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Chart-1

Table-1

Mean of Demographic data and Anthropometric Measurements of Students in Three Programs

Program

Number

Mean ± Standard deviation

Age

Weight (lb)

Height

BMI

WHR

Fat%

26.30±6.89

151.42±28.03

5.44±0.39

24.79 ± 5.15

32.45 ± 4.65

0.78 ± 0.065

25.10 ± 6.70

Nutrition

28.70±6.70

129.54±22.54

5.26±0.34

23.17 ± 3.29

30.32 ± 3.53

0.78 ± 0.07

26.19 ± 6.14

Non- Health related majors

21.20 ± 4.10

143.85± 25.67

5.45±0.23

24.22 ± 3.98

29.73 ± 3.80

0.76 ± 0.07

25.10 ± 6.10

Total

25.40±6.64

141.60±26.69

5.39±0.33

24.06 ± 4.19

30.83 ± 4.12

0.78 ± 0.07

25.45 ± 6.22

DC: Doctor of Chiropractic, BMI: Body Mass Index, WC: Waist Circumference, WHR: Waist-Hip Ratio.

Table 1 shows the mean of Demographic data and anthropometric measurements of participants among 60 students in the three deferent programs (Doctor of Chiropractic (DC), Nutrition and Non Health Related Programs). Female participants Age, Weight in pounds, Height in feet and inches, BMI, WC in inches, WHR, Fat% mean and standard deviations were found 25.40±6.64, 141.60±26.69, 5.39±0.33, 24.06±4.19, 30.83±4.12, 0.78±0.07, and 25.45±6.22. Among 20 students in DC program, the mean and standard deviations of age was 26.30±6.89, weight in pounds 151.42±28.03, height in feet and inches 5.44±0.39 BMI 24.79±5.15, WC 32.45±4.65, WHR 0.78±0.065, and Fat% 25.10± 6.70. Student from Nutrition obtained a mean of age of 28.70±6.70, weight in pounds 129.54±22.54, height in feet and inches 5.26±0.34, BMI 23.17±3.29, WC 30.32±3.53, WHR 0.78±0.07, and fat% 26.19±6.14. The mean age of students from non- health related programs was 21.20±4.10, weight 143.85±25.67, height 5.45±0.23, BMI 24.22 ± 3.98, WC 29.73 ± 3.80, WHR 0.76 ± 0.07, and fat% 25.10 ± 6.10.

Table-2

Comparison of Programs

Variable

Mean

Std. Deviation

Std. Error

P-Value

EAT-26 Score

7.25

8.783

1.964

NS(0.962)

Nutrition

6.85

9.241

2.066

Non Health Program

7.55

5.186

1.160

Total

7.22

7.816

1.009

TDS

32.40

3.393

0.759

NS(0.144)

Nutrition

31.50

3.069

0.686

Non Health Program

30.30

3.496

0.782

Total

31.40

3.381

0.436

BMI of Student

24.7850

5.15050

1.15169

NS(0.472)

Nutrition

23.1660

3.28575

.73472

Non Health Program

24.2150

3.97999

.88995

Total

24.0553

4.19260

.54126

WC of Student

32.4500

4.65069

1.03993

NS(0.088)

Nutrition

30.3200

3.52534

.78829

Non Health Program

29.7300

3.79974

.84965

Total

30.8333

4.12371

.53237

WHR of Student

0.7785

.06548

.01464

NS(0.716)

Nutrition

0.7810

.07297

.01632

Non Health Program

0.7640

.07358

.01645

Total

0.7745

.06997

.00903

Fat %

25.0700

6.69588

1.49724

NS(0.816)

Nutrition

26.1900

6.14414

1.37387

Non Health Program

25.1000

6.07012

1.35732

Total

25.4533

6.22391

.80350

Table 2 shows the comparison of EAT-26, TDS and body composition measurements between the three programs. Nutrition students had a little lower mean of EAT-26 score (6.85) and a lower mean of BMI (23.1660), and a little higher mean of fat mass percentage (26.1900) than DC and non-health program students. DC students had a little higher mean of TDS than nutrition and non-health program students, but non-health program students showed a little lower mean of WC (29.7300) and WHR (0.7640). However, there were no significant differences between students of the three groups of degrees and the EAT total score (p = 0.864), TDS (p=0.144) BMI (p=0.472), WC (p=0.088), WHR(p=0.716), and fat mass percentage (p=0.816).

Chart-2

Comparison the mean of Eating Attitude Test-26 (EAT-26) scores.

Chart-3

Comparison the mean of Tendency to Diet Scale (TDS) scores.

Table-3

Prevalence of eating disorder (EDs)

EAT-26 Score

%(n)

Nutrition

%(n)

Non Health Programs

%(n)

Total

%(n)

P-value

EAT < 19 (Normal)

95%(19)

90%(18)

100%(20)

95%(57)

0.349(NS)

EAT ≥ 20 (Eating disorder)

5.0%(1)

10%(2)

0.0%(0)

5.0%(3)

Total

100%(20)

100%(60)

Table 3 shows the prevalence of EDs among students that randomly selected from three different majors. Although there were no significant differences between students of the three groups of degrees and the EAT total score (p = 0.349), 5% of students were identified with EDs from the three programs. Five percent were identified with EDs in DC students, 10% in nutrition students indicated with EDs, while no students were identified with EDs in non-health related majors.

Table-4

Comparison of EAT-26 and TDS scores

Program

SCORE TYPE

Mean

Std. Deviation

P-Value

Score

EAT26

7.2167

7.81587

HS(0.000)

TDS

31.4000

3.38090

EAT26

7.2500

8.7821

HS(0.000)

TDS

32.4000

3.3945

Nutrition

EAT26

6.8500

9.2411

HS(0.000)

TDS

31.5000

3.0693

Non-health

EAT26

7.5000

5.1858

HS(0.000)

TDS

30.3000

3.4959

*HS(Highly significant)

Table 4 shows a Comparison of EAT-26 and TDS scores between the three groups of different majors. There was a significant association between EAT-26 and TDS, statically highly significant (p=0.000), which is ˂0.01. The results are indicating that students in all groups were a greater tendency to diet.

Table – 5

Comparison of EAT-26 and TDS between students in different years

Program

Variable

Year

Mean

Std. Deviation

P-Value

EAT-26 Score

Year 1 and 2

9.08

10.833

S(0.038)

Year 3 and 4

4.50

3.251

TDS Score

Year 1 and 2

32.00

3.742

NS(0.863)

Year 3 and 4

33.00

2.928

Nutrition

EAT-26 Score

Undergraduate

1.89

1.691

HS(0.002)

Graduate

10.91

10.940

TDS Score

Undergraduate

30.00

3.464

NS(0.414)

Graduate

32.73

2.149

Non-health

EAT-26 Score

Year 1 and 2

7.19

5.205

NS(0.0660)

Year 3 and 4

9.00

5.598

TDS Score

Year 1 and 2

30.88

3.462

NS(0.514)

Year 3 and 4

28.00

2.944

Table 5 shows a Comparison of EAT-26 and TDS between students in different years of the study. The mean of EAT-26 score in the first and second year DC students (9.08) was significantly higher than third and fourth-year students (P=0.038). However, the mean of TDS scores in the DC student in the different years was not significant (P=0.863). In the nutrition students, the mean of graduate students was highly significant than undergraduate students (p=0.002), while the TDS did not show significant differences between the nutrition students (p=0.414). The mean of EAT-26 and TDS scores in non-health related major students did not show significant differences (p=0.0660, 0.514 respectively). The results indicated that graduate nutrition and the first and second year DC students are at risk of EDs.

Chart-4

Comparison the mean of Eating Attitude Test-26 (EAT-26) scores between DC students.

Chart-5

Comparison the mean of Tendency to Diet Scale (TDS) scores between DC students

Chart-6

Comparison the mean of Eating Attitude Test-26 (EAT-26) scores between undergraduate and graduate nutrition students.

Chart-7

Comparison the mean of Tendency to Diet Scale (TDS) scores between undergraduate and graduate nutrition students.

Chart-8

Comparison the mean of Eating Attitude Test-26 (EAT-26) scores between non –health related major students.

Chart-9

Comparison the mean of Tendency to Diet Scale (TDS) scores between non –health related major students.

Table-6 Classification and comparison of BMI.

BMI Category

%(n)

Nutrition

%(n)

Non Health Programs

%(n)

Total

%(n)

P-value

Normal

65%(13)

75%(15)

65%(13)

68.3%(41)

0.501(NS)

Overweight

20%(4)

25%(5)

20%(4)

21.7%(13)

Obesity

15%(3)

10%(6)

Total

100%(20)

100%(60)

Table 6 shows the comparison of BMI categories between the three majors; DC, Nutrition and non-health related majors. Nutrition students had 75% of normal BMI and no obesity was identified compared to 65% of normal BMI and 15% obesity in DC students and non-health related programs. However, there was no statically significant found between the groups (P= 0.501).

Chart-10

Total of BMI Classification of Students in the Three Majors

Table 7 Waistcircumfrence classification and comparison.

Waistcircumfrence

%(n)

Nutrition

%(n)

Non Health Programs

%(n)

Total

%(n)

P-value

No Risk

60.0%(12)

65%(13)

63.3%(38)

0.931(NS)

Risk

40.0%(8)

35.0%(7)

36.7%(22)

Total

100%(20)

100%(60)

Table 7 shows the classification and comparison of Waist circumference among 60 students between the three majors. The majority of students (63.3%) were not at the risk of central obesity that associated with chronic diseases. Among the groups, 65% of nutrition and non-health related programs, and 60% of DC students were not at the risk of central obesity. However, the results showed no statically significant between the groups (P=0.931).

Chart-11

Total of WC Classification of Students in the Three Majors

Table 8 Waist Hip Ratio classification and comparisons

Waist Hip Ratio

%(n)

Nutrition

%(n)

Non- Health Programs

%(n)

Total

%(n)

P-value

Low

60%(12)

65.0%(13)

70%(14)

65%(39)

0.908(NS)

Moderate

30%(6)

20%(4)

23.3%(14)

High

10%(2)

15.0%(3)

10.0%(2)

11.7%(7)

Total

100%(20)

100%(60)

Table 8 shows the classifications and comparisons of the waist-hip ratio among the three majors. The results show that there were no statically significant was found between the groups (P= 0.908). The majority of students (65%) in the groups were in the low category of WHR. Non-health related program students were the majority that had the lowest category (70%) followed by nutrition students were 65% and DC students 60%. Fifteen percent of nutrition students had high WHR compared to 10% of students from the DC and non-health related majors.

Chart-12

Total of WHR Classification of Students in the Three Majors

Table 9 Classification and comparison of Fat Mass percentages

Fat%

%(n)

Nutrition

%(n)

Non -Health Programs

%(n)

Total

%(n)

P-value

≤24%

55%(11)

50%(10)

51.7%(31)

0. 890 (NS)

25-31%

30%(6)

35%(7)

25%(5)

30%(18)

≥32%

15%(3)

25%(5)

18.3%(11)

Total

100%(20)

100%(60)

Table 9 shows a comparison of fat mass percentage between the three programs. Around half of the students in the three programs had ≤24% of fat mass, which indicated that 51.7% students were fitness participants. Among the groups, 50% of nutrition and non-health related major students had ≤24% of fat mass compared to 55% of DC students. Obese students that had ≥32% of fat mass were observed more in non-health related major students (25%) in contrast to DC and nutrition students were 15%. No significant differences were found in fat mass percentage among the three groups, p = 0.890.

Chart-13

Total of Fat% Classification of Students in the Three Majors

Chart-14

Obesity Students in the Three Programs

Table- 10 Relation between body composition and EAT-26.

Model

Standardized Coefficients

Beta

Sig.

EAT-26

(Constant)

-.465

.644

BMI of Student

.202

.675

.502

WC of Student

-.170

-.570

.571

WHR of Student

.205

1.019

.313

Fat %

-.109

-.463

.645

Table9 shows the relation between body composition and EAT-26 between the groups. The results found no significance association between the response of EAT-26 scores and the body composition measurements, BMI (p=0.502), WC (p=0.571), WHR (p=0.313) and fat % (p=0.645).

Table 11 Relation between body composition and TDS

Model

Standardized Coefficients

Beta

Sig.

TDS

(Constant)

4.616

.000

BMI of Student

.218

.759

.451

WC of Student

.253

.885

.380

WHR of Student

-.076

-.0396

.694

Fat %

-.132

-.586

.560

Table 11 shows the relation between body composition and TDS between the groups. The results found no significance association between the response of TDS scores and the body composition measurements, BMI (p=0.451), WC (p=0.380), WHR (p=0.694) and fat % (p=0.560).

Table 12 Correlation between body composition measurements, EAT-26, and TDS scores

EAT-26

P-value

TDS

P-value

BMI

0.13

NS (0.924)

0.287

S(0.026)

0.32

NS (0.811)

0.286

S(0.027)

WHR

0.118

NS (0.367)

0.085

NS (0.520)

Fat %

-0.028

NS (0.834)

0.199

NS (0.127)

Table 12 shows the correlation between body composition measurement, EAT-26, and TDS scores between the participants in the three groups. Although there was no significant correlation between EAT-26 and body composition measurements, there were little correlations were found in BMI (0.13; p=0.924), WC (32; p=0.811), and WHR (0.118 p=0.367). The results showed a significance correlation between TDS and BMI (0.287;p=0.026), and in WC (0.286; p=0.027). TDS showed a little correlation in fat mass percentage (0.199), but the correlation was not significance (p=0.127)

Table 13 comparison of body composition between DC students in different years.

Year

Mean

Std. Deviation

P-Value

BMI of Student

Year 1 and 2

26.4250

5.77410

S(0.049)

Year 3 and4

22.3250

2.84341

WC of Student

Year 1 and 2

33.6667

5.22813

S(0.05)

Year 3 and 4

30.6250

3.06769

WHR of Student

Year 1 and 2

.7975

.07238

NS(0.187)

Year 3 and 4

.7500

.04309

Fat %

Year 1 and 2

26.6750

7.43115

NS(0.303)

Year 3 and 4

22.6625

4.88641

Table 13 shows a comparison of body composition between DC students in different years. First and second-year group and third and fourth years group of DC students had a significant association in BMI (p=0.049), and in WC (p=0.05). The BMI of third and fourth year DC students were normal (=22.3) and lower in WC (=30.6) compared to first and second year of DC students were overweight (=26.4) and higher in WC (=33.6).

Table 14 comparison of body composition between undergraduate and graduate nutrition students.

Nutrition

Program levels

Mean

Std. Deviation

P-Value

BMI of Student

Undergraduate

24.4778

3.59088

NS(0.373)

Graduate

22.0927

2.71687

WC of Student

Undergraduate

31.5556

4.30439

NS(0.204)

Graduate

29.3091

2.50857

WHR of Student

Undergraduate

.7678

.08772

NS(0.479)

Graduate

.7918

.06063

Fat %

Undergraduate

28.5556

7.20141

NS(0.361)

Graduate

24.2545

4.59138

Table 14 shows comparison of body composition between undergraduate and graduate nutrition students. The graduate students had a lower mean of BMI (22), WC (29), and fat% (24) than undergraduate students. However, the results of nutrition students did not show any significant association in body composition measurements between undergraduate and graduate students.

Table 15 comparison of body composition between non-health related majors student in different years.

Non-health

Program levels

Mean

Std. Deviation

P-Value

BMI of Student

Year 1 and 2

24.4688

4.36482

S(0.033)

Year 3 and4

23.2000

1.82939

WC of Student

Year 1 and 2

29.4125

4.10087

NS(0.112)

Year 3 and 4

31.0000

2.16025

WHR of Student

Year 1 and 2

0.7513

.07544

NS(0.362)

Year 3 and 4

0.8150

.03873

Fat %

Year 1 and 2

25.6250

6.23490

NS(0.764)

Year 3 and 4

23.0000

5.62494

Table 15 comparison of body composition between non-health related majors student in different years. There was a significant association between BMI, and the first and second year and third and fourth-year students from non-health related major (p=0.033). The third and fourth-year students from non-health related major students had a lower mean of BMI (=23.2), fat (=23%) than the first and second-year students. Although there no statically significant was found, first and second-year students had a lower mean of WC (=29.4), WHR (=0.75) than third and fourth-year students in non-health related major.

Table 16 ANOVA about the Relation between EAT-26 and TDS Scores

ANOVA

Sum of Squares

Mean Square

Sig.

TDSQ1

Between Groups

1.881

.627

.430

.732

Within Groups

84.506

1.457

Total

86.387

TDSQ2

Between Groups

7.824

2.608

3.394

.024

Within Groups

44.563

.768

Total

52.387

TDSQ3

Between Groups

3.041

1.014

1.491

.227

Within Groups

39.427

.680

Total

42.468

TDSQ4

Between Groups

2.822

.941

1.683

.181

Within Groups

32.420

.559

Total

35.242

TDSQ5

Between Groups

.852

.284

2.186

.099

Within Groups

7.535

.130

Total

8.387

TDSQ6

Between Groups

.046

.015

.956

.420

Within Groups

.938

.016

Total

.984

TDSQ7

Between Groups

.906

.302

.524

.667

Within Groups

33.432

.576

Total

34.339

TDSQ8

Between Groups

.233

.078

.258

.855

Within Groups

17.461

.301

Total

17.694

TDSQ9

Between Groups

2.912

.971

1.619

.195

Within Groups

34.766

.599

Total

37.677

TDSQ10

Between Groups

2.368

.789

1.101

.356

Within Groups

41.567

.717

Total

43.935

TDSQ11

Between Groups

1.531

.510

.621

.604

Within Groups

47.646

.821

Total

49.177

TDSQ12

Between Groups

1.417

.472

.730

.538

Within Groups

37.503

.647

Total

38.919

TDSQ13

Between Groups

.774

.258

.261

.853

Within Groups

57.419

.990

Total

58.194

TDSQ14

Between Groups

.959

.320

.469

.705

Within Groups

39.509

.681

Total

40.468

TDSQ15

Between Groups

5.764

1.921

2.476

.070

Within Groups

45.011

.776

Total

50.774

Table 16 based on the results of the ANOVA test that defines about the association between the variables of EAT-26 and all the TDS scores used in the model. The approach of one-way ANOVA is applied in the test as there are only two variables. The output of the ANOVA table explains about the existence of statistically difference between different group means. The results of the ANOVA test explain that there are two values of TDS 2 and TDS 15 that referred as statistically significantly when it comes to the p values in table. The p-values for these scores are 0.024 and 0.07 respectively which is below the standard of 0.05 ultimately referred as the existence of the significant mean difference exist between these groups.

The test of ANOVA based on the proper consideration of Analysis of Variance (ANOVA) that is used to identify the existing difference between means of groups to find out the prevailing difference ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"BNq9W8BQ","properties":{"formattedCitation":"(Vik, 2013)","plainCitation":"(Vik, 2013)","noteIndex":0},"citationItems":[{"id":606,"uris":["http://zotero.org/users/local/7Hi3kAOD/items/RPBQ6UJ7"],"uri":["http://zotero.org/users/local/7Hi3kAOD/items/RPBQ6UJ7"],"itemData":{"id":606,"type":"book","title":"Regression, ANOVA, and the General Linear Model: A Statistics Primer","publisher":"SAGE Publications","URL":"https://books.google.com.pk/books?id=CbMgAQAAQBAJ","ISBN":"978-1-4833-1601-7","author":[{"family":"Vik","given":"P."}],"issued":{"date-parts":[["2013"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Vik, 2013).

Table 17 F test about the Association between EAT-26 and TDS Scores

ANOVAa

Model

Sum of Squares

Mean Square

Sig.

Regression

13.465

.898

1.102

.381b

Residual

37.455

.814

Total

50.919

a. Dependent Variable: EATQ26

b. Predictors: (Constant), TDSQ15, TDSQ8, TDSQ2, TDSQ5, TDSQ14, TDSQ3, TDSQ11, TDSQ6, TDSQ10, TDSQ7, TDSQ9, TDSQ1, TDSQ4, TDSQ13, TDSQ12

Table 17 is the representation of the results of the F test that is used to determine about the overall fitness of the model. It explains about the overall significance of the regression model. The result of f test in the table explains about the variance of the group means. The value for the F test in 1.102 which is close to 1 that’s why it positively explains about the overall significance of the association. The significant value of p-value with the value of .381 ultimately helps to determine about the value of f test for the model. The overall f-test clearly explains about the overall strength of the relationship between the variables of EAT-26 and all the scores of TDS.

Table 18 Correlation between EAT-26 and TDS Scores

Correlations

EATQ26

TDSQ1

TDSQ2

TDSQ3

TDSQ4

TDSQ5

EATQ26

Pearson Correlation

-.135

-.175

.059

-.281*

-.192

Sig. (2-tailed)

.295

.174

.651

.027

.135

TDSQ1

Pearson Correlation

-.135

-.392**

-.005

.568**

.237

Sig. (2-tailed)

.295

.002

.971

.000

.063

TDSQ2

Pearson Correlation

-.175

-.392**

.261*

-.218

-.066

Sig. (2-tailed)

.174

.002

.041

.089

.609

TDSQ3

Pearson Correlation

.059

-.005

.261*

.000

-.015

Sig. (2-tailed)

.651

.971

.041

.997

.906

TDSQ4

Pearson Correlation

-.281*

.568**

-.218

.000

.311*

Sig. (2-tailed)

.027

.000

.089

.997

.014

TDSQ5

Pearson Correlation

-.192

.237

-.066

-.015

.311*

Sig. (2-tailed)

.135

.063

.609

.906

.014

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

Table 18 explains about the existing correlation between EAT-26 and the particular scores of TDS referred as TDS 1, TDS 2, TDS 3, TDS 4, and TDS 5. The statistical aspect in the form of correlation helps to determine about the existing strength of relationship between the variables. The following table indicate about the existing association between EAT-26 and TDS scores. The significance of p-value for the test determine on 2-tailed with the sample of 62. The value of -.135 determine about the significant association between EAT-26 and TDS 1 as the p-value is below 0.05. The value of -.175 determine about the significant association between EAT-26 and TDS 2 as the p-value is below 0.05. The p-value for TDS 3 is .059 that refer it as insignificant information to reject the null hypothesis. The value of -.281 determine about the significant association between EAT-26 and TDS 4 as the p-value is below 0.05. The results of TDS 5 also explain its strong linear relationship with EAT-26. The value of -.192 determine about the significant association between EAT-26 and TDS 5 as the p-value is below 0.05.

Table 19 Correlation between EAT-26 and TDS Scores

Correlations

EATQ26

TDSQ6

TDSQ7

TDSQ8

TDSQ9

TDSQ10

EATQ26

Pearson Correlation

.057

.068

.112

.004

-.207

Sig. (2-tailed)

.660

.598

.385

.977

.106

TDSQ6

Pearson Correlation

.057

-.219

.274*

.196

.005

Sig. (2-tailed)

.660

.087

.031

.127

.970

TDSQ7

Pearson Correlation

.068

-.219

-.224

-.020

.066

Sig. (2-tailed)

.598

.087

.079

.879

.612

TDSQ8

Pearson Correlation

.112

.274*

-.224

.087

-.154

Sig. (2-tailed)

.385

.031

.079

.499

.232

TDSQ9

Pearson Correlation

.004

.196

-.020

.087

.089

Sig. (2-tailed)

.977

.127

.879

.499

.493

TDSQ10

Pearson Correlation

-.207

.005

.066

-.154

.089

Sig. (2-tailed)

.106

.970

.612

.232

.493

*. Correlation is significant at the 0.05 level (2-tailed).

Table 19 is the explanation of the outcomes of correlation between the variables of EAT-26 and scores of TDS in the form of TDS 6, TDS 7, TDS 8. TDS 9, and TDS 10. The p value for the relationship between EAT-26 and TDS 6 identify as .057 that refer the insignificant association between these two elements. The p-value for TDS 7 is .068 that refer it as insignificant information to reject the null hypothesis. The p-value for TDS 8 is .112 that refer it as insignificant information to reject the null hypothesis. The value of .004 determine about the significant association between EAT-26 and TDS 9 as the p-value is below 0.05. The value of -.207 determine about the significant association between EAT-26 and TDS 10 as the p-value is below 0.05.

Table 20 Correlation between EAT-26 and TDS Scores

Correlations

EATQ26

TDSQ11

TDSQ12

TDSQ13

TDSQ14

TDSQ15

EATQ26

Pearson Correlation

-.007

-.024

.071

.082

-.143

Sig. (2-tailed)

.958

.851

.583

.526

.268

TDSQ11

Pearson Correlation

-.007

.678**

.622**

.427**

-.130

Sig. (2-tailed)

.958

.000

.001

.315

TDSQ12

Pearson Correlation

-.024

.678**

.607**

.673**

-.298*

Sig. (2-tailed)

.851

.000

.019

TDSQ13

Pearson Correlation

.071

.622**

.607**

.704**

-.177

Sig. (2-tailed)

.583

.000

.169

TDSQ14

Pearson Correlation

.082

.427**

.673**

.704**

-.236

Sig. (2-tailed)

.526

.001

.000

.065

TDSQ15

Pearson Correlation

-.143

-.130

-.298*

-.177

-.236

Sig. (2-tailed)

.268

.315

.019

.169

.065

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Table 20 is the explanation of the outcomes of correlation between the variables of EAT-26 and scores of TDS in the form of TDS 11, TDS 12, TDS 13, TDS 14, and TDS 15. The p value for the relationship between EAT-26 and TDS 11 identify as -.007 that refer the significant association between these two elements. The p-value for TDS 12 is -.024 that refer it as significant information to identify the existing relationship between EAT-26 and TDS 12. The p-value for TDS 13 is .071 that refer it as insignificant information to reject the null hypothesis. The value of .082 determine the insignificant association between EAT-26 and TDS 14 as the p-value is below 0.05. The value of -.143 determine about the significant association between EAT-26 and TDS 15 as the p-value is below 0.05.

References

ADDIN ZOTERO_BIBL {"uncited":[],"omitted":[],"custom":[]} CSL_BIBLIOGRAPHY Vik, P. (2013). Regression, ANOVA, and the General Linear Model: A Statistics Primer. SAGE Publications. Retrieved from https://books.google.com/books?id=CbMgAQAAQBAJ

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