Social Media and Depression
Introduction
Depression is one of the most prevalent psychiatric disorders in the developed nations and the developing nations. Research shows that a major depression affects 16
percent of the general population, with women showing higher prevalence of depression than men (Sagud et al., 2002). Sagud et al. (2002) shows that females have a
higher prevalence of incidence, as well as the morbidity risk of depressive disorders, with higher rates of depression seen at mid-puberty.
Recent research on depression has focused on the relationship between social media and depression. It has found a positive correlation between the use of social media
sites such as Facebook, Twitter, and other social media sites and increased level of depression among young adults (O’Keeffe and Clarke-Pearson, 2011). However, it has
failed to explain how this relation varies between the genders. Pantic et al. (2012) did a study examining the relationship between social networking and depression
in adolescent. They found a positive relation between online social networking and depression, but it failed to explain how the relationship varies between the two
genders. Kim et al. (2006) also showed that internet addiction was associated with increased levels of depression and suicidal ideation, but it did not show how the
depression varies between males and females.
Therefore, a literature gap exists of how social media relationships with depression vary between men and women. The gender differences in depressive disorder provide
a clear impression that it also affects the social media and depression relationship. However, this can be attributed to Silverstein et al. (2013) study. They
concluded that gender differences in the depressive prevalence result of somatic symptoms rather than the number of symptoms and the difference was larger for somatic
rather than atypical depression. As such, this research paper focuses on explaining how the relationship between social media and depression vary between men and
women.
Methods
Participants
The population description we chose for our study will consist of participants that are enrolled at Cal State Dominguez Hills. There will be a recruitment of a total
of 100 students ranging from ages 18- 35 years old. We will recruit these students from our former classes. We will ask our professors for permission to use student’s
emails in order to send them the direct link to our questionnaires for our study. For our sampling method we will use two types of sampling, Convenient and
Stratification. Convenient Sampling is where we will be using students from Cal State Dominguez Hills by means of proximity to our research study. We intend to recruit
students from classes we are enrolled in, and therefore won’t need to look for outside sources. In doing so, we hope to get a total of 100 participants. Stratification
Sampling will be used when we reach the amount of participants which are 50 males and 50 females; we won’t be able to take any more questionnaires once we have reached
our capacity. The sample characteristics in our study are making sure our participants fit our required demographics such as age range and gender. Participants also
need to be active in social media, specifically Facebook. There will be no compensation or incentive for participating in our study.
Measures
The variables we will be measuring for our study are depression and the use of social media: specifically Facebook. To measure depression we will use the Goldberg
Depression Questionnaire. This questionnaire consists of a total of 18 questions developed by Dr. Ivan K. Goldberg. It is a self-test that our participants will take
in order to see signs and symptoms that are linked to depression. In order to score the Goldberg Depression Questionnaire, participants will have to answer each one of
the questions. We will conclude how severe the depression is by looking at the scoring ranges: the greater the number, the more critical the depression.
To measure the use of social media, specifically Facebook, we will use the Facebook Intensity Quiz developed by N.B. Ellison, C. Steinfield and C. Lampe. The
Facebook Intensity Quiz will measure the participants frequents use of Facebook as well as whether their use of becoming an addiction. Participants will answer a 14-
item questionnaire by responding to categories that range from 1= strongly disagree to 5= strongly agree. The Facebook Intensity Scale will be scored by calculating
the main of the items on the scale.
Procedure
Our group will start by asking the professors from our former classes for permission to use students’ emails to send them the direct link to our questionnaire.
After our permission approval we will send a larger number than what we need in order to ensure we will receive our intended goal of 100 participants. Prior to
participating in our study, participants must agree to our consent form which will describe our study in detail. Once they have accepted the consent form it will
assure them of its confidentiality. Participants will also be notified that they can stop taking the questionnaires at any given time. The participants will answer the
demographic questions followed by the Depression and Facebook questionnaire. Once the questionnaires are completed the results will only be available for viewing by
our group.
SPSS RESULTS
Univariate Analysis of Variance
Notes
Output Created 25-NOV-2014 15:15:29
Comments
Input Data /Users/genesisrios/Downloads/Data_All_141125/survey data recoded.sav
Active Dataset DataSet1
Filter
Weight
Split File
N of Rows in Working Data File 95
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used Statistics are based on all cases with valid data for all variables in the model.
Syntax UNIANOVA depression_total BY gender FBmedian
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/EMMEANS=TABLES(gender*FBmedian)
/PRINT=OPOWER ETASQ HOMOGENEITY DESCRIPTIVE
/CRITERIA=ALPHA(.05)
/DESIGN=gender FBmedian gender*FBmedian.
Resources Processor Time 00:00:00.02
Elapsed Time 00:00:00.00
Between-Subjects Factors
Value Label N
What is your gender? 0 Female 29
1 Male 24
FBmedian .00 29
1.00 24
Descriptive Statistics
Dependent Variable: depression_total
What is your gender? FBmedian Mean Std. Deviation N
Female .00 28.3529 8.51426 17
1.00 23.6667 4.51932 12
Total 26.4138 7.41387 29
Male .00 39.0833 14.78610 12
1.00 33.7500 10.70365 12
Total 36.4167 12.91415 24
Total .00 32.7931 12.49966 29
1.00 28.7083 9.54385 24
Total 30.9434 11.34158 53
Levene’s Test of Equality of Error Variancesa
Dependent Variable: depression_total
F df1 df2 Sig.
3.401 3 49 .025
Tests the null hypothesis that the error variance of the dependent variable is equal across groups.a
a. Design: Intercept + gender + FBmedian + gender * FBmedian
Tests of Between-Subjects Effects
Dependent Variable: depression_total
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter
Corrected Model 1639.115a 3 546.372 5.302 .003 .245 15.905
Intercept 50476.261 1 50476.261 489.797 .000 .909 489.797
gender 1402.779 1 1402.779 13.612 .001 .217 13.612
FBmedian 325.081 1 325.081 3.154 .082 .060 3.154
gender * FBmedian 1.356 1 1.356 .013 .909 .000 .013
Error 5049.716 49 103.055
Total 57436.000 53
Corrected Total 6688.830 52
Tests of Between-Subjects Effects
Dependent Variable: depression_total
Source Observed Powerb
Corrected Model .911
Intercept 1.000
gender .951
FBmedian .414
gender * FBmedian .051
Error
Total
Corrected Total
a. R Squared = .245 (Adjusted R Squared = .199)
b. Computed using alpha =
Estimated Marginal Means
What is your gender? * FBmedian
Dependent Variable: depression_total
What is your gender? FBmedian Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
Female .00 28.353 2.462 23.405 33.301
1.00 23.667 2.931 17.778 29.556
Male .00 39.083 2.931 33.194 44.972
1.00 33.750 2.931 27.861 39.639
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