Print Сite this

Protective Factors Against Youthful Depression

Several iterations of multiple correlation, step-wise and hierarchical regression yielded inconclusive results about the antecedents and predictors of depression. In particular, the untreated data with respect to sports participation did not seem to relate to emotional wellbeing, mental health or depression.

We will write a
custom essay
specifically for you

for only $16.05 $11/page
308 certified writers online
Learn More

The weak link with sports involvement eventually provoked the realization that this predictor variable was being mediated by the other measures of self-worth.

Secondly, the construction of the sports involvement variables was broad enough to accommodate every possible field or PE activity high school students engaged in. This included gym class, about which neither the upbeat and self-possessed nor pessimistic student had any choice but to attend.

Accordingly, one of the most important analytical steps was to:

  • Filter out all those who had no sports involvement at all. Comprising as they did half the overall sample, they tended to weaken the force of the analysis by affording no possibility that exercise could obviate depression.
  • Since the other definitions of sports involvement also showed weak relationships on first iterations, the decision was made to alter this predictor variable to account for intensity of involvement (this is the compound variable “FitnessxCollectivoxIndividualPresente”). At this level, the variable was also recoded to remove gym class. However, the remaining (binomial) categories of individual and team sports provided enough variability for subsequent correlation and regression analysis.
self_esteem -0.431790991 0.000000
negative affects 0.513336799 0.000000
PSPP_PSW -0.276495557 0.000000
Fitness Presente Recoded -0.028344138 0.5067188

Finally, the distribution of the raw data on depression scores impelled the researcher to recode the Beck1988 variable, in which just 10.5 percent of the overall sample reported themselves as belonging to the two most intense categories (see Table 6 in the appendices).

On recoding, three of the mediating variables – self-esteem, negative affect and personal self-worth – bore substantive correlations with the recoded depression measure and in the expected directions (see Table 21).

Given the multiplicity of interacting variables, several possibly acting bi-directionally, one goes beyond the fundamental relationships between sports involvement and depression to conduct hierarchical regression that is effectively a test of predicting the criterion variable (depression) from the independent variables: sports involvement, self-perception, self-esteem, satisfaction with life, and negative affect.

Get your
100% original paper
on any topic

done in as little as
3 hours
Learn More

One opts for hierarchical multiple regression in this case because we have posed a theoretical construct about the relationships among the predictor variables. At the same time, it was the researcher’s choice from the very beginning how many predictors to measure with the set of study protocols.

Which variables to input in the analysis run? First, one tests the relationship with the recoded “Fitness Presente” variable, and subsequently adds in succession “satisfaction with life,” “personal self-worth,” self-esteem” and “negative affect”.

Examining the R2 values for the first linear regression run on frequency of indulging in sports activities, one obtains:

Table 2.

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
Practice sport? = yes (Selected) R Square Change F Change df1 df2 Sig. F Change
1 0.002997139 0.000009 -0.0036947 0.6435401 8.983E-06 0.0024254 1 270 0.960758
2 0.451039466 0.2034366 0.1975142 0.5754313 0.2034276 68.697644 1 269 0.000000 **
3 0.467086832 0.2181701 0.2094183 0.5711474 0.0147335 5.0504339 1 268 0.025434 *
4 0.507228405 0.2572807 0.2461538 0.55772 0.0391105 14.059841 1 267 0.000217 **
5 0.604905837 0.3659111 0.3539921 0.51629 0.1086304 45.570407 1 266 0.000000 **
a. Predictors: (Constant), Fitness Presente Recoded
b. Predictors: (Constant), Fitness Presente Recoded, life satisfaction
c. Predictors: (Constant), Fitness Presente Recoded, life satisfaction, PSPP_PSW
d. Predictors: (Constant), Fitness Presente Recoded, life satisfaction, PSPP_PSW, self_esteem
e. Predictors: (Constant), Fitness Presente Recoded, life satisfaction, PSPP_PSW, self_esteem, negative affects
**. Correlation is significant at the 0.01 level (2-tailed).

R Square and R Square Change

Order of Entry

Model 1 : Enter “Fitness Presente Recoded”

We will write a custom
essays
specifically
for you!
Get your first paper with
15% OFF
Learn More

Model 1: R square = 0.000009

The predictor “Type of sports x intensity of involvement” alone accounts for less than 0.001% of the variance in “Depression 88 Recoded”.

R2 = 0.000009

Model 2 : Enter “Life Satisfaction” next

Model 2: R square = 0.2034366

The Increase in R square: 0.2034366- 0.000009 = 0.203428

The predictor “Life Satisfaction” accounts for 20.3% of the variance in “Depression 1988 Recoded” after controlling for sports involvement as defined above.

R2 = 0.000009 + 0.203428 = 0.2034366

Need a
100% original paper
written from scratch

by professional
specifically for you?
308 certified writers online
Learn More

Model Three: Enter “Personal Self-Worth” third

Model 3: R square = 0.218170

The Increase in R square: 0.218170 – 0.203437 = 0.014734

The predictor “Personal Self-Worth” accounts for just 1.3%% of the variance in “Depression 1988 Recoded”, after sports involvement and “Life Satisfaction” were partialed out from “Personal Self-Worth.”

R2 = 0.000009 + 0.203428 + 0.014734 = 0.218170

Model Four: Enter “Self-Esteem” fourth

Model 4: R square = 0.257280655

The Increase in R square: 0.257280655 – 0.218170 = 0.039111

The predictor “Self-Esteem” accounts for 1.0% of the variance in “Depression 1988 Recoded” after sports involvement, “Life Satisfaction” and “Personal Self-Worth” were partialed out from “Self-Esteem”.

R2 = 0.000009 + 0.203428 + 0.014734 + 0.039111 = 0.257280

Model Five: Enter “Negative Affect” fifth

Model 5: R square = 0.365911071

The Increase in R square: 0.365911071 – 0.257280 = 0.108630

The predictor “Negative Affect” accounts for 11% of the variance in “Depression 1988 Recoded”, after “Frequency Weekly”, “Life Satisfaction”, “Personal Self-Worth” and “Self-Esteem” were partialed out from “Negative Affect”.

R2 = 0.000009 + 0.203428 + 0.014734 + 0.039111 + 0.108630 = 0.365911071

About 37% of the variance in the criterion variable “Depression 1988 Recoded” was explained by the first (.0001%), second (20.3%), third (1.5%), fourth (3.9%) and fifth (11%) predictor variables.

The F change for “Life Satisfaction”, Personal Self-worth,” Self-esteem” and “Negative Affect” are substantial and significance values for all four are p<.01. These suggest that the four independent variables are important predictors of “Depression 1988 Recoded.”

Table 3.

ANOVAf,g
Model Sum of Squares df Mean Square F Sig.
1 Regression 0.001004 1 0.001004 0.002425389 0.960758
Residual 111.8188 270 0.414144
Total 111.8199 271
2 Regression 22.74825 2 11.37413 34.3503389 0.000000 **
Residual 89.0716 269 0.331121
Total 111.8199 271
3 Regression 24.39575 3 8.131916 24.92852118 0.000000 **
Residual 87.4241 268 0.326209
Total 111.8199 271
4 Regression 28.76909 4 7.192271 23.12244031 0.000000 **
Residual 83.05077 267 0.311052
Total 111.8199 271
5 Regression 40.91612 5 8.183224 30.69990358 0.000000 **
Residual 70.90373 266 0.266555
Total 111.8199 271
a. Predictors: (Constant), Fitness Presente Recoded
b. Predictors: (Constant), Fitness Presente Recoded, life satisfaction
c. Predictors: (Constant), Fitness Presente Recoded, life satisfaction, PSPP_PSW
d. Predictors: (Constant), Fitness Presente Recoded, life satisfaction, PSPP_PSW, self_esteem
e. Predictors: (Constant), Fitness Presente Recoded, life satisfaction, PSPP_PSW, self_esteem, negative affects
f. Dependent Variable: BDI 1988 recode
g. Selecting only cases for which Practice sport? = yes

Model1: “Fitness Presente Recoded”

Only 0.01% (.0.001004/10 = 0.000100446) of the variance in the criterion variable “Depression 1988 Recoded” can be accounted for by “Fitness Presente Recoded”. The first model, which includes one predictor variable, resulted in an F ratio of 0.002 with a p >.05.

Model 2: “Life Satisfaction”

Fully 2.3% (22.75/10 = 2.3) of the variance in “Depression 1988 Recoded” can be accounted for by both “Fitness Presente Recoded” and “Life Satisfaction.” The second model, which includes two predictors (X1 and X2), resulted in a high F ratio of 34.35 with a p <.001.

Model 3: Personal Self-Worth

About 2.4% (24.4/10 = 2.4) of the variance in “Depression 1988 Recoded” can be accounted for by all three predictors (X1, X2 and X3). The third model, which includes all three predictors, resulted in a high F ratio of 24.92852118 with a p <.001.

Model 4: Self-Esteem

About 2.9 % (28.76/10 = 2.9) of the variance in “Depression 1988 Recoded” can be accounted for by all four predictors (X1, X2, X3 and X4). The fourth model, which includes all four predictors, resulted in a high F ratio of 23.12244031 with a p <.001.

Model 5: Negative Affect

About 4.1% (40.9/10 = 4.1) of the variance in “Depression 1988 Recoded” can be accounted for by all five predictors (X1, X2, X3, X4 and X5). The fifth model, which includes all five predictors, resulted in a high F ratio of 30.7 with p <.001.

This study has demonstrated an internally valid, comprehensive and interactive model regarding the therapeutic effects of exercise and sporting activities on depression and self-esteem. That it is arguably a cross-section analysis of one culture at a given moment in time should encourage other researchers to extend the program as a longitudinal study or to replicate the method across other cultures and national milieus.

Given that these findings are consistent with prior work on clinical cases of frank.

Replace Table 21 In Appendix B.

BIVARIATE CORRELATIONS WITH RECODED BDI 1988 CUT-OFF SCORES
Pearson Correlation Sig. (2-tailed)
self_esteem -0.431790991 0.000000
negative affects 0.513336799 0.000000
PSPP_PSW -0.276495557 0.000000
Fitness Presente Recoded -0.028344138 0.506718841
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

Cite this paper

Select style

Reference

StudyCorgi. (2021, October 25). Protective Factors Against Youthful Depression. Retrieved from https://studycorgi.com/protective-factors-against-youthful-depression/

Reference

StudyCorgi. (2021, October 25). Protective Factors Against Youthful Depression. https://studycorgi.com/protective-factors-against-youthful-depression/

Work Cited

"Protective Factors Against Youthful Depression." StudyCorgi, 25 Oct. 2021, studycorgi.com/protective-factors-against-youthful-depression/.

1. StudyCorgi. "Protective Factors Against Youthful Depression." October 25, 2021. https://studycorgi.com/protective-factors-against-youthful-depression/.


Bibliography


StudyCorgi. "Protective Factors Against Youthful Depression." October 25, 2021. https://studycorgi.com/protective-factors-against-youthful-depression/.

References

StudyCorgi. 2021. "Protective Factors Against Youthful Depression." October 25, 2021. https://studycorgi.com/protective-factors-against-youthful-depression/.

References

StudyCorgi. (2021) 'Protective Factors Against Youthful Depression'. 25 October.

This paper was written and submitted to our database by a student to assist your with your own studies. You are free to use it to write your own assignment, however you must reference it properly.

If you are the original creator of this paper and no longer wish to have it published on StudyCorgi, request the removal.