THE IMPACT OF SOCIAL MEDIA ON MENTAL HEALTH: A MIXED

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THE IMPACT OF SOCIAL MEDIA ON MENTAL HEALTH: A MIXED-THE IMPACT OF SOCIAL MEDIA ON MENTAL HEALTH: A MIXED-

METHODS RESEARCH OF SERVICE PROVIDERS’ AWARENESS METHODS RESEARCH OF SERVICE PROVIDERS’ AWARENESS

Sarah Nichole Koehler

Bobbie Rose Parrell

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THE IMPACT OF SOCIAL MEDIA ON MENTAL HEALTH: A MIXED-METHODS

RESEARCH OF SERVICE PROVIDERS’ AWARENESS

A Project

Presented to the

Faculty of

California State University,

San Bernardino

In Partial Fulfillment

of the Requirements for the Degree

Master of Social Work

Sarah Nichole Koehler

Bobbie Rose Parrell

June 2020

THE IMPACT OF SOCIAL MEDIA ON MENTAL HEALTH: A MIXED-METHODS

RESEARCH OF SERVICE PROVIDERS’ AWARENESS

A Project

Presented to the

Faculty of

California State University,

San Bernardino

Sarah Nichole Koehler

Bobbie Rose Parrell

June 2020

Approved by:

Dr. Rigaud Joseph, Faculty Supervisor, Social Work

Dr. Armando Barragán, MSW Research Coordinator

iii

ABSTRACT

The relationship between heavy use of social media and an increase in

mental health disorders has long been established. However, there is a gap in

the literature regarding mental health practitioners/providers’ responses to this

issue. This mixed-methods research embraced two theoretical perspectives—

Ecological Model and Generalist Intervention Model—toward determining the

extent to which mental health practitioners/providers assess for the impact of

heightened use of social media on mental health. Qualitative and quantitative

data were collected from 95 mental health practitioners (N = 95) via Qualtrics.

Non-parametric tests and descriptive statistics showed that prior training,

agency’s values, and credentials impact mental health practitioners’ responses to

social media use and its impact on mental health. Meanwhile, qualitative findings

pinpointed low self-esteem, increased depression, and increased anxiety as

three psychiatric conditions associated with uncontrolled use of social media.

Implications of these findings for theory, research, social work practice, and

social work education were discussed.

Keywords: heightened social media use, mental health, ecological model

generalist practice model, mixed-methods research, social work practice

ACKNOWLEDGMENTS

The researchers would like to acknowledge and extend our deepest

appreciation for the support provided by Dr. Armando Barragán, Dr. Rigaud

Joseph, and all others who have provided extra encouragement throughout this

research project over the past two years. Additionally, each researcher would like

to extend gratitude to one another for continuously pushing, encouraging growth,

and for the dedicated time spent on this project. Last but not least, the

researchers would like to acknowledge our amazing cohort who consistently

provided laughs in hard times, encouragement in low times, and smiles along the

way.

DEDICATION

I would like to dedicate this research to the inner child that lives in all of

us. The one that says, “Go dance through the meadow” and is silenced by the

voice that says, “But you don’t know what’s in there. That can be dangerous”. In

the meadow is where there is freedom, joy, and growth. I’m so thankful for

everyone that strengthened the voice of my inner child and has taught me about

the beauty of dancing in the meadow.

“You make me STRONG and BRAVE.” -Psalm 138:3

Sarah Koehler

I would like to dedicate this research paper to my family, friends, and

loved ones. A special acknowledgment to my significant other, Donnie, for

always providing words of encouragement and laughter during stressful times. I

would like to also dedicate this research to the graduating class of 2020 and

MSW cohort for persevering through the many changes and challenges our last

quarter brought. We did it!

“Don’t use social media to impress people; use it to impact people.” -Dave Willis

Bobbie Parrell

v 
 
TABLE OF CONTENTS 
ABSTRACT .......................................................................................................... iii 
ACKNOWLEDGMENTS .......................................................................................iv 
LIST OF TABLES ............................................................................................... viii 
LIST OF FIGURES ...............................................................................................ix 
CHAPTER ONE: PROBLEM FORMULATION ..................................................... 1 
Introduction ................................................................................................ 1 
Purpose of the Study ................................................................................. 3 
Significance of the Project for Mental Health Practice ............................... 4 
CHAPTER TWO: LITERATURE REVIEW ............................................................ 5 
Introduction ................................................................................................ 5 
Social Media Impact on Mental Health....................................................... 5 
Social Media and Mental Health Education ............................................... 7 
Diagnostic and Statistical Manual Void for Diagnosis and Treatment ........ 8 
Theories Guiding Conceptualization ........................................................ 10 
Ecological Model ........................................................................... 10 
Generalist Intervention Model ....................................................... 11 
Critical Analysis of the Theories Guiding This Research ............... 12 
Summary ................................................................................................. 13 
CHAPTER THREE: METHOD ............................................................................ 15 
Introduction .............................................................................................. 15 
Study Design ........................................................................................... 15 
Sampling .................................................................................................. 16 

vi 
 
Data Collection and Instruments .............................................................. 16 
Procedures .............................................................................................. 17 
Protection of Human Subjects ................................................................. 18 
Study Variables ........................................................................................ 18 
Dependent Variables ..................................................................... 24 
Independent Variables/Predictors ................................................. 30 
Hypothesis ............................................................................................... 20 
Data Analysis ........................................................................................... 21 
CHAPTER FOUR: RESULTS ............................................................................. 22 
Frequency Distributions ........................................................................... 22 
Presentation of the Findings .................................................................... 24 
Quantitative Findings .................................................................... 24 
Qualitative Findings ....................................................................... 30 
CHAPTER FIVE: DISCUSSION ......................................................................... 36 
Overview .................................................................................................. 36 
Consistency with Previous Research ....................................................... 37 
Implications .............................................................................................. 38 
Implications for Theory .................................................................. 38 
Implications for Research .............................................................. 39 
Implications for Social Work Practice ............................................ 39 
Implications for Social Work Education ......................................... 42 
Limitations and Recommendations .......................................................... 43 
APPENDIX A: SURVEY ..................................................................................... 45 
APPENDIX B: INFORMED CONSENT .............................................................. 49 

vii

APPENDIX C: INSTITUTIONAL REVIEW BOARD APPROVAL ........................ 51

REFERENCES ................................................................................................... 53

ASSIGNED RESPONSIBILITIES ....................................................................... 53

viii 
 
 LIST OF TABLES 
 
Table 1. Critical Analysis of Study Theoretical Perspectives with Joseph and 
MacGowan’s (2019) Theory Evolution Scale (TES) ........................................... 14 
Table 2. Frequency Distributions of Study Variables (N = 95) ............................ 23 
Table 3. Knowledge of Social Media Impact on Mental Health ........................... 27 
Table 4. Integration of Social Media Topic in Assessment ................................. 28 
Table 5. Integration of Social Media Topic in Treatment .................................... 30 
Table 6. Major Beliefs of Social Media’s Impact on Mental Health ..................... 31 
  
 
 
   

LIST OF FIGURES

Figure 1. Belief of Social Media Impact on Mental Health .................................. 24

Figure 2. Knowledge of Social Media Impact on Mental Health ......................... 25

CHAPTER ONE

PROBLEM FORMULATION

Introduction

With the continuing technological advancements, social media—also

known as social networking—has become the most popular form of

communication and interaction between people of all ages throughout the world.

Social media (SM) is a way to communicate and share content through various

technological platforms (Kaplan & Haenlein, 2010) such as Facebook, Instagram,

Twitter, Snapchat, Tumblr, etc. Research on the growing popularity of social

media use has found that nearly 8 in 10 Americans use social media, which

amounts to a total population basis of 68% on Facebook, 21% on Twitter, 25%

on Pinterest, and 26% on Instagram (Greenwood et al, 2018). Statistics show

that the extent of time people spend on social media sites amount to significantly

high rates. On average, 28% of the time spent using the internet is for social

media interaction (Huang, 2018).

There are some benefits associated with social media use. These

include—but are not limited to—awareness and destigmatizing mental health,

additional access to resources, and a platform for individuals to relate to one

another regarding their mental health symptoms while using the apps (Lattie et

al., 2019). Social media can also serve as a positive outlet to reduce the potential

barriers individuals of all backgrounds face when living with a mental health

diagnosis (Andrews et al., 2018). However, the literature contains several studies

that link social media use with several psychiatric disorders, including depressive

symptoms, anxiety, and low self-esteem (Lin et al., 2016; Pantic, 2014). Users of

social media may experience bullying, shaming, negative responses to their

posts. These users may also experience discomfort due to comparison of their

self-image and life satisfaction to other users (Belluomini, 2015). Additionally,

negative social media behaviors can cause isolation, depression, and mood

changes based on negative content users see while scrolling (Belluomini, 2015).

With an increase in the use of social media over the last decade, it is

important to assess any impact social media might have on mental health. There

is as yet is little action implemented by the mental health professionals regarding

the implications of social media for mental health. Additionally, there has been

minimal research done regarding the knowledge and preparedness of mental

health clinicians to address the impact of heavy social media use on the clients’

mental health.

Social media’s impact on mental health complicates social service delivery

on the micro level due to the significant growth of mental health symptoms. As

more individuals are presenting with anxiety, depression, low self-esteem, etc.

due to their social media use, increased service providers are needed. Mental

health service providers need to be aware of social media’s impact on mental

health to better serve individuals affected by this issue. There is also a need for

further training on how to assess for social media use and the potential impacts

on mental health. Having an increased understanding of the impacts of social

media use will lead to more efficient and effective treatment for clients.

Purpose of the Study

The purpose of this study is to explore mental health practitioners’

awareness/knowledge of the possible impacts heightened social media use can

have on clients’ mental health. This study also explored how that

knowledge/awareness (or lack thereof) influences the therapeutic process. This

study addressed the following four questions:

1) Is there a difference in the level of social media contents in

assessments and therapeutic sessions between agencies that are

proactive on the impact of heavy use of social media and those that

are not?

2) What is the level of awareness about the negative impact of heavy use

of social media on mental health among mental health practitioners?

3) How do mental health practitioners who completed some training on

social media compare to their non-trained counterparts with regard to

knowledge about the impact of social media on mental health?

4) What is the proportion of mental health practitioners who believe in a

monotonic correlation between heavy use of social media and adverse

mental health consequences?

Significance of the Project for Mental Health Practice

The proposed study is essential due to the limited number of research

studies conducted on how mental health practitioners are responding to

increased social media use and the impact on mental health. The observation of

a technological society has brought to question what the impacts of high social

media use are on a client’s mental health. As society evolves into a digital

culture, mental health practitioners need to be prepared to screen clients for

possible negative side effects of heavy social media.

The findings of this study will have implications for the field of social

services by identifying gaps in service provision, assessment, and treatment

planning with respect to social media’s impact on mental health. The findings

may lead to updates in a clinician’s approach to assessing the client’s concerns

and developing a treatment plan to address treatment goals. Although this

study’s main emphasis is on the micro-level (interaction between clinicians and

clients), the findings may contribute to social service provision on a macro level

by updating service accessibility and policies regarding social media outlets.

CHAPTER TWO

LITERATURE REVIEW

Introduction

This chapter will serve as an overview and examination of prior research

conducted on heavy social media use and its impact on mental health. The

subsections in this chapter will include the prevalence of social media usage,

lack of social media use recognizable as a mental health diagnosis in the

Diagnostic and Statistical Manual of Mental Disorders (DSM), mental health

education through social media, and current treatment gaps. The final subsection

will examine system theory and integrative theory, which is relevant to the

research topic.

Social Media Impact on Mental Health

The Mental Health of America (2018) has estimated that over 44 million

American adults have a mental health condition. The statistics of youths

experiencing mental health conditions, such as major depressive disorder,

continues to rise in high rates yearly (Mental Health of America, 2018). Mental

health in the United States continues to increase, and the amount of time

Americans spend using social media is also on the rise. To reiterate, on average,

Americans spend 28% of the time using the internet for social media interaction

(Huang, 2018). Multiple studies have found social media use as a contributing

link to various mental health symptoms associated with depression, anxiety, low

self-esteem, and negative well-being (Ashford, 2017; Hardy & Castonguay, 2018;

Hussain & Griffiths, 2018). These studies find that social media has a direct

impact on mental health and well-being through the pure nature of content and

interaction found while using social media sites. Although most studies find that

youth populations are at most risk, adults are also associated with high mental

health symptoms related to social media use.

Ashford (2017) found that individuals may experience feelings of social

isolation, depression, insecurity, jealousy, and poor self-esteem while using

social media. Some individuals develop cognitive distortions when comparing

their lives to other users’ content, which may lead to feelings of sadness and

depression (Ashford, 2017). Some examples include comparing users’ number of

likes and followers, feeling left out for not being invited to events, and comparing

grandiosity pictures to one’s photos. As a result, social media has a higher rate

of affecting vulnerable populations, like those who suffer from mental health

diagnosis and have the potential to cause mental health symptoms to surface.

Meanwhile, with social media being universal, access to anyone around

the world has become unlimited. While social media has brought new ways of

communication, new opportunities for bullying have also emerged, such as

cyberbullying. Cyberbullying can have immense negative impacts through users

taking cyberbullying so far that the victim commits suicide. Lowry et al.’s (2016)

work highlighted the real dangers and negative outcomes of cyberbullying: 13-

year-old, Megan, was cyberbullied on social media by a catfished "cute boy" who

turned out to be an adult female named Lori. Lori, impersonating a fake boy

named Josh created a strong friendship with Megan. The friendship ended when

Josh called her names, such as "liar and slut" online. Megan committed suicide

after receiving the last message, "you are a bad person, and everyone hates

you," "the world would be a better place without you."

While cyberbullying has been found to mostly affect adolescents (Gannett,

2013), research shows that adults can be impacted by this phenomenon as well.

Using social media, Kowalski (2017) conducted a study of cyberbullying in the

workplace and found that out of 3,666 participants, 30% report being victimized

and cyberbullied in the workplace.

Social Media and Mental Health Education

Mental health access and engagement is one of the main barriers mental

health practitioners run into when trying to reach vulnerable at-risk populations

who suffer from mental health diagnosis. Research demonstrates that these

barriers attribute to a lack of knowledge about symptoms and features of the

illnesses and avoidance in seeking treatment due to individual and public stigma

and discrimination (Henderson et al., 2013). While social media may impact

mental health for some individuals negatively, there are specific ways mental

health practitioners are utilizing social media platforms to address these barriers

in access to mental health care. Social media is a potentially useful tool used by

practitioners to engage and access unreachable populations to bring mental

health awareness, education, and support to those suffering from severe mental

health illnesses (Naslund & Riefer, 2018).

Using Twitter as an online platform, Naslund et al. (2017) conducted a

survey on people’s preferences on receiving education and tools to deal with

mental health symptoms through social media. The results of the survey

indicated that 85% of respondents favored receiving mental health programs

through social media, 72% for understanding health and welfare, and 90% prefer

turning to social media to gain new ways to cope with mental health

symptoms. Additionally, mental health practitioners can utilize social media to

raise awareness about risks such as privacy, safety, cyberbullying, stigma, and

discrimination (Naslund et al., 2017). Grove (2019) also found that social media

could serve as a tool by family members seeking information to gain more

education about a loved one mental illness.

Diagnostic and Statistical Manual Void for Diagnosis and Treatment

As previously demonstrated, there has been a significant increase in

social media use and the negative effects on an individual’s mental health.

Although the extent of this problem has only been studied within the last decade,

there is evidence that heavy social media use, or social media addiction, is a

prevalent mental disorder that requires treatment (King et al., 2011; 2012; Pantic,

2014; Young, 2009). The most updated version of the Diagnostic and Statistical

Manual of Mental Disorders (DSM-5) does not recognize social media addiction

as a diagnosis. This creates a barrier in service provision as there are no criteria

in the DSM-5 to help guide mental practitioners in treating symptoms of

heightened social media use. Yet, there is a section in the DSM-5 regarding

conditions for further study which includes internet gaming disorder, with several

proposed symptoms that are argued to fit that of social media addiction (Ashford,

2017; Fairburn et al., 2019; Gregory, 2019). Some of these proposed symptoms

include constant thinking about internet games, irritability, anxiety or sadness

when limited access to internet games, and using internet games as a way to

escape from difficult emotions (DSM, 2013). Griffiths and Szabo (2013) explained

that internet addiction is not merely being addicted to the internet, but rather,

different online tasks which can include social media.

Several researchers have found that due to the lack of a standardized

approach and definition of the problem, research that has occurred regarding the

prevalence and treatment of the problem may be skewed (King et al., 2012).

There is a push for the inclusion of a diagnosis or common language in the DSM-

5 regarding social media addiction (King et al., 2012; Young, 2009). The

inconsistent language in the DSM-5 is a hindrance to treatment because a

clinician may neglect asking questions regarding social media use or experience

difficulty differentiating normal and healthy social media use versus compulsive

and addictive social media use (King et al., 2012; Young, 2009).

Theories Guiding Conceptualization

Ecological Model

This research embraced the Ecological Model as guiding framework. Urie

Bronfenbrenner developed the Ecological Model in 1979. In this model,

Bronfenbrenner identified five systems that affect an individual’s behavior

throughout the lifespan: microsystem, mesosystem, exosystem, macrosystem,

and chronosystem. The microsystem pertains to factors at the individual level;

the mesosystem relates to factors at the family/school level; the exosystem deals

with community factors such as workplace and neighborhood; the macrosystem

explains factors such policy, and social media (Bronfenbrenner, 1979).

Bronfenbrenner’s Ecological Model is popularly known in social work as the

Person-in-Environment Perspective or Systems Theory.

Utilizing a Systems Theory approach in mental health can provide

important information about an individual’s emotions and motivations as related

to system dynamics. This perspective provides insights into how individual's

behaviors are shaped by the larger social context or system of social media. This

theory will guide the research by looking at social media as part of a system that

can influence mental health symptoms and behaviors. This theory may explain

why there is a correlation found in heavy social media use and mental health.

Analyzing the Systems perspective through mental health practitioners,

this theory explains the importance of understanding the influencing factors

social systems can have on individuals. Using the Systems theory in the

treatment of mental health requires that an individual be looked at holistically with

consideration of the complexities that make up the world around him/her. When

providing mental health treatment, the mental health practitioner needs to

complete an assessment that determines the presenting problem, which includes

cause for treatment, when symptoms began, what are possible influencers of the

symptoms, and other factors. For this study, Systems theory addresses the need

for practitioners to assess for all potential causes of mental health symptoms,

including the use of social media.

Generalist Intervention Model

Another framework guiding this research is the Generalist Intervention

Model (GIM). The GIM was developed over decades of social work practice

dating back to the formation of social work. The model focuses on evaluating

environmental stressors through the micro, mezzo, and macro levels while

providing intervention to help clients return to homeostasis and improve overall

well-being (Ebear et al., 2008). Thus, this model places importance on mental

health practitioners’ ability to think critically about the environment and systems

closest to a client to gain a deeper knowledge and understanding of how those

systems or environments may be involved in the identified issue or concern.

The model focuses on seven key areas of intervention for mental health

practitioners to support and guide clients in obtaining problem-solving skills while

protecting the client’s right to self-determination such as engagement,

assessment, planning, intervention, evaluation, and treatment. This model may

provide insight into the impacts of heavy social media use on mental health and

provides mental health practitioners deeper knowledge and understanding of its

effects on mental health when applying this model in assessment and treatment.

This perspective encourages clinicians to consider the client’s environment and

social influences, such as social media, and explore the client’s mental health.

This theory provides a strong framework for mental health practitioners to

evaluate a client's amount of social media use and its effects on mental health

symptoms or behaviors the client may be exhibiting. Lastly, using this

perspective as a conceptual guide to this research project will allow the

researchers to consider what environmental impact and social factors are

influencing clinicians’ assessment and treatment of individuals with mental health

concerns that may become a result of social media use. In other words, the GIM

itself can serve as an assessment-based tool for mental health practitioners to

gain insight and knowledge of social media impact on the clients’ mental health.

Critical Analysis of the Theories Guiding This Research

The researchers used Joseph & MacGowan’s Theory of Evolution Scale

(TES) to assess the quality of the theories in this research. The TES assesses

theories through nine separate criteria: coherence, conceptuality, conceptual

clarity, philosophical assumptions, historical roots, testability, empirical support,

boundaries, interactions between people and their environment, and human

agency within the environment (Joseph & MacGowan, 2019). The TES includes

a rating scale of 1-5 (1 being the lowest and five being the highest) with a total

score ranging from 9 to 45. The scoring scale ranges from 1-10= Poor; 10-19=

Fair; 20-29= Good; and 30-45= Excellent.

Under the lenses of the TES, both the Systems Theory and the GIM

produced an excellent quality score, in the shape of 35 and 41, respectively.

Table 1 details the scoring for both the Systems Theory and the GIM under the

TES. Hence, this research relies on high-quality theories to assess mental

practitioners’ knowledge about the impact of social media on mental health.

Summary

The correlation between an increase in mental health symptoms and

increased social media use has been proven in the literature. These mental

health symptoms include—but are not limited to—isolation, insecurity, poor self-

esteem, anxiety, and depression. Although there have been many studies

supporting the negative impact of social media, there are also benefits. Because

of the universal access to social media, mental health providers can use social

media as a medium to provide mental health education and treatment. However,

certain barriers exist for treatment because there is not enough research done to

include a diagnosis into the DSM-5. While negative impacts and benefits exist

with the increased use of social media, there requires a response by mental

health professionals. This study will use Systems Theory and The Generalist

Intervention Model as the framework to assess how/if mental health providers are

considering the impact of social media on the client’s mental health in the

assessment and treatment phases of mental health treatment.

Table 1. Critical Analysis of Study Theoretical Perspectives with Joseph and

MacGowan’s (2019) Theory Evolution Scale (TES)

Critical Analysis of Study Theoretical Perspectives with Joseph and Macgowan’s

(2019) Theory Evaluation Scale (TES)

Item

Criteria

Score

SP*

GIM**

The theory has coherence.

The theory has conceptual clarity.

The theory clearly outlines and explains its

philosophical assumptions.

The theory describes its historical roots in

connection with previous research.

The theory can be tested and proven false via

observational and experimental methods.

The theory has been critically tested and validated

through empirical evidence.

The theory explains its boundaries or limitations.

The theory accounts for the systems within which

individuals interact with people around them.

The theory recognizes humans as active agents

within their environment.

Overall score

Theory quality based on overall TES score: Excellent for both theoretical perspectives

*Systems Perspective

**Generalist Intervention Model

CHAPTER THREE

METHOD

Introduction

This provides a detailed account of the methods and steps taken

regarding how this study was conducted. Specifically, this chapter focuses on the

design of the study, sampling methods, instrument construction, data collection

procedures, protection of human subjects, research hypotheses, and data

analysis.

Study Design

The researchers used a mixed-methods approach toward assessing

whether mental health providers are aware of social media’s impact on mental

health. The quantitative portion of the study was descriptive in design, while the

qualitative piece pertained to the Grounded Theory methodology. This mixed-

method survey subjected participants to both open and closed questions,

allowing them to contribute their thoughts, instead of limiting them to a specific

range of answers. With the limited research regarding mental health practitioner’s

response to the increase of mental health symptoms, the mixed-methods design

provided a platform to identify barriers, insight, and possibly future feedback for

mental health education. A limitation of this research design is that with mixed-

method surveys, some participants may not have provided as much information

in the open-ended questions, as that required more effort and time. The

researchers have limited the number of qualitative questions to help mitigate this

limitation.

Sampling

This study used non-probability sampling, including both purposive

sampling and snowball sampling of mental health practitioners that are

completing assessments and treatment of individuals that have mental health

symptoms. The researchers approached mental health practitioners within their

network, who then approached other practitioners within their network.

Additionally, the researchers will solicited participants through a social media

group called “The Life of Social Work” within the network of Facebook. Selection

criteria included area of expertise, populations served, level of education, and

age. All participants must be 18 or older. The final sample consisted of 95

participants. Demographic characteristics of the participants are provided in the

“Results” section.

Data Collection and Instruments

Given the exploratory nature of the study, the researchers developed a

survey to collect demographic characteristics and information pertaining to the

purpose of the study. The survey quantitatively and qualitatively assessed for (1)

practitioners’ knowledge about the impact of social media on mental health, (2)

practitioners’ belief about the impact social media has on mental health, (3) the

incorporation level of social media contents in assessment, and (4) the

incorporation level of social media contents in therapeutic sessions. The

questionnaire encompassed relevant open-ended, closed-ended, and fill-in-the-

blank questions. Please see Appendix A for the complete list of questions on this

study. The survey was administered during the Winter 2020 Quarter, between

January and March.

Procedures

Researchers collected survey data for this research through Qualtrics. The

surveys were targeted to reach the specific population of mental health

practitioners who work closely with individuals suffering from mental health

diagnoses and symptoms to understand better the impact that social media has

on mental health. Surveys were administered through a social media group

called "The Life of Social Work" within the network of Facebook. This Facebook

group consists of over 12k mental health practitioners all over the United States

and some in other countries such as Canada and Europe regions. Survey

participation of these group members provided a great deal of information on the

perceptions and current assessment process on heavy social media use on the

national, state, and local levels. The researchers also utilized professional

contacts through known networks and by current employment and past

professors within the social service field. The researchers requested that the

survey participants recruit other mental health practitioners to complete the

online survey by utilizing a snowball technique to gather more data.

Protection of Human Subjects

The Institutional Review Board of California State University San

Bernardino approved this study in Fall 2019. The researchers made the

protection of human subjects the centerpiece of this researcher. The online

survey contained a disclaimer about the voluntary nature of participation in the

study and the appropriate steps the research team will take to preserve of the

confidential of the data. Additionally, participants were fully informed on the

parameters of the research study and reasons for conducting the specific

research before participation. The survey was solicited by a Facebook post with

a provided link to the research or through an email link to voluntary participants.

Demographic information was limited to non-identifiable data, so there was no

possibility of researchers to identify participants. Nonetheless, a disclaimer of

general information collection such as age, sex, current position, and years in the

field was collected but remained confidential (please see Appendix B for

information about the informed consent used for this study). The researchers

stored all completed surveys on a password/fingerprint protected computer. Only

the research team has had access to the data. The researchers will destroy the

files one year after the completion of the study.

Study Variables

Dependent Variables

This study had four dependent variables. The first of the dependent

variables was practitioners’ knowledge about the impact of social media on

mental health. The following question captured this variable: On a scale from 0-

10 (not at all knowledgeable to extremely knowledgeable) where do you rate your

knowledge about social media impact on mental health? The second dependent

variable was a binary one that measures practitioners’ belief about the impact of

social media on mental health. A nominal one as well, the dependent variable

looked at the incorporation level of social media contents in assessment.

Participants were asked, “do you incorporate social media use during mental

health assessments?” in which participants were able to answer “yes” or “no”.

The final dependent variable measured incorporation level of social media

contents in therapeutic sessions using the following scaling question, “On a scale

of 0-10 (0 rating meaning never and 10 rating meaning always), how often does

the topic of social media arise during individual sessions?”

Independent Variables/Predictors

There were eight categorical predictors in this research: race/ethnicity,

gender, age, region, education, experience, training, and value. For the

independent variable of race/ethnicity, the researchers divided participants

between Whites and non-Whites (the latter group includes Asian Americans,

African Americans, bi-racial individuals, and Hispanics). Gender reflected

participants who reported being male or female. Regarding age, participants

were divided into two groups: 18 to 34 and 35 or older. Education discriminated

between board certified/licensed practitioners and non-licensed practitioners.

Respondent with Under 5 years of experience were compared to those with 5

years of experience or more. When considering a participant’s history of training,

participants were able to answer a simple “yes” or “no” if participants had

received training regarding social media’s impact on mental health. The final

independent variable is value. This variable considers the value an agency

places on incorporating social media use into mental health assessment and

treatment. Participants were asked to answer “yes” or “no” in response to

whether or not the agency valued integrating social media use into mental health

practices.

Hypothesis

To answer the questions in this study, the researchers formulated the

following hypotheses:

• Hypothesis I: The proportion of mental health practitioners who believe

in a monotonic correlation between heavy use of social media and

adverse mental health consequences will be superior or equal to 75

percent.

• Hypothesis II: There will be a high level of awareness (at least 75

percent) about the negative impact of heavy use of social media on

mental health among mental health practitioners.

• Hypothesis III: Mental health practitioners who completed some

training on social media will have greater knowledge about the impact

of social media on mental health as opposed to their non-trained

counterparts.

• Hypothesis IV: There will be a statistically significant difference in the

level of social media contents in assessments between agencies that

are proactive on the impact of heavy use of social media and those

that are not.

• Hypothesis V: There will be a statistically significant difference in the

level of social media contents in treatment between agencies that are

proactive on the impact of heavy use of social media and those that

are not.

Data Analysis

For the quantitative portion of this mixed-methods study, the researchers

analyzed the data through IBM SPSS 26.0. Due to the non-normal distribution of

the data, the researchers ran two non-parametric tests: Man-Whitney U Test and

Spearman Correlation Test. These tests measured allowed the researchers to

validate or refute the study hypotheses. For its qualitative portion, this study used

thematic analysis, a process through which participants’ answers are coded and

then clustered based on similarity to form themes.

CHAPTER FOUR

RESULTS

Frequency Distributions

Table 2 presents the demographics for the 95 participants of this study.

Findings within this table show that three quarters of the participants identified as

White, leaving a quarter of the participants non-White. A majority of the

participants of this study were female, with very few male respondents. With

regard to age group, two-thirds of the participants were between 18 and 34 years

old. Participants that were licensed made up one-third of the responses, whereas

two-thirds of participants were non-licensed. A little less of a quarter of the

participants lived in California while a little more than three-quarters resided

outside of California. A little more than a quarter of participants have received

training on the impact social media has on mental health. Finally, a quarter of

participants agreed that their agency values the integration of social media and

mental health. For further breakdown, refer to Table 2:

Table 2. Frequency Distributions of Study Variables (N = 95)

Variables

Race

100

White

74.7

Non-White

25.3

Gender

100

Female

92.6

Male

7.4

Age Group

100

18-34

67.4

35 and over

32.6

Education

100

Licensed Clinicians

33.7

Non-Licensed Clinicians

66.3

Years in Practice

100

5 years of experience or more

50.5

Less than 5 years of experience

49.5

Region of Practice

100

Inside California

27.4

Outside California

72.6

Training on Impact of SM on Mental Health

100

Yes

28.4

71.6

Agency Values Integration of SM Assessment

100

Yes

23.2

76.8

Presentation of the Findings

Quantitative Findings

Hypothesis I. Due to the increased mental health symptoms associated

with heightened social media use, the researchers hypothesized that the

proportion of mental health practitioners who believe in a monotonic correlation

between heavy use of social media and adverse mental health consequences

would be superior or equal to 75 percent. Figure 1 details that all 95 participants

answered “yes” when asked about their belief regarding social media’s impact on

mental health, proving Hypothesis I to be true.

Figure 1. Belief of Social Media Impact on Mental Health

100%

Yes No

Hypothesis II. Similar to yet different form Hypothesis I, Hypothesis II

predicted a high level of awareness (at least 75 percent) about the negative

impact of heavy use of social media on mental health among mental health

practitioners. Figure 1 details how participants rated their level of awareness

about the negative impact heavy use of social media has on mental health.

Slightly half of the participants rated themselves to have minimal/somewhat

knowledge, while the other half are average/very knowledgeable. The majority of

respondents (around two-thirds) identified as having moderate knowledge of the

impact social media has on mental health, whereas less than one-fourth of

participants rated themselves as very knowledgeable and the remaining

respondents rated themselves as minimal. Hence, Hypothesis II was not

supported.

Figure 2. Knowledge of Social Media Impact on Mental Health

16%

32%

34%

18%

Mininmal/Fair Knowledge Somewhat Knowledgeable

Average Knowledge Very Knowledgeable

Hypothesis III. Table 3 details the findings for the Mann-Whitney Test with

respect to the relationship between mental health practitioner’s prior training and

the knowledge mental health practitioners have regarding the impact social

media has on mental health. As indicated in Table 3, there was a statistically

significant difference in the amount of knowledge about social media’s impact on

mental health when comparing mental health practitioners who completed some

training on social media to their non-trained counterparts (Z = -3.353, p < .001).

The size of the relationship between prior training and knowledge was moderate

(r = .34). In other words, prior training explained 12 percent of the variance in the

dependent variable (r

= .12). Hence, Hypothesis III was supported.

Since Mann-Whitney U Test does not allow the simultaneous analysis of

variables, the researchers ran separate tests to control for the other predictors.

As exhibited in Table 3, only education yielded a statistically significant

relationship with the dependent variable [knowledge a mental health practitioner

had about social media having an impact on an individual’s mental health] (Z= -

2.469, p < .014). The strength of the relationship between the level of education

and social media knowledge was minimal to moderate (r = .25). This also means

that education explained 6 percent of the variance in the dependent variable (r

.06).

Table 3. Knowledge of Social Media Impact on Mental Health

Asymptotic significance results for variables in Mann-Whitney U Test (N = 95)

Hypothesis IV. Table 4 details the findings for the Mann-Whitney Test with

respect to the relationship between an agency social media culture/value and

integration of social media contents in assessment. As indicated in Table 4, there

was a statistically significant difference in the level of social media contents in

assessments between agencies that are proactive on the impact of heavy use of

social media and those that are not (Z= -5.035, p < .000). This was a strong

correlation (r = .52). This result indicates that the predictor “agency value” by

itself explained 27 percent of the variance of the dependent variable [integration

of social media contents in assessments] (r

= .27). Thus, Hypothesis IV was

supported.

Variables

2-tailed α*

Z-Score r r

Race

.125

-1.535

Gender

.948

-.065

Age

.473

-.717

Education

.014

-2.469 .25 .06

Years in practice

.676

-.418

Region of practice

.223

-1.219

Prior training

.001

-3.353 .34 .12

Agency values

.198

-1.289

*Alpha level (p < .05)

In this model, the other predictors did not correlate with the dependent

variable, except for “prior training” (Z= -2.300, p < .021). The relationship

between the two variables was small to moderate (r = .24). Hence, in terms of

contribution, prior training explained 6 percent of the variable in integration of

social media contents in assessment (r

= .06). In sum, the total contribution of

the variables in the model (agency value and prior training) was 33 percent (r

.33). In other, there was a 67% coefficient of alienation (unexplained variance) in

this model.

Table 4. Integration of Social Media Topic in Assessment

Variables

2-tailed α*

Z-Score r r

Race

.727

-.322

Gender

.189

-1.313

Age

.531

-.627

Education

.315

-1.006

Years in practice

1.70

-1.373

Region of practice

.358

-.920

Prior training

.021

-2.300 .24 .06

Agency values

.000

-5.035 .52 .27

*Alpha level (p < .05)

Asymptotic significance results for variables in Mann-Whitney U Test (N = 95)

Hypothesis V. Table 5 details the findings for the Mann-Whitney Test with

respect to the relationship between an agency social media culture/value and

integration of social media contents in treatment. As indicated in Table 5, there

was a statistically significant difference in the level of social media contents

during treatment between agencies that are proactive on the impact of heavy use

of social media and those that are not (Z = -4.385, p < .001).

Alternatively, the researchers ran the Spearman Correlation Test

(Spearman's Rho) to evaluate the relationship between an agency social media

value and integration of social media contents in treatment. There was enough

evidence to suggest a positive correlation between an agency’s social media

culture/value and integration of social media contents in treatment r

(93) = .50, p

< .001. This was a strong difference (r = .50). The coefficient of determination (r

)

revealed that agency social media value explains 20-25 percent of the variance

in the integration of social media contents in treatment. Hence, Hypothesis V was

supported.

Again, prior training correlated with the dependent variable [integration of

social media contents in treatment] (Z= -3.099, p < .002). This was a moderate

correlation (r = .32) that explains 10 percent in the variable of the dependent

variable (r

= .10). The other predictors—race, gender, age, education, years of

practice had no statistically significant relationships with the dependent variable

(integration of social media contents in treatment). Therefore, the whole model

explained 30-35 percent of the variance in the dependent variable. In other

words, 65 to 70 percent of the variance in the dependent variable remains

unexplained.

Table 5. Integration of Social Media Topic in Treatment

Variables

2-tailed α*

Z-Score r r

Race

.733

-.341

Gender

.621

-.495

Age

.962

-.048

Education

.160

-4.04

Years in practice

.304

-1.027

Geography

.470

-.723

Prior training

.002

-3.099 .32 .10

Agency social media values

.000

-4.385 .45 .20

*Alpha level (p < .05)

Asymptotic significance results for variables in Mann-Whitney U Test (N = 95)

Qualitative Findings

From the responses from participants, two main themes emerged from the

data. Each major theme had subthemes which are detailed in Table 6.

Participants reported that increased social media use can have both negative

and positive impacts on an individual’s mental health. The subthemes that

emerged for negative impacts are low self-esteem, depression, and anxiety. The

subtheme that emerged from the positive responses was social

support/connection.

Table 6. Major Beliefs of Social Media’s Impact on Mental Health

1) Negative Impacts

a. Low Self-esteem

b. Increased Depression

c. Increased Anxiety

2) Positive Impacts

a. Increased Social Support/Connectedness

The first subtheme that emerged from the data was low self-esteem as a

result of heightened social media use. Over one-third of participants mentioned

that individuals that engage in high levels of social media use tend to have lower

self-esteem. Participants identified low self-esteem as: individuals comparing

their lives to others on social media, increased levels of body shame, unrealistic

expectations for one’s life, and not feeling adequate enough. Additionally,

participants included the idea of seeking approval by frequently checking their

social media posts and desiring a certain number of likes/responses to posts in

order to feel validated. Participants reported:

• Participant #20: Body image, relationships, misrepresentation and

distorted view of what a perfect life is. This can have a negative impact on

mental health (self-esteem)

• Participant #34: Comparing the highlights of others’ lives to your regular

daily life/routine can cause depression. Always felling

connected/monitored and/or expected to “keep up” with others can cause

anxiety

• Participant #40: Impacts on self-image and self-worth, either because of

comparison to others’ content or because of a drive for external validation

through likes/comments

• Participant #52: Social media is based on ideals. If all we're seeing on

social media is the very best of what people want to portray, that can

negatively affect how we see our own lives which are definitely not always

picture perfect

The second subtheme that emerged from the data that falls within the

negative impacts of social media use on mental health was depression. The

result of low self-esteem and negative self-image can lead to higher rates of

depression, as discovered in the responses of participants. Participants gave

examples of how social media can impact an individual’s mental health by

increasing depressive symptoms such as: isolation, suicide ideation, and

loneliness. These symptoms all correspond with criteria required for the DSM-5

diagnosis of depression. Additionally, many respondents included that

cyberbullying can play a large part in increased depressive symptoms, like

suicidal ideation. Participants reported:

• Participant #22: Increase isolation, depressive symptoms, increase suicide

ideation

• Participant #43: Feelings of isolation, loneliness, social anxiety, potential

other phobias, cyberbullying affecting mental health

• Participant #75. I have seen many stories and worked with many clients

that have committed suicide, attempted or had SI because of social media

bullying and so on

The final major subtheme that emerged from that data that falls within the

negative impacts of social media on mental health was anxiety. A quarter of

participants identified anxiety as a key response to heightened social media use.

Respondents used the following terms while describing anxiety: social anxiety,

isolation, increased distractions, difficulty sleeping and increased phobias.

Respondents noted that increased feelings of anxiety can be attributed to

comparative thinking, assessing one’s life based on that of others, and a

constant need to check one’s social media accounts. Participants reported:

• Participant #21: It tends to increase anxiety, depression, and loneliness. It

increases comparative thinking

• Participant #43: Feelings of isolation, loneliness, social anxiety, potential

other phobias, cyberbullying affecting mental health

Although the majority of responses received were exemplifying the

negative impacts social media has on mental health, several mental health

practitioners identified positive components of social media use. The key

subtheme recognized was social support/connectedness. Respondents stressed

the impact of an individual’s social media use was dependent on each

individual’s situation. Participants urged that individuals that had healthy

boundaries while using social media can see many positive outcomes.

Additionally, participants emphasized the community and support systems that

can be gained through social media are not constrained to geographical locations

and allows users to connect with people with similar circumstances, beliefs or

needs. Participants reported:

• Participant #7: Creating community, esp. for people who feel isolated due

to things like disability, not knowing people with shared experiences IRL

(in real life)

• Participant #35: I believe seeing positive things can improve ones mental

health. When social media is used to connect people in a positive way it

would improve mental health and decrease isolation

• Participant #50: In some ways it is helpful in providing a support system to

those with mental health related concerns

• Participant #65: Social media allows individuals to connect instantly,

regardless of distance. This may be beneficial for keeping relationships

with those when no longer living close

Overall, the qualitative findings of this research study conclude that all

mental health practitioners that participated in this study believe that mental

health is impacted by social media use. A large percentage of participants

identified the negative impacts social media has on mental health, such as: lower

self-esteem, depression and anxiety. There were several respondents that

identified positive impacts social media use can have on mental health, with the

main theme being social support and connectedness.

CHAPTER FIVE

DISCUSSION

Overview

The purpose of this study was to explore mental health practitioners’

knowledge, assessment and treatment for social media’s impact on mental

health. Given the technological advancements of the 21

century, individuals are

engaging in increased social media use as the main form of communication with

peers and family. Considering the impact that researchers are finding, the need

for knowledge about social media’s negative impacts is crucial in how mental

health practitioners assess and treat mental health symptoms and the modalities

agencies use across the globe. This study used a mixed methods survey which

was distributed using online platforms and snowball sampling. 95 mental health

practitioners from around the globe responded to both qualitative and quantitative

portions. For the quantitative data, the researchers used nonparametric methods

and descriptive statistics to test the study hypotheses. Overall, the study

hypotheses (one excepted) were supported. The data indicated that practitioners

with higher levels of education and trainings about social media had more

knowledge about the impact social media has on mental health. Additionally, the

data suggested that agencies that value the integration of social media and

mental health, often had questions regarding mental health on assessment forms

and more frequently had the topic of social media use arise during assessment

and treatment.

The qualitative findings for this research indicated that practitioners have

seen both positive and negative impacts on individual’s mental health due to

social media use. Common themes that surfaced regarding negative impacts

included: low self-esteem, higher rates of depression, and anxiety. Practitioners

described the positive impacts of social media use being increased social

support and connectedness.

Consistency with Previous Research

The findings of this research are consistent with previous studies in the

field, mainly those that highlight the impact of heightened use of social media has

on mental health (Ashford, 2017; Hardy & Castonguay, 2018; Hussain & Griffiths,

2018). In fact, findings in this research indicate that depression, anxiety and self-

esteem are mental health disorders associated with heavy consumption of social

media. These findings are similar to the ones found in the existing literature

(Ashford, 2017; Hardy & Castonguay, 2018; Hussain & Griffiths, 2018).

Meanwhile, previous research indicates that individuals of diverse

backgrounds may have positive experiences using social media due to the

reduction of barriers by increased access to mental health treatment as well as

connection with individuals with similar needs or backgrounds (Andrews et al.,

2018; Henderson et al., 2013; Naslund & Riefer, 2018; Naslund et al., 2017;

Grove, 2019; Lattie et al., 2019). This study did not find a correlation to

participants’ responses regarding increased access to mental health treatment.

However, the current research study found that mental health practitioners

believe social media use can have a positive impact on mental health by

increasing social support and connection of individuals that may otherwise have

difficulty connecting with others.

Implications

Implications for Theory

This research used Systems theory and Generalist Interventions Model

(GIM) to guide and conceptualize the ideas found in the data. Systems theory

acknowledges the impact different systems have on the development of an

individual. Different systems include family, technology, and environment. As

identified in Systems Theory perspective, an individual’s behavior can be

impacted by the direct and indirect involvement with the micro, mezzo, and

macro systems that surround them (Bronfenbrenner, 1979). Thus, social media

has been identified as a system that can impact symptoms associated with

mental health. The findings of this research illustrate support for Systems Theory

as 100% of participants agreed that social media impacts an individual’s mental

health.

Additionally, by directly addressing two main tenets in the GIM

(assessment and intervention/treatment), this study also has implications for this

model. The goal of the GIM is to guide practitioners toward identifying different

stressors in a client’s system while providing interventions that address mental

health symptoms and help improve overall well-being. This is accomplished by

the completion of a thorough bio-psycho-social-spiritual assessment and

appropriate therapeutic techniques during mental health treatment. The outcome

of effective treatment is dependent on the needs identified in the assessment.

The results in this research reveal that when agencies value the integration of

social media and mental health, there is more incorporation in assessment and

treatment.

Implications for Research

Although there are several studies completed about the impact social

media can have on mental health, the literature is limited regarding the specific

actions mental health practitioners should take in response to increased mental

health symptoms related to social media use. The current research study made a

significant contribution to the literature by exploring an under-researched area.

The main discovery of this research was the correlation between an agency’s

values and integration of social media content in assessment and treatment

planning. Moreover, this research contributes to the importance of mental health

practitioners staying current and proactive in expanding their knowledge about

the systems that impact an individual’s well-being, such as technological

advances like social media. Finally, this research brings awareness to the

significance of including questions and exploration of social media use on

assessment forms and in mental health treatment.

Implications for Social Work Practice

The findings of this study hold significant implications for social work

practice at all levels of intervention: micro (individuals), mezzo (family systems),

and macro.(mental health/social service organizations). The findings of this study

identified significant themes while evaluating mental health practitioners'

knowledge of social media impact on mental health. The themes showed that a

limited number of mental health agencies are incorporating social media

screening during the assessment phase of treatment, in addition to identifying

mental health practitioners' need for more training on the negative and positive

impacts of social media use. These findings identified gaps in social work service

provision, assessment, and treatment.

The implications for micro social work practice focus on service provision

on the individual level of treatment with clients. This implication will directly

impact the area of evaluation through the person-in-environment approach,

where mental health professionals screen individuals for social media use in the

biopsychosocial assessment phase. This incorporation of social media screening

in assessment can ensure that individuals affected by this issue are identified

and provided treatment accordingly. Additionally, when a practitioner is trained

and knowledgeable about mental health impact due to social media, practitioners

can provide individuals with effective treatment intervention and modalities such

as Cognitive Behavioral Therapy (CBT) to address symptoms of depression, self-

esteem, and anxiety through reframing techniques.

The implications for social work practice on the mezzo system of the

family can include providing psychoeducation about both the negative and

positive impacts social media can have on mental health. Providing education

about social media impacts on mental health may offer family systems new ways

of addressing the overuse of social media. Furthermore, social media can be

utilized in positive ways for family systems to identify education about mental

health diagnosis, treatment, and management for family members.

The implications for social work on the macro setting of mental

health/social work level are the need for agencies to provide more training on

social media impact on mental health. These pieces of training will directly impact

social work practice by providing more knowledge, awareness, and inclusion of

social media into the field of practice. Additionally, incorporation of social media

use in the General Intervention Model (GIM) on assessment forms will ensure

that the topic of social media addressed as a potential contributing factor to

mental health symptoms. Furthermore, social work practice implications on the

macro level include the need to for social workers and mental health practitioners

to advocate for the inclusion of social media as a diagnosis in the Diagnostic

Statistical Manual (DSM-5) to guarantee widespread acceptance of social media

impact on mental health in the service field.

In effect, statistics show that nearly 8 in10 Americans use social media,

which amounts to a total population basis of 68% on Facebook, 21% on Twitter,

25% on Pinterest, and 26% on Instagram (Greenwood, Perrin & Duggan,

2018). The social work profession prides itself on completing a full

biopsychosocial assessment to gather all information and systems of clients in a

holistic approach. With this standard in mind and the amount of Americans using

social media, the appropriate incorporation of social media into the field of social

work should appear as an essential area of growth in the field.

Implications for Social Work Education

This study has implications for social work education. In fact, social work

curriculum developers and social work educators can ensure that students

understand the impact of social media on mental health and identify ways to

assess and address social media-related issues. This can be achieved through

seminars, trainings, and classroom discussions about the signs and symptoms

associated with heightened social media use. In other words, social work

education can expand students’ knowledge about different systems that impact

an individual, including social media, and educate on effective treatment options

to address mental health symptoms associated with social media use.

Incorporating social media content into social work curricula is important,

as many social work students, once completing their education, work in mental

health settings. These students can address the gap in service provision

exposed in this study with a balanced curriculum that accounts for the impact of

social media. Form a macro aspect of social work education, faculty can

encourage students to advocate and lobby for changes in the DSM-5 as well as

safer ways the government and technology giants can protect consumers of

social media.

Limitations and Recommendations

Although every effort was made to address any limitations, this study was

not exempt from shortcomings. The biggest limitation in this study was the

relatively small sample size (n = 95); however, the sample size is considered

decent due to the exploratory nature of the research. Additionally, the non-

parametric method was not the strongest data analysis approach. Yet, this was

the appropriate approach for this study, considering the non-normal distribution

of the data. Furthermore, due to the cross-sectional nature of this study, there

was a lack of observation over time. The lack of randomization also rules out any

inferential interpretation of the findings. This was just a correlation study. Finally,

this research did not include all the possible predictors, as a large proportion of

the variance of the key dependent variables are still unexplained. Therefore,

based on the aforementioned limitations, the results should be interpreted with

caution.

Future research should attempt to address the shortcomings of this study.

Researchers who desire to expand or duplicate this research should incorporate

a stronger method for participant recruitment as well as using a longitudinal

approach to observe participants’ responses overtime. A greater sample size and

stronger data analysis method can help address internal validity issues this

research is possibly guilty of. Future research can build on this study’s findings

by exploring what barriers agencies are experiencing integrating social media

use in mental health treatment. The goal of future research should be about

producing generalizable knowledge. In the meantime, the findings in this study

constitute a fulcrum through which scholars and researchers can inform

themselves on mental health providers’ behaviors vis-à-vis the inclusion of social

media content in assessment and treatment planning.

APPENDIX A:

SURVEY

Mental Health Practitioner’s Assessment of Social Media Use

Demographic Information

1. Age ___________

2. Gender

o Male

o Female

o Other, please specify: ________________________________________________

3. Ethnicity

o Asian

o Black/African American

o Hawaiian/Pacific Islander

o Hispanic/Latino

o Indian/Alaskan

o White/Caucasian

o Prefer not to say

o Other, please specify: ________________________________________________

4. Level of Education

o Some College

o Bachelor's Degree (include major) __________________________________________

o Master's Degree (include major) ____________________________________________

o License (include title) ________________________________________________

o Doctorate (include title) ________________________________________________

5. Time in Practice (in years) __________________________________________________

6. Area of Practice (City, State) ________________________________________________

Mental Health Practitioner’s Assessment of Social Media Use

Survey Questions

7. How knowledgeable are you about social media impact on mental health?

8. On a scale of 0-10, where do you rate your knowledge about social media impact on mental

health?

9. Do you believe that social media can have an impact on an individual’s mental health?

o Yes

o No

10. Regarding the previous question, if you answered yes, what impact can social media have

on mental health? If you answered no, enter N/A.

11. Have you ever attended trainings regarding the impact of social media use on mental

health?

o Yes

o No

12. Has your agency ever provided training regarding the impact of social media use on mental

health?

o Yes

o No

13. Do you incorporate social media use during your mental health assessments?

o Yes

o No

14. On a scale of 0-10, how much do you incorporate social media use during your mental

health assessments?

Developed by: Sarah N. Koehler and Bobbie R. Parrell, Advanced Year MSW Candidates

Mental Health Practitioner’s Assessment of Social Media Use

15. Does your agency value the integration of social media impact in mental health

assessment?

o Yes

o No

16. On a scale of 0-10, how much does your agency value the integration of social media

impact during mental health assessment?

17. Does your agency’s assessment form include any questions regarding social media use?

o Yes

o No

18. On a scale of 0-10, how often does the topic of social media use arise during individual

sessions?

19. What would you recommend for agencies to do to assess the impact of social media use on

clients?

20. What would you recommend for agencies to do to treat/address the impact of social media

use on clients?

APPENDIX B:

INFORMED CONSENT

APPENDIX C:

INSTITUTIONAL REVIEW BOARD APPROVAL

REFERENCES

Andrews, G., Basu, A., Cuijpers P., Craske, M. G., McEvoy, P., English, C.L., &

Newby, J. M. (2018). Computer therapy for the anxiety and depression

disorders is effective, acceptable and practical health care: an updated

meta-analysis. Journal of Anxiety Disorders, 55, 70-78.

Ashford University. (2017, December 14). Causes of social media addiction

illness. Retrieved by https://www.ashford.edu/online-degrees/student-

lifestyle/causes-of-social-media-addiction-illness

Belluomini, E. (2015). Turn up the tech in social work: the internet made me

depressed: emotional contagion through social media. The New Social

Worker, 22(3), 31.

Bronfenbrenner, U. (1979). The ecology of human development: Experiments by

nature and design. Cambridge, MA: Harvard University Press.

Ebear, J., Csiernik, R., & Béchard, M. (2008). Applying the generalist model of

social work practice for a Catholic Church parish team. Journal of Religion

& Spirituality in Social Work: Social Thought, 27(1-2), 105-121.

Fairburn, C., Lane, C., Mataix-Cols, D., Tian, J., Grant, J., & Deneen, K. M.

(2019, May 13). Five new mental disorders you could have under DSM-5.

Retrieved from https://theconversation.com/five-new-mental-disorders-

you-can-have-under-dsm-5-14192

Forte, J. A. (2004). Symbolic interactionism and social work: A forgotten legacy,

Part 1. Families in Society, 85(3), 391-400.

Greenwood, S., Perrin, A., Duggan, M., Greenwood, S., Perrin, A., & Duggan, M.

(2017, May 18). Demographics of Social Media Users in 2016. Retrieved

from https://www.pewinternet.org/2016/11/11/social-media-update-2016/

Gregory, C. (2019). Internet addiction disorder- signs, symptoms, and

treatments. Retrieved from https://www.psycom.net/iadcriteria.html

Griffiths, M., & Szabo, A. (2013). Is excessive online usage a function of medium

or activity? an empirical pilot study. Journal of Behavioral Addictions, 3(1),

74-77.

Grové, C. (2019). Using social networking sites in research: An emerging

approach to engaging with young people who have a parent with a

mental illness and/or substance abuse disorder. Frontiers in Psychiatry,

10, 281.

Hardy, B. W., & Castonguay, J. (2018). The moderating role of age in the

relationship between social media use and mental well-being: An analysis

of the 2016 General Social Survey. Computers in Human Behavior, 85,

282-290.

Henderson, C., Evans-Lacko, S., & Thornicroft, G. (2013). Mental illness stigma,

help seeking, and public health programs. American Journal of Public

Health, 103(5), 777-780.

Huang, C. (2017). Time spent on social network sites and psychological well-

being: A meta-analysis. Cyberpsychology, Behavior, and Social

Networking, 20(6), 346-354.

Hussain, Z., & Griffiths, M. D. (2018). Problematic social networking site use

and comorbid psychiatric disorders: A systematic review of recent large

scale studies. Frontiers in Psychiatry, 9, 686.

Joseph, R., & Macgowan, M. J. (2019). The theory evaluation scale: An

epistemological tool for analyzing social work theories. Social Work

Education, 38(2), 269-281

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges

and opportunities of Social Media. Business Horizons, 53(1), 59-68.

King, D. L., Delfabbro, P. H., Griffiths, M. D., & Gradisar, M. (2011). Assessing

clinical trials of Internet addiction treatment; A systemic review and

consort evaluation. Clinical Psychology Review, 31(7), 1110-1116.

King, D. L., Delfabbro, P. H., Griffiths, M. D., & Gradisar, M. (2012). Cognitive-

behavioral approaches to outpatient treatment of Internet addiction in

children and adolescents. Journal of Clinical Psychology, 68(11), 1185-

1195.

Kowalski, R. M., Toth, A., & Morgan, M. (2018). Bullying and cyberbullying in

adulthood and the workplace. The Journal of Social Psychology, 158(1),

64-81.

Lattie, E. G., Lipson, S. K., & Eisenberg, D. (2019). Technology and College

Student Mental Health: Challenges and Opportunities. Frontiers in

Psychiatry, 10, 246.

Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., &

Primack, B. A. (2016). Association between social media use and

depression among US young adults. Depression and Anxiety, 33(4), 323-

331.

Lowry, P. B., Zhang, J., Wang, C., & Siponen, M. (2016). Why do adults engage

in cyberbullying on social media? An integration of online disinhibition and

deindividuation effects with the social structure and social learning model.

Information Systems Research, 27(4), 962-986.

Naslund, J. A., Aschbrenner, K. A., McHugo, G. J., Unützer, J., Marsch, L. A., &

Bartels, S. J. (2019). Exploring opportunities to support mental health care

using social media: A survey of social media users with mental illness.

Early Intervention in Psychiatry, 13(3), 405– 413.

https://doi.org/10.1111/eip.12496

Naslund, J., & Riefer, M. (2018, May 23). Engagement and recovery:

Social media/technology for outreach and engagement [Webinar]. In

Recovery to Practice, SAMSHA Webinar Series. Retrieved from

https://www.samhsa.gov/sites/default/files/sites/default/files/engagement

social media-rev_2cor-5-19-2018-final.pdf

Pantic, I. (2014). Online social networking and mental health. Cyberpsychology,

Behavior, and Social Networking, 17(10), 652-657.

Van den Eijnden, R.J., Lemmens, J.S., & Valkenburg, P.M. (2016). The social

media disorder scale. Computer in Human Behavior, 61, 478-487.

Young, K. (2009). Internet addiction: diagnosis and treatment considerations.

Journal of Contemporary Psychotherapy, 39(4), 241-246.

Zastrow, C. H., & Kirst-Ashman, K. K. (2016). Understanding Human Behavior

and the Social Environment. Boston: Cengage Learning.

ASSIGNED RESPONSIBILTIES

The researchers Sarah Koehler and Bobbie Parrell completed this project

wholeheartedly and collaboratively. Each researcher equally voiced opinions and

ideas which made this research possible. Sarah and Bobbie both have high

levels of interest in the research topic, which made communication and group

work successful. Additionally, researchers provided and welcomed mutual

feedback that helped contribute to the final result of this project. Collaborative

effort to complete each section is as follows:

• Introduction

• Literature Review

• Methods

• Results

• Conclusion

Both Sarah Koehler and Bobbie Parrell contributed to the formatting,

editing, and revisions process throughout the preparation of this paper for

submission.