Relationship between adherence and weight loss in a behavioral weight reduction program

BEHAVIOR THERAPY 14, 682-688 (1983)

BRIEF REPORTS Relationship between Adherence and Weight Loss in a Behavioral Weight Reduction Program BEVERLY A . S A N D I F E R

Pine Belt Mental Health and Retardation Services, Hattiesburg, MS

WILLIAM L. BUCHANAN Pine Belt Mental Health and Retardation Services and University of Southern Mississippi The present study assessed the relationship between adherence to prescribed behaviors and weight loss. Subjects were overweight adults participating in a behavioral weight reduction program in a community mental health center. Adherence was measured by daily self-report records of performance of behaviors as well as unobtrusive ratings of observable behaviors by trained family members. Eleven of the 13 variables entered into a stepwise multiple regression were significant predictors of weight reduction, with the single best predictor being taking a 2-min pause during meals. All program behaviors were significantly correlated with the Weight Reduction Index. High levels of agreement between family member ratings and self-report data were observed. Taken together, these results indicate the presence of a strong relationship between adherence and weight loss.

The past few years have witnessed a proliferation of published research showing that behavioral treatments of obesity yield demonstrable treatment effects. However, without validation, one may not assume that subjects' weight losses resulted from adherence to program behaviors (Mahoney, 1975). In many of the studies previously reported in the literature, data on the relationship between adherence and weight loss in behavioral programs have either been absent or have suffered from methodological drawbacks (Johnson, Wildman, & O'Brien, 1980). Fortunately, data regarding adherence in such programs have become more common in pubSpecial thanks are extended to Julie Carney, Kathy Barnhill, Bob Raines, Candace McBride, and John Ross, who assisted in various aspects of this research. Appreciation is also expressed to William G. Johnson for his ongoing consultation. The second author is currently at Georgia State University. Requests for reprints should be sent to Beverly Sandifer, Pine Belt Mental Health and Retardation Services, PO Drawer 1030, Hattiesburg, MS 39401. 682 0005-7894/83/0682-06885!.00/0 Copyright 1983by Associationfor Advancementof BehaviorTherapy All rightsof reproductionin any form reserved.

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lished research. For example, Epstein and his colleagues assessed children's compliance by contracting between parents and the targeted child (Epstein, Wing, Koeske, Andrasik, & Ossip, 1981) and assessed compliance to exercise programs by collecting fitness data (Epstein, Wing, Koeske, Ossip, & Beck, 1982). However, among those studies which have attended to the question of adherence, one finds a lack of consensus regarding the impact of adherence upon weight loss. Some report significant correlations between weight loss and behavior change (e.g., Katell, Callahan, Fremouw, & Zitter, 1979; Mahoney, 1974; Ost & G6testam, 1976; Wollersheim, 1970), while others report nonsignificant correlations or significant relationships with only one or two variables (e.g., Bellack, Rozensky, & Schwartz, 1974; Brownell, Heckerman, Westlake, Hayes, & Monti, 1978; Jeffrey, Wing, & Stunkard, 1978; Stalonas, Johnson, & Christ, 1978). Further, the efforts of a few experimenters to establish reliability by using independent observers have been relatively unsuccessful (e.g., Brownell et al., 1978; Epstein & Martin, 1977). Because of the need for further clarification of the adherence question, the present study evaluated: (a) the extent to which daily records of selfreported adherence to program behaviors were correlated to the Weight Reduction Index (Feinstein, 1959), and (b) the extent to which family member ratings of six observable behaviors were in agreement with selfreport data. METHOD

Subjects Subjects were 19 females and 2 males who were recruited by a newspaper article and television program for participation in a behavioral weight reduction program at a community mental health center. These subjects averaged 38 years of age (range = 23-61), 63 pounds overweight (range = 16-119), and 57% overweight (range = 13-211), as defined by Metropolitan Life Actuarial data (1969).

Therapists Groups were led by a female psychologist with assistance of either a male with an M,S. in Counseling Psychology or a female with an M.S.W. These three nonobese individuals were all experienced behavior therapists and group leaders.

Procedure Following a preliminary screening interview, subjects participated in the Weight No Longer program, a 10-week weight reduction program designed to facilitate stepwise behavioral changes in the areas of balanced nutrition, increased exercise, appropriate eating habits, and a more active lifestyle (Johnson & Stalonas, 1981). A self-administered reward system for program adherence was included in the program. The program consisted of 10, 1½-hour group sessions. Prior to each session, each subject met with a group leader for a 10-min individual

684

SANDIFER AND BUCHANAN TABLE 1 CORRELATION MATRIX OF WEIGHT REDUCTION INDEX AND PROGRAM BEHAVIORS

Variable I. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

WRI Foodin Exercise UCE Foodarea Refrain Graph Distinct Chain Pause Liquid Count K Oneserve Aversive

1

2

3

4

5

6

7

8

9

10

11

12

13

.57 .64 .65 .45 .60 .59 .66 .68 .78 .63 .62 .67 .59

.93 .89 .74 .91 .99 .95 .94 .77 .98 .87 .89 .54

.90 .80 .87 .93 .89 .91 .79 .93 .82 .79 .62

.82 .79 .88 .89 .90 .80 .92 .85 .87 .59

.73 .70 .74 .75 .61 .78 .60 .67 .74

.9O .92 .88 .74 .92 .80 .84 .55

.95 .94 .77 .98 .89 .90 .53

.96 .80 .98 .84 .91 .57

.87 .95 .86 .90 .64

.79 .74 .73 .49

.85 .90 .58

.95 .58

.65

df =

19.

Note: r = .43, p < .05, two tailed,

14

r = .54, p < .01. r = .59, p < .005. r --- .67, p < .001.

progress review. Group meetings included didactic instructions, modeling, behavior rehearsal, feedback, reinforcement, and group discussion (Johnson & Stalonas, 1981). Assessment Self-report data. The Reward Computation Work Sheets reflected participants' self-reported daily adherence to a total of 13 behaviors. These behaviors included recording all food intake (foodin), daily exercise (exercise), limiting uncontrolled eating and snacking (UCE), eating only in a designated food area (foodarea), refraining from other activities during the meal (refrain), making the eating area distinctive (distinct), chaining (chain), taking a 2-min pause during meals (pause), limiting liquid intake during meals (liquid), limiting intake to one serving of each food (oneserve), recording daily exercise and snacking on visual charts (graph), inhibiting eating urges by using aversive imagery (aversive), and monitoring calorie intake (count K). Points were recorded when the client reported adherence to a given behavior, while no points were given for noncompliance. These points were then totaled to yield composite scores. Reward Computation Work Sheets were available for weeks 3-10 following collection of baseline data. Family member observations. Participants were asked to have a family member living in the household attend one of several scheduled orientation meetings. Family members of 12 subjects attended a meeting and

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subsequently made and recorded unobtrusive observations of clients' performance of assigned behaviors at mealtime. At the family meeting, observers were trained to rate six behaviors (liquid, chain, foodarea, oneserve, pause, and refrain) chosen for assessment because of their observability at mealtime. Through verbal descriptions of each behavior and through practice ratings of standardized live vignettes, observers were trained to a criterion level of 100% accuracy on three successive trials. Ratings were dichotomous, indicating only the presence or absence of a given behavior. At the beginning of each week, the observer selected one meal in the coming week in which to observe the subject's eating behavior. He or she reviewed the behavior list immediately prior to the meal, made observations as unobtrusively as possible, and recorded observations on the checklist immediately following the meal. The collaboration between observer and subject was assumed to be minimal because upon questioning in individual progress review sessions, subjects were unable to specify correctly at what meal observations were made. Periodic telephone contacts helped to further assure that ratings were being made according to experimental directions. All checklists were returned promptly on a weekly basis in self-addressed envelopes provided by researchers.

RESULTS Weight loss for group members averaged 9.3 pounds ( S D = 4.8; Range = 1-34 pounds). The Weight Reduction Index (WRI) was used for subsequent data analysis (Feinstein, 1959). WRI scores ranged from 5.0 to 105.5 (M = 24.1; S D = 22.4). Daily scores for each program behavior from the Reward Computation Work Sheet were totaled for each subject. Along with the WRI, these data were entered into a stepwise (forward) multiple regression. A Pearson product-moment correlation matrix was generated (Table 1). All program behaviors were significantly correlated with weight reduction ( d f = 19, p < .05). Pause (r = .78), chain (r = .68), and oneserve (r = .67) had the highest correlations and were significant at level p < .001. Results of the stepwise multiple regression are presented in Table 2. Eleven of the 13 behaviors entered into the regression were significant predictors of weight reduction. Pause was the best predictor (r = .78), accounting for 60.1% of the variance (p < .001). The overall multiple r for the 11 variables was .935, accounting for 87.5% of the variance in the WRI scores (F = 5.72, p < .01). Phi coefficients were calculated as a measure of the relationship between the self-report ratings and family member ratings for 12 of the 21 subjects. It should be noted that a potential underestimation of agreement between self-report and family member ratings was built into the assessment procedure. Family member ratings were made for only one meal, while subject ratings were based on adherence for all meals during the day. The observer might report compliance for a given meal while the subject might report noncompliance, referring to behavior at another meal

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TABLE 2 SUMMARY TABLE FOR STEPWISE (FORWARD) MULTIPLE REGRESSION OF PROGRAM BEHAVIORS WITH THE WEIGHT REDUCTION INDEX a

Step

Variable

Multiple-R

R-Square

F

I 2 3 4 5 6 7 8 9 10 I1

Pause Aversive Foodarea UCE Count K Refrain Chain Oneserve Exercise Foodin Liquid

.780 .817 .850 .863 .878 .888 .906 .912 .919 .935 .935

.609 .667 .723 .745 .771 .789 .822 .832 .844 .875 .875

29.59*** 18.02"** 14.76"** 11.66"** 10.08"** 8.70*** 8.56*** 7.42*** 6.61"* 6.98** 5.72*

Graph *p < ** p < *** p <

a

and Distinct did not enter the regression due to an insufficient tolerance level. .01. .005. .001.

on the same day. Though both might be accurate accounts of the subject's performance, such an instance could have been counted as interrater disagreement for the calculations of the phi coefficients. Despite this, each of the rated behaviors yielded significant correlations between selfreport and family member ratings. The overall phi coefficient for all selfreport ratings with all family member ratings was .33 (p < .001). The phi coefficient for each of the six observed behaviors were---liquid: .85 (p < .001); oneserve: .79 (p < .001); foodarea: .45 (p < .005); chain: .36 (p < .001); pause: .34 (p < .05); and refrain: .28 (p < .005). Family member ratings were also significantly correlated to the WRI for all six behaviors. Pearson product-moment correlations between WRI and family member ratings were--pause: r = .75 (p < .005); foodarea: r = .74 (p < .01); refrain: r = .74 (p < .01); liquid: r = .74 (p < .01); oneserve: r = .73 (p < .01); and chain: r = .60 (p < .05).

DISCUSSION Results of this study indicate the presence of a strong relationship between program adherence and weight loss. Daily self-report records of adherence to prescribed behaviors correlated significantly with the WRI, as did family member ratings of six behaviors observable at mealtime. Analysis of the self-report data yields findings which are the strongest evidence to date of a relationship between adherence and weight reduction. In contrast to several other studies (e.g., Bellack et al., 1974; Epstein & Martin, 1977; Jeffrey et al., 1978; Stalonas et al., 1978), subjects in this study reported their daily adherence to each behavior and all data

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for weeks 3-10 were included, perhaps allowing for a more sensitive detection of potent treatment variables. High levels of agreement were found between self-report and family member ratings, as were strong correlations between observer ratings and the WRI. Taken together, these data strongly support the positive relationship between program adherence and weight reduction. The divergent findings of this study and the Brownell et al. (1978) study remain puzzling, given the similarity of assessment procedures. Replications are warranted to identify variables contributing to these differences. While all behaviors in the present study were significantly correlated with the WRI, the 2-rain pause was the single best predictor of weight loss. This somewhat surprising finding may relate to subjects' complaints about the inconvenience of this behavior. It may be that those individuals who performed this personally unappealing behavior were most likely to adhere to other assigned behaviors. Several limitations of this study bear mention. First, these findings are based on an admittedly small sample (n = 21) with only 12 observers. Second, this study reliably assessed adherence only at mealtime in the presence of an observer. Third, follow-up data regarding continued adherence after formal treatment were not available. Despite these interpretive cautions, these findings are noteworthy. They strongly support the concept that behavioral adherence in weight reduction programs leads to weight loss, an idea which has inherent logical appeal but which until now has suffered from a relative lack of empirical validation.

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Katell, A., Callahan, E. J., Fremouw, W. J., & Zitter, R. E. The effects of behavioral treatment and fasting on eating behaviors and weight loss: A case study. Behavior Therapy, 1979, 10, 57%587. Mahoney, M.J. Self-reward and self-monitoring techniques for weight control. Behavior Therapy, 1974, 5, 48-57. Mahoney, M.J. The obese eating style: Bites, beliefs and behavior modification. Addictive Behaviors, 1975, 1, 47-53. Metropolitan Insurance Company. New weight standards for men and women. Statistical Bulletin, 1969, 40, 1-8. t)st, L., & G6testam, K . G . Behavioral and pharmacological treatments for obesity: An experimental comparison. Addictive Behaviors, 1976, 1, 331-338. Stalonas, P. M., Johnson, W. G., & Christ, M. Behavior modification for obesity: The evaluation of exercise, contingency management and program adherence. Journal of Consulting and Clinical Psychology, 1978, 46, 463-469. Wollersheim, J . P . Effectiveness of group therapy based upon learning principles in the treatment of overweight women. Journal of Abnormal Psychology, 1970, 76, 462--474. RECEIVED: January 14, 1983 FINAL ACCEPTANCE:May 2, 1983