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Normative Emotional Responses to Behavior Analysis Jargon or How Not to Use Words to Win Friends and Influence People


It has been suggested that non-experts regard the jargon of behavior analysis as abrasive, harsh, and unpleasant. If this is true, excessive reliance on jargon could interfere with the dissemination of effective services. To address this often discussed but rarely studied issue, we consulted a large, public domain list of English words that have been rated by members of the general public for the emotional reactions they evoke. Selected words that behavior analysts use as technical terms were compared to selected words that are commonly used to discuss general science, general clinical work, and behavioral assessment. There was a tendency for behavior analysis terms to register as more unpleasant than other kinds of professional terms and also as more unpleasant than English words generally. We suggest possible reasons for this finding, discuss its relevance to the challenge of deciding how to communicate with consumers who do not yet understand or value behavior analysis, and advocate for systematic research to guide the marketing of behavior analysis.

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  1. For whatever it is worth, the historical record portrays Attila as ruthlessly efficient but, at unpredictable intervals, surprisingly compassionate and ethical (Howarth, 1994).

  2. In which we perceive no small irony given that a behaviorist, John B. Watson, is credited as a major innovator in modern marketing (Buckley, 1982).

  3. One relevant finding is that positively emotional communication makes a speaker seem more familiar (Garcia-Marques et al., 2004). If the opposite is true—that negatively emotional communication makes speakers seem strange or remote—then those who use unpleasant words are unlikely to be the “comfortable” therapists that consumers prefer (Backer et al., 1986; Barrett-Lennard, 1962; Rosenzweig, 1936).

  4. In Warriner et al. (2013), the raters were about 60% female and reflected a broad range of ages and levels of education.

  5. Non-practitioners take note: There is even some evidence that the linguistic style of scientific abstracts affects the probability that an article will “go viral” via citations and professional social media communication (Guerini et al., 2012).

  6. Three terms (punish, shape, and escape) were evaluated using the University of South Florida Free Association Norms ( This corpus provides the proportion of individuals who generated a forward (word to associate) match and the proportion who generated a backward (associate to word) match; Fig. 5 reflects the sum of these. Three other terms (operation, avoid, and extinct[ion]) were evaluated using the Edinburgh Associative Thesaurus ( This corpus provides only forward association data. Thus, although the source and format of data varied across panels, each panel provides on means of estimating high-probability word associations.


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Correspondence to Thomas S. Critchfield.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

This article does not contain any studies with human participants performed by any of the authors. It drew instead on archival, public domain data sets. Therefore, Institutional Review Board oversight does not apply.

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Summary of the Warriner et al. (2013) Rating Procedure

Each participant was paid 75 US cents for rating a set of approximately 350 words. A rater evaluated a given set of words on only one emotional dimension (e.g., only pleasantness or arousal). The first 10 words provided raters with practice using the full range of possible ratings and were drawn from lists of words shown in previous research to evoke a wide range of emotional responses (for pleasantness: jail, invader, insecure, industry, icebox, hat, grin, kitten, joke, and free; for arousal: statue, rock, sad, cat, curious, robber, shotgun, assault, thrill, and sex). Of the remaining words, 40 were drawn from a previous study of about 1000 words (Bradley & Lang, 1999) and served as a validity check. A participant whose ratings of these words did not correlate sufficiently with those in the Bradley and Lang (1999) corpus was dropped from the analysis.

Prior to beginning the procedure, raters of pleasantness read the following instructions:

You are invited to take part in the study that is investigating emotion, and concerns how people respond to different types of words. You will use a scale to rate how you felt while reading each word....The scale ranges from 1 (happy) to 9 (unhappy). At one extreme of this scale, you are happy, pleased, satisfied, contented, hopeful. When you feel completely happy you should indicate this by choosing rating 1. The other end of the scale is when you feel completely unhappy, annoyed, unsatisfied, melancholic, despaired, or bored. You can indicate feeling completely unhappy by selecting 9. The numbers also allow you to describe intermediate feelings of pleasure... If you feel completely neutral, neither happy nor sad, select the middle of the scale (rating 5). Please work at a rapid pace and don’t spend too much time thinking about each word. Rather, make your ratings based on your first and immediate reaction as you read each word. (Warriner et al., 2013, p. 1193).

For raters of arousal, the scale was described as ranging from 1 = “excited” [elaborated as “stimulated, excited, frenzied, jittery, wide-awake, or aroused”] to 9 = “calm” [elaborated as, “relaxed, calm, sluggish, dull, sleepy, or unaroused”] (p. 1193).

Consistent with practices in the psycholinguistic literature, Warriner et al. (2013) reported their results with ratings in reverse-scored format, such that 1 = unhappy/unpleasant [calm/unaroused] and 9 = happy/pleasant [excited/aroused]. We did the same.

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Critchfield, T.S., Doepke, K.J., Kimberly Epting, L. et al. Normative Emotional Responses to Behavior Analysis Jargon or How Not to Use Words to Win Friends and Influence People. Behav Analysis Practice 10, 97–106 (2017).

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