate and post-graduate performance, but there was restriction of range in entrants. General Certificate of Secondary Education (GCSE)/O-level results also predicted undergraduate and post-graduate outcomes, but less so than did A-level results, but there may be incremental validity for clinical and post-graduate performance. The AH5 had some significant correlations with outcome, but they were inconsistent. Sex and ethnicity also had predictive effects on measures of educational attainment, undergraduate, and post-graduate performance. Women performed better in assessments but were less likely to be on the Specialist Register. Non-white participants generally underperformed in undergraduate and post-graduate assessments, but were equally likely to be on the Specialist Register. There was a suggestion of smaller ethnicity effects in earlier studies. CONCLUSIONS: The existence of the Academic Backbone concept is strongly supported, with attainment at secondary school predicting performance in undergraduate and post-graduate medical assessments, and the effects spanning many years. The Academic Backbone is conceptualized in terms of the development of more sophisticated underlying structures of knowledge ('cognitive capital' and 'medical capital'). The Academic Backbone provides strong support for using measures of educational attainment, particularly A-levels, in student selection.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies.

BACKGROUND: Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. METHODS: Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. RESULTS: Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. CONCLUSIONS: Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, 'dark matter' and 'dark energy' are posited to balance various theoretical equations, so medical student selection must also have its 'dark variance', whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills.

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools.

BACKGROUND: Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. METHODS: A prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010. RESULTS: UKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments. CONCLUSIONS: This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general.