We introduce the ReAL model for the Implicit Association Test (IAT), a multinomial processing tree model that allows one to mathematically separate the contributions of attitude-based evaluative associations and recoding processes in a specific IAT. The ReAL model explains the observed pattern of erroneous and correct responses in the IAT via 3 underlying processes: recoding of target and attribute categories into a binary representation in the compatible block (Re), evaluative associations of the target categories (A), and label-based identification of the response that is assigned to the respective nominal category (L). In 7 validation studies, using an adaptive response deadline procedure in order to increase the amount of erroneous responses in the IAT, we demonstrated that the ReAL model fits IAT data and that the model parameters vary independently in response to corresponding experimental manipulations. Further studies yielded evidence for the specific predictive validity of the model parameters in the domain of consumer behavior. The ReAL model allows one to disentangle different sources of IAT effects where global effect measures based on response times lead to equivocal interpretations. Possible applications and implications for future IAT research are discussed.
Two decades ago, the introduction of the Implicit Association Test (IAT) sparked enthusiastic reactions. With implicit measures like the IAT, researchers hoped to finally be able to bridge the gap between self-reported attitudes on one hand and behavior on the other. Twenty years of research and several meta-analyses later, however, we have to conclude that neither the IAT nor its derivatives have fulfilled these expectations. Their predictive value for behavioral criteria is weak and their incremental validity over and above self-report measures is negligible. In our review, we present an overview of explanations for these unsatisfactory findings and delineate promising ways forward. Over the years, several reasons for the IAT’s weak predictive validity have been proposed. They point to four potentially problematic features: First, the IAT is by no means a pure measure of individual differences in associations but suffers from extraneous influences like recoding. Hence, the predictive validity of IAT-scores should not be confused with the predictive validity of associations. Second, with the IAT, we usually aim to measure evaluation (“liking”) instead of motivation (“wanting”). Yet, behavior might be determined much more often by the latter than the former. Third, the IAT focuses on measuring associations instead of propositional beliefs and thus taps into a construct that might be too unspecific to account for behavior. Finally, studies on predictive validity are often characterized by a mismatch between predictor and criterion (e.g., while behavior is highly context-specific, the IAT usually takes into account neither the situation nor the domain). Recent research, however, also revealed advances addressing each of these problems, namely (1) procedural and analytical advances to control for recoding in the IAT, (2) measurement procedures to assess implicit wanting, (3) measurement procedures to assess implicit beliefs, and (4) approaches to increase the fit between implicit measures and behavioral criteria (e.g., by incorporating contextual information). Implicit measures like the IAT hold an enormous potential. In order to allow them to fulfill this potential, however, we have to refine our understanding of these measures, and we should incorporate recent conceptual and methodological advancements. This review provides specific recommendations on how to do so.
These findings suggest that implicit and explicit age stereotypes in different life domains represent largely independent constructs. Differential age group effects are assumed to reflect the result of accommodative and assimilative processes that are used to cope with age-related changes. Implications for future studies of implicit and explicit age stereotypes and their influence on developmental regulation are discussed.
Implicit Association Tests (IATs) employing pictures as target stimuli usually yield smaller scores than those with verbal target stimuli, suggesting weaker attitudes in the former compared to the latter case. As the attribute dimension of attitude IATs is typically represented by words, we hypothesized the target modality effect to be actually due to a modality match between targets and attributes. We manipulated stimulus modality independently for targets and attributes and confirmed our assumption in two attitude IATs (Experiment 1: flower/insect, Experiment 2: old/young): Employing verbal attributes, IAT scores were smaller for pictorial compared to verbal targets. However, the target modality effect disappeared or was even reversed if pictures were employed as attributes. Applying the ReAL model revealed that this modality match effect is mediated by recoding processes. Importantly, evaluative associations remained unaffected by modality match and reflected equal or even stronger preferences for pictorial compared to verbal targets.
Zusammenfassung Hintergrund In Deutschland findet Palliativversorgung (PV) ambulant, stationär, allgemein und spezialisiert statt. Da bisher wenig bekannt ist über die zeitliche Entwicklung und regionale Unterschiede in den Versorgungsformen, war es Ziel der vorliegenden Studie, dies zu untersuchen. Methoden Retrospektive Routinedatenstudie mit 417.405 in den Jahren 2016–2019 verstorbenen BARMER-Versicherten. Anhand mindestens einmalig abgerechneter Leistung im letzten Lebensjahr ermittelten wir die Inanspruchnahmeraten allgemeiner ambulanter Palliativversorgung (AAPV), besonders qualifizierter und koordinierter palliativmedizinischer Versorgung (BQKPmV), spezialisierter ambulanter Palliativversorgung (SAPV), stationärer Palliativ- und Hospizversorgung. Wir berechneten Zeittrends, regionale Unterschiede und kontrollierten für versorgungsbedarfsbezogene Patientenmerkmale und zugangsbezogene Wohnkreismerkmale. Ergebnisse Von 2016 bis 2019 stieg die Inanspruchnahme von PV insgesamt von 33,8 % auf 36,2 %, SAPV von 13,3 % auf 16,0 % (max.: Rheinland-Pfalz), stationärer PV von 8,9 % auf 9,9 % (max.: Thüringen); AAPV sank von 25,8 % auf 23,9 % (max.: Brandenburg); BQKPmV kam 2019 auf 4,4 % (max.: Saarland); Hospiz blieb konstant bei 3,4 %. Die regionale Variabilität der Inanspruchnahmeraten nahm bei AAPV und stationärer PV von 2016 auf 2019 zu, bei SAPV und Hospiz ab, blieb insgesamt jedoch hoch. Die regionalen Unterschiede zeigten sich auch nach Adjustierung. Diskussion Zunehmend mehr SAPV, weniger AAPV und hohe, nicht durch bedarfs‑/zugangsbezogene Merkmale erklärbare regionale Variabilität sprechen dafür, dass sich der Einsatz palliativer Versorgungsformen weniger am Bedarf als an regional verfügbaren Versorgungskapazitäten orientiert. Angesichts demografiebedingt wachsenden PV-Bedarfs und abnehmender personeller Ressourcen ist diese Entwicklung kritisch zu sehen.
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