La parentalidad y la integración en la comunidad

Randomization has been transformed from a method that was intended to assist scientific investigation to a dogma by which research is reflexively judged. We would argue for the opposite stance—randomization should always be explicitly justified. An investigator must explain why randomization was undertaken, the extent to which it was successfully implemented, and whether this strategy compensated for the accompanying loss of generalizability.

Along a similar line, there are probably no “main effects” in the real world, in any case, and certainly no main effects in clinical research. The

characteristics of any therapeutic phenomenon are jointly, and interactively, determined by the particular patients, the particular therapists, the particular interventions actually involved, and the particular organizational,

sociocultural, geographic, and historical contexts in which treatment occurs.

Each study of a treatment reflects a limited sampling of patients, therapists, therapies, and contexts. If the comparisons made between different

therapies, different types of patients, different types of therapists, or different contexts are to be internally valid and are to be an accurate representation of differences that would result in the populations sampled (externally valid), then one must find ways to cope with the deleterious effects of data attrition from any of these sources.

We have reviewed strategies for “correcting” attrition, and we have suggested that, except for the most conservative strategy (interval estimates based on substituting best and worst values), they all rely on the untenable and untestable assumption of random attrition. In fact, as we have shown, there are no certain remedies for data loss. Those we have reviewed are limited by the assumptions they require concerning randomness of data loss-assumptions that beg the very question one would want to answer. It appears that we must accept the fact of attrition and realize that we cannot know, much less repair, its effects after it has occurred. We cannot depend on estimates of the counter-to-fact conditional-what would have happened if patients who rejected treatment had accepted it. It is never very

satisfactory to speculate about events that could never happen or to come to the conclusion that a treatment would have been effective if only all patients had accepted it. That is a very big if.

With or without attrition, one has information about only the variable levels for which observations actually exist. There is no reason to expect these to conform sufficiently to any experimental design to give unbiased estimates of main effects or of interactions among variables. It would be

unreasonable to claim, however, that the data collected are therefore worthless. Investigators must accept the inevitable incompleteness of actual observations at the relatively few points they occupy in the independent-variable space defined by the various combinations of patient, therapist, therapy, and setting characteristics. Once this is accepted, a perspective on clinical research opens up that reframes the problem of attrition as a problem of bias. This perspective also, serendipitously, integrates traditional exploratory, single-case studies with the strategy of controlled treatment-contrast, multiple-case research. The basic unit of study in this perspective is the individual case, described with as much dependent- and independent-variable information as is required in the present state of development of substance-abuse research.

In substance-abuse research, what one is really seeking are optimal points in the independent-variable space in terms of dependent-variable outcomes.

Optimum-seeking (Adby and Dempster 1974) involves seeking the points in the independent-variable space associated with the best outcomes, and it is surely the most sensible approach to substance-abuse research designed to provide clinically relevant findings. It is the knowledge of which points in the independent-variable space are associated with the best average

outcomes that is ultimately of clinical importance. Some sample

methodology and a more technical explication is provided by Howard and coworkers (1986).

CONCLUSION

It is time for us to give up the confirmatory approach to comparative treatment research. In clinical research, we are rarely in the position to test formal, theoretical hypotheses. Clinical research has to be judged by its informativeness, and we have argued that so-called “true” experiments tend to yield trivial information. In any case, it seems self-defeating to espouse a methodology that we must always fail to implement properly and to be forced to move apologetically to secondary analyses to make sense of our results. Instead, we recommend the adoption of exploratory methodology and a greater emphasis on the generalizability and the constructive replication of findings.

Where attrition denies one information at certain points, one must remain ignorant until further cases can be gathered. Where systematically comparable single-case studies yield information on certain specific independent-variable points, something really is learned that, however partial, remains the best one knows until further information is obtained at those points. At certain stages, what is missing may be as important as what is known. The detection of significant gaps in coverage of the independent-variable space serves the useful function of attracting further research attention, especially where optima are suggested to exist. The more extensively the independent-variable space has been covered with cases, the more one can supplement replication at a point by interpolation to that point from surrounding points. Optiium-seeking depends on

interpolation and extrapolation from the pattern of observed outcomes across the various points, and precision of estimation at any given point depends on replication. The realistic progress of scientific knowledge requires both optima and precision, and while attrition detracts from both, it is fatal to neither.

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ACKNOWLEDGMENTS

This chapter is based, in large part, on a 1986 paper by Howard, Krause, and Orlinsky. This work was partially supported by research grant R01 MH42901 from the National Institute of Mental Health.

AUTHORS

Kenneth I. Howard, Ph.D.

Professor of Psychology Department of Psychology Northwestern University Evanston, IL 60208 W. Miles Cox, Ph.D.

North Chicago Veterans Administration Medical Center University of Health Sciences/The Chicago Medical School North Chicago, IL 60064

Stephen M. Saunders, Ph.D.

Department of Psychology Northwestern University Evanston, IL 60208

Conceptualizing and Selecting