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Online Game Addiction and the 
Level of Depression Among 
Adolescents in Manila, Philippines 
 
Ryan V. Labana1*, Jehan L. 
Hadjisaid2, Adrian R. Imperial2, 
Kyeth Elmerson Jumawid2, Marc 
Jayson M. Lupague2, Daniel C. 
Malicdem2 
 
 
1Department of Biology, College of 
Science, Polytechnic University of the 
Philippines, Manila, Philippines;  
2Senior High School, Polytechnic 
University of the Philippines, Manila, 
Philippines 
 
*Corresponding Author 

 
Vol. 9, No. 1 (2020)   |   ISSN 2166-7403 (online)  
DOI 10.5195/cajgh.2020.369 |   http://cajgh.pitt.edu 



 
 
LABANA 

 
This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369 | http://cajgh.pitt.edu 

 
 

Abstract 

Introduction: World Health Organization recognizes online game addiction as a mental health condition. The rise of excessive 
online gaming is emerging in the Philippines, with 29.9 million gamers recorded in the country. The incidence of depression is also 
increasing in the country. The current correlational analysis evaluated the association between online game addiction and 
depression in Filipino adolescents. 
Methods: A paper-and-pencil self-administered questionnaire assessing depression and online game addiction was distributed from 
August to November, 2018. The questionnaire included socio-demographic profiles of the respondents, and the 14-item Video 
Game Addiction Test (VAT) (Cronbach's α=0.91) and the Patient Health Questionnaire-9 (Cronbach's α=0.88) to determine levels 
of online game addiction and depression, respectively. Multiple regression analyses were used to test the association between 
depression and online game addiction. 
Results: Three hundred adolescents (59% males, 41% females) participated in the study. Fifty-three out of 300 respondents (12.0% 
males, 5.7% females) had high level of online game addiction as reflected in their high VAT scores. In this study, 37 respondents 
(6.7% males, 5.7% females) had moderately severe depression and 6 (2.0%) females had severe depression. Online game addiction 
was positively correlated with depression in this study (r=0.31; p<0.001). When multiple regression analysis was computed, 
depression was found to be a predictor of online game addiction (Coefficient=0.0121; 95% CI-8.1924 - 0.0242; p=0.05).  
Conclusion: Depression, as associated with online game addiction, is a serious threat that needs to be addressed. High level of 
online game addiction, as positively correlated to the rate of depression among adolescents in Manila, could potentially be attributed 
to the booming internet industry and lack of suffiicent mental health interventions in the country. Recommended interventions 
include strengthening depression management among adolescents and improving mental health services for this vulnerable 
population groups in schools and within the communities.  

Keywords: Mental health; Public health; Addiction; Video games; Depression; Neuroscience  

Online Game Addiction and the Level 
of Depression Among Adolescents in 
Manila, Philippines 
 
Ryan V. Labana1*, Jehan L. 
Hadjisaid2, Adrian R. Imperial2, 
Kyeth Elmerson Jumawid2, Marc 
Jayson M. Lupague2, Daniel C. 
Malicdem2 
 
 
1Department of Biology, College of Science, 
Polytechnic University of the Philippines, 
Manila, Philippines;  
2Senior High School, Polytechnic University 
of the Philippines, Manila, Philippines 

Research 

Based on the report of the European Mobile 
Game Market in 2016, there were more than 2.5 billion 
video gamers across the globe.1 Several studies have 
found that the majority of these players were adolescents 
aged 12-17 years,2-5 with more usage among males than 
females.6 In 2017, newzoo.com reported that the active 
gamers in the Philippines were 52% males and 48% 
females.7 In the US, 60% of the video gamers were males 
and 40% are females.6 Studies have shown that there are 
similarities between males and females in regard to 
choice of games, behavior toward video gaming, and 
motives for engaging in this activity.8 Some of the 
reported reasons to engage in video games include having 
fun and for recreation,9-10 to de-stress,11-12 and to avoid 
real life issues.13-14 The prevalence of video gaming 



 
 
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This journal is published by the University Library System of the University of Pittsburgh as part  
of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 
Central Asian Journal of Global Health 

Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369 | http://cajgh.pitt.edu 

 
 

addiction varies from region to region based on the socio-
cultural context and the criteria used for the assessment.15 

However, it is well established that video gaming is 
addictive,16-18 and there is clinical evidence for the 
symptoms of biopsychosocial problems among video 
game addicts.19 It is a serious threat to the mental and 
psychosocial aspects of an individual, as it lead to stress, 
loss of control, aggression, anxiety, and mood 
modification.20-21  

In the Philippines, online gaming is an emerging 
industry. The country ranks 29th in game revenues across 
the globe. In 2017, there were more than 29.9 million 
gamers recorded in the country. Most of the gamers were 
21-35 years of age, followed by the adolescents 10-20 
years of age.7 Adolescents accounted for 30.5% of the 
total population in the country.22 In general, this age 
group is already facing mental health issues, such as 
anxiety, mood disorders, and depression. This concern 
gets more alarming as rates of suicide among high school 
and college students are growing worldwide.23 

World Health Organization lists video game 
addiction as a mental health problem.24 Psychiatric 
research reported evidence on the links between 
depression and video game addiction. Among the 
findings are MRI scans of video game addicts showing 
disruption of some brain parts and overriding of the 
'emotional' part with the 'executive' part.25 A study in 
China has also reported that gamers are at increased risk 
of being depressed in comparison to those who did not 
play video games.26 In the field of neuroscience, 
depression caused by online game addiction is explained 
as a reduction of synaptic activities due to permanent 
changes in the dopaminergic pathways. This means that 
long exposure to online gaming causes changes in a 
person’s sense of natural rewards, often making activities 
less pleasurable. This neuroadaptation is also associated 
with chronic depression.27 

There is a paucity of studies on video game 
addiction in the Philippines, making its implications not 
well understood. There are reports of the impact of video 

game addiction on the academic performance of the 
gamers,28-30 but no study has been found associating 
video game addiction and depression in the Philippine 
setting. Based on the 2004 report from the Department of 
Health in the Philippines, over 4.5 million cases of 
depression were reported in the country. Recently, World 
Health Organization reported that 11.6% of the 8,761 
surveyed young Filipinos considered committing suicide; 
16.8% of them (of 8,761) had attempted it.31 This 
phenomenon is said to be instigated by several factors, 
including the individual’s exposures to technology. 
Video game addiction and depression are two emerging 
public health issues among adolescents in the 
Philippines.31-32 This small-scale study aims to 
understand the association between these two factors and 
produce baseline information that can be used in 
formulating evidence-based public health policies in the 
country. 

 

Methods 

Research site and participants 

This study was conducted in the months of 
August-November 2018 in the city of Manila, the capital 
of the Philippines. Manila is situated on the eastern 
shores of Manila Bay, on the western edge of Luzon 
(14o35’45”N 120o58’38”E). It is one of the most 
urbanized areas and the center of technological 
innovation in the country. It has a population of 1.78 
million, based on 2016 census.33 Manila covers 896 
barangays (villages), which are grouped into six districts. 
Based on the 2010 census, the total population of Filipino 
adolescents, regardless of sex, was 166,391.34 This 
population estimate was used for computing the sample 
size needed for this study. Sample size calculation was 
estimated using the online calculator from OpenEpi.35 
The completion rate of the questionnaires was 78.13%, 
for a total of 300 consenting respondents who were all 
online video gamers. They were selected if they were 
residents of Manila City and reported playing video 
games on the regular basis. 



 
 
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This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369 | http://cajgh.pitt.edu 

 
 

Figure 1. Map of Manila from the National Capital Region of the Philippines 

Instruments 

The study used a paper-and-pencil self-
administered questionnaire. To determine the level of 
online game addiction of the respondents, the study used 
the Video Game Addiction Test (VAT) developed by van 
Rooij et al.36 from the 14-item version of the Compulsive 
Internet Use Scale (CIUS).37 VAT was utilized in several 
studies among adolescents in the past, and it has 
demonstrated excellent reliability and validity. The scale 
outcomes were found to be comparable across gender, 
ethnicity, and learning year, making it a helpful tool in 
studying video game addiction among various 
subgroups.36 The survey contains questions in five 
categories: loss of control, conflict, salience, mood 
modification, and withdrawal symptoms. Each question 
was measured on a 5-point scale: 0–never to 4–very 
often. The results were then used as an indicator of the 
level of addiction. This study adapted the calculations 
conducted by van Rooij et al.38 wherein the average scale 
scores of all the respondents were arranged from 0-4 and 
then were divided into two groups. The first group had an 
average of 0-2 or 'never' to 'sometimes', while the second 
group had an average of 3-4 or 'often' to 'very often'. The  

 
latter group was considered to have the highest level of 
problematic gaming or, in this study, with online game 
addiction.38 The internal reliability of the VAT in this 
study was excellent at Cronbach's α of 0.91. 

The level of depression of the respondents was 
determined by using the Patient Health Questionnaire-9 
(PHQ-9).39 It is a 9-item depression module taken from 
the full PHQ. The questionnaire allows the respondents 
to rate their health status in the past six weeks. There are 
9 diagnostic questions in which the respondents rated 0 
for 'not at all', 1 for 'several days', 2 for 'more than half 
the days', and 3 for 'nearly every day'. The total of the 
PHQ-9 scores was used to measure severity of 
depression. Since there are 9 items in the questionnaire 
and each question can be rated from 0-3, the PHQ-9 
scores can range from 0-27. The score was interpreted as 
‘no depression’ (0-4 points), ‘mild depression’ (5-9 
points), ‘moderate depression’ (10-14 points), 
‘moderately severe depression’ (15-19 points), and 
‘severe depression’ (20-27 points).39 In this study, the 
internal reliability of PHQ-9 had a Cronbach's α of 0.88. 

 



 
 
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This work is licensed under a Creative Commons Attribution 4.0 United States License. 
 

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of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 
Central Asian Journal of Global Health 

Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369 | http://cajgh.pitt.edu 

 
 

Data gathering procedure 

The study randomly surveyed gamers in various 
parts of Manila. Since there are no reliable records of the 
gamers in the area available for research, various 
sampling techniques were utilized. A convenience 
sampling was done by visiting internet cafes in the city 
and requesting the gamers to answer the questionnaire 
during their time-out (from the game). A verbal consent 
was provided by each respondent after hearing a brief 
explanation of the research objectives and the necessary 
instructions. While answering the questionnaire, the 
respondents were assisted by the investigator for any 
clarifications and questions. The questionnaire was 
completed by the respondents in approximately 2.5 
minutes. Other procedures included snowball sampling, 
accidental, and voluntary response sampling after the 
distribution of invitation to respond among internet cafes, 
gamers’ social media groups/sites, and online gamers’ 
organizations. The study was approved by the ethical 
board of the Polytechnic University of the Philippines. 

Statistical analysis 

All the responses from the questionnaires were 
inputted into MS Excel and into SPSS version 23.0 (IBM 
Corp., Armonk, NY, USA). Descriptive statistics of 
responses were computed and included the frequencies 

(f), percentages (%), averages (x̄) and standard deviations 
(SD). The association between online game addiction and 
depression was analyzed using Pearson's correlation and 
was further analyzed using a multiple regression analysis. 
The study hypothesized that there is no significant 
correlation between online game addiction and level of 
depression among adolescents in the City of Manila, 
Philippines. All statistical results were considered 
significant at the p value <0.05. 

 

Results 

Profile of the respondents 

A total of 300 consenting adolescents 
participated in the study. There were more males (n=176; 
59%) than females (n=124; 41%) who participated in the 
study. Most of the respondents were adolescents (aged 
less than 19 years), except for the six respondents who 
were already 20 years old during the data gathering. The 
mean age of the participants was 17 years old (SD=0.90). 
Figure 2 presents the profiles of the respondents based on 
their gender and age characteristics. The VAT analysis 
shows that there were more males (12.0%) who were 
addicted to online games than females (5.7%). 
Meanwhile, 15-, 17-, and 18-year old respondents had the 
highest VAT scores among the six age groups.

 

 

 

 

 

 

 

 

Figure 2. Profiles of the respondents based on gender and age

  



 
 
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This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369|http://cajgh.pitt.edu 

 
 

Level of online game addiction 

The 14-item VAT was ranked from the highest 
to the lowest mean score to understand the common 
conditions experienced by the respondents. The item with 
the highest mean was No. 13: Do you game because you 
are feeling down? (x̄=2.1, SD=1.40). This question had 
the third greatest number of “4-very often” ratings 
(N=46/300). It was followed by the item No. 3: Do others 
(e.g., parents or friends) say you should spend less time 

on games? (x̄=2.06, SD=1.41). The third item with the 
highest mean score was item No. 7: Do you look forward 
to the next time you can game? (x̄=2.0, SD=1.27). The 
item with the highest number of “4-very often” rating 
was item No. 14: Do you game to forget about problem? 
(N=67/300). Items 12 and 2 also had high mean scores: 
Do you neglect to do your homework because you prefer 
to game? (Item 12; x̄=1.98, SD=1.34); and Do you 
continue to use the games despite your intention to stop? 
(Item 2; x̄=1.84, SD=1.20).

Profiles 
Overall 
Profile 

Respondents with high 
VAT scoresa 

Respondents with high 
VAT scoresb 

 N % N % N % 
Gender       

   Male 176 58.7 36 12.0 36 20.5 
   Female 124 41.3 17 5.7 17 13.7 
Age       

15 years old 12 4.0 3 1.0 3 25.0 
16 years old 42 14.0 3 1.0 3 7.1 
17 years old 168 56.0 34 11.3 34 22.0 
18 years old 60 20.0 12 4.0 12 20.0 
19 years old 12 4.0 1 0.3 1 8.3 
20 years old 6 2.0 0 0.0 0 0.0 

aPercentage was computed against the overall number of participants (N=300) 
bPercentage was computed against N of each profile of the respondents 

Table 1. Levels of online game addiction based on gender and age
 
Level of depression 

The PHQ-9 was used to quantify the symptoms 
of depression of the respondents and identify its severity. 
The majority of the respondents demonstrated no 
depression (47%), followed by having mild depression 
(22%), and moderate depression (17%). Of note, the 
current study revealed 12% of the respondents had 
moderately severe depression and 2% had severe 
depression. We found that higher PHQ-9 scores were 
associated with decreased functional status. The most  
common symptoms reported by the respondents based on  
 

 
 
the mean scores of each item in PHQ-9 include …feeling 
tired or having little energy (x̄=1.89, SD=1.30), …poor 
appetite or overeating (x̄=1.87, SD=1.37), … feeling 
down, depressed or hopeless (x̄=1.81, SD=1.18), 
…trouble falling or staying asleep, or sleeping too much 
(x̄=1.78, SD=1.33), and …trouble concentrating on 
things, such as reading newspaper or watching television 
(x̄=1.75, SD=1.40). Interestingly, the six respondents 
who were identified to have “severe” depression were all 
females, and four of them had high VAT scores. 

 



 
 
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This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369 | http://cajgh.pitt.edu 

 
 

Profiles 
No Depression 

N (%) 
Mild 
N (%) 

Moderate 
N (%) 

Moderately Severe 
N (%) 

Severe 
N (%) 

Gender      

      Male 87 (29.0) 38 (12.7) 31 (10.3) 20 (6.7) 0 (0.0) 
Female 54 (18.0) 28 (9.3) 19 (6.3) 17 (5.7) 6 (2.0) 

Age      

15 years 5 (1.7) 1 (0.3) 2 (0.7) 2 (0.7) 0 (0.0) 
16 years 24 (8.0) 9 (3.0) 3 (1.0) 7 (2.3) 0 (0.0) 
17 years 77 (25.7) 34 (11.3) 31 (10.3) 22 (7.3) 5 (1.7) 
18 years 26 (8.7) 17 (5.7) 10 (3.3) 5 (1.7) 1 (0.3) 
19 years 5 (1.7) 4 (1.3) 3 (1.0) 1 (0.3) 0 (0.0) 
20 years 4 (1.3) 1 (0.3) 1 (0.3) 0 (0.0) 0 (0.0) 

Table 2. Level of depression of the respondents based on the PHQ-9 scores 

Association between online game addiction and 
depression 

The association between online game addiction 
based on the VAT scores and the level of depression 
among the respondents was evaluated through Pearson's 
correlation analysis. Results (Table 3) show that the level 
of online game addiction was positively correlated with 
the level of depression (r=0.31, p<0.001) but was not 
significantly correlated with age or gender (r=-0.80, 
p<0.171 and r= 0.10, p<0.097, respectively). 

A multiple linear regression was calculated to 
predict online game addiction based on gender and 
depression. This regression analysis was performed with 
all participants and with the subset of participants with 
high VAT scores, which indicated online game addiction. 
A significant regression equation was found (F(2.50)= 
2.247, 0.10), with an R2 of 0.082. Table 4 shows that 
depression was a significant predictor of online game 
addiction. 

Variables Gender Age 
Online game 

addiction 
Depression 

Gender 
1 -.080 .100 .070 
 .171 .097 .212 

Age 
-.080 1 -.080 -.020 
.171  .171 .739 

Online game  
addiction 

.100 -.080 1 .310 

.097 .171  .000* 
Depression .070 -.020 0.310 1 

 .212 .739 .000*  

*significant at p ≤0.001 in correlation matrix 

Table 3. Pearson’s correlation coefficient among gender, age, online game addiction, and depression of the 
adolescents in Manila 



 
 
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This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369 | http://cajgh.pitt.edu 

 
 

Variables 
Regression 
coefficient 

95% CI p value 

Adolescents playing online games (N=300) 

Age -0.0224 -0.1298 - 0.0850 0.68 

Depression 0.0418 0.0271 - 0.0565 0.47 

Adolescents with addiction playing online games (n=54) 

Age -0.0443 -0.1305 - 0.0417 0.30 

Depression 0.0121 -8.1924 - 0.0242 0.05* 

        *significant at p<0.05 

Table 4. Multiple regression analysis for prediction of online game addiction based on age and level of depression 

 

Discussion 

The correlation between online game addiction 
and the levels of depression in this study was weak but 
statistically significant. This positive correlation was 
previously reported in other research studies across the 
globe.40-41 In a study conducted by Rikkers et al.40 among 
children and adolescents (11-17 years old) in Australia, 
electronic gaming was positively associated with 
emotional and behavioral problems including depression. 
Longer gaming hours were also associated with severe 
depressive symptoms, somatic symptoms, and pain 
symptoms among young people in Taiwan.41 Online 
game addiction was associated by Zamani et al.42 not 
only with depression but also with sleep disorder, 
physical complaints, and social dysfunctions of students 
in Iran. In a study conducted by Dong et al.,43 depression 
came out as one of the outcomes of the internet addiction 
disorder. 

In the current study, most of the respondents 
looked forward to the next time they would game, with 
the most common reason of engaging in games reported 
to be easing the moments of feeling down. Another 
reason of the respondents’ addiction to online games was 
that they want to forget about problems. It is considered 

as one of the core symptoms of addiction as described by 
Brown.44 The second most common experience of the 
respondents was the 'inability to voluntarily reduce the 
time spent on online games', which is another core 
symptom of addiction.45 Most of the respondents 
admitted that they were getting advice from their parents 
or friends to spend less time on games, but they could not 
control it, despite their intention to stop. In fact, gaming 
negatively affected homework completion among many 
study participants. This effect was previously studied 
among high school students in Los Baños, Philippines, 
where the video gamers had 39% probability to fail in 
school. In this previously published study, 6 out of 10 
video gamers spent their daily allowances on computer 
games, giving them access to continuously spend their 
time playing.29 The addiction of the adolescents in 
Manila could have been influenced by the ubiquitous 
nature of internet in the city. Internet cafes are very 
accessible in the country, and they are thriving in almost 
all corners of the city. In addition, the rent for internet 
and online games in Metro Manila costs 10 to 20 pesos 
per hour only (US $0.19 to US $0.38 per hour), making 
playing video games affordable. Some internet hubs are 
even offering discounts and promotions for longer stays 
of 10-12 straight hours of playing online games.  



 
 
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Central Asian Journal of Global Health 

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Based on the most cited symptoms of the 
respondents in this study, it could be implied that 
adolescents cope with their emotional distress by playing 
online games. This means that the high occurrence of 
online game addiction goes along with the high 
occurrence of depression among the same group. In 
regard to depression, most respondents in this study were 
feeling tired, having poor appetite, feeling hopeless, 
having trouble falling asleep, or having trouble 
concentrating on things that require enough attention, 
like reading books. These symptoms were also reported 
by Schmit et al.45 as related to online game addiction, 
where the people who spent longer hours playing online 
games got higher scores for loneliness and isolation. This 
study did not capture the number of hours spent by the 
respondents in online games, which could be 
incorporated in the next study for further analysis. 

Depression, as associated to online game 
addiction, may lead to anxiety, compulsion, and suicide 
ideations.46 This is a serious threat to the population 
health that needs to be addressed. Interventions may 
include strengthening depression management among 
adolescents, either in school or in the community. There 
are several ways to manage depression. The schools and 
the community should reinforce sports by making it more 
challenging, engaging, and motivating. In the 
Philippines, numerous factors make receiving mental 
health care a challenge. There is only one psychiatrist for 
every 250,000 mentally ill patients, budget dedicated to 
mental health interventions is limited,47 a guidance and 
counseling system has not yet matured,48 and there was 
even a report that online counseling was preferred by the 
students than its face-to-face counterpart.49 The poor 
availability of the mental health interventions in the 
country may lead to upsurge of depression cases among 
adolescents. Meanwhile, the booming online game 
industry in the country leads to the increased numbers of 
addicted adolescents to online game addiction. Policy 
makers, the government, and its stakeholders should start 
addressing these issues before it becomes an even bigger 
health concern, especially in the face of ongoing COVID-
19 pandemic.  

The Philippine government should also assess 
their existing intervention programs in mental health 
issues. In 2016, "Hopeline" was launched in the 
Philippines. It was a national hotline for mental health 
assistance for the prevention of depression and suicide 
cases in the country. The hotline is equipped with a 
professional team of counselors as responders.50 No 
study has been found to assess the effectiveness of this 
intervention for depression. National trainings and 
workshop programs have been implemented in other 
countries to empower the people in dealing with the 
stigma of depression which includes mental health 
literacy campaign, peer services, and advocacies.51 This 
is an essential step to correct various misconceptions on 
depression, especially among adolescents.  

This study was cross-sectional and cannot 
determine causality. This is the first report on the 
association between online game addiction and the levels 
of depression among adolescents in the city of Manila, 
Philippines. Despite the small sample and the limited 
scope of the research, the current study has shown 
interesting preliminary results that could be instrumental 
in the conduct of a bigger scale study in the country. To 
facilitate participation of the larger number of 
respondents, the future investigators are suggested to 
coordinate with various high schools in Metro Manila 
and use these schools as a sampling frame for a robust 
sampling technique. In this study, the level of online 
game addiction has no statistically significant association 
with age and gender. The association between age and 
online game addiction could have been improved by 
including older age groups in this study. Data from a 
group of young adults (college students), who are also 
exposed to online gaming, could be compared to these 
data for further analysis. Gender is commonly associated 
with the level of online game addiction in many studies, 
but it is not statistically significant in this present study. 
The sample size in this study was only 300 and may not 
have been representative enough of a general population. 
Also, our sample size was not large enough to capture 
distinctions between males and females.  This could also 
be addressed by a wider scale of surveys in the future 
research. 



 
 
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This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
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Central Asian Journal of Global Health 
Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.369|http://cajgh.pitt.edu 

 
 

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