TECHNIQUES OF OUTCOME EVALUATION IN ALCOHOL, DRUG ABUSE, AND MENTAL HEALTH PROGRAMS (FROM PROGRAM EVALUATION ALCOHOL, DRUG ABUSE, AND MENTAL HEALTH SERVICES, 1975, BY JACK ZUSMAN ET AL - SEE NCJ-50594)

• NCJ Number: 50597
• Author(s): S B SELLS
• Date Published: 1975
• Length: 17 pages
• Corporate Author: D C Heath and Co
• Publication Format: Document
• Publication Type: Report (Study/Research)
• Language: English
• Country: United States of America

Annotation

THIS ARTICLE DISCUSSES FUNCTIONS, CHARACTERISTIC ROLES, AND PLANNING FOR OUTCOME EVALUATION. IT THEN REVIEWS EXPERIENTIAL REALITY CONSTRAINTS THAT PROVIDE A FRAME OF REFERENCE AND STRATEGY FOR OUTCOME EVALUATION RESEARCH.

Abstract

EVALUATION RELATES SEMANTICALLY BUT DIFFERS FUNCTIONALLY FROM TWO COMMON CONCEPTS OFTEN CONFUSED WITH IT. THESE ARE THE AUDIT FUNCTION, NORMALLY EMPHASIZING ACCOUNTABILITY FOR FUNDS AND RESOURCES, AND THE PROGRAM ASSISTANCE OR DEVELOPMENT FUNCTION, INVOLVING THE REVIEW OF ONGOING OPERATIONS AND PROGRAM PRACTICES AND SOMETIMES INCLUDING INITIAL PLANNING. PROGRAM GOALS FOR EVALUATION INCLUDE PROGRAMMED RESULTS OR EFFECTS OF PARTICULAR ACTIVITIES WITHIN SPECIFIED TIME PERIODS AND COSTS IN TERMS OF PERSONNEL AND RESOURCE UTILIZATION, RISKS RELATED TO RELATIONSHIPS WITH SIGNIFICANT CONSTITUENCIES, AND MONIES EXPENDED IN CONNECTION WITH PARTICULAR ACCOMPLISHMENTS. OUTCOME EVALUATION IS CONCERNED ONLY WITH PROGRAM RESULTS. VARIABLES TO CONSIDER IN CREATING A FRAME OF REFERENCE FOR EVALUATION RESEARCH DESIGN ARE SOURCES OF VARIANCE, THE SPECIFICATION OF PROGRAM PARADIGMS, PROSPECTIVE VERSUS RETROSPECTIVE DESIGNS, CRITERION PROBLEMS, TIME PERSPECTIVES, PROBLEMS IN FIELD RESEARCH, ETHICS, THE USE OF COMPUTERS, AND REACTIVE VERSUS NONREACTIVE MEASURES. THE DESIGN OF EVALUATION RESEARCH AND EVALUATION PROCEDURES PERTAIN TO DATA ORGANIZATION, DATA MANAGEMENT, AND ANALYTIC MODELS. IMPORTANT DATA MANAGEMENT PROBLEMS INCLUDE CLIENT (PATIENT) IDENTIFICATION, CODING ALL NONPRECODED ITEMS OF INFORMATION, COMPUTER INPUT, EDITING COMPUTER INPUT, HANDLING MISSING DATA, DEVELOPING ALGORITHMS FOR DATA CLASSIFICATION AND SCALING, SEQUENTIAL PREPARATION OF THE FINAL DATA MATRIX, AND MAINTAINING BACKUP TAPES AND FILES. THE MOST OBVIOUS ADVANTAGE OF ANALYTIC MODELS IS THAT THEY DEAL WITH COMPLEX FIELD SITUATIONS AS THEY OCCUR AND ARE THEREFORE GENERALIZABLE TO SUCH SITUATIONS. IN ADDITION, THESE MODELS ARE ABLE TO INCORPORATE EXTRANEOUS FACTORS THAT ARE NOT PART OF TREATMENT PER SE BUT FREQUENTLY INTERACT WITH TREATMENT IN REAL LIFE SITUATIONS. NOTES ARE INCLUDED. (DEP)