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PART I. Issues of Theory and Methodology

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Human Performance Research: An Overview Monica J. Harris and Robert Rosenthal Harvard University

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Table of Contents Interpersonal Expectancy Effects eeeeeeeeee.~ee.~1 Definition. eeeeeee.~eeeeeeeeeeeeaeee.eeeeeeee.eeeee.eeeeeeee.~.e.1 Evidence for Expectancy Effects eee.eee.~eeeeee..eee.~.eeaeeeae.~.e2 Methodological Implications of Expectancy Effects ee.~.ee.~.e.~3 Mediation of Interpersonal Expectancy Effects e.~.eeeee.~.eeeee5 Ran: i ~ I .C$:tl-.C ~ The Four-Factor Theory e.~eeaee.~eeeee.~ee..eee.~. Meta-Analysis of Expectancy Mediation eeee..eeeee Human Performance Technologies and Expectancy Effects ee e. Research on Accelerated Learning... Neurolinguistic Programming... ee Imagery and Mental Practiced... Biofeedback......... Parapsychology eeeeeeeeeseeeeae.~41 Situational Taxonomy of Human Performance Technologies 52 Sugges t ions for Future Research . e.~. 57 Expectancy Con tro 1 Des i gns . . . . . e.~.e. 57 Central ~ for Expectancy Effects .. ~ ~ ...... Expectancies ant the Enhancement of Human Performance.... Conclusion................................ Ref erence se~~eea~~ ~~e ^~.ea.~62 ooe.65

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4 interpretation of results: Increasing ransom noise merely makes it more difficult to obtain significant results, but increasing systematic bias can result in completely erroneous cone fusions . Experimenter expectancy effects are a potential source of problems for any research area, but they may be especially influential in more recent research areas lacking well-established findings. This is because the first studies on a given treatment or technique are typically carries out by creators or proponents of the technique who tend to hold very positive expectations for the efficacy of the technique. It is not until later that the technique may be investigated by more impartial or skeptical researchers, who may be less prone to expectancy effects operating to favor the technique. Many of the human performance technologies of interest in the present paper are relatively recent innovations, and thus may be especially susceptible to expectancy effects. In principle, expectancy effects could be investigated by introducing expectations as a manipulation in addition to the independent variable of theoretical interest. This method, which will be described in detail later, allows the direct comparison of the magnitudes of the effects due to the phenomenon and effects due to expectancies. Another approach, perhaps even richer theoretically, is to examine directly the processes underlying expectancy effects as they occur in various areas. In same areas, such as the area of teacher expectancy effects, a considerable amount of research has been conducted in this manner, and there is now a good general understanding of what variables are important in mediating teacher expectancies. However, in other areas, such as the human technologies of interest here, this background research is lacking. The best that can be done in such cases is: (a) to

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Interpersonal Expectancy Effects and Human Performance Research Monica J. Harris and Robert Rosenthal Humans have long tried to surmount their traditional limitations and to increase their performance. Long ago such efforts were aided by social institutions of religion, proto-medicine, and magic. More recently, Such efforts have been aides by social institutions of science ant its associated technologies. Systematic programs have been developed with such aims as improving communication, accelerating learning, ant increasing conscious control over physiological processes. Because the promise of enhancing human performance is so appealing, considerable resources, both in terms of time ant money, are being invested in these programs. The time has come to step back ant evaluate human performance technologies so that resources may be directed more appropriately. The purpose of this paper is to aid in such an evaluation. We will focus specifically on the possible influence of interpersonal expectancy effects on several human performance technologies. The paper advances in three steps: First, we describe the methodological, theoretical, ant empirical issues relevant to the study of expectancy effects, including how expectancy effects are mediated. Second, we describe each of several types of human performance research and speculate on the extent to which expectancy effects may be responsible for the experimental results. Finally, we discuss more generally how the literature on expectancy effects can be applied to the development and evaluation of human performance technologies. Interpersonal Expectancy Effects Def inition An interpersonal expectancy effect occurs when a person (A), acting in accordance with a set of expectations, treats another person (B.) in such a

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2 manner as to elicit behavior that tends to confirm the original expectations (Rosenthal, 1966, 1976~. For example, a teacher who believes that certain pupils are especially bright may act more warmly toward them, teach them more material, and spend more time with them. Over time, such a process could result in greater gains in achievement for those students than would have occurred otherwise. The concept of an expectancy effect was first introduced by Merton (1948) in his discussion of the self-fulfilling prophecy, which he defined as "a false definition of the situation evoking a new behavior which makes the originally false conception come true" (p. 195~. The first systematic application of the concepts of expectancy effects in the field of psychology came in the 1960s with a program of research on experimenter expectancy effects (e.g., Rosenthal, 1963~. This research demonstrated that the experimenter's hypothesis may act as an unintended determinant of experimental results. In other words, experimenters may obtain the results they predicted not because the relationship exists as predicted in the real world but because the experimenters expected the sub jec ts to behave as they did . Evidence for Interpersonal Expectancy Effects Although originally fraught with controversy, the existence of interpersonal expectancy effects is no longer in serious doubt. In 197B, Rosenthal ant Rubin reported the results of a meta-analysis of 345 studies of expectancy effects. A meta-analysis is the quantitative combination of the results of a group of studies on a given topic. This meta-analysis showed that the probability that there is no relationship between experimenters' expectations and their subjects' subsequent behavior is less than .0000001. The practical importance of expectancy effects was also substantial; the mean

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effect size of expectancy effects across the 345 studies was equivalent to a correlation coefficient of .33. This meta-analysis also investigated the importance of expectancy effects within a wide variety of research domains. There were eight categories of expectancy studies: reaction time experiments, inkblot tests, animal learning, laboratory interviews, psychophysical judgments, learning and ability, person perception, and everyday situations or field studies. Although effect sizes varied across categories, the importance of expectancy effects within each category was firmly established. These results suggest that expectancy effects may occur in many different areas of behavioral research and emphasize the importance of taking into account the possibility of expectancy effects when designing and conducting studies. Although initially focused on the psychological experiment as the domain of interest, research on expectancy effects turned quickly to other domains where expectancy effects might be operating, domains such as teacher-student, employer-employee, and therapist-client interactions. Over the years, research interest has also turned from merely documenting the existence of expectancy effects to delineating the processes underlying expectancy effects. Methodological Implications of Expectancy Effects Experimenter expectancy effects are a source of rival hypotheses in accounting for experimental results. In other words, a given result could be causes not by the independent variable under investigation but rather by the experimenter' a expectation that such a result would be obtained. As rival hypotheses, expectancy effects can be considered a threat to the internal validity of a study; they are a source of systematic bias rather than random error. Consequently, expectancy effects present a serious danger to the

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4 interpretation of results: Increasing random noise merely makes it more difficult to obtain significant results, but increasing systematic bias can result in completely erroneous cone fusions . Experimenter expectancy effects are a potential source of problems for any research area, but they may be especially influential in more recent research areas lacking well-established findings. This is because the first studies on a given treatment or technique are typically carried out by creators or proponents of the technique who tend to hold very positive . expectations for the efficacy of the technique. It is not until later that the technique may be investigated by more impartial or skeptical researchers, who may be less prone to expectancy effects operating to favor the technique. Many of the human performance technologies of interest in the present paper are relatively recent innovations, and thus may be especially susceptible to expectancy effects. ~ . In principle, expectancy effects could be investigated by introducing expectations as a manipulation in addition to the independent variable of theoretical interest. This method, which will be described in detail later, allows the direct comparison of the magnitudes of the effects due to the phenomenon and effects due to expectancies. Another approach, perhaps even richer theoretically, is to examine directly the processes underlying expectancy effects as they occur in various areas. In Some areas, such as the area of teacher expectancy effects, a considerable amount of research has been conducted in this manner, ant there is now a good general understanding of what variables are important in mediating teacher expectancies. However, in other areas, such as the human technologies of interest here, this background research is lacking. The best that can be done in such cases is: (a) to

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Us analyze the situations of interest, (b) to determine whether mediating mechanisms shown to be important in traditional research areas are likely to be present in the new areas, and (c) to estimate the extent to which expectancy effects could be influential in the new area. The present paper undertakes such an analysis. Mediation of Interpersonal Expectancy Effects Basic Issues - A primary question of interest with respect to expectancy effects is the question of mediation: How are one person's expectations communicated to another person so as to create a self-fulfilling prophecy? This question in turn can be broken down into two components. The first component is the differential behaviors that are displayed by the expecter as a result of holding differential expectancies (the expecter-behavior link). For example, in what ways do teachers treat their high expectancy students differently? The second component is the differential behaviors that are associated with actual change in expectee behavior and self-concept (the behavior-outcome link). For example, what teacher behaviors result in better academic performance by the students? Both these aspects are critical in understanding expectancy mediation, for even if we could show an enormous effect of expectancy on expecter behavior (e.g., teachers smile more at high expectancy students), that behavior would not be important in expectancy mediation unless it actually impacted on the expectee to create better outcomes (e.g., being smiled at leads to better grates). The Four-Factor "Theory" ~ , Rosenthal (1973a, 1973b) proposed a four-factor "theory" of the mediation of teacher expectancy effects. In this view, four broad groupings of teacher

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6 behaviors are hypothesized to be involved in teacher expectancy effects. The first factor is climate, referring to the warmer 60cioemotional climate that teachers may create for their high expectancy students. This factor includes warmth communicated in both verbal and nonverbal channels. The second factor, feedback, refers to teachers' tendency to give more differentiated feedback to high expectancy students. The third factor, input, refers to the tendency to teach more material and more difficult material to high expectancy students. The fourth factor is output, or the tendency for teachers to spend more time with high expectancy students and provide them with greater opportunities for responding. Although the four factor theory was originally proposed to account for the mediation of teacher expectancy effects, it seems reasonable to think that these factors may also operate in other domains where expectancy effects may be operating. Meta-analysis _ Expectancy Mediation The question of how expectancy effects are mediated is ultimately an empirical one. Luckily, many studies address the mediation of expectancy effects, and we have conducted a meta-analysis of this literature (Harris & Rosenthal, 1985). Essentially, we read all the studies we could find that examined expectancy mediation (resulting in an initial pool of 180 studies) and classified them according to the mediating variables that were investigated. This resulted in 31 mediating behaviors each of which was examined in at least four studies. We then computed an overall significance level and effect size for each of the 31 categories, separately for the expectancy-behavior effects and the behavior-outcome effects. The results of this meta-analysis pointed to the practical importance of 16 behaviors in mediation: negative climate, physical distance, input,

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7 positive climate, off-task behavior, duration of interactions, frequency of interactions, asking questions, encouragement, eye contact, smiles, praise, accepting students' ideas, corrective feedback, nods, and wait-time for responses. Table 1 summarizes the results of the meta-analysis for these 16 behaviors, presenting the effect sizes for the expectancy-behavior links and the behavior-outcome links separately. An intuitive way of understanding these effect sizes is given by the Binomial Effect Size Display (BESD; Rosenthal & Rubin, 1982). The BE SD expresses correlations in terms of percent increase in "success" rates due to a given "treatment," with the treatment group success rate computed as .50~(r/2) and the control group success rate computed as .50-(r/2). So, for example, the correlation of .21 for Positive Climate can be interpreted using the BE SD as meaning that the percentage of teachers exhibiting above average amounts of Positive Climate will increase from 39.5Z [.50-(.21/2)] for low expectancy students to 60.5: [.50+(.21/2)] for high expectancy students. The other effect sizes can be similarly interpreted. Note that in Table 1 the effect sizes for behavior-outcome relations tend to be larger than the effect sizes for expectancy-behavior relations. One possible reason for this is that expectancies are manifested in myriad ways, meaning that the relationship between expectations and any particular behavior is not likely to be very strong. However, we can more accurately predict a person's response to a particular behavior once we know that a particular behavior has occurred. In other words, if we can condition on the behaviors emitted, we are in a better position to make more accurate predictions. We also presented a summary analysis evaluating the four factor theory. The ten behavior categories with the most studies (and therefore providing the most stable estimates) were reclassified into the four factors of climate, feedback, input, and output. We then computed an overall significance level

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38 belief in the new ~anscenderd physics remains. Some recent examples of the "vividness" criteria in media reports are Me press coverage given ~ me~-bend~ng children (e.g. Defty, Washington Post' March 2, 1980) and the tremendous attention given the Columbus, Ohio, poltergeist (Safran, Reader's Digest, December 1984; San Francisco Chron- icle, March 7, 1984, from Associated Press). Both stones developed Croup extremely unreliable per- sonal experience (Rand), 1983; Kurtz, 1984b) and demonstrate the way Mat personal reports fit me requirements of the media better than caution or rigor. Expenmental analysis is rarely as dramatic or newsworthy as personal reports, especially since rigorous analysis emphasizes a cautious conservative approach. FoDow-up stones on the "debunking" of these phenomena rarely receive comparable atten- non to the first excited reports. The public television program Nova is regarded as one of the best popular freemen of scientific affairs in any communicator medium. Yet itS program on ESP has been vilified by skeptics of paranonnal phenomena (Lutz, 1984b). It tried to show both sides of the issue-- it included dramatic "recreations" of the most famous ESP experiments and interviews with civics of ESP who proposed altemadve explanations of these experiments. The mcreated stones were more exciting and vividly memorable than the interviews. The enthusiasm and hopefulness of the believed was. more gripping than the skeptics' "accenn~abon of Me negative". What were the producers of Nova to do about the fact that what made a good story also was memorable and persuasive-- even though these elements were irrelevant to what was ~e? In this case, Hey went for the good story.

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39 Perceptual biases and mediated information People with strong pm-exisiing beliefs are rarely affected by any presentation of evidence. Instead, Hey manage to find some confim~adon in aU presentations. The "biased assimilator" of evi- dence relevant to our beliefs is a phenomenon that seems obviously true of omen, but sometimes difficult to believe In ourselves. Consider a classic social psychological study of students' perceptions of the annual Pr~nceton-Darunouth football game. (Hastorf and Cant, 19541. Students from the opposing schools watched a movie of the rough 1951 football game and were asked to carefully record an infractions. The Ho groups ended up with different scorecards based on the same game. Of coupe, this is not remarkable at an. We see this in sports enthusiasts and portico pow even day. But what is worth noting is that the students used objective trial by trim recording techniques and they sod saw different games if Hey were on different sides. This is a clue to the reason that people cannot understand why others continue to disagree wad them, even after they have been shown the "truth". We construct our perceived wodd on the basis of expectations and theones, and then we fall to take this constructed nature of the world into account. When we talk about the same "facts" we may not be arguing on the basis of the same construed evi- dence. This is especially important when we are faced with ~nte~prei~ng mixed evidence. IN almost an real-world cases, evidence does not come neatly packaged as "pro" or "con", and we have to interpret how each piece of evidence supports each side. IN a more recent extension of this idea, social psychologists at Stanford University presented proponents and opponents of capital punishment with some studies that purported to show Hat deter- rence worked, and some studies apparently showing that capital punishment had no deterrence effect Cord, Ross & Lepper, 1979~. They reasoned that common sense must dictate that mixed evidence should lead to a decrease in certainty In the beliefs of both partisan groups. But if partisans accept

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40 supportive evidence at face value, critically scrutinize contradictory evidence, and construe ambiguous evidence according to their theones, both sides might actuary strengthen their beliefs on the basis of the mixed evidence. '1he answer was clear in our subjects assessment of the pertinent deterrence studies. Both groups believed that the methodology that had yielded evidence supportive of Weir view had been clearly superior, both in its relevance and freedom from artifact, lo the methodology that had yielded non-suppor~ve evidence. ~ fact however, the sum jects were evaluating exactly the same designs and procedures, wad only me purported results vaned....To put the matter more bluntly, the two opposing groups had each con- strued the "box-score" vis a vis empirical evidence as tone good study supporting my view, and one lousy study supporting the opposite view'-- a state of affairs that seem- ingly justified the maintenance and even the strengthening of their paracular viewpoint" (Ross, 1986, p. 14). This result leads to a sense of pessimism for those of us who Mink that "truth" comes from the objective scientific collection of data, and from a solid replicable base of research. Giving the same mixed evidence to two opposing groups may drive the partisans farther apart. How is intellectual and emotional rapprochement possible? One possible source of optimism comes from related work by Ross and his colleagues (Ross, Lepper & Hubbard, 1975) in which the experimenters gave subjects false information about their abil- ity on some task. After subjects built up a theory to explain this ability, the experimenters discredited the original information, but the subjects retained a weaker form of the theory they had built up. The only form of debriefing that effectively abolished the (inappropriate) theory involved telling the sub- jects about the perseverance phenomenon itself. This debriefing about the actual psychological process involved finally aDowed the subjects to remove the effect of the false information. Biased assimilation may be weakened in a similar way: when we understand that our most "objective" evaluations of evi- dence involves such bias, we may be more able to understand that our opponents truly are reasonable people.

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41 Another reaction to processed evidence is the perception of hostile media bias. Why should politicians from both ends of the spectrum believe that the media is particularly hostile to their side? At first glance, this widespread phenomenon seems to contradict assimilative biases-- often, we don't react to stories in the press by selectively choosing supportive evidence; instead we perceive that the news story is deliberately slanted in favor of evidence against our side. Ross and colleagues speculated that the same biasing construal processes are at work. A partisan has a rigid construction of the truth that lines up with his or her beliefs, and when "evenhanded" evaluations am presented, they seem to stress the questionable evidence for the opposition. Support for these speculations came from studies on the news coverage of both the 1980 and 1984 presidential election and the 1982 "Beirut Massacre" (Vallone, 1986; Vallone, Ross ~ Lepper, 1985). These issues were chosen because there were actively involved partisans on both sides avail- able. The opposing parties watched clips of television news coverage. Not only did they disagree about the validity of the facts presented, and about the likely beliefs of the producers of the program, but they acted as if they saw different news clips. "Viewem of the the same 30-minute videotapes reported that the other side had enjoyed a greater proportion of favorable facts and references, and a smaller proportion of negative ones, than their own side" (Ross, 1986, p. 18). However, objective viewers tended to rate the broadcasts as relatively unbiased. These "objective" viewers were defined by the experimenters as those without personal involvement or strong opinions about the issues. But the partisans themselves-- if they are involved in college football, the capital punishment debate, party politics or the Arab-Israeli conflict-- claim to be evaluating the evidence on its own merits. And in a sense they are: They evaluate the quality of the evidence as they have constructed it in their mind. It is the illusion of "direct perception" that is the fatal barrier to understanding why others disagree with us. To the extent that we "fill in" ambiguities

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42 in me infom~a~aon given we can find inte~pretatons mat make the evidence fit our model. Because scientific practice demands public definition of concepts, measures and phenomena, personal constn~c- dons are minimized and meanings debate can take place. But when we rely on casual observation, personal experience and entenain~ng narratives as sources of evidence, we have too much room to create our own persuasive consnual of the evidence. Problems in Evaluanng Evidence [V: The Elect of Formal Research FonTIal research structure and quantitative analysis may not be me only, or best, route to "understanding" problems. Often, an in~epth qualitative familianty with a subject area is necessary ~ truly grasp the nature of a problem. But in all public policy programs, a private understanding must be followed by a public demonstration of the efficacy of the program. Only quantitative analysis leads to such a demonstration, and only quantitative evidence will force partisans to take the other side seriously. The effect of the acceptance of this argument can be seen in different ways in two domains: parapsycholog~cal research, and medicine. The effect of the rejec~acn of this argument can be seen In the development of the human potential movement. Modem parapsychology is almost entirely an experimental science, as any CUmOIy look Hugh its influential journals vAI1 demonstrate. Articles published in He Journal of Parapsychology or the Journal of the Sociery for Psychical Research explicitly discuss the statistical assumptions and con- trolled research design used in their studies. Most active parapsychological researchers believe that the path to scientific acceptance lies Hugh me adoption of rigorous experimental method. Robert Jahn, formerly dean of engineering and applied sciences at Princeton University and an active experimenter in this field, argues that "further careful study of this formidable field seems justified, but only within Be context of very well conceived and technically impeccable experiments of

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43 large data-base capability, with disciplined attention to the pertinent aesthetic factors, and with more constructive involvement of the critical community" (Jahn, 1982, quoted in Hyman, 1985, p. 4). This attitude has not caused the traditional scientific institutions to embrace parapsychology, so what have parapsychologists gained from it? Parapsycholog~sts have now amassed a large literature of experiments, and this compendium of studies and results can now be assessed using the language of science. Discussions of the status of parapsychological theories can be argued on the evidence: quantified, explicit evidence. As it stands, the evidence for psychic phenomena is not convincing to most traditional scientists (Hymen, 1981). But critical discussions of the evidence can take place on the basis of specifiable problems, and not only on the basis of beliefs and attitudes (e.g. the exchange between Hyman and HonoIton on the qual- ity of the design and analysis of the psi ganzfeld experiments, starting with Hym an, 1977; and Honor- mn, 1979). In direct contrast to this progression is the attitude of the human potential movement towards evaluation and measurement. Kurt Back (1972) titled his personal history of the human potential movement "Beyond Words" but it could have been just as accurately called "Beyond Measurement". He begins his book and his history with an examination of the roots of the movement in the post-war enthusiasm for applied psychology. Academic psychologists and sociologists were anxious to measure the increase in efficiency that would result from group educational activities. They examined group productivity, the solidarity and cohesion of the groups themselves, as wed as the weD-being of the group members. Few measurable changes were found, and this led the research-oriented scientists to either lose interest in these group phenomena or to lose interest in quantitative measurement. Many of those involved in the group experiments-- even some of the scientist who began with clearly experimental

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outlooks-- were caught up in the phenomenology, the experience of the group processes. 44 Back describes many influendal workers in this movement who started out with keen beliefs that controBed experiments wad groups processes would reveal significant observable effects. When these were not forthcoming, Me believers made two claims: We effects of group processes were too subtle, diffuse and holistic to be measure by reductionist science, and the only evidence that really mattered was subjective experience-- the individual case was We only level of interest, and this level could never be cape by extemal "objective" measurements. "Believing the language of the movement, one might look for msearch, proof, and the acceptability, of disproof. In fact, me followers of me movement are quote immune to rational argument or persuasion. The experience they are seeking exists, and me believ- ers are happy in their closed system which shows Hem mat Hey alone have mue Lights and emotional beliefs....Seen in this light, He history of sensitivity mining is a struggle to get beyond science" (Back, p. 204). The dangem in trying to get beyond science In an important policy area am best described by an example from surgical medicine. This example is often used in introductory statistics' classes because it demonstrates that good research really makers In the world. It shows how opt bask on personal experience or even unconsoled research can cause the adoption or condnuanon of dangerous policies. One treannent for severe bleeding caused by cinhosis of me liver is to send the blood Trough a portacaval she. This operation is time-consuming and risky. Many studies (at least 50y, of varying sophistication' have been undertaken to determine if the benefits outweigh the risks. These studies are reviewed in Grace, Muench, and Chahners, 1966; He stadsucal meaning is discussed in Freedman' Pisan~ & Pukes, 1978~. The message of the studies is clear: the poorer studies exaggerate He benefits of the surgery. Seventy-five percent of the studies without control groups (24 out of 32) were very enthusiastic about

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45 tile benefits of the shunt. In the studies which had control groups which were not randomly assigned, 67% (IO out of IS) were very en~usiasuc about Me benefits. But none of the studies widi random assignment to contm} and experimental groups had results that led to a high degree of enthusiasm. He of these studies showed Be shunt to have no value whatsoever. on the experiments without controls, me physicians wem accidentally biasing the outcome by including only the most healthy patients in the study. In the e~cpenments with non~domued controls, me physicians were accidentally biasing the outcome by assigning Be poorest padents to the control group that did not receive the shunt. Ordy when the confound of patient heath was removed by mn- domizanon was it clear that the risky operation was of lime or no vague. Good research does matter. Even physicians, highly selected for intelligence and highly trained in intuitive assessment, were misled by their daily expenence. Because He Amoral studies were publicly available, and because the quality of the studies could be evaluated on the basis of their exper- unental method, the overall conclusions were decisive. Until the human potential movement agrees on the importance of quantitative evaluation, it win remain spUt into factions based on ideologies main- tained by personal experience. Focal research methods are not He orgy or necessarily best way to team about the true state of nature. But good research is He ordy way to ensure Hat real phenomena win drive out illusions. The story of the "discovery" of N-rays in France in 1903 reveals how even physics, the hardest of the hard sciences, could be led astray by subjective evaluation (Broad ~ Wade, 1982, p. Ilk. This "new" form of X-rays made sparks brighten when viewed by the naked eye. The best physical scientists in France accepted this breakOuough because they wanted to believe in iL It took considerable logical and experiment effort to convince the scientific establishment that He actual phenomenon was self- decepi~on. Good research can disconfirm theones, subjective judgment rawly does.

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46 In his clique of the use of poor research practices, Pitfalls of Hwnan Research, Barber (1976) points out that many Saws of natural inference can creep into scientific research. "The validity and generalizability of experiments can be significantly improved by malting more explicit the pitfalls Mat are integral to their planning...and by keeping the pitfalls in full view of researchers who conduct experimental studies" (pp. 90-91). While scientists and scientific methods are not immune to the flaws of subjective judgment, good research is designed to minimize the impact of these problems. We proper use of science in public policy involves replacing a "person-onent~" approach win a "me~od-onented" approach (Hammond, 1978~. When cndcs or supporters focus on the person who is setting policy cntena, the debate involves the bias and mobvanons of me people involved. But attempts to precisely define the variables of interest and to gather data that relate to these variables focus the adversanal debate on He quality of He nietho~s used. This "is sc~entificaBy defensible not because it is flawless (it isn't), but because it is readily subject to scientific cnucism" (Hammond, 1978, p. 135~. Intuitive Judgment and the evaluation of evidence: A summary Personal experience seems a compeding source of evidence because it involves He most basic processing of information: perception, attention, and memory storage and retrieval. Yet while we have great confidence in the accuracy of our subjective impressions, we do not have conscious access to the actual processes unsolved. Psychological expenment~ion has revealed that we have too much confidence in our own accuracy and objectivity. Humans are designed for quick thinking rather than accurate thinking. Quick, confident assessment of evidence is adaptive when hesitation, uncertainty and self-doubt have high costs. But natural shortcut methods are subject to systematic errors and our in~s- peci~ve feelings of accuracy are misleading.

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47 These ergo of intuitive judgment lead people to search OUt confirming evidence, to interpret mixed evidence in ways that confirm their expectations, and to see meaning in chance phenomena. This same biased processing of information makes it very difficult to change our beliefs and tO under- stand the point of view of those with opposing beliefs. These errors and biases are now well- documented by psychologists and decision theorists, and the improvement of human judgment is of central concern in current research. Me long-tenn response to this knowledge requites broad educa- tional programs in basic statistical inference, and formal decision-m~king, such as those proposed and examined by various authors in Kahneman et al (1982). Already, business schools include "de- biasing" procedures in their programs of formal decision-making. But with the complex technological nature of our society, most researchers believe that some instruction on how ~ be a better consumer of infonnadon should start In public schools. The immediate response should be a renewed commitment to formal structures In deciding important policy, and a new realization that personal experience cannot be decisive in forming such policy. As Gilbert, Light and Mosteller (1978) post Out ~ their review of me efficacy of social ~nno- vations, only true experiment teals can yield knowledge that is reliable and cumulate. While for- mal research is slow and expensive, and scientific knowledge increases by Any increments, Me final result is impressively useful. Perhaps most important, explicit public evidence is our best hope for moving toward a consensus on appropriate public policy.

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