The melody of surprise: maternal surprise vocalizations during play with her infant

Two groups of mothers and their infants (24 infants, mean age=3.5 months and 24 infants, mean age=5.5 months) were video‐ and audio‐taped in their homes while playing with a Jack‐in‐the‐box. The mean fundamental frequency of spontaneous surprise exclamations of mothers when opening the toy were analysed, and infant and maternal facial expressions of surprise were coded in three regions of the face. A t‐test established that significantly more of the older children in comparison with younger children showed surprise (t=?2.96, df=46, p<0.005, 2‐tailed). Twenty‐nine per cent of the younger infants, in comparison with 67% of the older children showed facial expressions of surprise. A t‐test of maternal pitch height (Hz) indicated that mothers exclaimed in surprise with a higher pitch when the child did not show a surprise facial expression (mean=415.61 Hz) in comparison with the child showing surprise (mean=358.97 Hz; t=2.9, df=46, p=0.006, 2‐tailed). A multiple regression established that infant's expression was a stronger predictor of maternal vocal pitch than was the age of the infant. These results are discussed in terms of maternal use of emotional expressions as ‘social signals’. Copyright © 2002 John Wiley & Sons, Ltd.     

Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method

In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on statistical reporting. This is unfortunate, as the p-value provides at best a rough estimate of the evidence that the data provide for the presence of an experimental effect. An alternative and arguably more appropriate measure of evidence is conveyed by a Bayesian hypothesis test, which prefers the model with the highest average likelihood. One of the main problems with this Bayesian hypothesis test, however, is that it often requires relatively sophisticated numerical methods for its computation. Here we draw attention to the Savage–Dickey density ratio method, a method that can be used to compute the result of a Bayesian hypothesis test for nested models and under certain plausible restrictions on the parameter priors. Practical examples demonstrate the method’s validity, generality, and flexibility.     

Default “Gunel and Dickey” Bayes factors for contingency tables

The analysis of R×C contingency tables usually features a test for independence between row and column counts. Throughout the social sciences, the adequacy of the independence hypothesis is generally evaluated by the outcome of a classical p-value null-hypothesis significance test. Unfortunately, however, the classical p-value comes with a number of well-documented drawbacks. Here we outline an alternative, Bayes factor method to quantify the evidence for and against the hypothesis of independence in R×C contingency tables. First we describe different sampling models for contingency tables and provide the corresponding default Bayes factors as originally developed by Gunel and Dickey (Biometrika, 61(3):545–557 (1974)). We then illustrate the properties and advantages of a Bayes factor analysis of contingency tables through simulations and practical examples. Computer code is available online and has been incorporated in the “BayesFactor” R package and the JASP program (jasp-stats.org).     

Testing Variance Components in Linear Mixed Modeling Using Permutation

Abstract

Inference of variance components in linear mixed modeling (LMM) provides evidence of heterogeneity between individuals or clusters. When only nonnegative variances are allowed, there is a boundary (i.e., 0) in the variances’ parameter space, and regular inference statistical procedures for such a parameter could be problematic. The goal of this article is to introduce a practically feasible permutation method to make inferences about variance components while considering the boundary issue in LMM. The permutation tests with different settings (i.e., constrained vs. unconstrained estimation, specific vs. generalized test, different ways of calculating p values, and different ways of permutation) were examined with both normal data and non-normal data. In addition, the permutation tests were compared to likelihood ratio (LR) tests with a mixture of chi-squared distributions as the reference distribution. We found that the unconstrained permutation test with the one-sided p-value approach performed better than the other permutation tests and is a useful alternative when the LR tests are not applicable. An R function is provided to facilitate the implementation of the permutation tests, and a real data example is used to illustrate the application. We hope our results will help researchers choose appropriate tests when testing variance components in LMM.     

Clarifying the role of impulsivity in dietary restraint: A structural equation modeling approach

This study was designed to clarify the relationship between the four dimensions of impulsivity in Whiteside and Lynam’s (2001) model and the two aspects of dietary restraint (Concern for Dieting and Weight Fluctuation) in a non-clinical sample. Data were collected from a volunteer community sample (N = 216) of women who responded to two self-report instruments related to impulsivity (UPPS Impulsive Behavior Scale, Whiteside & Lynam, 2001) and dietary restraint (Restraint Scale, Polivy, Herman, & Warsh, 1978). A structural equation model was tested. The model provided a good fit to the data (χ²/df = 1.64, p < .0001, RMSEA = 0.054, 90% CI = 0.050–0.058, p-value for test of close fit (RMSEA > 0.05) = .035) and revealed that Concern for Dieting was positively related to Urgency (standardized β = 0.25, p < .01). Weight Fluctuation was related to lack of Perseverance (standardized β = 0.25, p < .01) and tended to relate to Sensation Seeking (standardized β = 0.17, p = .056). Urgency and lack of Perseverance were found to play a significant role in predicting Concern for Dieting and Weight Fluctuation.     

Effects of telephone support on exercise capacity and quality of life in patients with chronic obstructive pulmonary disease: a meta-analysis

The aim of this meta-analysis was to evaluate the effects of disease education or pulmonary rehabilitation programs assisted with telephone support on physical capacity and quality of life (QOL) in chronic obstructive pulmonary disease (COPD) patients. A systematic search of PubMed, Embase, Web of Science and The Cochrane Library was conducted until May 2017. Randomized controlled trials (RCTs) examining the effects of telephone-assisted intervention versus a control group on exercise tolerance and QOL in patients with COPD were included. Two independent authors assessed the methodological quality of the trials using the Cochrane risk of bias tool. A meta-analysis was conducted with the Revman5.3 to quantify the effects of telephone-assisted interventions on walking capacity and QOL. In total, 10 studies involving 1037 participants were included. Due to the effect of telephone-assisted interventions, statistically significant results were found on Saint-George’s Respiratory Questionnaire (SGRQ) symptom scores [standard mean difference (SMD) ?.18, 95% confidence interval (CI) ?.33, ?.03, p-value .02)], SGRQ impact scores [SMD ?.35, 95% CI ?.60, ?.10, p-value .006)], SGRQ activity scores [SMD ?.30, 95% CI ?.45, ?.15, p-value < .0001)], SGRQ total score [SMD ?.36, 95% CI ?.51, ?.21, p-value < .00001)]. The effects on 6-min walk test (6MWT) and all Chronic Respiratory Questionnaire (CRQ) subscales were not significant (p > .05) based on the insufficient evidence. In conclusion, the role of telephone-assisted interventions in the management of COPD remains equivocal. Some encouraging results were seen with regard to SGRQ symptom, SGRQ impact, SGRQ activity and SGRQ total score. We believe that more methodologically rigorous large-scale randomized controlled trials are necessary to answer this study question.     

The cognitive structure of surprise: looking for basic principles

We develop a conceptual and formal clarification of notion of surprise as a belief-based phenomenon by exploring a rich typology. Each kind of surprise is associated with a particular phase of cognitive processing and involves particular kinds of epistemic representations (representations and expectations under scrutiny, implicit beliefs, presuppositions). We define two main kinds of surprise: mismatch-based surprise and astonishment. In the central part of the paper we suggest how a formal model of surprise can be integrated with a formal model of belief change. We investigate the role of surprise in triggering the process of belief reconsideration. There are a number of models of surprise developed in the psychology of emotion. We provide several comparisons of our approach with those models.

Health-related Internet habits and health anxiety in university students

Health-related Internet use has grown rapidly, yet little research has considered how health anxious individuals use the Internet for this purpose. Our aim was to examine the relationships between health anxiety and the extent of, reasons for, and consequences of health-related Internet usage in university students (n = 255). Responses on a purpose-made Internet use questionnaire were correlated with health anxiety scores; multiple regression analyses controlling for depression and anxiety were also conducted. Health anxiety positively correlated with (all ps < .01): frequency of health-related searching (r_s = .163), proportion of health-related information sought (r_s = .200), time spent online for health purposes (r_s = .166), and number of searches for both illness (r_s = .453) and wellness (r_s = .208) information. Health anxiety further positively correlated with advantages perceived in health-related Internet use (r_s = .183), heightened tension (r_s = .364) and relief (r_s = .174) post-search, and perceived doctor disadvantages (r_s = .306), yet a greater likelihood to visit a doctor post-search (r_s = .217). Health anxiety also correlated with six measures of possible addiction to using the Internet for health purposes (r_s range = .171 to .366, all ps < .01). Some (including several potentially dysfunctional) aspects of health-related Internet use correlate with health anxiety. Research evaluating the possible role of Internet use in the development and maintenance of health anxiety is warranted.     

The relationship between testosterone and aggression: a meta-analysis

In non-human animals, the relationship between testosterone and aggression is well established. In humans, the relationship is more controversial. To clarify the relationship, Archer conducted three meta-analyses and found a weak, positive relationship between testosterone and aggression. Unfortunately, each of the analyses included only five to six studies. The aim of the present study was to re-examine the relationship between testosterone and aggression with a larger sample of studies. The present analyses are based on 45 independent studies (N=9760) with 54 independent effect sizes. Only studies that reported a p-value or effect size were included in the analyses and the sample may underestimate the proportion of non-significant findings in the population. Correlations ranged from −0.28 to 0.71. The mean weighted correlation (r=0.14) corroborates Archer's finding of a weak positive relationship.     

How Accurate Is the Pearson r-from-Z Approximation? A Monte Carlo Simulation Study

The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.     

SPSS macros to compare any two fitted values from a regression model

In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests—particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.     

Maximum likelihood estimation of the joint covariance matrix for sections of tests given to distinct samples with application to test equating

Consider an old testX consisting ofs sections and two new testsY andZ similar toX consisting ofp andq sections respectively. All subjects are given testX plus two variable sections from either testY orZ. Different pairings of variable sections are given to each subsample of subjects. We present a method of estimating the covariance matrix of the combined test (X ₁, ...,X _s ,Y ₁, ...,Y _p ,Z ₁, ...,Z _q ) and describe an application of these estimation techniques to linear, observed-score, test equating.The author is indebted to Paul W. Holland and Donald B. Rubin for their encouragement and many helpful comments and suggestions that contributed significantly to the development of this paper.This research was supported by the Program Statistics Research Project of the ETS Research Statistics Group.     

Rate of Torque Development and Feedforward Control of the Hip and Knee Extensors: Gender Differences

The purpose of this study was to determine whether women demonstrate decreased rate of torque development (RTD) of the hip and knee extensors and altered onset timing of the vastus lateralis and gluteus maximus during a drop-jump task when compared with men. On average, women demonstrated significantly lower normalized RTD of the hip extensors (women: 11.6 ± 1.3 MVT.s^?1, men: 13.1 ± 0.9 MVT.s^?1; p ≤ .01); however, there was no significant difference in knee extensor RTD. Women also demonstrated significantly earlier activation of their vastus lateralis (women: 206.0 ± 130.6 ms, men: 80.9 ± 69.6 ms; p ≤ .01) and gluteus maximus (women: 85.7 ± 58.6 ms, men: 54.5 ± 35.4 ms; p = .02). In both men and women, there was a significant negative correlation between the hip extensor RTD and the vastus lateralis electromyographic onset time (men: r = –.386, p = .046; women: r = –.531, p = .008). The study findings suggest that women may utilize a feedforward control strategy in which they activate their knee extensors earlier than men to compensate for deficits in hip extensor RTD. The impaired capacity to rapidly stabilize the hip and knee joints during dynamic maneuvers may contribute to the increased risk of anterior cruciate ligament injury observed in women.     

A practical solution to the pervasive problems of<Emphasis Type="Italic">p</Emphasis> values

In the field of psychology, the practice ofp value null-hypothesis testing is as widespread as ever. Despite this popularity, or perhaps because of it, most psychologists are not aware of the statistical peculiarities of thep value procedure. In particular,p values are based on data that were never observed, and these hypothetical data are themselves influenced by subjective intentions. Moreover,p values do not quantify statistical evidence. This article reviews thesep value problems and illustrates each problem with concrete examples. The three problems are familiar to statisticians but may be new to psychologists. A practical solution to thesep value problems is to adopt a model selection perspective and use the Bayesian information criterion (BIC) for statistical inference (Raftery, 1995). The BIC provides an approximation to a Bayesian hypothesis test, does not require the specification of priors, and can be easily calculated from SPSS output.     

Psychiatric Distress and Suicidal Tendencies in Adult Cancer Survivors: Verifying the Validity of the Brief Symptom Inventory-18 for Identifying Suicidal Ideation in the Hospitalized Population of Mainland China

The Brief Symptom Inventory-18 (BSI-18) is widely used to assess psychiatric distress but has not been verified in the Chinese population. From March to April 2019, 293 hospitalized cancer patients, aged 20–87, completed the cross-sectional survey with demographics questionnaire, BSI-18, and PHQ-9. We analyzed the single suicide-related item of PHQ-9 with the full score clinical outpoint for BSI-18 and PHQ-9 using SPSS 22.0 and R 2.15, including Pearson's χ² test and ROC curve analyses. A Pearson's χ² test was carried out to compare the three different methods with the gold screening criteria. The p-value was correspondingly to .006, .066, .838. When the PHQ-9?≥?10 criteria for the BSI-18, receiver operating characteristic analysis revealed that AUC values were 0.839, optimal cut-off points for both BSI-18?≥?50, the sensitivity of 85.8%, and 62.5%, respectively. The BSI-18 is suitable for a screening tool for psychological distress and could also be used in clinical settings for preliminary screening of hospitalized cancer patients.

     

Perceptual learning and recognition confusion reveal the underlying relationships among the six basic emotions

The six basic emotions (disgust, anger, fear, happiness, sadness, and surprise) have long been considered discrete categories that serve as the primary units of the emotion system. Yet recent evidence indicated underlying connections among them. Here we tested the underlying relationships among the six basic emotions using a perceptual learning procedure. This technique has the potential of causally changing participants’ emotion detection ability. We found that training on detecting a facial expression improved the performance not only on the trained expression but also on other expressions. Such a transfer effect was consistently demonstrated between disgust and anger detection as well as between fear and surprise detection in two experiments (Experiment 1A, n?=?70; Experiment 1B, n?=?42). Notably, training on any of the six emotions could improve happiness detection, while sadness detection could only be improved by training on sadness itself, suggesting the uniqueness of happiness and sadness. In an emotion recognition test using a large sample of Chinese participants (n?=?1748), the confusion between disgust and anger as well as between fear and surprise was further confirmed. Taken together, our study demonstrates that the “basic” emotions share some common psychological components, which might be the more basic units of the emotion system.     

Priming the holiday spirit: Persistent activation due to extraexperimental experiences

The concept of activation is a critical component of many models of cognition. A key characteristic of activation is that recent experience with a concept or stimulus increases the accessibility of the corresponding representation. The extent to which increases in accessibility occur as a result of experiences outside of laboratory settings has not been extensively explored. In the present study, we presented lexical stimuli associated with different holidays and festivities over the course of a year in a lexical decision task. When stimulus meaning and time of testing were congruent (e.g., leprechaun in March), response times were faster and accuracy greater than when meaning and time of test were incongruent (e.g., leprechaun in November). Congruency also benefited performance on a surprise free recall task of the items presented earlier in the lexical decision task. The discussion focuses on potential theoretical accounts of this heightened accessibility of time-of-the-year-relevant concepts.     

Back to the basics: Rethinking partial correlation network methodology

The Gaussian graphical model (GGM) is an increasingly popular technique used in psychology to characterize relationships among observed variables. These relationships are represented as elements in the precision matrix. Standardizing the precision matrix and reversing the sign yields corresponding partial correlations that imply pairwise dependencies in which the effects of all other variables have been controlled for. The graphical lasso (glasso) has emerged as the default estimation method, which uses ℓ₁-based regularization. The glasso was developed and optimized for high-dimensional settings where the number of variables (p) exceeds the number of observations (n), which is uncommon in psychological applications. Here we propose to go ‘back to the basics’, wherein the precision matrix is first estimated with non-regularized maximum likelihood and then Fisher Z transformed confidence intervals are used to determine non-zero relationships. We first show the exact correspondence between the confidence level and specificity, which is due to 1 minus specificity denoting the false positive rate (i.e., α). With simulations in low-dimensional settings (p ≪ n), we then demonstrate superior performance compared to the glasso for detecting the non-zero effects. Further, our results indicate that the glasso is inconsistent for the purpose of model selection and does not control the false discovery rate, whereas the proposed method converges on the true model and directly controls error rates. We end by discussing implications for estimating GGMs in psychology.     

Effects of Mentally Subtracting Positive Events on Affective Status in Japanese College Students

This study examined the effect on positive and negative emotions in Japanese college students of mentally subtracting grateful events. Participants (N = 62) were randomly assigned to one of the following three conditions: (a) writing with surprise the ways that a positive thing or event might never have happened or might never have been part of life (the mentally subtracting a present good [MS] group), (b) writing without surprise the ways in which a positive thing or event happened easily or was certain to become a part of life (the counting gratitude group), and (c) no writing control. The results of analysis of variance showed that the MS group experienced significantly increased positive emotion and decreased negative emotion between pre‐test and post‐test. Furthermore, the MS group showed significantly greater positive emotion than the control group at post‐test. Surprise mediated the effects of the MS group intervention on positive emotion but not on negative emotion. Issues related to gratitude induction and mediation of surprise are discussed.     

The role of surprise in the attribution process

Abstract

We report five studies which compared two theories linking surprise to causal attribution. According to the attributional model, surprise is frequently caused by luck attributions, whereas according to the expectancy-disconfirmation model, surprise is caused by expectancy disconfirmation and stimulates causal thinking. Studies 1 to 3 focused on the question of whether surprise is caused by luck attributions or by unexpectedness. In Studies 1 and 2, subjects had to recall success or failure experiences characterised by a particular attribution (Study 1) or by low versus high surprisingness (Study 2), whereas in Study 3, unexpectedness and luck versus skill attributions were independently manipulated within a realistic setting. The main dependent variables were unexpectedness (Studies 1 and 2), degree of surprise (Studies 1 and 3), and causal attributions (Study 2). The results strongly suggest that surprise is caused by expectancy disconfirmation, whereas luck attributions are neither sufficient nor necessary for surprise. Studies 4 and 5 addressed the question of whether surprise stimulates attributional thinking, again using a remembered-incidents technique. The findings of the previous studies were replicated, and it was confirmed that surprising outcomes elicit more attributional search than unsurprising ones. Additional results from Study 5 suggest that causal thinking is also stimulated by outcomes that are both negative and important.