The power law as behavioral illusion: reappraising the reappraisals.

Marken and Shaffer (Exp Brain Res 235:1835-1842, 2017) have argued that the power law of movement, which is generally thought to reflect the mechanisms that produce movement, is actually an example of what Powers (Psychol Rev 85:417-435, 1978) dubbed a behavioral illusion, where an observed relationship between variables is seen as revealing something about the mechanisms that produce a behavior when, in fact, it does not. Zago et al. (Exp Brain Res. https://doi.org/10.1007/s0022-017-5108-z , 2017) and Taylor (Exp Brain Res, https://doi.org/10.1007/s00221-018-5192-8 , 2018) have "reappraised" this argument, claiming that it is based on logical, mathematical, statistical and theoretical errors. In the present paper we answer these claims and show that the power law of movement is, indeed, an example of a behavioral illusion. However, we also explain how this apparently negative finding can point the study of movement in a new and more productive direction, with research aimed at understanding movement in terms of its purposes rather than its causes.

Systematic bias in predictions of new drugs' budget impact: analysis of a sample of recent US drug launches.

OBJECTIVE: Expectations about the budget impact of new drug launches may affect payer behavior and ultimately consumer costs. Therefore, we evaluated the accuracy of pre-launch US budget impact estimates for a sample of new drugs. METHODS: We searched for publicly available budget impact estimates made pre-launch for drugs approved in the US from 1 September 2010 to 1 September 2015 and compared them to actual sales. Accuracy was calculated as the ratio of pre-launch estimate to actual sales. Quantitative analyses, including multivariate regressions, were used to identify factors associated with accuracy. RESULTS: We identified 25 budget impact estimates: 23 for one of 14 individual drugs and 2 for the category of PCSK9 inhibitors. The ratios of predicted to actual budget impact ranged from 0.2 (estimate was 20% of sales) for secukinumab to 37.5 (estimate was 37.5 × sales) for PCSK9 inhibitors. Mean ratio was 5.5. In multivariate analyses, larger eligible population, more recent estimate year (e.g. 2015 vs. 2012), and being first in class, were associated with statistically significant, greater overestimation of budget impact. CONCLUSIONS: For every $5.5 of predicted cost, there was $1 of actual cost to the healthcare system. This study, although based on a small, non-random sample, suggests possible cognitive bias on the part of the estimators. Overestimating budget impact may lead to early access restrictions, higher copays, and other changes that ultimately impact patients. Analysts and non-profits should be attuned to likely sources of error in order to improve their predictions.

The power law of movement: an example of a behavioral illusion.

The curved movements produced by living organisms follow a power law where the velocity of movement is a power function of the degree of curvature through which the movement is made. The exponent of the power function is close to either 1/3 or 2/3 depending on how velocity and curvature are measured. This power law is thought to reflect biological and/or kinematic constraints on how organisms produce movements. The present paper shows that the power law is actually a statistical artifact that results from mistaking a correlational for a causal relationship between variables. The power law implies that curvature influences the velocity of movement. In fact, the power law is a mathematical consequence of the way that these variables are calculated. The appearance that curvature affects the velocity of movement is shown to be an example of a "behavioral illusion" that results from ignoring the purpose of behavior.

Control blindness: Why people can make incorrect inferences about the intentions of others.

There is limited evidence regarding the accuracy of inferences about intention. The research described in this article shows how perceptual control theory (PCT) can provide a "ground truth" for these judgments. In a series of 3 studies, participants were asked to identify a person's intention in a tracking task where the person's true intention was to control the position of a knot connecting a pair of rubber bands. Most participants failed to correctly infer the person's intention, instead inferring complex but nonexistent goals (such as "tracing out two kangaroos boxing") based on the actions taken to keep the knot under control. Therefore, most of our participants experienced what we call "control blindness." The effect persisted with many participants even when their awareness was successfully directed at the knot whose position was under control. Beyond exploring the control blindness phenomenon in the context of our studies, we discuss its implications for psychological research and public policy.

Catching objects thrown to oneself: Testing control strategies for object interception in a novel domain.

A considerable amount of research has been performed to determine the strategies people use to intercept moving objects. Much of this research has been done using target objects such as baseballs and Frisbees that are launched to people from distances ranging from 10 m to 50 m. This research has qualified the range of domains in which each strategy is effective, but there is still controversy regarding which strategy has the most general application. The present research sought to further reduce the range of possible domains in which these strategies work by testing object interception in a situation that had never been tested before, where people launch the target objects to themselves. A strategy based on controlling optical velocity--acting to keep the optical velocity of the object at zero--provided the best match to catcher ground movements and optical trajectories. These results suggest that control of optical velocity is currently the best explanation of effective interception of both other- and self-launched objects.

Understanding the Change Process Involved in Solving Psychological Problems: A Model-based Approach to Understanding How Psychotherapy Works.

UNLABELLED: A review of the literature on psychotherapy suggests that improvements in effectiveness, efficiency and accessibility have been hampered by a lack of understanding of how psychotherapy works. Central to gaining such understanding is an accurate description of the change process that occurs when someone solves a psychological problem. We describe the Perceptual Control Theory (PCT) model of human functioning, which can be used to understand the nature of psychological problems and how they are solved. PCT suggests that problems can be broadly grouped into two categories: those that can be solved using existing skills and those that require the generation of new skills. In general, psychological problems belong in the second category. PCT describes a fundamental form of learning in which existing structures and systems are reorganized to create new skills, perspective and insights. Psychotherapy based on PCT is aimed at directing reorganization to the source of the problem. KEY PRACTITIONER MESSAGE: Understanding the phenomenon of control is central to understanding how psychotherapy works. Conflict could be considered a general formulation for psychological distress. Therapy will be efficient when the reorganization process is focused at the right level of the client's control hierarchy. Therapy will be effective only when the client's reorganization system-not the therapist-has managed to come up with a solution to the client's problem. What the client says about the nature and reason for their problem is less important than the point of view from which these problems are being discussed.

Testing for controlled variables: a model-based approach to determining the perceptual basis of behavior.

Perceptual control theory (PCT) views behavior as being organized around the control of perceptual variables. Thus, from a PCT perspective, understanding behavior is largely a matter of determining the perceptions that organisms control-the perceptions that are the basis of the observed behavior. This task is complicated by the fact that very often the perceptions that seem to be the obvious basis of some behavior are not. This problem is illustrated using a simple pursuit-tracking task in which the goal was to keep a cursor vertically aligned with a target set at various horizontal distances from the cursor. The "obvious" perceptual basis of the behavior in this task is the vertical distance between cursor and target. But a control model suggests that a better description of the perceptual basis of the behavior is the angle between cursor and target. The experiment shows how a control model can be used to do the test for the controlled variable, a control-theory-based approach to distinguishing the actual from the apparent perceptual basis of any behavior.

Making inferences about intention: perceptual control theory as a "theory of mind" for psychologists.

Theory of Mind (ToM) assumes that humans and possibly other primates understand behavior in terms of inferences about intentions. While there is evidence that primates make such inferences, little attention has been paid to the question of their validity. In order to answer this question it is necessary to know the true intentions underlying behavior. The present paper shows that Perceptual Control Theory can provide a scientific basis for making such determinations using methods derived from control engineering. These methods--called the "Test for the Controlled Variable" (TCV)--are based on the assumption that intentional behavior is equivalent to the process of control. The TCV provides an objective approach to inferring the intentions underlying behavior in terms of the perceptual variables under control and the goal states of those variables. Thus, Perceptual Control Theory represents an empirical ToM for psychologists--one that can be used to understand behavior in terms of inferences about intention that are based on the results of active experimentation rather than passive observation.

Chasin' choppers: using unpredictable trajectories to test theories of object interception.

Three theories of the informational basis for object interception strategies were tested in an experiment where participants pursued toy helicopters. Helicopters were used as targets because their unpredictable trajectories have different effects on the optical variables that have been proposed as the basis of object interception, providing a basis for determining the variables that best explain this behavior. Participants pursued helicopters while the positions of both pursuer and helicopter were continuously monitored. Using models to predict the observed optical trajectories of the helicopter and ground positions of the pursuer, optical acceleration was eliminated as a basis of object interception. A model based on control of optical velocity (COV) provided the best match to pursuer ground movements, while one based on segments of linear optical trajectories (SLOT) provided the best match to the observed optical trajectories. We describe suggestions for further research to distinguish the COV and SLOT models.

Taking purpose into account in experimental psychology: testing for controlled variables.

Experimental research in psychology is based on a causal model--the General Linear Model (GLM)--that assumes behavior has causes but not purposes. Powers (1978) used a control theory analysis to show that the results of psychological experiments based on such a model can be misleading if the organisms being studied are purposeful (control) systems. In the same paper, Powers presented evidence that organisms are such systems. Nevertheless, psychologists continue to use methods that ignore purpose because the behavior in most experiments appears to be non-purposeful (a caused result of variations in the independent variable). The experiments described in this paper show how purposeful behavior can appear to be caused by the independent variable when an organism's purposes are ignored. The results show how taking purpose into account using the control theory-based "Test for the Controlled Variable" can provide a productive new methodological direction for experimental research in psychology.

Motor control as the control of perception.

This paper describes a test of Perceptual Control Theory (PCT), which views motor control as part of a process of controlling perceptual inputs rather than motor outputs. Sixteen undergraduate students (M age = 19.9 yr.) were asked to control one of three different perceptual aspects of an animated display--a shape, a motion or a sequence--using the same motor output, a key press. Animation rate was varied while quality of control was measured in terms of the proportion of time that the perception was maintained in the goal state. The results showed that increased animation rate made it hardest to control the more complex perceptions (motion and sequence) even though the same output was used to control all perceptions. This result is consistent with PCT, which predicts that the temporal constraints on control are ultimately a function of the type of perception controlled rather than the type of output used to control it.

When causality does not imply correlation: more spadework at the foundations of scientific psychology.

Experimental research in psychology is based on an open-loop causal model which assumes that sensory input causes behavioral output. This model was tested in a tracking experiment where participants were asked to control a cursor, keeping it aligned with a target by moving a mouse to compensate for disturbances of differing difficulty. Since cursor movements (inputs) are the only observable cause of mouse movements (outputs), the open-loop model predicts that there will be a correlation between input and output that increases as tracking performance improves. In fact, the correlation between sensory input and motor output is very low regardless of the quality of tracking performance; causality, in terms of the effect of input on output, does not seem to imply correlation in this situation. This surprising result can be explained by a closed-loop model which assumes that input is causing output while output is causing input.

Optical trajectories and the informational basis of fly ball catching.

D. M. Shaffer and M. K. McBeath (see record 2002-02027-006) plotted the optical trajectories of uncatchable fly balls and concluded that linear optical trajectory is the informational basis of the actions taken to catch these balls. P. McLeod, N. Reed, and Z. Dienes (see record 2002-11140-016) replotted these trajectories in terms of changes in the tangent of optical angle over time and concluded that optical acceleration is the informational basis of fielder actions. Neither of these conclusions is warranted, however, because the optical trajectories of even uncatchable balls confound the information that is the basis of fielder action with the effects of those same actions on these trajectories. To determine the informational basis of fielder action, it is necessary to do the control-theory-based Test for the Controlled Variable, in which the informational basis of catching is found by looking for features of optical trajectories that are protected from experimentally or naturally applied disturbances.

Functional characteristics of commercial ambulatory electronic prescribing systems: a field study.

OBJECTIVE: To compare the functional capabilities being offered by commercial ambulatory electronic prescribing systems with a set of expert panel recommendations. DESIGN: A descriptive field study of ten commercially available ambulatory electronic prescribing systems, each of which had established a significant market presence. Data were collected from vendors by telephone interview and at sites where the systems were functioning through direct observation of the systems and through personal interviews with prescribers and technical staff. MEASUREMENTS: The capabilities of electronic prescribing systems were compared with 60 expert panel recommendations for capabilities that would improve patient safety, health outcomes, or patients' costs. Each recommended capability was judged as having been implemented fully, partially, or not at all by each system to which the recommendation applied. Vendors' claims about capabilities were compared with the capabilities found in the site visits. RESULTS: On average, the systems fully implemented 50% of the recommended capabilities, with individual systems ranging from 26% to 64% implementation. Only 15% of the recommended capabilities were not implemented by any system. Prescribing systems that were part of electronic health records (EHRs) tended to implement more recommendations. Vendors' claims about their systems' capabilities had a 96% sensitivity and a 72% specificity when site visit findings were considered the gold standard. CONCLUSIONS: The commercial electronic prescribing marketplace may not be selecting for capabilities that would most benefit patients. Electronic prescribing standards should include minimal functional capabilities, and certification of adherence to standards may need to take place where systems are installed and operating.

Recommendations for comparing electronic prescribing systems: results of an expert consensus process.

Commercially available electronic prescribing systems may differ in their effects on patients' health outcomes and on patients' ability to manage costs. An expert panel convened to recommend specific features that would enable electronic prescribing systems to advance these goals. The panel authored sixty recommendations and rated each using a modified Delphi process. Ratings identified fifty-two recommendations as clearly positive for patient safety and health outcomes and forty-three recommendations as achievable in the average clinician's office within three years. Overall, these recommendations offer a synthesis of evidence and expert opinion that can help guide the development of electronic prescribing policy.

A conceptual framework for evaluating outpatient electronic prescribing systems based on their functional capabilities.

OBJECTIVE: Electronic prescribing (e-prescribing) may substantially improve health care quality and efficiency, but the available systems are complex and their heterogeneity makes comparing and evaluating them a challenge. The authors aimed to develop a conceptual framework for anticipating the effects of alternative designs for outpatient e-prescribing systems. DESIGN: Based on a literature review and on telephone interviews with e-prescribing vendors, the authors identified distinct e-prescribing functional capabilities and developed a conceptual framework for evaluating e-prescribing systems' potential effects based on their capabilities. Analyses of two commercial e-prescribing systems are presented as examples of applying the conceptual framework. MEASUREMENTS: Major e-prescribing functional capabilities identified and the availability of evidence to support their specific effects. RESULTS: The proposed framework for evaluating e-prescribing systems is organized using a process model of medication management. Fourteen e-prescribing functional capabilities are identified within the model. Evidence is identified to support eight specific effects for six of the functional capabilities. The evidence also shows that a functional capability with generally positive effects can be implemented in a way that creates unintended hazards. Applying the framework involves identifying an e-prescribing system's functional capabilities within the process model and then assessing the effects that could be expected from each capability in the proposed clinical environment. CONCLUSION: The proposed conceptual framework supports the integration of available evidence in considering the full range of effects from e-prescribing design alternatives. More research is needed into the effects of specific e-prescribing functional alternatives. Until more is known, e-prescribing initiatives should include provisions to monitor for unintended hazards.

Error in skilled performance: a control model of prescribing.

A control model of skilled performance is proposed as a framework for understanding why prescribing errors occur at a particular rate. Model error rate depends on skill level, system design characteristics, the range of different types of prescriptions that are produced and the time available to complete each prescription. The parameters of the model can be adjusted so it produces error rates that are quantitatively equal to those found in studies of the incidence of different types of prescribing error. The model will also produce error rates that are qualitatively consistent with the results of studies that show increases in prescribing error rates as a result of increases in distractions and workload. The model is used to determine the likely effectiveness of different prescribing error prevention interventions.

Perceptual organization of behavior: a hierarchical control model of coordinated action.

The behavior of individual subjects is compared with a hierarchical control system model of behavioral organization. Subjects varied the position of two control handles simultaneously to keep the distance constant between two pairs of lines. Three variations on this basic experiment that illustrate some fundamental properties of coordinated action are shown: first, how independent actions, compensating for unpredictable and undetectable disturbances, can produce a single behavioral result; second, how the ability to produce a particular result is maintained when the connection between action and result is changed; and third, how two independent outputs can appear to be related as coordinative structures when one output disturbs a result being controlled by the other. The correlation between the behavior of subjects and model in all experiments is typically on the order of .99. A detailed examination of the operation of the model shows that actions are structured by perception, not by central commands or equations of constraint.