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By Sally Singer Horwatt, Ph.D
The most immediate task facing the mental health professional is to identify preoperative psychiatric, behavioral, cognitive and environmental factors that are shown to be related to treatment failure, serious postoperative complications or death. To the problems discussed in previous articles, add the fact that traditional self-report measures have a number of limitations: First, the tendency for impression management can confound self-report when the evaluator is seen as a gate-keeper to a desired medical treatment. Second, traditional self-report measures typically require participants to report on behaviors, beliefs or feelings or events that occurred weeks or years prior to their responding. Third, memory bias research shows that recall of attitudes or emotions is consistently influenced by current attitudes or emotions such that the most salient and most recent events will disproportionately influence ratings. Fourth, is the poor convergent validity between physiological processes identified in the laboratory environment and those in natural settings (Engel, et al, 2005).
In their chapter in Mitchell and Pearson’s Assessment of Eating Disorders, (2005) Engel, et al, presents a description of Ecological Momentary Assessment (EMA). EMA reduces retrospective recall bias while allowing for assessment in a natural setting. In addition, EMA allows for the delineation of temporal ordering of variables of interest, greatly enhancing empirical assessments of cause and effect. It can be used to test models that integrate state and trait variables. An example would be investigating whether certain personality traits, (eg, emotional liability) moderate the relationship between stressful events and momentary mood. They note that the vast majority of EMA articles in the current literature on eating disorders are longitudinal studies investigating variables that are thought to cause or relate to eating disorder behavior in a particular temporal order. A PsychINFO search using “ecological momentary”, “experience sampling” and “daily diary” shows 224 articles between 2000-2004 using EMA-related terms. Given the prevalence of mobile phones with texting capability it seems likely that we will use this capability more and more.
Minimally, if the patient’s behavior is evaluated over a period of weeks in a random manner, even at night, he will be monitoring his own behavior at the same time. Thus, EMA has the possibility of benefitting the patient as well.
Additionally, three models of data collection are appropriate for unequal group sizes, missing data on a repeated measure, and the measurement of subjects on different time intervals. Limitations of EMA are reactivity, fleeting affective states, and complex statistical analysis. The authors refer to a number of excellent software programs that provide the resources for analyzing multilevel models (HLM-5, SAS PROC MIXED).
The NIH Consensus Conference (1991) identified the lack of standards for comparison of results as one of the key problems in evaluating reports in the surgical treatment of severe obesity. The analysis of outcomes after bariatric surgery should include weight loss, improvement in obesity-related comorbidities, and quality of life (QoL) assessment (Oria, et al 1998). The resulting system defines five outcome groups (failure, fair, good, very good, and excellent), based on a scoring table that adds or subtracts points while evaluating three main areas: percentage of excess weight loss, changes in medical conditions, and QoL. To assess changes in QoL after treatment, they created a patient questionnaire that addresses self-esteem and four daily activities. Complications and preoperative surgery deduct points, thus avoiding the controversy of considering reoperations as failures. The resulting Bariatric Analysis and Reporting Outcome System (BAROS) analyzes outcomes in a simple, objective, unbiased, and evidence-based fashion. The authors recommend this measure be considered by international organizations for the adoption of standards for the outcome assessment of bariatric treatments, and for the comparison of results among surgical series.
The Moorehead-Ardelt QoL questionnaire self esteem and activity levels are presented in this article and could conceivably be used as a presurgical QoL measure. It is simple, criterion-related measure of variables most relevant to the patient, and takes a few minutes and so would not be costly to the patient or take much time. While comparing the post-surgical weight loss and resolution of comorbidities with presurgical values would be a completed by the medical team, the QoL measure is relevant to the mental health professional and, most important, to the patient (DiGregorio, 2001).
Finally, the reader is encouraged to read a paper by Wadden, T.; Sarwer, D. (2006). It is entitled Behavioral Assessment of Candidates for Bariatric Surgery: A Patient-Oriented Approach, and it includes the use of the Weight and Lifestyle Inventory. Responses on this instrument guide the subsequent interview with the patient. It describes the goals and methods of a behavioral assessment at the University of Pennsylvania. Finally the paper discusses the challenge of predicting the therapeutic response on the basis of preoperative variables.
The fantasy for the psychological evaluation of the future is that assessment is useful to the patient; does not project a paternalistic attitude or imply “psychopathology” has led him to weigh so much; does not cost so much in time and money; and can be conducted unobtrusively while the patient lives his life outside the office.
Until that time, the following sites present some assessment tools typically used in bariatric evaluations:
http.//www.assessmentpsychology.com/psychtests-bariatric-asbs.htm
http//www.assessmentpsychology.com/psychtests-bariatric-va.htm
References
DiGregorio, J.; Palkoner, R. (2001). Quality of Life after Obesity Surgery, an Evidence-Based Medicine Literature Review: How to Improve Systematic Searches for Enhanced Decision-Making and Clinical Outcomes. Obesity Surgery, 11, 318-326.
Engel, S.; Wonderlich, S; Crosby, R. (2005). Ecological Momentary Assessment in Mitchell, J; Peterson, C., Eds. Assessment of Eating Disorders. New York, New York: The Guilford Press.
NIH Consensus Statement Online. (1991) Gastrointestinal Surgery for Severe Obesity. March 25-27; 9(1):1-20.
Oria, H. and Moorehead, M. (1998). Bariatric Analysis and Reporting Outcome System (BAROS). Obesity Surgery, 8, 487-499.
Wadden, T.; Sarwer, D. (2006). Behavioral Assessment of Candidates for Bariatric Surgery: A Patient-Oriented Approach. Obesity 14, 53s-62s.