An implicit association test (IAT) measures differential association of 2 target concepts with an attribute. The 2 concepts appear in a 2-choice task (e.g., flower vs. insect names), and the attribute in a 2nd task (e.g., pleasant vs. unpleasant words for an evaluation attribute). When instructions oblige highly associated categories (e.g., flower + pleasant) to share a response key, performance is faster than when less associated categories (e.g., insect + pleasant) share a key. This performance difference implicitly measures differential association of the 2 concepts with the attribute. In 3 experiments, the IAT was sensitive to (a) near-universal evaluative differences (e.g., flower vs. insect), (b) expected individual differences in evaluative associations (Japanese + pleasant vs. Korean + pleasant for Japanese vs. Korean subjects), and (c) consciously disavowed evaluative differences (Black + pleasant vs. White + pleasant for self-described unprejudiced White subjects).

http://faculty.fortlewis.edu/burke_b/Senior/BLINK%20replication/IAT.pdf

Measuring individual differences in implicit cognition: The implicit association test.

The emerging field of emotion regulation studies how individuals influence which emotions they have, when they have them, and how they experience and express them. This review takes an evolutionary perspective and characterizes emotion in terms of response tendencies. Emotion regulation is denned and distinguished from coping, mood regulation, defense, and affect regulation. In the increasingly specialized discipline of psychology, the field of emotion regulation cuts across traditional boundaries and provides common ground. According to a process model of emotion regulation, emotion may be regulated at five points in the emotion generative process: (a) selection of the situation, (b) modification of the situation, (c) deployment of attention, (d) change of cognitions, and (e) modulation of responses. The field of emotion regulation promises new insights into age-old questions about how people manage their emotions.

http://www.elaborer.org/cours/A13/lectures/Gross1998.pdf

The emerging field of emotion regulation: An integrative review.

Many prominent theorists have argued that accurate perceptions of the self, the world, and the future are essential for mental health. Yet considerable research evidence suggests that overly positive selfevaluations, exaggerated perceptions of control or mastery, and unrealistic optimism are characteristic of normal human thought. Moreover, these illusions appear to promote other criteria of mental health, including the ability to care about others, the ability to be happy or contented, and the ability to engage in productive and creative work. These strategies may succeed, in large part, because both the social world and cognitive-processing mechanisms impose niters on incoming information that distort it in a positive direction; negative information may be isolated and represented in as unthreatening a manner as possible. These positive illusions may be especially useful when an individual receives negative feedback or is otherwise threatened and may be especially adaptive under these circumstances. Decades of psychological wisdom have established contact with reality as a hallmark of mental health. In this view, the well-adjusted person is thought to engage in accurate reality testing, whereas the individual whose vision is clouded by illusion is regarded as vulnerable to, if not already a victim of, mental illness. Despite its plausibility, this viewpoint is increasingly difficult to maintain (cf. Lazarus, 1983). A substantial amount of research testifies to the prevalence of illusion in normal human cognition (see Fiske& Taylor, 1984;Greenwald, 1980; Nisbett & Ross, 1980; Sackeim, 1983; Taylor, 1983). Moreover, these illusions often involve central aspects of the self and the environment and, therefore, cannot be dismissed as inconsequential. In this article, we review research suggesting that certain illusions may be adaptive for mental health and well-being. In particular, we examine evidence that a set of interrelated positive illusions—namely, unrealistically positive self-evaluations, exaggerated perceptions of control or mastery, and unrealistic optimism—can serve a wide variety of cognitive, affective, and social functions. We also attempt to resolve the following para

/pdf/illusion-and-well-being-a-social-psychological-perspective-5acx7rw6hx.pdf

Illusion and well-being: a social psychological perspective on mental health

The goals of this chapter are (1) to outline and substantiate a broad conceptualization of what it means to think mathematically, (2) to summarize the literature relevant to understanding mathematical thinking and problem solving, and (3) to point to new directions in research, development, and assessment consonant with an emerging understanding of mathematical thinking and the goals for instruction outlined here. The use of the phrase “learning to think mathematically” in this chapter’s title is deliberately broad. Although the original charter for this chapter was to review the literature on problem solving and metacognition, the literature itself is somewhat ill defined and poorly grounded. As the literature summary will make clear, problem solving has been used with multiple meanings that range from “working rote exercises” to “doing mathematics as a professional”; metacognition has multiple and almost disjoint meanings (from knowledge about one’s thought processes to self-regulation during problem solving) that make it difficult to use as a concept. This chapter outlines the various meanings that have been ascribed to these terms and discusses their role in mathematical thinking. The discussion will not have the character of a classic literature review, which is typically encyclopedic in its references and telegraphic in its discussions of individual papers or results. It will, instead, be selective and illustrative, with main points illustrated by extended discussions of pertinent examples. Problem solving has, as predicted in the 1980 Yearbook of the National Council of Teachers of Mathematics (Krulik, 1980, p. xiv), been the theme of the 1980s. The decade began with NCTM’s widely heralded statement, in its Agenda for Action, that “problem solving must be the focus of school mathematics” (NCTM, 1980, p. 1). It concluded with the publication of Everybody Counts (National Research Council, 1989) and the Curriculum and Evaluation Standards for School Mathematics (NCTM, 1989), both of which emphasize problem solving. One might infer, then, that there is general acceptance of the idea that the primary goal of mathematics instruction should be to have students become competent problem solvers. Yet, given the multiple interpretations of the term, the goal is hardly clear. Equally unclear is the role that problem solving, once adequately characterized, should play in the larger context of school mathematics. What are the goals for mathematics instruction, and how does problem solving fit within those goals? Such questions are complex. Goals for mathematics instruction depend on one’s conceptualization of what mathematics is, and what it means to understand mathematics. Such conceptualizations vary widely. At one end of the spectrum, mathematical knowledge is seen as a body of facts and procedures dealing with quantities, magnitudes, and forms, and the relationships among them; knowing mathematics is seen as having mastered these facts and procedures. At the other end of the spectrum, mathematics is conceptualized as the “science of patterns,” an (almost) empirical discipline closely akin to the sciences in its emphasis on pattern-seeking on the basis of empirical evidence. The author’s view is that the former perspective trivializes mathematics; that a curriculum based on mastering a corpus of mathematical facts and procedures is severely impoverished—in much the same way that an English curriculum would be considered impoverished if it focused largely, if not exclusively, on issues of grammar. The author characterizes the mathematical enterprise as follows:

Learning to think mathematically: Problem solving, metacognition, and sense-making in mathematics.

Learning to Think Mathematically: Problem Solving, Metacognition, and Sense Making in Mathematics (Reprint):

Fundamentals of behavior pathology

Changes in non-treated subjects over time: Data on a fear survey schedule and the test anxiety scale

Cancer patients and their families: Readings on disease course, coping, and psychological interventions.

The predictive validity of projective measures : a fifteen-year evaluative review of research

This article provides detailed information on anxiety management training, a relaxation-based, self-control therapy for the treatment of generalized anxiety, phobias, anger, and other stress-related disorders. The article describes in detail the specific procedures of anxiety management training to enable the reader to utilize it with individuals and groups. Additionally, research findings are summarized, and the means for deciding on the proper use of anxiety management training are outlined. The article is coauthored by the developer of the technique and a leading researcher in its applications.

Anxiety Management Training

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