How Does Virtual World Influence Our Mental Health?

Abstract
I design this online depression survey to study the relationship between indulgence in Internet and depression. The survey form contains 10 questions traditionally used for scaling of depression, as well as 10 questions judging the extent of indulgence in internet. The result suggested that cyberholic does have a bigger chance to have depression. It cannot be determined from this survey whether depression is the result of cyberholic or the opposite, but the correlation between the two is worthy of advanced research.
Keyword: depression, cyber depression, zung’s self-rating depression scale (SDS), paired t test, linear regression

Introduction:
Depression is a mental status in which a person experiences extreme sadness and reduction in the level of functioning, which involves the body, mood, and thoughts. It affects the way a person eats and sleeps, the way one feels about oneself, and the way one thinks about things. A depressive disorder is not the same as a passing blue mood. It is not a sign of personal weakness or a condition that can be willed or wished away. People with a depressive illness cannot merely “pull themselves together” and get better. Without treatment, symptoms can last for weeks, months, or years. In 1990, depression is recognized as the “4th leading cause of disease” worldwide by WHO.
The most common type of depression (major depression) is manifested by a combination of symptoms (see symptom list) that interfere with the ability to work, study, sleep, eat, and enjoy once pleasurable activities.
Depression symptom list:
Ã?·Persistent sad, anxious, or “empty” mood
�·Feelings of hopelessness, pessimism
�·Feelings of guilt, worthlessness, helplessness
�·Loss of interest or pleasure in hobbies and activities that were once enjoyed
Ã?·Decreased energy, fatigue, being “slowed down”
�·Difficulty concentrating, remembering, making decisions
�·Insomnia, early-morning awakening, or oversleeping
�·Appetite and/or weight loss or overeating and weight gain
�·Thoughts of death or suicide; suicide attempts
�·Persistent physical symptoms that do not respond to treatment, such as headaches, digestive disorders, and chronic pain
What I define as cyber depression here has very similar symptoms as the above list. The difference lays in the fact that Internet has being used as an escape from the problem and stress in the real world. It is more easily for cyberholics to ignore their own depression, as they can gain temporary comfort from virtual world. Such indulgence will gradually deprive people of normal functioning in real life and culture mental dependence, finally lead to aggravation of depressive disorder.
Traditionally, for screening of depression, we use Zung’s self-rating depression scale, or its derivatives, such as Wakesfield questionnaire and Hamilton depression scale. But by the time these scales were made (Zung at 1965,Wakesfield at 1971), Internet didn’t have such an important role in people’s life(TCP/IP was developed in 1973 and 10 years after that Internet was popularized in America.),so it was never considered as a source of depression and put into analysis.
My questionnaire is designed based on Zung’s SDS and its derivatives, considering clinic symptoms of depression as well as an understanding of cyberholics’ mental world and life style.
Method
My questionnaire contains 20 questions, 1-5 Likert scale is employed to evaluate the strength of agreement to the statement of question. 10 of them are depression-scaling questions, covering all the general depression symptoms (see the symptom list in introductory part). The other 10 questions are design to judge how heavily testees are dependent on Internet and their feeling about the real life. Questions are mixed together, put in either negative or positive way, and written in the first person, as to minimize possible measurement problems.
*Q1/4/6/9/10/13/15/16/18/20 are depression-scaling questions.
*Q2/3/5/7/8/11/12/14/17/19 are cyberholic-scaling questions.
(1) I can remember things I need to do in my real life.always 1 2 3 4 5 never
(2) I can stay on net for more then 5 hours without feeling tired.never 1 2 3 4 5 always
(3) I feel lonely when I am in crowd.never 1 2 3 4 5 always
(4) I have regular work,rest and eating time.always 1 2 3 4 5 never
(5) I act in a very different way in virtual world from that in real world.never 1 2 3 4 5 always
(6) I have plans about my future. always 1 2 3 4 5 never
(7) I think my netfriends understand me much better than people in the real world.not at all 1 2 3 4 5 very true
(8) I feel more frustrated when I have no access to net than I fail my work/exam.not at all 1 2 3 4 5 very true
(9) I have trouble with constipation.never 1 2 3 4 5 always
(10) I can hardly concentrate on my work or study.always 1 2 3 4 5 never
(11) I still care about things happened around.very much 1 2 3 4 5 not at all
(12) I find it hard to communicate with people in the real world.never 1 2 3 4 5 always
(13) I have hobbies in the real world that I still enjoy working on.a lot 1 2 3 4 5 not at all
(14) I can control my time spent online.always 1 2 3 4 5 never
(15) I feel that real life is dull and meaningless.never 1 2 3 4 5 always
(16) I have trouble sleeping at night.never 1 2 3 4 5 always
(17) I have inferiority complex towards my own body. not at all 1 2 3 4 5 very much
(18) I want to keep my mind empty and think of nothing.never 1 2 3 4 5 always
(19) I have true friend(s) in real world on whom I can trust.a lot 1 2 3 4 5 not at all
(20) I feel that others will be better off without me.never 1 2 3 4 5 always

This survey form is created online at www.surveyanywhere.com and stored at the following URL:
http://www.surveyanywhere.com/cgi-bin/sa.cgi?id=162311934269654185
According to simple random sampling technique, I pasted this link to several famous forums, including Yahoo messenger board, Blogger forum, Sina and MSN forum, in order to widen the accessible population, randomize and maximize the sample size.
It is a voluntary response survey. I ended up with 81 responses in 3 days. After removing incomplete and repeated data, finally I got 73 fully answered questionnaires.
The low response rate (comparing to the high click rate of my poster) suggested that there is a good chance for nonresponse bias in this survey, which means that the response may not be representative of the whole population online. ButBecause of the limit on time, energy and expense, as well as the nature of this topic (It is not something people care much so it is not very attractive.), I cannot further modify the sampling method or increase the sample size.

Result
Survey data
Based on the collected data, I calculate the total score, depression scaling score and cyberholic-scaling score respectively, and transform them each into 4 categorical scores.
For total score: 1(k<=40);2(40<=50);3(50<=60);4(k>60).
For depression scaling score and cyberholic-scaling score: 1(k<=20); 2(20<=25); 3(25<=30); 4(k>30).
Classes are divided according to four clinical depression severity groups classified on the basis of the global rating, which Zung’s SDS can differentiate at 0.05 level.
Sample size: n=73, including 47 female and 26 male testees. It is understandable as women are always more interested in psychometric test than men. The female/male ratio in clinical depression cases also has the value near 2:1,which indicates that this is pretty normal. It can be rooted in the fact that women tends to care more about their mental status.

1) Raw data
Row Labels q1 q2 q3 q4 q5 q6 q7 q8 q9 q10 q11 q12 q13 q14 ����
1 C1 1 5 4 3 5 3 3 1 2 2 1 4 2 5 3 �����
2 C2 1 5 3 3 5 1 1 3 5 1 5 3 3 5 1 �����
��������������������������������������..
���������������������������������������
72 C72 1 4 2 2 1 1 3 2 1 4 1 1 1 3 1 �����
73 C73 1 4 2 2 1 2 2 3 1 2 1 1 1 2 1 �����

2) Scores
Sum Dep Cyb
c1 5525 30
c2 70 34 36
c3 62 31 31
c4 49 27 22
c5 22 12 10
����������.
3) Categorical score
SUM DEP CYB
C1 3 3 3
C2 4 44
C3 4 44
C4 2 32
C5 1 11
C6 1 11
C7 2 22

Descriptive analysis
Based on a WHO report, there are around 340 million people suffering from depression in the world, compared with the total population of 6 billion, the incidence rate is between 4.6-8.8%. There is also statistical data in 1984 showing that the incidence rate of depression in America is 10.6%.
From my study, the incidence rate of cyber depression is about 19.71% (depression judgments are made based on depression categorical scores. Dep categorical score equals 4 are taken as depression case. The raw ratio is 14/73. ) This is much higher than general depression incidence rate. This is confirmed by a 2-p test.
Because of the digit limit in trial and event input, I use the ratio 34000000/600000000 instead of 3400000000/60000000000. The influence should be very small when n is so large.
Ho: Cyber depression and general depression have the same incidence rate.
Ha: Cyber depression and general depression have different incidence rate.
Test and CI for Two Proportions

Sample X N Sample p
1 3400000 60000000 0.056667
2 14 73 0.191781

Difference = p (1) – p (2)
Estimate for difference: -0.135114
95% CI for difference: (-0.225428, -0.0448004)
Test for difference = 0 (vs not = 0): Z = -2.93 P-Value = 0.003
With Z=-2.93 and p value=0.003<0.05, reject Ho, supporting that the 2 incidence rate are significant different.
This conclusion indicates that Internet does have some influence on depression incidence.

Variable N N* Mean StDev Median IQR Skewness
sum 73 0 49.00 12.25 49.00 15.00 0.07
dep 73 0 24.151 6.297 23.000 9.000 0.14
cyb 73 0 24.877 6.394 24.000 8.000 0.06
From the histograms and box plot on depression and cyberholic scaling scores as well as sum scores, it can be concluded that they are all unimodal and have approximately normal distribution, with the depression score distribution slightly skewed to the left. That makes sense because it suggests that the mental status of major population is between depression and absolutely healthy level. As people generally all have depressed period but usually not as severe as depression. There is only one point in the upper mild outlier of sum score distribution. I didn’t remove it, as it is a true case, though it seems somewhat extreme in my study with this small size sample, it could be normal if larger sample size is available. So I keep it as to reflect the truth. It can also be seen from the box plot that depression score and cyberholic score have similar distribution,which suggests that there may be some linear relationship between the two.

p value for the three normality test are all >0.05, which confirmed their normal distribution.

Inferential Analysis
As indicated above, there may be linear relationship existing between depression score and cyberholic score distribution.
Linear regression analysis is done to test this.

Scatter plot also gave the impression of linear relationship. I use cyberholic score as predictor and depression score as response, as the initial question is “Is indulgence in Internet (virtual world) having influence on depression?”.

Regression Analysis: C76 versus C77

The regression equation is
Depression score = 3.20 + 0.842 cyberholic score

Predictor Coef SE Coef T P
Depression score 3.199 1.556 2.06 0.043
Cyberholic score 0.84220 0.06059 13.90 0.000

S = 3.28723 R-Sq = 73.1% R-Sq(adj) = 72.8%

Analysis of Variance

Source DF SS MS F P
Regression 1 2088.1 2088.1 193.24 0.000
Residual Error 71 767.2 10.8
Total 72 2855.3

Unusual Observations

Obs cyb dep Fit SE Fit Residual St Resid
5 10.0 12.000 11.621 0.980 0.379 0.12 X
8 10.0 10.000 11.621 0.980 -1.621 -0.52 X
17 41.0 39.000 37.730 1.050 1.270 0.41 X
30 26.0 32.000 25.097 0.391 6.903 2.12R
33 29.0 21.000 27.623 0.459 -6.623 -2.03R
34 29.0 21.000 27.623 0.459 -6.623 -2.03R
46 29.0 20.000 27.623 0.459 -7.623 -2.34R

R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large influence.

Normplot of Residuals for C76

Residuals vs Fits for C76

Linear regression test confirmed that there is strong linear relationship existing between depression score and cyberholic score.
Evidences:
1)R square is 73.1%, r=R>0.8 means that this is a strong linear correlation between the two;
2)With F=193.24 and p value <0.001<0.05 from linear regression AOV, Ho of ?=0 is rejected, confirming the existence of significant linear relationship;
3)P value from residual normality test is 0.840>0.05, confirming the satisfaction of normality assumption;
4)The evenly distribution of residuals on both sides of x axis on residuals vs. fit plot proved that the linear relationship is capable of capturing all of the x-y relationship.

Discussion:
According to my study, there is a positive correlation between cyberholic (indulgence in virtual world) and depression level. People spending too much time on Internet tend to be more depressed in real life. It is not clear whether cyberholic is the cause of depression or depression is the cause for cyberholic. It could be bidirectional too, as people who are depressed in real life tend to seek for vent in virtual world, and gradually can’t live without it.
And that forms a vicious circle.

Limitations:
The study has a low response rate, which could be the source of selection bias, as it is based on volunteered testees, it could be that only those who are interested in this topic been investigated. I got some returned forms with missing values. But for the study I only used the complete data.

Recommendation:
Enlarging the sample size may help to elevate R-value of linear regression. Also if there is more time, it is worth to try stratified random sampling, which can better randomize the data and minimize bias.

Leave a Reply

Your email address will not be published. Required fields are marked *


8 + three =