Organic self-talk content categories and their relations to sport-specific contextual and personal factors

While strategic self-talk interventions are well documented, less is known regarding organically occurring self-talk. Previously, eight organic self-talk content categories were identified, however contextual and personal factors relating to these categories is unexplored. The aim of the study was to explore the relationships between stress, coping, athletic identity, demographic and sport-related factors and the eight organic self-talk categories of anxiety control, confidence, disengagement, instruction, psych-up, somatic fatigue, worry, and irrelevant. 216 NCAA student-athletes were recruited. Regression was used to determine the relationships between the contextual and personal variables and organic self-talk. Stress, coping and self-talk categories were compared in and out-of-season. Stress was associated with all self-talk frequencies except confidence. Coping was associated with psych-up, confidence and worry. Athletic identity was associated with psych-up, confidence, instruction and disengagement. Age was associated with anxiety control and instruction. Lastly, sport type and division level were associated with disengagement and instruction self-talk respectively.

Measuring State and Trait Anxiety: An Application of Multidimensional Item Response Theory

The State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA) is a widely used measure of state and trait anxiety. Within the Classical Testing Theory model, consistent findings provide support for its multidimensional factor structure, discriminant, convergent, and nomological validity, as well as age and gender invariance, across healthy and clinical samples. Nevertheless, some issues regarding STICSA dimensionality and item-scale composition remain unresolved (e.g., both bifactor and two-factor models were found to fit data equally well). The goal of this study was to investigate the STICSA's dimensionality within the Item Response Theory, and to assess the tenability of the bifactor model as a plausible model over the multidimensional model. The sample consisted of 3338 Italian participants (58.21% females; 41.79% males) with an average age of 35.65 years (range: 18-99; SD = 20.25). Both bifactor and two-correlated dimensions of the STICSA scales were confirmed to fit data by applying the multidimensional Item Response Theory (mIRT). While the bifactor model showed better fit indices, the multidimensional model was more accurate and precise (0.86-0.88) in estimating state and trait latent anxiety. A further comparison between multidimensional item parameters revealed that the multidimensional and bifactor models were equivalent. Findings showed that the STICSA is an accurate and precise instrument for measuring somatic and cognitive symptomatology dimensions within state and trait anxiety. The use of the state/trait total score requires special attention from the clinicians and researchers to avoid bias in the psychodiagnostic assessment.

Computational perspectives on human fear and anxiety

Fear and anxiety are adaptive emotions that serve important defensive functions, yet in excess, they can be debilitating and lead to poor mental health. Computational modelling of behaviour provides a mechanistic framework for understanding the cognitive and neurobiological bases of fear and anxiety, and has seen increasing interest in the field. In this brief review, we discuss recent developments in the computational modelling of human fear and anxiety. Firstly, we describe various reinforcement learning strategies that humans employ when learning to predict or avoid threat, and how these relate to symptoms of fear and anxiety. Secondly, we discuss initial efforts to explore, through a computational lens, approach-avoidance conflict paradigms that are popular in animal research to measure fear- and anxiety-relevant behaviours. Finally, we discuss negative biases in decision-making in the face of uncertainty in anxiety.

Self-Injurious Behavior in Community Youth

The rapid increase of self-injurious behavior among Korean adolescents, and its reckless spread on social media, has driven the necessity to study this behavior. The present study investigates the characteristics of self-injurious behavior among adolescents in local communities, and the psychological factors affecting such behavior. Questionnaires were administered to 516 sixth graders in elementary school and first to third graders in middle school of both genders, nationwide. They measured the prevalence and characteristics of self-injurious behavior and the relevant psychological factors, such as levels of depression, anxiety, and self-esteem. Furthermore, group differences were assessed for self-injury experience and the characteristics relevant to self-injurious behavior. In addition, this study performs logistic regression to explore the risk factors predicting self-injurious behavior. In all, 166 participants (32.2%) reported self-injury, with a higher rate of self-injury in female students than in male students. Although the study finds high rates of mild forms of self-injury, such as "biting", "pulling hair," and "hitting self", it also finds relatively high reports of more risky methods, such as "cutting or carving". The logistic regression shows a significant effect of the negative self-image sub-factor of depression (CDI) and oversensitivity and physical and sleep problems sub-factors of anxiety (RCMAS) on self-injurious behavior. The rates of self-injury were higher in female participants than in male ones, and adolescents in local communities reported higher rates of mild forms of self-injury than the moderate/severe forms. The results of this study suggest that early screenings and interventions should be conducted through evaluation of self-image and emotional stability of early adolescents to hinder the risk of self-harm.

Assessment of patient-reported symptoms of anxiety

Patient self-reported symptoms are of crucial importance to identify anxiety disorders, as well as to monitor their treatment in clinical practice and research. Thus, for evidence-based medicine, a precise, reliable, and valid (ie, “objective”) assessment of the patient's reported “subjective” symptoms is warranted. There is a plethora of instruments available, which can provide psychometrically sound assessments of anxiety, but there are several limitations of current tools that need to be carefully considered for their successful use. Nevertheless, the empirical assessment of mental health status is not as accepted in medicine as is the assessment of biomarkers. One reason for this may be that different instruments assessing the same psychological construct use different scales. In this paper we present some new developments that promise to provide one common metric for the assessment of anxiety, to facilitate the general acceptance of mental health assessments in the future.

Dimensionality of somatic complaints: factor structure and psychometric properties of the Self-Rating Anxiety Scale

Somatic complaints are often key features of anxiety pathology. Although most measures of anxiety symptoms capture somatic complaints to some degree, the Self-Rating Anxiety Scale (SAS) was developed primarily as a measure of somatic symptoms associated with anxiety responding. We evaluated the psychometric properties and factor structure of the SAS in two large undergraduate samples who completed the SAS and measures of anxiety and depression. Exploratory factor analysis revealed four lower-order SAS factors in both samples: (1) anxiety and panic; (2) vestibular sensations; (3) somatic control; and, (4) gastrointestinal/muscular sensations. The SAS demonstrated good reliability in both samples, and the correlations between the SAS factors and other anxiety variables provide supportive evidence for convergent validity, though evidence for discriminant validity was limited. The strengths and limitations of the SAS are offered as well as the implications of our findings for the nature and assessment of somatic complaints in anxiety disorders.

Starting at the beginning: an introduction to coefficient alpha and internal consistency

Cronbach's a is the most widely used index of the reliability of a scale. However, its use and interpretation can be subject to a number of errors. This article discusses the historical development of a from other indexes of internal consistency (split-half reliability and Kuder-Richardson 20) and discusses four myths associated with a: (a) that it is a fixed property of the scale, (b) that it measures only the internal consistency of the scale, (c) that higher values are always preferred over lower ones, and (d) that it is restricted to the range of 0 to 1. It provides some recommendations for acceptable values of a in different situations.