The predictive validity of a computer-assisted career decision-making system: A six-year follow-up

The present study tested the predictive validity of Making Better Career Decisions (MBCD), a computer-assisted career decision-making system. Seventy clients who had used MBCD six years earlier were interviewed by telephone about their present field of study or occupation and the degree of their satisfaction with their occupational choice. The participants were divided into two groups: one consisted of clients whose chosen occupation was on the list of occupations recommended by MBCD, whereas the other consisted of clients whose chosen occupation was not on the recommended list. In the first group, 84% were highly satisfied with their occupational choice and 16% were satisfied to a moderate extent. Among those whose chosen occupation was not on the recommended list, only 38% were highly satisfied with their chosen occupation, 44% were satisfied to a moderate extent, and 18% were dissatisfied with their choice. These findings support the predictive validity of MBCD. Implications for counseling and computer-assisted career guidance systems are discussed.     

European Management Selection Methods: A Comparison of Five Countries

There is some disagreement in the recent literature on how similar or different are the methods used to select employees in different European countries. The confusion comes about in part because different samples and questions have been used in different countries to investigate this issue, making comparison between countries very difficult. This study investigates managerial selection methods in three members of the European Community, Belgium, Germany and Italy, using the same questionnaire and sample characteristics previously used in Britain and France. This allows a direct comparison between the five countries. The samples comprised 250 companies randomly drawn from the top 1,000 in each country. Questionnaires sent to the companies asked a range of questions concerning the frequency of use of selection methods and attitudes towards their use. Results show major differences in frequency of use of different methods. Some of these differences are: British and German companies tend to use assessment centres much more often than other countries, while Germany and Italy are relatively infrequent users of psychological tests. Companies in the Flemish (Dutch speaking) part of Belgium are the most likely to use biodata, while their French speaking compatriots are similar to the French in their liking for graphology. Both Belgium and France make much less use of references than do Britain, Germany and Italy. Results suggest that harmonization of selection practice in Europe is a long way off. Habit, tradition and culture determine the choice of selection method much more than do the relative predictive validities of the techniques.     

Predictive coding explains binocular rivalry: an epistemological review

Binocular rivalry occurs when the eyes are presented with different stimuli and subjective perception alternates between them. Though recent years have seen a number of models of this phenomenon, the mechanisms behind binocular rivalry are still debated and we still lack a principled understanding of why a cognitive system such as the brain should exhibit this striking kind of behaviour. Furthermore, psychophysical and neurophysiological (single cell and imaging) studies of rivalry are not unequivocal and have proven difficult to reconcile within one framework. This review takes an epistemological approach to rivalry that considers the brain as engaged in probabilistic unconscious perceptual inference about the causes of its sensory input. We describe a simple empirical Bayesian framework, implemented with predictive coding, which seems capable of explaining binocular rivalry and reconciling many findings. The core of the explanation is that selection of one stimulus, and subsequent alternation between stimuli in rivalry occur when: (i) there is no single model or hypothesis about the causes in the environment that enjoys both high likelihood and high prior probability and (ii) when one stimulus dominates, the bottom-up, driving signal for that stimulus is explained away while, crucially, the bottom-up signal for the suppressed stimulus is not, and remains as an unexplained but explainable prediction error signal. This induces instability in perceptual dynamics that can give rise to perceptual transitions or alternations during rivalry.     

Predictive validity of the medical specialty preference inventory

Medical schools can assist students by providing them with quality career counseling to help them choose a medical specialty. Many schools use interest inventories to help identify students’ specialty interests. This study examined the predictive validity of one such inventory, the Medical Specialty Preference Inventory (MSPI). In a longitudinal design, we used discriminant function analysis to examine how well students’ scores on the MSPI fit their chosen medical specialty one year later. The MSPI correctly predicted students’ future medical specialty choice 58.1% of the time. These results can help career advisors interpret MSPI scores, and identify students’ most likely medical specialty choice, as well as their second most likely choice.     

Predictive coding: an account of the mirror neuron system

Is it possible to understand the intentions of other people by simply observing their actions? Many believe that this ability is made possible by the brain’s mirror neuron system through its direct link between action and observation. However, precisely how intentions can be inferred through action observation has provoked much debate. Here we suggest that the function of the mirror system can be understood within a predictive coding framework that appeals to the statistical approach known as empirical Bayes. Within this scheme the most likely cause of an observed action can be inferred by minimizing the prediction error at all levels of the cortical hierarchy that are engaged during action observation. This account identifies a precise role for the mirror system in our ability to infer intentions from actions and provides the outline of the underlying computational mechanisms.     

Know thy agency in predictive coding: Meta-monitoring over forward modeling

Though the computation of agency is thought to be based on prediction error, it is important for us to grasp our own reliability of that detected error. Here, the current study shows that we have a meta-monitoring ability over our own forward model, where the accuracy of motor prediction and therefore of the felt agency are implicitly evaluated. Healthy participants (N = 105) conducted a simple motor control task and SELF or OTHER visual feedback was given. The relationship between the accuracy and confidence in a mismatch detection task and in a self-other attribution task was examined. The results suggest an accuracy-confidence correlation in both tasks, indicating our meta-monitoring ability over such decisions. Furthermore, a statistically identified group with low accuracy and low confidence was characterized as higher schizotypal people. Finally, what we can know about our own forward model and how we can know it is discussed.     

Analysis of distractor difficulty in multiple-choice items

Two psychometric models are presented for evaluating the difficulty of the distractors in multiple-choice items. They are based on the criterion of rising distractor selection ratios, which facilitates interpretation of the subject and item parameters. Statistical inferential tools are developed in a Bayesian framework: modal a posteriori estimation by application of an EM algorithm and model evaluation by monitoring posterior predictive replications of the data matrix. An educational example with real data is included to exemplify the application of the models and compare them with the nominal categories model.This research was supported by the DGI grant BSO2002-01485.I would like to thank Eric Maris and Vicente Ponsoda for their advice, Juan Botella for providing the data for the empirical application, and three anonymous reviewers for their comments that were essential for improving the quality of the paper.     

Predictors for re-employment success in newly unemployed: A prospective cohort study

The aim of the present study was to examine which personal and situational factors affect reemployment success in persons in their first year of unemployment. In a prospective cohort study with a one-year follow-up, we investigated a sample of 3618 subjects who became unemployed. A survey was sent to all participants, including personal and situational factors, based on Wanberg's model, the Theory of Planned Behavior model and the Valence–Instrumentality–Expectancy model. Our results showed that ten key-factors predicted re-employment success in the first year after becoming unemployed. Knowing these factors, and in particular those which are amenable to change through any intervention program, may help to develop effective intervention strategies for those who facilitate reemployment in order to shorten the duration of unemployment.     

The role of prediction in mental processing: A process approach

Although prediction plays a prominent role in mental processing, we have only limited understanding of how the brain generates and employs predictions. This paper develops a theoretical framework in three steps. First I propose a process model that describes how predictions are produced and are linked to behavior. Subsequently I describe a generative mechanism, consisting of the selective amplification of neural dynamics in the context of boundary conditions. I hypothesize that this mechanism is active as a process engine in every mental process, and that therefore each mental process proceeds in two stages: (i) the formation of process boundary conditions; (ii) the bringing about of the process function by the operation – within the boundary conditions – of a relatively ‘blind’ generative process. Thirdly, from this hypothesis I derive a strategy for describing processes formally. The result is a multilevel framework that may also be useful for studying mental processes in general.     

The felt presence of other minds: Predictive processing,counterfactual predictions,and mentalising in autism

The mental states of other people are components of the external world that modulate the activity of our sensory epithelia. Recent probabilistic frameworks that cast perception as unconscious inference on the external causes of sensory input can thus be expanded to enfold the brain’s representation of others’ mental states. This paper examines this subject in the context of the debate concerning the extent to which we have perceptual awareness of other minds. In particular, we suggest that the notion of perceptual presence helps to refine this debate: are others’ mental states experienced as veridical qualities of the perceptual world around us? This experiential aspect of social cognition may be central to conditions such as autism spectrum disorder, where representations of others’ mental states seem to be selectively compromised. Importantly, recent work ties perceptual presence to the counterfactual predictions of hierarchical generative models that are suggested to perform unconscious inference in the brain. This enables a characterisation of mental state representations in terms of their associated counterfactual predictions, allowing a distinction between spontaneous and explicit forms of mentalising within the framework of predictive processing. This leads to a hypothesis that social cognition in autism spectrum disorder is characterised by a diminished set of counterfactual predictions and the reduced perceptual presence of others’ mental states.