مقایسهٔ روش‌ها

	Evaluative Priming	Affect Misattribution Procedure	Affective Priming Task
حوزه	روان‌شناسی اجتماعی	روان‌شناسی اجتماعی	روان‌شناسی اجتماعی
خانواده	Process / pipeline	Process / pipeline	Process / pipeline
سال پیدایش	1986	2005	1994
پدیدآور	Russell H. Fazio and colleagues	B. Keith Payne and colleagues	Dirk Hermans, Jan De Houwer & Paul Eelen
نوع	Reaction-time implicit attitude paradigm	Implicit attitude measurement procedure	Reaction-time automatic evaluation paradigm
منبع بنیادین	Fazio, R. H., Sanbonmatsu, D. M., Powell, M. C., & Kardes, F. R. (1986). On the automatic activation of attitudes. Journal of Personality and Social Psychology, 50(2), 229-238.	Payne, B. K., Cheng, C. M., Govorun, O., & Stewart, B. D. (2005). An inkblot for attitudes: Affect misattribution as implicit measurement. Journal of Personality and Social Psychology, 89(3), 277-293.	Hermans, D., De Houwer, J., & Eelen, P. (1994). The affective priming effect: Automatic activation of evaluative information in memory. Cognition and Emotion, 8(6), 515-533.
نام‌های دیگر	Automatic Evaluation Task, Fazio Priming Task, Bona Fide Pipeline	AMP, Affect Misattribution Task, Inkblot for Attitudes	Affective Priming Paradigm, Naming Affective Priming, Pronunciation Priming Task
مرتبط	3	3	3
خلاصه	Evaluative priming, introduced by Fazio and colleagues in 1986, is the foundational reaction-time paradigm for measuring automatic attitudes. On each trial an attitude object (the prime) is briefly presented and is quickly followed by a clearly positive or negative target word that the participant categorizes as 'good' or 'bad' as fast as possible. When the prime and target share the same valence -- a liked object followed by a positive word -- responses are faster; when they mismatch, responses slow. This congruency effect reveals that merely seeing an attitude object automatically activates its associated evaluation, which then facilitates or interferes with judging the target. Because the attitude is inferred from response speed rather than self-report, evaluative priming gives a window onto spontaneous evaluations and became, in its 'bona fide pipeline' form, an early standard for measuring implicit attitudes including racial prejudice.	The Affect Misattribution Procedure (AMP), introduced by Payne, Cheng, Govorun, and Stewart in 2005, is an implicit measure of attitudes built on a simple cognitive error: people misattribute the feeling evoked by one stimulus to another. On each trial a brief affective prime (such as a Black or White face, or a positive or negative word) is flashed, followed by a neutral target -- typically an unfamiliar Chinese pictograph -- which the participant rates as more or less pleasant than average while being explicitly told to ignore the prime. Because the prime's affect bleeds into the judgment of the ambiguous target, the proportion of pleasant ratings following positive versus negative primes yields an index of the attitude toward the primes. The AMP proved remarkably reliable and resistant to control, and it predicts self-reported attitudes, voting intentions, and intergroup bias, making it one of the most widely used implicit measures alongside the Implicit Association Test.	The affective priming task, developed by Hermans, De Houwer, and Eelen in 1994, demonstrates that stimulus evaluation is automatic and goal-independent. Like evaluative priming it pairs a valenced prime with a valenced target, but instead of asking participants to judge the target's valence it asks them simply to pronounce or name the target aloud as fast as possible. Targets are named faster when preceded by an affectively congruent prime than an incongruent one, even though the naming task never requires evaluating valence. This is a crucial theoretical point: because evaluation facilitates responding even when it is irrelevant to the task, the affective reaction must be triggered automatically and unintentionally. The naming variant became an important tool for distinguishing genuinely automatic evaluation from response-competition artifacts that can arise in valence-classification tasks.