Disentangling behavioral intention and behavioral expectation

Social psychologists have extensively researched behavioral intention and its relation to future behavior, usually within the framework of M. Fishbein and I. Ajzen's (1975, Belief, attitude, intention and behavior: An introduction to theory and research, Reading, MA: Addison-Wesley) theory of reasoned action. However, the field has confounded two separate constructs while investigating intention: behavioral intention (BI) and what P. R. Warshaw, B. H. Sheppard, and J. Hartwick (in press, in R. Bagozzi (Ed.), Advances in marketing communication, Greenwich, CT: JAI Press) have coined behavioral expectation (BE), which is the individual's self-prediction of his or her future behavior. In this paper we define both constructs and explain how they differ in terms of the processes by which they are formed, their roles in determining behavior, and their utilities as behavioral predictors. We propose that behavioral expectation is the more accurate overall predictor since many common behaviors are unreasoned (i.e., mindless or habitual) behaviors, goal-type actions, or behaviors where the individual expects his or her intention to change in a foresseable manner. These are all cases where present intention (BI) is not the direct determinant of behavior but where the individual may be capable of appraising whatever additional determinants exist and of including them within his or her behavioral expectation. A study (N = 197) is reported in which student subjects received either a BE (n = 113) or a BI (n = 84) version of a questionnaire pertaining to their performance of 18 common behaviors. Overall, behavioral expectation was the better predictor of self-reported performance.     

Training behavioral technicians to implement naturalistic behavioral interventions using behavioral skills training

Training behavioral technicians mainly focuses on teaching accurate implementation of structured behavioral intervention programs. Often behavioral technicians are unable to adequately promote their clients' learning in less structured environments, which can limit opportunities for generalization of the clients' skills to the natural environment. The aim of the present study was to evaluate the effectiveness of using behavioral skills training to coach behavioral technicians on the implementation of naturalistic behavioral interventions. Naturalistic behavioral interventions take advantage of naturally occurring situations to teach new skills and practice mastered skills in natural settings, thus promoting generalization across environments and in the presence of natural contingencies. Five behavioral technicians were trained to implement a novel protocol based on play therapy. Specifically, they were coached to engage in well‐defined positive behaviors during their interactions with clients (e.g., labeled praise). All participants reached mastery criteria, maintained skills at follow‐up, and demonstrated generalization of skills with novel clients.     

How research in behavioral pharmacology informs behavioral science

Behavioral pharmacology is a maturing science that has made significant contributions to the study of drug effects on behavior, especially in the domain of drug-behavior interactions. Less appreciated is that research in behavioral pharmacology can have, and has had, implications for the experimental analysis of behavior, especially its conceptualizations and theory. In this article, I outline three general strategies in behavioral pharmacology research that have been employed to increase understanding of behavioral processes. Examples are provided of the general characteristics of the strategies and of implications of previous research for behavior theory. Behavior analysis will advance as its theories are challenged.     

Rate dependency, behavioral mechanisms, and behavioral pharmacology.

Behavioral pharmacology has become increasingly independent of the experimental analysis of behavior. At its beginning, behavioral pharmacology was closely related to the experimental analysis of behavior, with developments in each field aiding the other. Early attempts to systematize data in behavioral pharmacology culminated with the development of the rate-dependency concept, but as this principle was found to have more limited generality than originally was hoped, a theoretical void developed. This circumstance was followed by increased reliance on pharmacological theory as a basis for experimentation and interpretation, with an attendant decrease in emphasis on environmental variables and behavioral interpretations. Lack of interplay between behavioral pharmacology and the experimental analysis of behavior is detrimental to both disciplines because each could contribute significantly to the other. The current trend might be reversed if more research were directed at elucidating behavioral mechanisms of drug action.     

Anticipated emotions and personal experience for predicting behavioral intentions and behavioral expectations

We tested how anticipated emotions interact with personal experience in risk behavior to improve predictions from TPB on behavioral intention (BI) and behavioral expectation (BE) for sex without condom (Study 1) and excessive drinking (Study 2). In the moderate-high experience group, anticipated emotional profiles (AEPs) improve TPB prediction from 28% to 45% in the case of BI and from 19% to 40% in that of BE in relation to sexual risk behavior (Study 1), and from 23% to 36% in the case of BI and from 17% to 31% in that of BE in relation to binge drinking (Study 2). However, in the low-experience group (Study 2) AEPs improve TPB predictions for BI (12% to 34%) but not for BE, showing that in less experienced people BI and BE are not equivalent: anticipated emotions have different relevance in their prediction. These results were replicated using a general negative anticipated emotion index (averaging emotional categories).     

Making behavioral technology transferable

The paucity of transferred behavioral technologies is traced to the absence of strategies for developing technology that is transferable, as distinct from strategies for conducting research, whether basic or applied. In the field of engineering, the results of basic research are transformed to candidate technologies that meet standardized criteria with respect to three properties: quantification, repetition, and verification. The technology of vitrification and storage of nuclear waste is used to illustrate the application of these criteria. Examples from behavior analysis are provided, together with suggestions regarding changes in practice that will accelerate the development and application of behavioral technologies.     

Engineering the behavioral engineer

Twenty-eight nursing staff members treated, by operant methods, a simulated headbanging patient. They were randomly assigned to four experimental conditions, involving improvement versus non-improvement of the "patient" and promise of reward versus no promise of reward. The promise of reward significantly improved accuracy of treatment. Improvement of the patient, however, did not improve accuracy.     

Choice and behavioral patterning

Ten pigeons pecked left and right keys in a discrete-trials experiment in which access to food was contingent upon changeovers to the right key after particular runs of left-key pecks. In each of three sets of conditions, two run lengths were reinforced according to a concurrent variable-interval schedule: reinforcement followed runs of either 1 or 2, 1 or 4, or 2 or 4 left-key pecks preceding changeovers. The intertrial interval separating successive pecks was varied from .5 to 10.0 sec, and the relative frequency of reinforcement for the shorter of the two reinforced runs was varied from 0 to .75. The contingencies established local behavioral patterning that roughly approximated that required for reinforcement. For a fixed pair of reinforced run lengths, preference for the shorter of the two frequently increased as the intertrial interval increased and therefore as the minimum temporal durations of both reinforced runs increased. Preference for the shorter of the two also increased as its corresponding relative frequency of reinforcement increased. Both of these effects on preference were qualitatively similar to corresponding effects in previous research with two different kinds of reinforced behavioral patterns, interresponse times and interchangeover times. In all these experiments, analytical units were found in the temporal patterns of behavior, not in the behavior immediately contiguous with a reinforcer. It is suggested that a particular local temporal pattern of behavior is established to the extent to which it is repeatedly remembered when reinforcers are delivered, regardless of whether the delivery of a reinforcer is explicitly contingent upon that pattern.     

Metaphors in behavioral genetics

Behavioral geneticists sometimes use metaphorsto describe the role of genes in humanbehavior. In this paper, five sample texts areanalyzed: a popular book, a textbook, ascientific review article, and two originalscientific articles representing differentapproaches in behavioral genetics. Metaphorsare found in all the different kinds of sampletexts, not only in the popular book and thetextbook. This suggests that metaphors are usednot only for rhetorical or pedagogical purposesbut play a more fundamental role in scientificunderstanding. In the sample texts, themetaphors tend to be antideterministic, i.e.,they do not imply genetic determinism butstress the interaction of multiple genes andmultiple environmental factors. No conclusioncan be drawn, however, as to whetherantideterminism is representative ofpresent-day behavioral geneticists in general.Certain historically important metaphors thatmay imply genetic determinism are qualified,avoided, or explicitly rejected. There aretensions between some of the metaphors, makingthem difficult to combine. All the metaphorsthat are used appear empirically apt, howeversometimes only with certain qualifications.