Rebecca Maguire

Making sense of surprise: an investigation of the factors influencing surprise judgments.

Surprise is often defined in terms of disconfirmed expectations, whereby the surprisingness of an event is thought to be dependent on the degree to which it contrasts with a more likely, or expected, outcome. The authors investigated the alternative hypothesis that surprise is more accurately modeled as a manifestation of an ongoing sense-making process. In a series of experiments, participants were given a number of scenarios and rated surprise and probability for various hypothetical outcomes that either confirmed or disconfirmed an expectation. Experiment 1 demonstrated that representational specificity influences the relationship that holds between surprise and probability ratings. Experiment 2 demonstrated that the inclusion of an enabling event lowers surprise ratings for disconfirming outcomes. Experiment 3 explored the reason for this effect, revealing that enabling events lower surprise by reducing uncertainty, thus enhancing ease of integration. Experiment 4 evaluated the contrast hypothesis directly, showing that differences in contrast are not correlated with differences in surprise. These results provide converging support for the view that the level of surprise experienced for an event is related to the difficulty of integrating that event with an existing representation. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Engaging students emotionally: the role of emotional intelligence in predicting cognitive and affective engagement in higher education

ABSTRACT Student engagement is a key predictor of academic performance, persistence and retention in higher education. While many studies have identified how aspects of the college environment influence engagement, fewer have specifically focused on emotional intelligence (EI). In this study, we sought to explore whether EI could predict cognitive and/or affective engagement in a sample of undergraduate psychology students in Ireland. Ninety-one students completed two forms of the student engagement instrument, rating current engagement and retrospective secondary school engagement, along with the trait EI (TEI) questionnaire. After controlling for academic ability, gender and school engagement, multiple regression analyses found TEI to be a positive predictor of both cognitive and affective engagement. Previous academic performance acted as an additional predictor of cognitive engagement, while retrospective affective school engagement predicted current affective engagement. These results suggest that interventions aimed at increasing EI may have positive implications for many aspects of student engagement, and hence performance at third level.

The Influence of Interactional Semantic Patterns on the Interpretation of Noun-Noun Compounds

The CARIN theory (C. L. Gagné & E. J. Shoben, 1997) proposes that people use statistical knowledge about the relations with which modifiers are typically used to facilitate the interpretation of modifier-noun combinations. However, research on semantic patterns in compounding has suggested that regularities tend to be associated with pairings of semantic categories, rather than individual concepts (e.g., P. Maguire, E. J. Wisniewski, & G. Storms, in press; B. Warren, 1978). In the present study, the authors investigated whether people are sensitive to interactional semantic patterns in compounding. Experiment 1 demonstrated that the influence of a given modifier on ease of interpretation varies depending on the semantic category of the head. Experiment 2 demonstrated that the relation preference of the head noun influences ease of interpretation when the semantic category of the modifier is compatible with that preference. In light of these findings, the authors suggest that people are sensitive to how different semantic categories tend to be paired in combination and that this information is used to facilitate the interpretation process.

Understanding burden in caregivers of colorectal cancer survivors: what role do patient and caregiver factors play?

This study investigated how both caregiver and patient factors predict different aspects of burden in colorectal cancer caregivers. One hundred and fifty-three caregiver-survivor dyads separately provided information on patient disease and treatment-related factors, and perceived global health status (EORTC QLQ30), along with caregiver socio-demographic factors, health and care-related activities. Four multiple regression analyses were conducted to assess the influence of caregiver characteristics, patient characteristics and care-related activities on four dimensions of burden from the Caregiver Reaction Assessment scale. Caregiver characteristics significantly predicted health and financial burden (11%-13% of explained variance) with comorbidity and younger age increasing this risk. Patient health, in particular global health status and the presence of a stoma, predicted all burden scores, explaining 14%-22% of variance. Care-related activities was also a significant predictor of all burden scores, explaining an additional 5%-11% of variance, with time involved in caring the most consistent predictor. Results highlight that a combination of factors influence caregiver burden. These results may be used to identify those most at risk, allowing practitioners to deliver tailored effective support. In particular, efforts to alleviate the burden of caring on caregiver schedule may be merited, given that this was the domain in which the burden was greatest.

A test of the inventory of attitudes towards seeking mental health services

This study investigates the construct validity, composite reliability and concurrent validity of the Inventory of attitudes towards seeking mental health services (IASMHS). A large sample of Irish police officers (N = 331) participated in the study. Confirmatory factor analysis supported the three-factor structure of the scale, while composite reliability results demonstrated that the IASMHS possessed excellent internal reliability. Structural equation modelling indicated that help-seeking propensity was the strongest predictor of intentions to engage in psychological counselling followed by psychological openness. Neuroticism was a weak, significant predictor of intentions. Implications of these results are discussed in relation to improving utilisation rates of mental health services.

The role of experience in the interpretation of noun---noun combinations

Gagné and Shoben’s (J Exp Psychol Learn Mem Cogn 23:71–87, 1997) Competition Among Relations In Nominals (CARIN) theory maintains that the interpretation of modifier-noun combinations is influenced primarily by how the modifying noun has been used in the past. As support for this theory, they found that modifiers typically associated with the instantiated relation are interpreted reliably faster than those whose modifiers are less frequently associated with the relation. The CARIN theory explains this phenomenon by proposing that people store statistical distributions regarding the frequency with which modifying nouns have combined with each relation in the past. However, we maintain that an association between relation frequency and response time does not imply a causal influence. In this study we explore whether the effects observed by Gagné and Shoben were caused by the influence of relation frequency per se. Two experiments were conducted in which experiential knowledge about the modifier was controlled. The first experiment involved combinations whose modifiers were relatively rare and the second involved the presentation of nouns without a modifier-head syntax. In both of these experiments, knowledge about historical modifier usage was irrelevant. Our results show that correlations between modifier preference and response time persist even in situations where a knowledge of the modifier’s history is not available. These findings provide converging evidence that the relationship between relation frequency and response time is not a causal one. Instead, an understanding of the relationship between modifier properties and usage, as appropriate to the given context, may be the dominant influence on interpretation in many circumstances. In light of this, we propose an alternative account of the factors influencing ease of interpretation.

Worry in Head and Neck Cancer Caregivers: The Role of Survivor Factors, Care-Related Stressors, and Loneliness in Predicting Fear of Recurrence

Background Fear of recurrence (FOR) is a primary concern for both cancer survivors and their caregivers, yet little is known about what care-related factors exacerbate this worry. Objectives This study aimed to establish the role of care-related stressors—as distinct from survivor characteristics—in predicting FOR in head and neck cancer caregivers. Methods HNC survivor–caregiver dyads took part in a mailed survey. Survivors provided information on health and quality of life (using the Functional Assessment of Cancer Therapy Questionnaire). Caregivers provided sociodemographic information, impact of caring on their time and finances, as well as their level of social support (Oslo Support Scale), loneliness (3-point loneliness scale), and completed the Worry of Cancer Scale (to measure FOR). Results Data from 180 dyads were available for analysis. Multiple regression analysis was used to examine the role of caregiver stressors, social support, and loneliness while controlling for caregiver and survivor characteristics. The model explained 28% of the variance in Worry of Cancer scores (FOR). Caregivers who reported more loneliness, spent more time caring, and had greater financial stress from caring had higher scores on Worry of Cancer (FOR). Female caregivers, those caring for younger survivors, and those with survivors who had undergone less extensive forms of surgery also reported higher FOR. Discussion A combination of factors place caregivers at greater risk of cancer-related worry, paving the way for designing interventions aimed at reducing FOR in caregivers of patients with head and neck cancers.

Maximizing positive porfolio diversification

We introduce a new strategy for optimal diversification which combines elements of Diversified Risk Parity and Diversification Ratio, with emphasis on positive risk premiums. The Uncorrelated Positive Bets strategy involves the identification of reliable, independent sources of randomness and the quantification of their positive risk premium. We use principal component analysis to identify the most significant sources of randomness contributing to the market and then apply the Randomness Deficiency Coefficient metric and principal portfolio positivity to identify a set of reliable uncorrelated positive bets. Portfolios are then optimized by maximizing their diversified positive risk premium. We contrast the performance of a range of diversification strategies for a portfolio held for a two-year out-of-sample period with a 30 stock constraint. In particular, we introduce the notion of diversification inefficiency to explain why diversification strategies might outperform the market.

A probabilistic risk-to-reward measure for evaluating the performance of financial securities

Existing risk-to-reward measures, such as the Sharpe ratio [1] or M2 [2], are based on the idea of quantifying the excess return per unit of deviation in an investment. In this preliminary article we introduce a new probabilistic measure for evaluating investment performance. Randomness Deficiency Coefficient (RDC) expresses the likelihood that the observed excess return of an investment has been generated by chance. Some of the advantages of RDC over existing measures are that it can be used with small historical datasets, is time-frame independent, and can be easily adjusted to take into account the familywise error rate which results from selection bias. We argue that RDC captures the fundamental relationship between risk and reward and prove that it converges with Sharpes ratio.

Seeing Patterns in Randomness: A Computational Model of Surprise

While seemingly a ubiquitous cognitive process, the precise definition and function of surprise remains elusive. Surprise is often conceptualized as being related to improbability or to contrasts with higher probability expectations. In contrast to this probabilistic view, we argue that surprising observations are those that undermine an existing model, implying an alternative causal origin. Surprises are not merely improbable events; instead, they indicate a breakdown in the model being used to quantify probability. We suggest that the heuristic people rely on to detect such anomalous events is randomness deficiency. Specifically, people experience surprise when they identify patterns where their model implies there should only be random noise. Using algorithmic information theory, we present a novel computational theory which formalizes this notion of surprise as randomness deficiency. We also present empirical evidence that people respond to randomness deficiency in their environment and use it to adjust their beliefs about the causal origins of events. The connection between this pattern-detection view of surprise and the literature on learning and interestingness is discussed.