Using Groups to Measure Intergroup Prejudice

2016 ◽  
Vol 43 (1) ◽  
pp. 46-59 ◽  
Author(s):  
Erin Cooley ◽  
B. Keith Payne
Keyword(s):  
Predictive Validity ◽  
Measurement Tool ◽  
Implicit Measure ◽  
Implicit Measures ◽  
Social Category ◽  
Social Categories ◽  
Time Points ◽  
Black And White ◽  
Group Members ◽  
Test Retest Reliability

Implicit measures of racial attitudes often assess reactions to images of individuals to infer attitudes toward an entire social category. However, an increasing amount of research indicates that responses to individuals are highly dependent on context and idiosyncratic features of individual exemplars. Thus, using images of individuals to assess beliefs about a whole social category may not be ideal. Across three time points, we predicted that using images of groups would mitigate the influence of idiosyncratic features of individual targets and, thus, provide a better measurement tool to assess beliefs about a category to which all group members belong. Results revealed that an implicit measure that presented images of Black and White groups had greater construct validity, test–retest reliability, and predictive validity as compared with an implicit measure that presented the same exemplars individually. We conclude that groups provide a window into existing beliefs about social categories.

Ego Depletion Moderates the Influence of Automatic and Controlled Precursors of Reactive Aggression

2015 ◽  
Vol 46 (3) ◽  
pp. 132-141 ◽  
Author(s):  
Alexander F. Schmidt ◽  
Philipp S. Zimmermann ◽  
Rainer Banse ◽  
Roland Imhoff
Keyword(s):  
Predictive Validity ◽  
Reactive Aggression ◽  
Ego Depletion ◽  
Self Report ◽  
Implicit Measure ◽  
Acting Out ◽  
Implicit Measures ◽  
Dual Systems ◽  
Taylor Aggression Paradigm ◽  
Systems Perspective

From a dual-systems perspective, it has been proposed that predictive validity of whether individuals act out or stifle their reactive aggression will be maximized if (a) automatic and (b) controlled precursors of aggression are assessed and (c) situational boundaries in favor of acting out or restraining oneself are specified. In the present research we experimentally manipulated participants’ self-regulatory efforts in an ego depletion paradigm and subsequently measured reactive aggression in the Taylor Aggression Paradigm. Assessing automatic and controlled precursors of reactive aggression via an Implicit Association Test of Aggressiveness (Agg-IAT) and self-report reactive aggressiveness questionnaire, respectively, we demonstrated a theoretically expected double dissociation: Reactive aggression of ego depleted individuals was predicted by the implicit measure whereas non-depleted participants’ reactive aggression was predicted by their explicit self-reports. The results corroborate the usefulness of both explicit and implicit measures of aggressiveness and point to boundary conditions of these measures’ predictive validity.

Predictive Validity of IAT Aggressiveness in the Context of Provocation

2010 ◽  
Vol 41 (1) ◽  
pp. 27-34 ◽  
Author(s):  
Juliette Richetin ◽  
Deborah South Richardson ◽  
Gregory D. Mason
Keyword(s):  
Aggressive Behavior ◽  
Predictive Validity ◽  
Implicit Measure ◽  
Implicit Measures ◽  
Explicit Measures

This study examines the extent to which implicit measures of aggressiveness predict actual aggressive behavior in response to provocation. Participants (n = 77) completed implicit measures of aggressiveness, were or were not exposed to insult from an experimenter, evaluated the performance of the experimenter (i.e., opportunity for aggressive behavior), and completed explicit measures of aggressiveness. Results showed that the implicit measure of aggressiveness significantly predicted aggressive behavior in response to provocation, whereas it was not predictive when there was no provocation. The discussion deals with the validity of implicit measures as predictors of aggressive behavior and their moderators.

What We Know

2019 ◽  
pp. 130-158
Author(s):  
E. Tory Higgins
Keyword(s):  
Social Norms ◽  
Social Category ◽  
Social Categories ◽  
The World ◽  
Group Members ◽  
Over Time

“I know it when I see it.” That’s what we think. But mostly we know what our shared realities have taught us, and tell us, to know. Not only do we learn from others the names for things in the world, we learn the names for traits to characterize people. We learn which traits are relevant and relevance makes these traits salient and accessible. This makes it more likely that we will see these traits in others, such as seeing people behave in a “stubborn” way even for behaviors that are ambiguous or vague. Our perceptions of a person’s behaviors can also be biased by how that person was previously characterized by someone else, such as saying this person is “warm” or “cold.” A car in an accident will be seen as going faster if someone describes the event as “smashed” versus “hit.” People who have a conversation about an event will converge over time in what they remember about the event. Group members will also converge in their judgments, creating consensual social norms. And groups can create these shared realities about the world even when the consensual belief is false. Stereotypes are an example of this. They can overgeneralize the negative characteristics of a social category, describing members as having traits that are rare and/or no more prevalent than in other social categories. Even worse, the stereotypes are treated as being simply descriptions of reality when they are actually evaluations based on the in-group’s values or standards (ethnocentrism).

scholarly journals Psychometric Comparisons of 4 Measures for Assessing Upper-Extremity Function in People With Stroke

2009 ◽  
Vol 89 (8) ◽  
pp. 840-850 ◽  
Author(s):  
Jau-Hong Lin ◽  
Miao-Ju Hsu ◽  
Ching-Fan Sheu ◽  
Tzung-Shian Wu ◽  
Ruey-Tay Lin ◽  
...  
Keyword(s):  
Psychometric Properties ◽  
Upper Extremity ◽  
Motor Function ◽  
Predictive Validity ◽  
Concurrent Validity ◽  
Interrater Reliability ◽  
Time Points ◽  
Function Test ◽  
Wolf Motor Function Test ◽  
Test Retest Reliability

BackgroundFunctional limitation of the upper extremities is common in patients with stroke. An upper-extremity measure with sound psychometric properties is indispensable for clinical and research use.ObjectiveThe purpose of this study was to compare the psychometric properties of 4 clinical measures for assessing upper-extremity motor function in people with stroke: the upper-extremity subscale of the Fugl-Meyer Motor Test (UE-FM), the upper-extremity subscale of the Stroke Rehabilitation Assessment of Movement, the Action Research Arm Test (ARAT), and the Wolf Motor Function Test.DesignThis was a prospective, longitudinal study.MethodsFifty-three people with stroke were evaluated with the 4 measures at 4 time points (14, 30, 90, and 180 days after stroke). Thirty-five participants completed all of the assessments. The ceiling and floor effects, validity (concurrent validity and predictive validity), and responsiveness of each measure were examined. Interrater reliability and test-retest reliability also were examined.ResultsAll measures, except for the UE-FM, had significant floor effects or ceiling effects at one or more time points. The Spearman ρ correlation coefficient for each pair of the 4 measures was ≥.81, indicating high concurrent validity. The predictive validity of the 4 measures was satisfactory (Spearman ρ, ≥.51). The responsiveness of the 4 measures at 14 to 180 days after stroke was moderate (.52 ≤ effect size ≤ .79). The 4 measures had good interrater reliability (intraclass correlation coefficient [ICC], ≥.92) and test-retest reliability (ICC, ≥.97). Only the minimal detectable changes of the UE-FM (8% of the highest possible score) and the ARAT (6%) were satisfactory.LimitationsThe sample size was too small to conduct data analysis according to type or severity of stroke. In addition, the timed component of the Wolf Motor Function Test was not used in this study.ConclusionsAll 4 measures showed sufficient validity, responsiveness, and reliability in participants with stroke. The UE-FM for assessing impairment and the ARAT for assessing disability had satisfactory minimal detectable changes, supporting their utility in clinical settings.

scholarly journals Validity, reliability, and calibration of the physical activity unit 7 item screener (PAU-7S) at population scale

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Helmut Schröder ◽  
Isaac Subirana ◽  
Julia Wärnberg ◽  
María Medrano ◽  
Marcela González-Gross ◽  
...  
Keyword(s):  
Physical Activity ◽  
Predictive Validity ◽  
Internal Consistency ◽  
Regression Models ◽  
Weighted Kappa ◽  
Linear Regression Models ◽  
Retest Reliability ◽  
Activity Unit ◽  
Test Retest Reliability ◽  
Acceptable Internal Consistency

Abstract Background Validation of self-reported tools, such as physical activity (PA) questionnaires, is crucial. The aim of this study was to determine test-retest reliability, internal consistency, and the concurrent, construct, and predictive validity of the short semi-quantitative Physical Activity Unit 7 item Screener (PAU-7S), using accelerometry as the reference measurement. The effect of linear calibration on PAU-7S validity was tested. Methods A randomized sample of 321 healthy children aged 8–16 years (149 boys, 172 girls) from the nationwide representative PASOS study completed the PAU-7S before and after wearing an accelerometer for at least 7 consecutive days. Weight, height, and waist circumference were measured. Cronbach alpha was calculated for internal consistency. Test-retest reliability was determined by intra-class correlation (ICC). Concurrent validity was assessed by ICC and Spearman correlation coefficient between moderate to vigorous PA (MVPA) derived by the PAU-7S and by accelerometer. Concordance between both methods was analyzed by absolute agreement, weighted kappa, and Bland-Altman statistics. Multiple linear regression models were fitted for construct validity and predictive validity was determined by leave-one-out cross-validation. Results The PAU-7S overestimated MVPA by 18%, compared to accelerometers (106.5 ± 77.0 vs 95.2 ± 33.2 min/day, respectively). A Cronbach alpha of 0.76 showed an acceptable internal consistency of the PAU-7S. Test-retest reliability was good (ICC 0.71 p < 0.001). Spearman correlation and ICC coefficients of MVPA derived by the PAU-7S and accelerometers increased from 0.31 to 0.62 and 0.20 to 0.62, respectively, after calibration of the PAU-7S. Between-methods concordance improved from a weighted kappa of 0.24 to 0.50 after calibration. A slight reduction in ICC, from 0.62 to 0.60, yielded good predictive validity. Multiple linear regression models showed an inverse association of MVPA with standardized body mass index (β − 0.162; p < 0.077) and waist to height ratio (β − 0.010; p < 0.014). All validity dimensions were somewhat stronger in boys compared to girls. Conclusion The PAU-7S shows a good test-retest reliability and acceptable internal consistency. All dimensions of validity increased from poor/fair to moderate/good after calibration. The PAU-7S is a valid instrument for measuring MVPA in children and adolescents. Trial registration Trial registration numberISRCTN34251612.

What Can Experimental Studies of Bias Tell Us About Real-World Group Disparities?

2021 ◽  
pp. 1-82
Author(s):  
Joseph Cesario
Keyword(s):  
Real World ◽  
Experimental Studies ◽  
White Men ◽  
Human Mind ◽  
Behavioral Differences ◽  
Social Categories ◽  
Systematic Testing ◽  
Black And White ◽  
Research Tradition ◽  
The Social

Abstract This article questions the widespread use of experimental social psychology to understand real-world group disparities. Standard experimental practice is to design studies in which participants make judgments of targets who vary only on the social categories to which they belong. This is typically done under simplified decision landscapes and with untrained decision makers. For example, to understand racial disparities in police shootings, researchers show pictures of armed and unarmed Black and White men to undergraduates and have them press "shoot" and "don't shoot" buttons. Having demonstrated categorical bias under these conditions, researchers then use such findings to claim that real-world disparities are also due to decision-maker bias. I describe three flaws inherent in this approach, flaws which undermine any direct contribution of experimental studies to explaining group disparities. First, the decision landscapes used in experimental studies lack crucial components present in actual decisions (Missing Information Flaw). Second, categorical effects in experimental studies are not interpreted in light of other effects on outcomes, including behavioral differences across groups (Missing Forces Flaw). Third, there is no systematic testing of whether the contingencies required to produce experimental effects are present in real-world decisions (Missing Contingencies Flaw). I apply this analysis to three research topics to illustrate the scope of the problem. I discuss how this research tradition has skewed our understanding of the human mind within and beyond the discipline and how results from experimental studies of bias are generally misunderstood. I conclude by arguing that the current research tradition should be abandoned.

scholarly journals Reducing Social Judgment Biases May Require Identifying the Potential Source of Bias

2018 ◽  
Vol 45 (8) ◽  
pp. 1232-1251 ◽  
Author(s):  
Jordan R. Axt ◽  
Grace Casola ◽  
Brian A. Nosek
Keyword(s):  
Social Judgment ◽  
Bias Reduction ◽  
Social Category ◽  
Social Categories ◽  
Zero Bias ◽  
Social Bias ◽  
Total N ◽  
Potential Source ◽  
Judgment Biases ◽  
Social Biases

Social judgment is shaped by multiple biases operating simultaneously, but most bias-reduction interventions target only a single social category. In seven preregistered studies (total N > 7,000), we investigated whether asking participants to avoid one social bias affected that and other social biases. Participants selected honor society applicants based on academic credentials. Applicants also differed on social categories irrelevant for selection: attractiveness and ingroup status. Participants asked to avoid potential bias in one social category showed small but reliable reductions in bias for that category ( r = .095), but showed near-zero bias reduction on the unmentioned social category ( r = .006). Asking participants to avoid many possible social biases or alerting them to bias without specifically identifying a category did not consistently reduce bias. The effectiveness of interventions for reducing social biases may be highly specific, perhaps even contingent on explicitly and narrowly identifying the potential source of bias.

scholarly journals Psychometric properties of gross motor assessment tools for children: a systematic review

BMJ Open ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. e021734 ◽  
Author(s):  
Alison Griffiths ◽  
Rachel Toovey ◽  
Prue E Morgan ◽  
Alicia J Spittle
Keyword(s):  
Psychometric Properties ◽  
Predictive Validity ◽  
Methodological Quality ◽  
Clinical Utility ◽  
Assessment Tools ◽  
Motor Assessment ◽  
Gross Motor ◽  
Retest Reliability ◽  
Validity Test ◽  
Test Retest Reliability

ObjectiveGross motor assessment tools have a critical role in identifying, diagnosing and evaluating motor difficulties in childhood. The objective of this review was to systematically evaluate the psychometric properties and clinical utility of gross motor assessment tools for children aged 2–12 years.MethodA systematic search of MEDLINE, Embase, CINAHL and AMED was performed between May and July 2017. Methodological quality was assessed with the COnsensus-based Standards for the selection of health status Measurement INstruments checklist and an outcome measures rating form was used to evaluate reliability, validity and clinical utility of assessment tools.ResultsSeven assessment tools from 37 studies/manuals met the inclusion criteria: Bayley Scale of Infant and Toddler Development-III (Bayley-III), Bruininks-Oseretsky Test of Motor Proficiency-2 (BOT-2), Movement Assessment Battery for Children-2 (MABC-2), McCarron Assessment of Neuromuscular Development (MAND), Neurological Sensory Motor Developmental Assessment (NSMDA), Peabody Developmental Motor Scales-2 (PDMS-2) and Test of Gross Motor Development-2 (TGMD-2). Methodological quality varied from poor to excellent. Validity and internal consistency varied from fair to excellent (α=0.5–0.99). The Bayley-III, NSMDA and MABC-2 have evidence of predictive validity. Test–retest reliability is excellent in the BOT-2 (intraclass correlation coefficient (ICC)=0.80–0.99), PDMS-2 (ICC=0.97), MABC-2 (ICC=0.83–0.96) and TGMD-2 (ICC=0.81–0.92). TGMD-2 has the highest inter-rater (ICC=0.88–0.93) and intrarater reliability (ICC=0.92–0.99).ConclusionsThe majority of gross motor assessments for children have good-excellent validity. Test–retest reliability is highest in the BOT-2, MABC-2, PDMS-2 and TGMD-2. The Bayley-III has the best predictive validity at 2 years of age for later motor outcome. None of the assessment tools demonstrate good evaluative validity. Further research on evaluative gross motor assessment tools are urgently needed.

scholarly journals Reducing social judgment biases may require identifying the potential source of bias

2018 ◽  
Author(s):  
Jordan Axt ◽  
Grace Casola ◽  
Brian A. Nosek
Keyword(s):  
Social Judgment ◽  
Bias Reduction ◽  
Social Category ◽  
Social Categories ◽  
Zero Bias ◽  
Social Bias ◽  
Total N ◽  
Potential Source ◽  
Judgment Biases ◽  
Social Biases

Social judgment is shaped by multiple biases operating simultaneously, but most bias-reduction interventions target only a single social category. In seven pre-registered studies (Total N &gt; 7,000), we investigated whether asking participants to avoid one social bias impacted that and other social biases. Participants selected honor society applicants based on academic credentials. Applicants also differed on social categories irrelevant for selection: attractiveness and ingroup status. Participants asked to avoid potential bias in one social category showed small but reliable reductions in bias for that category (r = .095), but showed near zero bias reduction on the unmentioned social category (r = .006). Asking participants to avoid many possible social biases or alerting them to bias without specifically identifying a category did not consistently reduce bias. The effectiveness of interventions for reducing social biases may be highly specific, perhaps even contingent on explicitly and narrowly identifying the potential source of bias.

scholarly journals A Diffusion Model Approach for Understanding the Impact of 17 Interventions on the Race Implicit Association Test

2020 ◽  
Author(s):  
Jessica Röhner ◽  
Calvin K. Lai
Keyword(s):  
Decision Making ◽  
Implicit Association Test ◽  
Association Test ◽  
Implicit Measure ◽  
Implicit Association ◽  
Implicit Measures ◽  
Long Term Effects ◽  
Sham Intervention ◽  
The Impact ◽  
Speed Accuracy

<p>Performance on implicit measures reflects construct-specific and non-construct-specific processes. This creates an interpretive issue for understanding interventions to change implicit measures: change in performance could reflect changes in the constructs-of-interest or changes in other mental processes. We re-analyzed data from six studies (<i>N</i> = 23,342) to examine the process-level effects of 17 interventions and one sham intervention to change race Implicit Association Test (IAT) performance. Diffusion models decompose overall IAT performance (<i>D</i>-scores) into construct-specific (ease of decision-making), and non-construct-specific processes (speed-accuracy tradeoffs, non-decision-related processes like motor execution). Interventions that effectively reduced <i>D-</i>scores changed ease of decision-making on compatible and incompatible trials. They also eliminated differences in speed-accuracy tradeoffs between compatible and incompatible trials. Non-decision-related processes were impacted by two interventions only. There was little evidence that interventions had any long-term effects. These findings highlight the value of diffusion modeling for understanding the mechanisms by which interventions affect implicit measure performance.</p>

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