1 INTRODUCCIÓN
1.2 Antecedentes y justificación
1.2.3 Contaminantes de vertederos de RU: lixiviados
This chapter presents the process of data screening, the demographic data for the participants, and the results of the hierarchical regression analyses. The purpose of this study was to assess the combined effects of individual problem solving styles (sufficiency of originality, efficiency, and rule/group conformity) and planned behavior (attitudes towards overeating, subjective norms, behavioral intentions to manage eating behavior, perceived behavioral control), after first controlling for body mass index, on eating behaviors. This study proposes a relationship between the predictor variables (perceived behavioral control, attitude towards overeating, subjective norms, and intentions to manage eating behavior as measured by TPB, and sufficiency of originality, efficiency, and rule/group conformity as measured by KAI, and BMI) and eating behaviors as measured by EDE-Q6. In order to investigate this relationship, the specific research question was presented: Is eating behavior affected by body mass index, perceived behavioral control, attitude towards overeating, subjective norms, intention to manage eating behavior, sufficiency of originality, efficiency, and rule/group conformity?
Data Screening and Cleaning
The data collection instruments and the process of data collection followed all the guidelines described in chapter 3. A total of 145 participants responded to the
questionnaire employed in this study. After data collection, the data were visually screened and five surveys were excluded from the sample. Three of these surveys were missing responses on an entire page of the survey. Kirton (1999) explained that
participants who frequently answer the KAI instrument with ten or more 3s (the median point on the response scale) often are unwilling to commit to honestly disclosing
cognitive style and thus, according to Condition 3 of scoring the KAI instrument, results in a score that is unreliable and must be dismissed (Kirton, 2008). Two completed surveys had ten or more 3s, including 1 or 2 omitted responses, in the KAI section of the questionnaire and were therefore dismissed.
The data from the remaining 140 questionnaires were entered into an SPSS version 15.0 data set document. Male participants were coded using the value “1” and female participants were coded using the value “2”. Participants’ ethnicities were coded as European American = 1, African American = 2, Hispanic American = 3, Asian American = 4, and Native American = 5.
Assumptions and Pretest Analyses
Prior to accepting the results of a multiple regression analysis a number of assumptions regarding the data collected should be checked. These considerations
include the following: outliers, multicollinearity, normality of residuals, homoscedasticity of residuals, and reliability analyses.
Outliers
To determine whether the remaining data included any outliers, a regression analysis was conducted that involved all variables. The procedure produced the maximum value of 40.592 for the Mahalanobis distance. This distance is evaluated against chi-square at a p value of .001 for a degree of freedom equal to the number of variables. In this case there were a total of nine variables and the critical value calculated
was 27.88. Therefore, any case with a value greater than 27.88 was considered to be a multivariate outlier. Three cases in data rows 69, 98, and 105 fell into this category and thus reduced the sample size to 137.
Multicollinearity, Normality, Linearity, and Homoscedasticity
An analysis of the relationships among the independent variables is required when using multiple regression modeling so correlations were checked between the eight independent variables. Pearson correlations between the IVs ranged from r(137) = .005, p = .479 to r(137) = .650, p < .001. Table 1 contains additional relevant correlation statistics.
Table 1
Correlations: IVs by IVs
Variables BMI A SN PBC I SO E R
BMI 1.000
A -.021 1.000
SN -.018 .448* 1.000
PBC -.240* .154* .315* 1.000
I -.169* .404* .323* .650* 1.000
SO -.020 -.027 .031 .334* .221* 1.000
E -.023 -.010 .005 .139 .167* .313* 1.000
R -.052 -.011 .029 .201* .081 .366* .502* 1.000
Note. N= 137. BMI = Body Mass Index; A = Attitude; SN = Subjective Norm; PBC = Perceived Behavioral Control; I = Intentions; SO = Sufficiency of Originality; E = Efficiency; and R = Rule/Group Conformity. * p <.05.
The Variance Inflation Factor (VIF) values were all under 5, making the possibility of collinearity between independent variables unlikely. Further, a review of Scatterplots of the Standardized Residuals by the Regression Standardized Predicted Values revealed randomly scattered residuals around the horizontal line which demonstrated relatively homogenous distributions for all variables.
Sample Characteristics
The final sample contained 137 participants; 55.5% were female and 44.5% were male. The ages ranged from 18 years old to 64 years old (median = 39). The majority of respondents were European American (85.4%) followed by Hispanic Americans (8.0%) and included African Americans (2.9%), Asian Americans (2.9%), and a Native
American (0.7%). Table 2 provides additional sample characteristics.
Table 2
Demographic Characteristics of Study Sample (N = 137)
Characteristic N Percent
Gender
Male 61 44.5
Female 76 55.5
Total 137 100.0
Ethnicity
European American 117 85.4
African American 4 2.9
Hispanic American 11 8.0
Asian American 4 2.9
Native American 1 .7
Total 137 100.0
Data Analyses Reliability Analysis
Cronbach’s alpha coefficient for internal consistency reliability should be calculated for any scales or subscales one may be using (Gliem & Gliem, 2003).
Therefore, Cronbach’s alpha coefficient for internal consistency and reliability for all subscales in this study were calculated using SPSS.
The EDE-Q6 contains four subscales. The dietary restraint subscale consisted of 5 items (α = .775), the eating concern subscale consisted of 5 items (α = .867), the shape concern subscale consisted of 8 items (α = .919), and the weight concern subscale consisted of 5 items (α =.790). The Cronbach’s alphas for these subscales are within acceptable range.
The TPB questionnaire contains four subscales. The attitude subscale consisted of 3 items (α = .764), the subjective norm subscale consisted of 3 items (α = .842), the perceived behavioral control subscale consisted of 3 items (α = .829), and the intention subscale consisted of 3 items (α =.765). The Cronbach’s alphas for these subscales are within acceptable range.
Lastly, the KAI inventory contains three subscales. The rule/group conformity subscale consisted of 12 items (α = .732), the efficiency subscale consisted of 7 items (α
= .824), and the sufficiency of originality subscale consisted of 13 items (α =.717). The Cronbach’s alphas for these subscales are within acceptable range.
Descriptive Statistics
Descriptive statistics for the variables are depicted in Table 3. The total sample of the predictor variables reported a mean BMI score of 26.02 (SD = 5.17) with the potential range of scores of less than 18.5 being underweight and greater than 30 being obese , mean Attitude score of 16.84 (SD = 3.52) with the range of scores being 3 to 21, mean Subjective Norm score of 15.62 (SD = 3.97) with the range of scores being 3 to 21, mean Perceived Behavioral Control score of 15.09 (SD = 4.17) with the range of scores being 3 to 21, mean Intention score of 13.48 (SD = 3.79) with the range of scores being 3 to 21, mean Sufficiency of Originality score of 42.70 (SD = 7.02) with the range of scores being 13 through 65, mean Efficiency score of 20.48 (SD = 6.13) with the range of scores being 7 through 35, and mean Rule/Group score of 35.43 (SD = 7.23) with the range of scores being 12 through 60.
The total sample of the criterion variables reported mean Dietary Restraint score of 1.55 (SD = 1.42) with the range of scores being 0 through 6, mean Eating Concern score of .741 (SD = 1.07) with the range of scores being 0 through 6, mean Shape Concern score of 2.23 (SD = 1.71) with the range of scores being 0 through 6, and mean Weight Concern score of 1.74 (SD = 1.45) with the range of scores being 0 through 6.
Table 3
Descriptive Statistics for Variables
N Minimum Maximum Mean SD
Body Mass Index 137 17.37 50.07 26.02 5.178
Restraint 137 0.00 5.00 1.55 1.422
Eating Concern 137 0.00 4.80 .74 1.079
Shape Concern 137 0.00 6.00 2.23 1.711
Weight Concern 137 0.00 5.40 1.74 1.452
Attitude 137 3.00 21.00 16.84 3.524
Subjective Norms 137 3.00 21.00 15.62 3.971
Perceived Behavioral Control 137 4.00 21.00 15.09 4.173
Intention 137 3.00 21.00 13.48 3.793
Sufficiency of Originality 137 25.00 58.00 42.70 7.023
Efficiency 137 8.00 33.00 20.48 6.135
Rule/Group Conformity 137 17.00 52.00 35.43 7.238
The EDE-Q6 contains the four criterion variables, described prior in the study, and also calculates an overall mean global score by adding the subscore totals together and then dividing by four. In this research, the total sample reported a mean EDE-Q6 global score of 1.56 (N = 137, SD = 1.21). Table 4 presents descriptive data and
percentile ranks for the EDE-Q6 global score and four subscale scores for this research sample.
Table 4
EDE-Q6 Percentile Ranks for EDE-Q6 Global and Subscale Scores (N = 137)
GS R EC SC WC
Note. GS = mean global score, R = dietary restraint subscale, EC = eating concern subscale, SC = shape concern subscale, WC = weight concern subscale.
Hierarchical Multiple Regression Analyses
A hierarchical multiple regression analysis was performed on each of the four criterion variables to test the hypothesis. To determine the relative relationship between the predictor variables and eating behavior, variables were entered using a hierarchical block approach. Body mass index was entered first to account for as much variance as possible in the criterion variable. Subsequently, the remaining predictor variables were entered to account for any remaining variance.
The first component of eating behavior this study examined was dietary restraint.
In the first regression model body mass index was not found to be statistically significant, R2 = .015, F(1, 135) = 2.007, p = .159. When perceived behavioral control, attitude, subjective norms, intentions, and sufficiency of originality, efficiency, and rule/group conformity were entered into the equation, the change in variance accounted for a significant proportion of the dietary restraint variance after controlling for the effects of body mass index, R2 change = .148, F(7, 128) = 3.102, p = .003. Table 5 provides the regression summary.
Table 5
Summary of Hierarchical Regression Analysis for Variables Predicting Dietary Restraint (N = 137)
Variable B SEB β Sig.
Step 1
Body Mass Index .033 .023 .121 .159
Step 2
Body Mass Index .021 .023 .077 .361
Attitude .118 .040 .292 .003
Subjective Norm .051 .034 .142 .134
Perceived Behavioral Control -.069 .040 -.201 .089
Intention -.014 .044 -.038 .750
Sufficiency of Originality .010 .019 .048 .608
Efficiency -.023 .022 -.100 .301
Rule/Group Conformity .012 .019 .062 .528
Note. R2 = .015 for Step 1; ΔR2 = .148 for Step 2 ( p < .05).
In the second model it was found that attitude towards overeating significantly predicted dietary restraint (β = .292, p =. 003).
The second component of eating behavior this study examined was eating concern. In the first regression model body mass index accounted for 5.2% of the eating concern variability, R2 = .052, F(1, 135) = 7.340, p = .008. When perceived
behavioral control, attitude, subjective norms, intentions, and sufficiency of originality, efficiency, and rule/group conformity were entered into the equation, the change in
variance accounted for a significant proportion of the eating concern variance after controlling for the effects of body mass index, R2 change = .253, F(7, 128) = 6.993, p
< .001. Table 6 provides the regression summary.
Table 6
Summary of Hierarchical Regression Analysis for Variables Predicting Eating Concern (N = 137)
Variable B SEB β Sig.
Step 1
Body Mass Index .047 .017 .227 .008
Step 2
Body Mass Index .022 .016 .106 .168
Attitude .060 .027 .197 .029
Subjective Norm .025 .023 .091 .292
Perceived Behavioral Control -.083 .028 -.319 .003
Intention -.084 .031 -.296 .007
Sufficiency of Originality .003 .013 .018 .835
Efficiency .019 .015 .107 .225
Rule/Group Conformity -.010 .013 -.064 .473
Note. R2 = .052 for Step 1; ΔR2 = .253 for Step 2 ( p < .05).
In the second model it was found that attitude towards overeating significantly predicted eating concern (β = .197, p =. 029), as did perceived behavioral control (β = -.319, p = .003), and intention to manage eating behavior (β = -.296, p = .007).
The third component of eating behavior this study examined was shape concern.
In the first regression model body mass index accounted for 8.8% of the shape concern variability, R2 = .088, F(1, 135) = 13.023, p < .001. When perceived behavioral control, attitude, subjective norms, intentions, and sufficiency of originality, efficiency, and rule/group conformity were entered into the equation, the change in variance
accounted for a significant proportion of the shape concern variance after controlling for the effects of body mass index, R2 change = .315, F(7, 128) = 10.882, p < .001. Table 7 provides the regression summary.
Table 7
Summary of Hierarchical Regression Analysis for Variables Predicting Shape Concern (N = 137)
Variable B SEB β Sig.
Step 1
Body Mass Index .098 .027 .297 .000
Step 2
Body Mass Index .060 .023 .183 .011
Attitude .169 .040 .349 .000
Subjective Norm .039 .034 .090 .261
Perceived Behavioral Control -.129 .041 -.315 .002
Intention -.124 .045 -.276 .007
Sufficiency of Originality -.010 .019 -.041 .597
Efficiency -.022 .023 -.077 .343
Rule/Group Conformity .011 .020 .045 .586
Note. R2 = .088 for Step 1; ΔR2 = . 315 for Step 2 ( p < .05).
In the second model it was found that body mass index significantly predicted shape concern (β = .183, p = .011), as did attitude towards overeating (β = .349, p < .001), perceived behavioral control (β = -.315, p = .002), and intention to manage eating behavior (β = -.276, p = .007).
The fourth and final component of eating behavior this study examined was weight concern. In the first regression model body mass index accounted for 12.3% of the
weight concern variability, R2 = .123, F(1, 135) = 18.866, p < .001. When perceived behavioral control, attitude, subjective norms, intentions, and sufficiency of originality, efficiency, and rule/group conformity were entered into the equation, the change in variance accounted for a significant proportion of the weight concern variance after controlling for the effects of body mass index, R2 change = .366, F(7, 128) = 13.095, p
< .001. Table 8 provides the regression summary.
Table 8
Summary of Hierarchical Regression Analysis for Variables Predicting Weight Concern (N = 137)
Variable B SEB β Sig.
Step 1
Body Mass Index .098 .023 .350 .000
Step 2
Body Mass Index .062 .018 .222 .001
Attitude .155 .032 .377 .000
Subjective Norm .010 .034 .090 .261
Perceived Behavioral Control -.105 .032 -.302 .001
Intention -.135 .035 -.353 .000
Sufficiency of Originality -.005 .015 .022 .761
Efficiency -.019 .018 -.078 .299
Rule/Group Conformity -.011 .015 -.055 .473
Note. R2 = .123 for Step 1; ΔR2 = . 366 for Step 2 ( p < .05).
In the second model it was found that body mass index significantly predicted weight concern (β = .222, p = .001), as did attitude towards overeating (β = .377, p < .001), perceived behavioral control (β = -.302, p = .001), and intention to manage eating behavior (β = -.353, p < .001).
Primary Research Question and Hypotheses Evaluation This research addressed the following primary question: Are each of four components of eating behavior affected by the variables of BMI, perceived behavioral control, attitude towards overeating, subjective norms, intention towards eating behavior, sufficiency of originality, efficiency, and rule/group conformity. Based on the
presumption that eating behaviors are affected by cognitive style and motivation, four hypotheses were formulated and their corresponding null forms are presented below.
Null Hypothesis (Ho):
Null 1: In a hierarchical multiple regression there will be no significant relationship between the predictor variables (perceived behavioral control, attitude, subjective norms, and intentions as measured by TPB, and sufficiency of originality, efficiency, and rule/group conformity as measured by KAI, and BMI) and dietary restraint as measured by EDE-Q6 (R = 0).
The results of the hierarchical regression showed that the combined effects of the eight predictor variables did significantly predict dietary restraint and therefore the null hypothesis is rejected.
Null 2: In a hierarchical multiple regression there will be no significant relationship between the predictor variables (perceived behavioral control, attitude,
subjective norms, and intentions as measured by TPB, and sufficiency of originality, efficiency, and rule/group conformity as measured by KAI, and BMI) and eating concern as measured by EDE-Q6 (R = 0).
The results of the hierarchical regression showed that the combined effects of the eight predictor variables did significantly predict eating concern and therefore the null hypothesis is rejected.
Null 3: In a hierarchical multiple regression there will be no significant relationship between the predictor variables (perceived behavioral control, attitude, subjective norms, and intentions as measured by TPB, and sufficiency of originality, efficiency, and rule/group conformity as measured by KAI, and BMI) and shape concern as measured by EDE-Q6 (R = 0).
The results of the hierarchical regression showed that the combined effects of the eight predictor variables did significantly predict shape concern and therefore the null hypothesis is rejected.
Null 4: In a hierarchical multiple regression there will be no significant relationship between the predictor variables (perceived behavioral control, attitude, subjective norms, and intentions as measured by TPB, and sufficiency of originality, efficiency, and rule/group conformity as measured by KAI, and BMI) and weight concern as measured by EDE-Q6 (R = 0).
The results of the hierarchical regression showed that the combined effects of the eight predictor variables did significantly predict weight concern and therefore the null hypothesis is rejected.
Therefore, to address the research question, attitude towards overeating affects the eating components of dietary restraint, eating concern, shape concern and weight
concern; perceived behavioral control affects the eating components of eating concern, shape concern and weight concern; intention towards eating behavior affects the eating components of eating concern, shape concern, and weight concern; and, BMI affects the eating components of shape concern and weight concern.
Additional Findings and Observations
Additional findings and observations of the data related to the results that should be discussed is the overall results of the EDE-Q6 as they relate to the clinically
significant range of eating disorders. A clinically significant eating disorder score or negative eating behavior pattern can be determined by a total score that is greater than or equal to 4.0 on the dietary restraint subscale, eating concern subscale, shape concern subscale, weight concern subscale, or the mean global score (Fairburn & Cooper, 1993;
Fairburn, Cooper, Doll, & Davies, 2005; Luce, Crowther, & Pole, 2008).
Using the cut-off value of ≥ 4.0 for clinical significance, 8% of the sample (n = 11) scored in clinical significance range on dietary restraint, 3% of the sample (n = 5) scored in clinical significance range on eating concern, 17% of the sample (n = 24) scored in clinical significance range on shape concern, 11% of the sample (n = 16) scored in clinical significance range on weight concern, and 5% of the sample (n = 7) scored in clinical significance range on the global scale. The total sample that reported one or more subscale scores in clinical significance range was 20% (n = 28).
Observed Consistencies and Inconsistencies
Several aspects of the findings relate to observed consistencies and
inconsistencies among the individual participant survey responses. One such observation was noted with male respondents. If an individual reports a score of zero on any of the EDE-Q6 subscales it is interpreted as an absence of the eating behavior feature, and a score of 1 is interpreted as a feature almost, but not quite, absent (Fairburn, 2008). On reviewing the raw data, it was noted that 13 male participants reported individual answers on the EDE-Q6 of all zeros with a few reported scores of 1. Further, five male
participants had overall EDE-Q6 global mean scores of 0.00. Alternatively, the top 20 highest EDE-Q6 global mean scores were reported by female participants. Only one female participant in the sample population reported individual answers on all the EDE-Q6 subscales of all zeros. All the remaining female participants in the sample reported at least one individual score as a 2 or higher. This could be explained in that female
participants in this sample have more negative eating behaviors or an increased
awareness regarding their eating behaviors, whereas male participants have less negative eating behaviors or less awareness regarding their eating behaviors. Or this could be alternatively interpreted that women are more comfortable disclosing any issues or concerns they may have regarding eating behaviors, whereas men are less likely to disclose any eating concerns or behaviors. Research using the Eating Disorders Examination has noted that women are more likely than men to report negative eating behaviors associated with emotional responses (Tanofsky, Wilfley, Spurrell, Welch, &
Brownell, 1998). However, there are relatively few studies in this research area and
therefore these aspects of this research must be considered merely observations and not findings.
Summary
This chapter described data screening, assumptions and pretest analyses, sample characteristics, and reported the demographic statistics for the survey participants.
Additionally a description of the data analyses and the results of the hierarchical regression analyses were presented. These results were used to answer the research question through the study hypotheses that attitude towards overeating affects the eating components of dietary restraint, eating concern, shape concern and weight concern;
perceived behavioral control affects the eating components of eating concern, shape concern and weight concern; intention towards eating behavior affects the eating
components of eating concern, shape concern, and weight concern; and, BMI affects the eating components of shape concern and weight concern.
Lastly, additional findings and observations from the research were addressed.
Chapter 5 summarizes the study, discusses the conclusions and implications, addresses the positive social change implications of the study, and presents recommendations for future action and further study.
CHAPTER 5: DISCUSSION