INTRODUCTION

  Every single year, millions of students are enrolled in tertiary education. In the Philippines alone, there were approximately 3.4 million students in a pre-baccalaureate to doctoral program in the Academic Year 2019-2020 [1]. Many of these college students live away from home, and because of this, it begins their first step to completely independent living [2]. However, being away from home may give rise to new challenges as they are away from their loved ones and increased chances of isolation. Therefore, the new college environment may influence personal adaptability and attachment to others.

  This paper intends to investigate this recurring phenomenon. Specifically, this study will seek possible linear correlations between Emotional Adaptability and Attachment Anxiety, which are two variables that were part of a larger survey and study by Liu et al. [3]. The study by Liu et al. did not provide definitions for these variables. This paper therefore defines Emotional Adaptability as the mechanism that minimizes negative emotions, such as anxiety, by regulating one’s overall emotions when faced with obstacles or uncertainty. On the other hand, Attachment Anxiety is defined as the necessity of another person’s comfort and the fear of being neglected by these figures, which are usually romantic partners or other attachment figures as seen in the study of Eastwick (2008) [4]. Its concept revolves around the Attachment Theory, and through this framework, it has been beneficial in understanding different attachment styles. In the study of Levy et al. (2011), it is discussed that some have a secure and dismissive attachment, which pertains to how comfortable or uncomfortable they may feel when managing their relationships with attachment figures [5].

RATIONALE

  Specifically, this project will address a gap in the study conducted by Luo et al. [6], which used data gathered by Liu et al. In the study of the aforementioned researchers, it was noted that Emotional Adaptability was a “key factor” that influenced the other variables in their study, namely those related to nomophobia and mobile phone addiction [5]. However, their study did not analyze the possible relationship between adaptability and adult attachment. Therefore, Attachment Anxiety, one of two variables in adult attachment, was chosen for this project. Additionally, Emotional Adaptability was chosen as this project’s independent variable since it correlated with all other variables in the study of Luo et al. With that said, this study hopes to investigate the possibility of a relationship between Emotional Adaptability and Attachment Anxiety.

METHODOLOGY

  The dataset and the initial research were taken from a survey conducted by Liu et al. (2022). The dataset can be found in the researchers’ repository, linked here [7], or in their research article uploaded to Elsevier’s Data in Brief. In this data repository, 678 volunteers of varying year levels (ranging from freshmen to post-baccalaureates) from Tianjin Normal University were recruited to complete a 5-8 minute survey through both online and pencil-and-paper questionnaires. A total of 673 responses were collected in the analysis after five survey respondents were omitted due to several missing items. The questionnaire was created with Likert-type questions, which corresponded to various variables that related to mobile phone use, adaptability, and adult attachment.

  In this R-Markdown project, the researchers investigated the strength of correlation and whether or not a relationship existed between Emotional Adaptability (independent variable) and Attachment Anxiety (dependent variable). A linear regression test was used to determine if a relationship existed between the variables, and a Pearson’s correlation test was used to determine the strength of correlation. After encoding the necessary data in a spreadsheet, the researchers imported it into R-Studio to run a simple linear regression analysis. The following code was used:

library("ggplot2")
model <- lm(att ~ emo, data = dataset)
summary(model)
ggplot(dataset, aes(emo, att)) + geom_point() + stat_smooth(method = lm) 
`geom_smooth()` using formula 'y ~ x’

  The first line of code loads the data visualization package for RStudio. The second line creates the model for simple linear regression. The command ‘lm’ is responsible for simple and multiple linear regression. Furthermore, the last line creates the linear regression graph with a regression line. \[\hat{y} = \alpha + \beta*x_{i} + random \hspace{0.09cm} error_{i}\]

Hypotheses:

In order to test for the relationship of the two variables, we test the following hypotheses with a confidence interval of 95% (𝜶 = 0.05) and let \(\beta_{1}\) be the regression coefficient:

Null hypothesis: \[H_{0}: \beta_{1} = 0\] Alternative hypothesis: \[H_{a}: \beta_{1} \neq 0\]

Reject \(H_{0}\) if: \(P-value\) < 0.05 or \(f_{0} > f_{\alpha, 1, n-2}\)

RESULTS AND DISCUSSION

Simple linear regression:

\[\hat{y}=\alpha + \beta*x_{i} + random\hspace{0.09cm}error\]

Residuals:

Min 1Q Median 3Q Max
-66.496 -9.583 1.440 10.434 49.400

Coefficients:

Estimate Std. Error t value Pr(>|t|)
(Intercept) 98.4734 2.4305 40.52 <2e-16 ***
emo -1.9942 0.1478 -13.49 <2e-16 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ’ ’ 1
Residual standard error: 15.4 on 671 degrees of freedom Multiple R-squared: 0.2135 Adjusted R-squared: 0.2123
\(F-statistic\): 182.1 on 1 and 671 DF \(p-value\): < 2.2e-16
\(F = MS_{Treatment} / MS_{Error}\) = 43205.8071123757 =182.126311947 / 237.2299
\(F_{crit}\) = 182.1 on 1 and 671 DF
Regression equation:
Attachment Anxiety = 98.47 - 1.994 Emotional Adaptability
\(\hat{y}\) = 98.47 — 1.994x
F and P-values
\(F\) = 182.1
\(F_{0.05, 1, 671}\) = 3.85
3.85 < \(F_{crit}\) < 3.89
\(F\) > \(F_{crit}\)
\(P_{(f)}\) = 6.78926092488422E-37
\(P\) < 0.05

Reject \(H_{0}\), regression is significant

  R Studio reports that there is a very low P-value (p<0.05), which means that the regression is significant and the null hypothesis can be rejected. This statistic would imply that there is, in fact, a correlation between Emotional Adaptability and Attachment Anxiety.

  However, the low R-squared shows that the model does not explain the variation in the data. The model can therefore not be used to predict any values with confidence. Still, the very low P-value is indicative of correlation, which means that there is a relationship between the two variables under study. To test for correlation, Pearson’s correlation will be utilized to determine the strength and direction of the statistical relationship between emotional adaptability and attachment anxiety.

The following code was used:

corellate <- cor.test(dataset\$att, dataset$emo, method = "pearson") 
corellate

The first line of code runs the correlation test to determine the Pearson correlation coefficient. The second line shows the data.

Hypotheses: In order to test for the correlation of the two variables, we test the following hypotheses with a value between -1 and 1, with negative values in the negative direction and positive values in the positive direction, and where strength is rated as follows:

Range Strength
0 None
0 < \(|\rho|\) < 0.3 Weak
0.3 < \(|\rho|\) < 0.5 Moderate
0.5 < \(|\rho|\) Strong

Let \(\rho\) be the correlation coefficient value: Null hypothesis: \[H_{0}: \rho = 0\] Alternative hypothesis: \[H_{0}: \rho \neq 0\] Reject \(H_{0}\) if: \[|t_{0}| > t_{\alpha /2,n - 2}\] The first line of code runs the correlation test to determine the Pearson correlation coefficient. The second line shows the data.

Pearson's product-moment correlation

data:  dataset$att and dataset$emo
t = -13.495, df = 671, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.5194762 -0.4004477
sample estimates:
       cor 
-0.4620401

  RStudio gives us a t-value of -13.495. Using the t-table, the critical value of t is found to be between 1.962 and 1.984. Comparing this to the given criteria shows:

\[|t_{0}| = |-13.495| > t_{0.05 /2, \hspace{0.09cm}673 - 2}\]

  This allows for the null hypothesis to be rejected, and that the correlation coefficient is \(\rho \neq 0\). The calculated value for the correlation coefficient \(\rho\) is -0.46. This value lies between 0.3 and 0.5, and is negative. Therefore, there is a moderate negative correlation between emotional adaptability and attachment anxiety.

CONCLUSION

  The study held by Luo et al. discussed the relationship between Emotional Adaptability with variables such as nomophobia and mobile addiction. However, they were not able to look into the relationship between Emotional Adaptability and Attachment Anxiety, a variable under the category of adult attachment. With that said, the researchers of this project specifically focused on such variables from the data set.

  The researchers utilized a simple linear regression to determine if there is a relationship between the two variables. A correlation test was then used to determine the strength of the correlation. The findings of this paper allowed the researchers to conclude that there was sufficient evidence to reject the null hypothesis. Rejecting this meant that a relationship was found between the independent variable, Emotional Adaptability, and the dependent variable, Attachment Anxiety. However, the correlation test determined that there was a moderate negative correlation with a Pearson’s correlation coefficient of -0.46. This can be attributed to the large sample size, which may be affecting the correlation. It shows that, while there is a negative correlation between Emotional Adaptability and Attachment Anxiety, other factors might have a stronger influence. Given the existence of a relationship between the two, it would be prudent to consider one’s emotional adaptability when facing the dilemma of Attachment Anxiety. However, one must also consider other, possibly more pertinent factors.

  Therefore, universities and their student-service departments can consider this information as an additional factor, particularly when addressing issues faced by students. Perhaps this project can also be a wake-up call for guardians, parents, and educational institutions to focus and build upon their child’s emotional capabilities at a young age for them to be better prepared for possible times of separation. Furthermore, if this phenomenon was found in college students, then there is a high probability that it also can be found in secondary students and perhaps even established professionals. This ever-present phenomenon of Attachment Anxiety could possibly be aided by further emotional development amongst individuals. Therefore, the link found in this project can be further explored by future researchers who may be interested in finding ways to mitigate Attachment Anxiety in individuals.

REFERENCES

[1] Commission on Higher Education, “Higher Education Enrollment by Discipline Group: AY 2010-11 to 2019-20,” CHED.gov.ph, 08-Oct-2020. [Online]. Available: https://ched.gov.ph/wp-content/uploads/Higher-Education-Enrollment-by-Discipline-Group-AY-2019-20.pdf. [Accessed: 23-Jul-2022].

[2] C. H. Mulder and W. A. Clark, “Leaving home for college and gaining independence,” Environment and Planning A: Economy and Space, vol. 34, no. 6, pp. 981–999, Jun. 2002.

[3] X. Liu, T. Liu, X. Liu, X. Lu, and Y. Li, “Data on mobile phone use, adaptability and adult attachment among college students in China,” Data in Brief, vol. 43, pp. 1–8, Jun. 2022.

[4] Eastwick, Paul W.; Finkel, Eli J. (2008). The attachment system in fledgling relationships: An activating role for attachment anxiety.. Journal of Personality and Social Psychology, 95(3), 628–647. doi:10.1037/0022-3514.95.3.628

[5] K. N. Levy, W. D. Ellison, L. N. Scott, and S. L. Bernecker, “Attachment style,” Journal of Clinical Psychology, vol. 67, no. 2, pp. 193–203, Jun. 2010.

[6] J. Luo, S. Ren, Y. Li, and T. Liu, “The effect of college students’ adaptability on Nomophobia: Based on Lasso regression,” Frontiers in Psychiatry, vol. 12, pp. 1-9, Oct. 2021.

[7] L. Tour, “Liutour/mobile-phone-use-correlates-to-adaptability-and-attachment: Dib1.0.0,” Zenodo, 18-May-2022. [Online]. Available: https://zenodo.org/record/6560781#.Yqbnoy21F0s. [Accessed: 20-Jul-2022].