A research paper on Smartphone Addiction Among Students
Research Paper Topic and Thesis Statement
Smartphone Addiction as a Predictor of Interpersonal Relationship and Loneliness in Students
First of all ,I thank Allah almighty, the most gracious and compassionate, whose endless blessing provide me with hope, courage and patience to accomplish my target in life. During my research work I came across several individuals without whom the research work could not have been completed. I am indebted to thank my people who supported me with their guidance, encouragement and friendship during different stages of m research project.
First and foremost of all I would like to express my gratitude for the continuous guidance of my research supervisor, Institute of Applied Psychology. I thank her for admirable tolerance and endurance during the process of research work. In spite of her different official engagement she always made herself available to provide me with her advice and guidance. I would like to thanks heads of educational institutes who gave me permission to collect the data and also to participants for giving me required information. I would like to thanks Kwon, Parker, Cohen, Hoberman, and Russell who gave me permission to use their tools.
I would like to show appreciation for my parents who gave me their unstained support and always prayed for attainment of my goals. Their encouragement and prayers never allowed to tire down. Finally I can’t forget to thank library and computer staff for their full cooperation and help in acquisition of knowledge.
Smartphone Addiction Among Students – Table of Contents
- Title Page
- Table of Contents
- List of Tables
- List of Appendices
- List of Abbreviations and Symbols
- 1.1 Smart Phone
- 1.1.1 From a habit to smart Phone addiction
- 1.1.2 Habit Forming and Smart phone
- 1.1.3 Addiction
- 1.1.4 Behavioral addiction
- 1.1.5 Smartphone addiction
- 18.104.22.168 (Online) Social network
- 22.214.171.124 Dependency
- 126.96.36.199 Connection worldwide
- 188.8.131.52 Feeling of control
- 184.108.40.206 Permanent Mobility
- 220.127.116.11 Entertainment
- 1.1.6 Theoretical perspective
- 18.104.22.168 Relational Dialectics Theory
- 22.214.171.124 Uses and Gratifications Theory
- 1.2 Interpersonal relationship
- 1.2.1 Need to belong
- 1.2.2 Social exchange
- 1.2.3 Relational-self
- 1.2.4 Power and Dominance
- 1.2.3 Stages
- 1.2.4 Theoretical Perspective
- 126.96.36.199 Confucianism
- 188.8.131.52 Minding Relationship
- 1.3. Loneliness
- 1.3.1 Typology
- 1.3.2 Theoretical Perspective
- 184.108.40.206 Attachment theory
- 220.127.116.11 Behavioral approach
- 18.104.22.168 Cognitive approach
- Literature review
- 2.1 International researches
- 2.2 Indigenous researches
- 2.3 Rational
- 2.4 Objective
- 2.5 Hypothesis
- 3.1 Research design
- 3.2 Sample
- 3.2.1 Inclusion criteria
- 3.2.2 Exclusion criteria
- 3.3 Operational definitions
- 3.3.1 Smart Phone addiction
- 3.3.2 Interpersonal Relationship
- 3.3.3 Loneliness
- 3.4 Assessment measure
- 3.4.1 Demographic questionnaire
- 3.4.2 Smart Phone Addiction Scale – Short Version
- 22.214.171.124 Pilot testing
- 3.4.2 Interpersonal Support Evaluation List-short Version
- 3.4.3 UCLA Loneliness Scale
- 3.5 Ethical Consideration
- 3.6 Procedure
- 3.7 Statistical Analysis
- 4.1 Reliability Analysis
- 4.2 Correlation
- 4.3 Hierarchical Regression
- 4.5 Additional Analysis
- 4.6 Summary of Findings
- 5.1 Limitation
- 5.2 Recommendation
- 5.3 Implications
List of Tables
- Table 3.1 Descriptive statistics of demographic characteristics of study sample (N=150).
- Table 4.1 Reliability Coefficients of the Scales Used in the Present Study (N=120).
- Table 4.2 Correlation among demographic variables and smart phone addiction,inter personal relationship and loneliness.
- Table 4.3 A hierarchical Regression Analysis Predicting smart phone addiction,inter personal relationship and loneliness (N=120)
List of Appendices
- Appendix A Authority Letter
- Appendix B Permission from Authors of Assessment Measures
- Appendix C Consent Form
- Appendix D Demographic Information Sheet
List of Abbreviations and Symbols
- f = Frequency
- % = Percentage
- P = Significance Value
- N = Total no of Items
- N = Number of Participants in a Group
- SD = Standard Deviation
- M = Mean
- α = Reliability Coefficient
- β = Standardized Regression Coefficient
The present study on Smartphone Addiction Among Students aimed to investigate the smartphone addiction as a predictor of interpersonal relationship and loneliness in university students. It was hypothesized that smartphone addiction would be negatively correlated with of interpersonal relationship and positively correlated with loneliness. Moreover, it was also hypothesized that smartphone addiction would be the negative predictor of interpersonal relationship and positive predictor of loneliness in university students. Furthermore, it was hypothesized that there would be the higher level of smartphone addiction in woman than men. Correlation research design was used in this study and the sample was comprised of (N=100) orphans and (n=45) men and (n=55) woman with age range 18-28 years (M=22.07, SD=2.29). Smartphone Addiction Scale-Short Version (Kwon et al. 2013), Interpersonal Support Evaluation List – Short Version (Cohen & Hoberman, 1983) and UCLA Loneliness Scale – Version 3(Russell et al., 1978) was used to assess the smartphone addiction , interpersonal relationship and loneliness. Data was analyzed in SPSS. Results indicated that smartphone addiction was negatively correlated with interpersonal relationship and positively correlated with loneliness in university students. Moreover, it was found that smartphone addiction was negative predictor of interpersonal relationship and also positive predictor of loneliness in university students. In addition, the finding showed that women have a higher level of smartphone addiction than men. The study has important implication in an education setting to integrate understanding the problem of smartphone addicted students and the effect on their performances, resolving their conflicts with teachers and peers. Moreover, in counseling field to enhance their interpersonal relationship circle and for the motivation of academic performance.
Key words: Smartphone Addiction, Interpersonal Relationship, Loneliness and Gender Difference
Now a day our personal life is highly dependent on the technology that people have developed. Technology has advanced with years and it has changed the way we purchase products, the way we live , the way we communicate , the way we travel , the way we learn and so many changes have been brought about by these continuous technological advancements. When we talk about the mobile phone the type of mobile phones we had in 1995 are no longer on demand in this century, the demands of mobile phone users have changed greatly, Now people demand simplicity and more functionality, which has forced mobile phone manufactures to develop computer minded smart phones, which are so easy to use, but also they come with more functionality compared to the type of mobile phones we used to have in the past. Recently, smartphone addiction has emerged as a significant problem among users (Kwon et al., 2013). Smartphone users could access information and entertainment content almost everywhere whenever they want to. This could lead to addiction in the form of frequent checking or habitual checking (Lee, 2015; Oulasvirta et al.,2012). People are now less attentive to whom they are with in person and indulge themselves in their smartphones, (Wei & Leung, 1999). In addition, past research has found that lonely people and shy people are more likely to be addicted to different substances.
1.1 Smart Phone
The smartphone is a most popular mobile device, most people own a smartphone, it is commonly used, there is a large number of applications available and it is more affordable than a tablet. In addition, due to its small size and functions, this device is carried around most. Smartphones are carried everywhere: in bed, at the restroom, at work, at restaurants, etc. Therefore, smartphone devices are different from other mobile or technical devices, as they are extensions of the human being (Mcluhan, 1964). As usage per device is different, it is important to choose one device.
Smartphones have unique factors, such as size, screen size, applications, ubiquity, and flexibility in both time and space (Nielsen & Fjuk, 2010). The smartphone is an extension of many people lives; due to its size and features it is carried around 24/7by its owner. Different applications promote the 24/7 usage of smartphones and the need of being online (Okazaki & Hirose, 2009). Applications are suitable in different contexts, like mobile internet, camera, telephone connection, agenda, among many more downloadable applications. Life without a smartphone is for many people unthinkable; thus, people are getting in some way dependent on their smartphone (Haverlag, 2013). Thus, the use of smartphones is intense because it is always accessible.
1.1.1 From a habit to smartphone addiction.
The smartphone is 24/7 accessible with applications that stimulate its continuous usage. These devices could lead to excessive and impulsive behavior because of problematic habitual evolvement (Oulasvirta, Rattenbury, Ma, &Raita, 2011).
1.1.2 Habit forming and smartphones.
Online mobile applications on smartphones can cause habits (Oulasvirta, Rattenbury, Ma &Raita, 2011). How do habits develop and become addictive? Habits are formed through repeated acts in certain circumstances (Oulasvirta et al., 2011). In cognitive research, habits are defined as “an automatic behavior triggered by situational cues, such as places, people, and preceding actions (Oulasvirta et al., 2011). Habits are behavioral acts without self-instruction or conscious thinking (La Rose & Eastin, 2004).
Habits can have both positive and negative effects (Wood & Neal, 2007). Positive effects of habits line in that, due to the fast automatic behavior aspect, they enable multitasking and accomplishment of complex tasks. Habits give control over behavior in novel situations, where fast anticipation is needed (Wood & Neal, 2007). Habits have also a positive social feature, because they identify a person, because habit characterizes a person and predicts that person’s actions (Oulasvirta, et al., 2011; Wood & Neal, 2007). On the other hand, habits can have a negative influence on someone’s behavior. They can cause unintended behavior activated by internal or external cues interfering other acts. This is also called maladaptive habits, as people create excessive urges, for example, unintended smartphone checking. It could interfere with daily life; however, due to regulations or social norms, people are able to limit these negative influences (Rush, 2011).
Oulasvirta et al. (2011) concluded that smartphones causes negative checking habits. Checking habits are automatic actions whereby the smartphone is unlocked to check the start screen for new messages, notifications, alerts, and application icons; these habits can be triggered by external (ringtone) and internal cues (emotional state, urge). Those habits can be maladaptive and interfere with people’s life. Checking for information can be rewarding, if someone has a new message or notification, the so-called new information reward. Rewards can enforce repeated actions (Everitt, & Robbins, 2005).
How persistent a habit is depends on the habit strength (La Rose, Lin, Eastin, 2003). Habit strength is the degree of automaticity of a habit. The strength of the habit is formed through operant conditioning (Rush, 2011). Operant conditioning is the development of habits and addictions. When previous actions had desirable outcomes, those actions will likely reoccur. The frequency of these actions and the salience of the reward determine the strength of the habit (and can form the basis of an addiction) (Rush, 2011). A habit that is often repeated has a stronger degree than the one that is less automatic and repeated.
Strong habits are repeated more often and are easier provoked by cues (La Rose, Lin, Eastin, 2003). This can reach the level where they become annoying, such as inappropriate use of a smartphone at restaurants, concerts, and/or family gatherings Companies are aware of the value that habitual behavior creates for them. Social media, application, and game publishers create compulsion loops so that users spend more time and repeat their actions on their mobile applications or social platforms. To summarize, smartphone usage could form habits through different cues, repetitions, and stimulation of application publishers.
Addiction is a term with a long history of reference to alcohol or drugs abuse arising from the addictive effect that those substances have on the human body and brain. However, taking large amounts of drugs or alcohol for a long period are not the only types of addiction (APA, 2001). People can develop addictions not only towards substances, but also to specific behavioral patterns (APA, 2001). The positive reinforcement of a substance or action, the time between consumption or action, and physiological response determines how addiction originates (Carbonell, Oberst, & Beranuy, 2013). Thus, when the positive reinforcement is strong, there is a short time between an action and a corresponding physiological response; as a result, that action becomes more addictive.
1.1.4 Behavioral Addiction
Internet and smartphone addictions are different from other addictions such as alcohol or drugs. Drugs addictions are not behavioral addictions; rather, these but are termed substance dependence (APA, 2001). Behavioral addiction can be defined as “a disorder where behavior (only) functions to produce pleasure and to relieve feelings of pain and stress in which a person: 1. Fails to control the behavior; 2. Continues to execute (addictive) behavior despite significant harmful consequences (Isaac, 2008).
1.1.5 Smartphone Addiction
Whang, Lee, and Chang (2003) defined internet addiction as “an impulse-control disorder with no involvement of an intoxicant; therefore, it is akin to pathological gambling”.
Online mobile- or smartphone addiction is closely related to internet addictions because the features are similar (Kwon, Kim, Choi, Gu, Hahn & Min, 2013). Internet addiction mostly begins with habits such as the checking habit; digital addictions are often the result of using habits to relieve pain or escape from the reality (Huisman, Garretsen, & van den Eijnden, 2000). Therefore, there is frequently an undesirable situation with certain habits that become problematic, such as playing games, visiting social media or forums (Young, 1999). Some characteristics, such as stress, loneliness, or isolation, could play a role as well (Young, 1999).
People often do not turn of their smartphones, do not go out without them, and use them for business, relaxation, and socializing. Smartphone usage can lead to addicted behavior (Wood & Neal, 2007; La Rose &Eastin, 2004). The relationship between people and their smartphone is much more developed than expected compared to the fixed telephone and even with their desktop or laptop computer (Carbonell, Oberst & Beranuy, 2013). This is particularly true of adolescents, as they spend much time with and on their smartphones; in addition, adolescents are more sensitive to rewards and cues than older people (Haverlag, 2013).
The difference between internet and smartphone addiction is in the usage gratifications and usage context of the two (Carbonell, Oberst, & Beranuy, 2013; Ghose, Goldfarb, & Han, 2010). Gratifications of a substance or behavior create the addiction (Carbonell, Oberst, & Beranuy, 2013) Smartphones have different gratifications or features that can make a strong positive reinforcement (pleasurable experience) for it users. Carbonell, Oberst, and Beranuy (2013) collected the (unique) gratifications of smartphones that (can) cause positive reinforcement by its users, namely: Euphoria: Getting text messages, calls, or social media response creates a feeling of being valued or loved. Instrumental functions: Smartphone function as a clock, camera, recorder, diary, agenda, radio, music player, navigation. These and others functions can all be used to the users’ requirements. Identity and status symbol: Smartphones do not only have functional properties, but also function as an identity symbol of its user. This is caused not only by the device, but also by the number of messages, notifications, and calls a person receives. It can cause usage in public places to showcase a user’s identity and creates an emotional bondage with the owner.
- 126.96.36.199 (Online) Social network.
Smartphones functions can create and maintain social networks. Social networks that are different from those created by physical (face-to-face) social network are evolving through smartphones and are rapidly changing. Teenagers are particularly prone to creating and maintaining social networks with their smartphones.
- 188.8.131.52 Dependency.
Due to the identity and social network implications of smartphones, users get dependent of their smartphones. Staying in 24/7 contact with their social networks creates a feeling of belongingness (“they have one, so I need one, too”).
- 184.108.40.206 Connection worldwide.
Smartphones make it easy to connect to the online world; therefore, it is possible for users to connect with people/peers worldwide. There are no boundaries any more. When face-to-face communication is not possible, communication through smartphones is then most applicable.
- 220.127.116.11 Feeling of control:
In recent years, people stopped going outside without their smartphones. Due to the accessibility of other contacts afforded by smartphones, people feel more secure and in control. Without a smartphone, a feeling of fear can emerge due to disconnection.
- 18.104.22.168 Permanent Mobility:
Because smartphones are on and always at hand for many individuals, it is expected that others are also permanently connected and accessible. This leads to a feeling of concern when people do not react in time. Hereby, the use and bonding with the smartphone is being reinforced.
- 22.214.171.124 Entertainment:
Many applications are available on smartphones; thus, the device can function as an online mobile game console. Apart from games, the online functions of a smartphone can offer shopping, browsing, and watching multimedia gratifications.
Expression of feelings: Smartphone features like calling, text messaging, communication applications, and social media make it possible to express or share feelings, experiences, and situations in text, videos, and pictures.
1.1.6 Theoretical Perspective.
In addition to theories that is related to smartphone addiction are following:
- 126.96.36.199 Relational Dialectics Theory.
This theory proposed by Baxter and Simon (1993). This theory described that people rely on cell phones to communicate, share, include and validate. Although being able to contact others is one of the most liked qualities of cell phones, being continuously available for others’ contact is also one of its most disliked qualities that badly affect their interpersonal relationship. People experience internal tensions inconsistently, while being in a relationship. Over time the pressures will be recurring in nature and from this extreme tendencies, the relationship sustains. For instance, consider the point between harmony and separation. Communication patterns causing a constant state of instability acts as a contrary in sustaining a relationship.
- 188.8.131.52 Uses and Gratifications Theory.
UG theory founded by Elihu Katz in 1959. According to Katz (1959), the outcomes of media usage depend on why and how they decided to use the media. Therefore, there are two main components that discuss in U&G theory which are media that choose to be engaged and gratification that get from the media. By explaining about the U&G theory, mainly this theory works operationally through the social and the psychological needs for individuals generating motives and expectation of mass media (Katz, 1959), and how individuals use media to satisfy their needs and to achieve their goals. U&G theory is commonly used to: “(1) Explain how the psychological and social needs of people give rise to their expectation and motivations to choose and to use the mass media that will best meet their needs and expectations, (2) Explain how people use the media to meet their specific needs, (3) Understand the motives for their dependency on a particular media, and (4) Identify the consequences that resulted from the needs, motives, and dependency on a particular media
1.2 Interpersonal Relationship:
Interpersonal relationship is a strong, deep, or close association or acquaintance between two or more people that may range in duration from brief to enduring. This association may be based on inference, love, solidarity, regular business interactions, or some other type of social commitment. Interpersonal relationships are formed in the context of social, cultural and other influences. The context can and may and perhaps will vary from family or kinship relations, friendship, marriage, relations with associates, work, clubs, neighborhoods, and places of worship. They may be regulated by law, custom, or mutual agreement, and are the basis of social groups and society as a whole. Human beings are innately social and are shaped by their experiences with others. There are multiple perspectives to understand this inherent motivation to interact with others (Shahsavarani, et.al 2016).
1.2.1 Need to belong.
According to Maslow’s hierarchy of needs, humans need to feel love (sexual/nonsexual) and acceptance from social groups (family, peer groups). In fact, the need to belong is so innately ingrained that it may be strong enough to overcome physiological and safety needs, such as children’s attachment to abusive parents or staying in abusive romantic relationships. Such examples illustrate the extent to which the psycho-biological drive to belong is entrenched (Sujatha, 2001).
1.2.2 Social exchange.
Another way to appreciate the importance of relationships is in terms of a reward framework. This perspective suggests that individuals engage in relations that are rewarding in both tangible and intangible ways. The concept fits into a larger theory of social exchange(Wayne, Shore, & Liden, 1997). This theory is based on the idea that relationships develop as a result of cost-benefit analysis. Individuals seek out rewards in interactions with others and are willing to pay a cost for said rewards. In the best-case scenario, rewards will exceed costs, producing a net gain. This can lead to “shopping around” or constantly comparing alternatives to maximize the benefits or rewards while minimizing costs.
1.2.3 Relational self.
Relationships are also important for their ability to help individuals develop a sense of self. The relational self is the part of an individual’s self-concept that consists of the feelings and beliefs that one has regarding oneself that develops based on interactions with others (Andersen, & Chen, 2002) In other words, one’s emotions and behaviors are shaped by prior relationships. Thus, relational self-theory posits that prior and existing relationships influence one’s emotions and behaviors in interactions with new individuals, particularly those individuals that remind him or her of others in his or her life. Studies have shown that exposure to someone who resembles a significant other activates specific self-beliefs, changing how one thinks about oneself in the moment more so than exposure to someone who does not resemble one’s significant others
1.2.4 Power and Dominance.
Sidanius and Pratto (2001) define power is the ability to influence the behavior of other people. When two parties have or assert unequal levels of power, one is termed “dominant” and the other “submissive”. Expressions of dominance can communicate intention to assert or maintain dominance in a relationship. Being submissive can be beneficial because it saves time, emotional stress, and may avoid hostile actions such as withholding of resources, cessation of cooperation, termination of the relationship, maintaining a grudge, or even physical violence. Submission occurs in different degrees; for example, some employees may follow orders without question, whereas others might express disagreement but concede when pressed.
Groups of people can form a dominance hierarchy. For example, a hierarchical organization uses a command hierarchy for top-down management. This can reduce time wasted in conflict over unimportant decisions, prevents inconsistent decisions from harming the operations of the organization, maintain alignment of a large population of workers with the goals of the owners (which the workers might not personally share) and if promotion is based on merit, help ensure that the people with the best expertise make important decisions. This contrasts with group decision-making and systems which encourage decision-making and self-organization by front-line employees, who in some cases may have better information about customer needs or how to work efficiently. Dominance is only one aspect of organizational structure.
A power structure describes power and dominance relationships in a larger society. For example, a feudal society under a monarchy exhibits a strong dominance hierarchy in both economics and physical power, whereas dominance relationships in a society with democracy and capitalism are more complicated.
In business relationships, dominance is often associated with economic power. For example, a business may adopt a submissive attitude to customer preferences (stocking what customers want to buy) and complaints (“the customer is always right”) in order to earn more money. A firm with monopoly power may be less responsive to customer complaints because it can afford to adopt a dominant position. In a business partnership a “silent partner” is one who adopts a submissive position in all aspects, but retains financial ownership and a share of the profits.
Two parties can be dominant in different areas. For example, in a friendship or romantic relationship, one person may have strong opinions about where to eat dinner, whereas the other has strong opinions about how to decorate a shared space. It could be beneficial for the party with weak preferences to be submissive in that area, because it will not make them unhappy and avoids conflict with the party that would be unhappy.
Interpersonal relationships are dynamic systems that change continuously during their existence. Like living organisms, relationships have a beginning, a lifespan, and an end. They tend to grow and improve gradually, as people get to know each other and become closer emotionally, or they gradually deteriorate as people drift apart, move on with their lives and form new relationships with others. One of the most influential models of relationship development was proposed by psychologist George Levinger. This model was formulated to describe heterosexual, adult romantic relationships, but it has been applied to other kinds of interpersonal relations as well. According to the model, the natural development of a relationship follows five stages (Levinger, 1983).
- 184.108.40.206 Acquaintance and Acquaintanceship
Becoming acquainted depends on previous relationships, physical proximity, first impressions, and a variety of other factors. If two people begin to like each other, continued interactions may lead to the next stage, but acquaintance can continue indefinitely. Another example is association.
- 220.127.116.11. Buildup.
During this stage, people begin to trust and care about each other. The need for intimacy, compatibility and such filtering agents as common background and goals will influence whether or not interaction continues.
- 18.104.22.168 Continuation.
This stage follows a mutual commitment to quite a strong and close long-term friendship, romantic relationship, or even marriage. It is generally a long, relatively stable period. Nevertheless, continued growth and development will occur during this time. Mutual trust is important for sustaining the relationship.
- 22.214.171.124 Deterioration.
Not all relationships deteriorate, but those that do tend to show signs of trouble. Boredom, resentment, and dissatisfaction may occur, and individuals may communicate less and avoid self-disclosure. Loss of trust and betrayals may take place as the downward spiral continues, eventually ending the relationship. (Alternately, the participants may find some way to resolve the problems and reestablish trust and belief in others.)
- 126.96.36.199 Ending.
The final stage marks the end of the relationship, either by breakups, death, or by spatial separation for quite some time and severing all existing ties of either friendship or romantic love.
1.2.4 Theoretical Perspective
- 188.8.131.52 Confucianism.
Confucianism is a study and theory of relationships especially within hierarchies (Yan, & Sorenson, 2006). Social harmony, the central goal of Confucianism, results in part from every individual knowing his or her place in the social order, and playing his or her part well. Particular duties arise from each person’s particular situation in relation to others. The individual stands simultaneously in several different relationships with different people: as a junior in relation to parents and elders, and as a senior in relation to younger siblings, students, and others. Juniors are considered in Confucianism to owe their seniors reverence and seniors have duties of benevolence and concern toward juniors. A focus on mutuality is prevalent in East Asian cultures to this day.
- 184.108.40.206 Minding Relationship.
The mindfulness theory of relationships shows how closeness in relationships may be enhanced. Minding is the “reciprocal knowing process involving the nonstop, interrelated thoughts, feelings, and behaviors of persons in a relationship” (Harvey, & Pauwels, 2009). Snyder, Lopez, and Pedrotti (2010) give five components of “minding” include;
1. Knowing and being known: seeking to understand the partner
2. Making relationship-enhancing attributions for behaviors: giving the benefit of the doubt
3. Accepting and respecting: empathy and social skills
4. Maintaining reciprocity: active participation in relationship enhancement
5. Continuity in minding: persisting in mindfulness
Sahu and Gupta, (2016) defined loneliness is a complex and usually unpleasant emotional response to isolation. Loneliness typically includes anxious feelings about a lack of connection or communication with other beings, both in the present and extending into the future. As such, loneliness can be felt even when surrounded by other people. The causes of loneliness are varied and include social, mental, emotional, or even physical factors. People can experience loneliness for many reasons, and many life events may cause it, like the lack of friendship relations during childhood and adolescence, or the physical absence of meaningful people around a person. At the same time, loneliness may be a symptom of another social or psychological problem, such as chronic depression.
Following are the typology of loneliness
220.127.116.11 Feeling lonely vs. being socially isolated.
There is a clear distinction between feeling lonely and being socially isolated (for example, a loner). In particular, one way of thinking about loneliness is as a discrepancy between one’s necessary and achieved levels of social interaction (Peplau, & Perlman, 1982). while solitude is simply the lack of contact with people. Loneliness is therefore a subjective experience; if a person thinks they are lonely, then they are lonely. People can be lonely while in solitude, or in the middle of a crowd. What makes a person lonely is the fact that they need more social interaction or a certain type of social interaction that is not currently available. A person can be in the middle of a party and feel lonely due to not talking to enough people. Conversely, one can be alone and not feel lonely; even though there is no one around that person is not lonely because there is no desire for social interaction. There have also been suggestions that each person has their own sweet spot of social interaction. If a person gets too little or too much social interaction, this could lead to feelings of loneliness or over-stimulation (Suedfield, 1987).
Solitude can have positive effects on individuals. One study found that, although time spent alone tended to depress a person’s mood and increase feelings of loneliness, it also helped to improve their cognitive state, such as improving concentration. Furthermore, once the alone time was over, people’s moods tended to increase significantly (Larson, Csikszentmihalyi, & Graef, 1982). Solitude is also associated with other positive growth experiences, religious experiences, and identity building such as solitary quests used in rites of passages for adolescents (Suedfeld, 1982).
Loneliness can also play an important role in the creative process. In some people, temporary or prolonged loneliness can lead to notable artistic and creative expression, for example, as was the case with poet Emily Dickinson, and numerous musicians. This is not to imply that loneliness itself ensures this creativity, rather, it may have an influence on the subject matter of the artist and more likely be present in individuals engaged in creative activities.
18.104.22.168 Transient vs. chronic loneliness.
The other important typology of loneliness focuses on the time perspective (Peplau, & Perlman, 1982). In this respect, loneliness can be viewed as either transient or chronic. It has also been referred to as state and trait loneliness. Transient (state) loneliness is temporary in nature, caused by something in the environment, and is easily relieved. Chronic (trait) loneliness is more permanent, caused by the person, and is not , easily relieved (Sahu, Gupta, & Jaib 2016). For example, when a person is sick and cannot socialize with friends would be a case of transient loneliness. Once the person got better it would be easy for them to alleviate their loneliness. A person who feels lonely regardless of if they are at a family gathering, with friends, or alone is experiencing chronic loneliness. It does not matter what goes on in the surrounding environment, the experience of loneliness is always there.
22.214.171.124 Loneliness as a human condition.
The existentialist school of thought views loneliness as the essence of being human. Each human being comes into the world alone, travels through life as a separate person, and ultimately dies alone. Coping with this, accepting it, and learning how to direct our own lives with some degree of grace and satisfaction is the human condition (Becker, 2007).
Some philosophers, believe in an epistemic loneliness in which loneliness is a fundamental part of the human condition because of the paradox between people’s consciousness desiring meaning in life and the isolation and nothingness of the universe (Booth, 1997). Conversely, other existentialist thinkers argue that human beings might be said to actively engage each other and the universe as they communicate and create, and loneliness is merely the feeling of being cut off from this process (Blackham, 2012).
1.3.2 Theoretical Perspective
Following is the theoretical perspective of loneliness
126.96.36.199 Attachment theory
Attachment theory was the foundation for an influential psychological theory of loneliness developed by the sociologist Robert S. Weiss. Weiss identified six social needs that, if unmet, contribute to feelings of loneliness. Those needs are attachment, social integration, nurturance, reassurance of worth, sense of reliable alliance, and guidance in stressful situations. As would be predicted by attachment theory, Weiss maintained that friendships complement but do not substitute for a close, intimate relationship with a partner in staving off loneliness (Cacioppo, & Patrick, 2008).
188.8.131.52 Behavioral approach
Another theoretical perspective, the behavioral approach, holds that loneliness is characterized by personality traits that are associated with, and possibly contribute to, harmful patterns of interpersonal interaction. For instance, loneliness is correlated with social anxiety, social inhibition (shyness), sadness, hostility, distrust, and low self-esteem, characteristics that hamper one’s ability to interact in skillful and rewarding ways. Indeed, lonely individuals have been shown to have difficulty forming and maintaining meaningful relationships. They are also less likely to share information about themselves with their peers, and that helps to explain why they report a lack of intimacy with close friends (Heinrich, & Gullone, 2006)..
184.108.40.206 Cognitive approach
The cognitive approach to loneliness is based on the fact that loneliness is characterized by distinct differences in perceptions and attributions. Lonely individuals tend to have a pessimistic general outlook: they are more negative than are individuals who are not lonely about the people, events, and circumstances in their lives, and they tend to blame themselves for not being able to achieve satisfactory social relationships. In addition, the cognitive approach largely takes account of the attachment and behavioral perspectives by explaining how (a) failure to meet the need for attachment, social integration, nurturance, and other social needs results in perceived relationship discrepancies that are experienced as loneliness, and (b) loneliness is perpetuated by way of a self-fulfilling prophecy in which poor social skills result in unsatisfactory personal relationships that in turn result in negative self-attributions that lead to further social isolation and relationship dissatisfaction (Perlman, & Peplau, 1981)
This section is an over view of selected scholarly literature that has been published in the area of smart phone addiction, interpersonal relationship and loneliness. Each area has been discussed briefly and along with the discussion of relationship with them.
2.1 International Researches
Jeong and et al (2016) studied What type of content are smartphone users addicted to?: SNS vs. games. The purpose of the study was to examine the predictor of smart phone addiction AND the user characteristics and media content types that can lead to addiction. The sample consisted of 944 respondents who were recruited from 20 elementary schools. Results showed that those who have lower self-control and those who have greater stress were more likely to be addicted to smartphones. For media content types, those who use smartphones for SNS, games, and entertainment were more likely to be addicted to smartphones, whereas those who use smartphones for study-related purposes were not. Although both SNS use and game use were positive predictors of smartphone addiction, SNS use was a stronger predictor of smartphone addiction than game use.
Casey (2012) studied the Linking Psychological Attributes to Smart Phone Addiction, Face-to-Face Communication, Present Absence and Social Capital. The sample consisted of 414 university students. The results of this study showed that the higher one scored on loneliness and shyness, the higher the likelihood one would be addicted. Students who reported the greater amount of smart phone used, the higher level of face-to-face communication and present absence they would report. The study also found that the smart phone addiction symptoms are significantly and negatively related to the level of face-to-face communication and positively related to present absence. Furthermore, the most powerful factors affect bonding social capital were gender, grade, and loneliness; while the most powerful factor affecting bridging social capital was face-to-face communication with friends.
Kim (2013) investigated the Effect of Smart-phone Addiction on Youth`s Sociality Development. This study examined effects of smart-phone addiction on the youth`s sociality development empirically by questionnaire survey. To conduct this study, 339 high school students participated in the survey. The results of this study revealed that Smart-phone addiction had a significant influence on sociality development in negative way. Specifically, sub-domain of smart-phone addiction (disturbance of adaptive, virtual life orientation, tolerance) affect on sociality development in negative. Interesting, Smart-phone using time affect on sociality development in positive.
Caplan (2006) examined The Relations among Loneliness, Social Anxiety, and Problematic Internet Use. The model of problematic Internet use advanced and tested in the current study proposes that individuals’ psychosocial well-being, along with their beliefs about interpersonal communication (both face-to-face and online) are important cognitive predictors of negative outcomes arising from Internet use. The study examined the extent to which social anxiety explains results previously attributed to loneliness as a predictor of preference for online social interaction and problematic Internet use. The results support the hypothesis that the relationship between loneliness and preference for online social interaction is spurious, and that social anxiety is the confounding variable.
Lo, Wang, & Fang, (2005) investigated Physical Interpersonal Relationships and Social Anxiety among Online Game Players. Many online game players spend inordinate amounts of time in their favorite virtual worlds. A large percentage of these players are teenagers who show behaviors normally associated with physical addiction. Parents, educators, and social scientists are therefore saying that online games are sources of social problems. The authors surveyed 174 Taiwanese college-age online players to collect data on the potential effects of online games on the quality of interpersonal relationships and levels of social anxiety. According to the results, the quality of interpersonal relationships decreased and the amount of social anxiety increased as the amount of time spent playing online games increased.
Leena, Tomi, & Arja, (2005) studied the Intensity of mobile phone use and health compromising behaviors—how is information and communication technology connected to health-related lifestyle in adolescence? The association of mobile phone use with health compromising behaviors (smoking, snuffing, alcohol) was studied in a survey comprising a representative sample of 14–16-year-olds (N=3485) in 2001. Mobile phone was used by 89% of respondents and by 13% for at least 1 h daily. The results of this study showed that he intensity of use was positively associated with health compromising behaviors. The associations remained, although somewhat reduced, after including weekly spending money in the models. This study concludes that, at least in the present developmental level of communication technologies, intensive mobile phone use seems to be part of the same health-related lifestyle as health compromising behaviors.
Darcin, (2016) studies the Smartphone addiction and its relationship with social anxiety and loneliness. The study aimed to determine the relationship of smartphone addiction with social phobia and loneliness. The sample consisted of three hundred and sixty-seven students who owned smartphones. The results of this study indicate that social phobia was associated with the risk for smartphone addiction in young people. Younger individuals who primarily use their smartphones to access social networking sites also have an excessive pattern of smartphone use.
Pettegrew, and Day. (2015) investigated Smart Phones and Mediated Relationships: The Changing Face of Relational Communication. This exploratory study provides an initial empirical base for communication scholars to reconsider their reliance on the treatment of computer mediated communication and mobile technology (MT) as an addendum to FtF communication, and instead to recognize that individuals use mobile communication to develop close relationships across a wide variety of interrelated and converging contexts. Survey data collected from 526 undergraduate students. This is true for both close relationships and intimate relationships We call for researchers to consider the transformational implications of this new communication phenomenon, how it transforms interpersonal and relational development and specific research agendas that should be undertaken. The communication has quickly grown more complex and messier.
Gökçearslan and et.al (2016) studied Modeling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyber loafing in university students. This study investigates the roles of smartphone usage, self-regulation, general self-efficacy and cyber loafing in smartphone addiction. an online survey was conducted which received responses from 598 participants attending a public university in Ankara, Turkey. The results showed that both the duration of smartphone usage and cyber loafing positively affected smartphone addiction. The effect of self-regulation on smartphone addiction was negative and significant. In addition, neither self-regulation nor general self-efficacy had an effect on cyber loafing.
Salehan,and Negahban (2013) examined the Social networking on smartphones: When mobile phones become addictive. It investigates the role of mobile social networking applications on mobile addiction This study finds that the use of SNS mobile applications is a significant predictor of mobile addiction. The result also shows that the use of SNS mobile applications is affected by both SNS network size and SNS intensity of the user.
Tan and et al (2013) studied the Loneliness and Mobile Phone. This study aimed to analyses loneliness of university students according to mobile phone addiction, daily phone use time and gender. Survey model is used for this research. To collect data; personal information form, problematic mobile phone use scale, and UCLA-loneliness scale were applied for 527 students who are from different Departments of Faculty of Education at Fırat University. To analyses these data; correlation, t test, one way variance (ANOVA) analysis and Scheffe test were used. Results revealed that loneliness was significantly associated with problematic mobile phone use (r=.35) Furthermore, there were significant differences between loneliness and independent variables (gender, mobile phone addiction and daily phone use time).
Yu and et al (2008) studied Characteristics of Excessive Cellular Phone Use in Korean Adolescents. The objective of this study was to evaluate the possible psychological problems related to excessive cellular phone use in adolescents. Results from 595 participants showed that the potentially excessive user group had a tendency to identify themselves with their cellular phones and to have difficulties in controlling usage. They expressed more depressive symptoms, higher interpersonal anxiety, and lower self-esteem. A positive correlation was also observed between excessive cellular phone use and Internet addiction.
Weilenmann, Larsson (2001) conducted field studies on public use of mobile phones among teenagers in Sweden. Their study shed light on how the mobile phone has come to be used as a tool for local social interaction, rather than merely as a device for communication with dislocated others. Their observations pointed towards the collaborative nature of mobile phone use. The researchers examined how phones were shared and how their field data could be of use when designing new mobile technology and services for the youth.
Choliz in 2010 in his research reveals that many people develop dependency to new technological devices as they become increasingly integrated into their daily lives. For example, some view that excessive internet use, along with pathological gambling, should be included as behavioral addiction. Similarly, excessive use and dependency on the cell phone may be considered an addictive disorder.
2.2 Indigenous Researches
Ali and et al. (2014) studied the Cell Phone Mania and Pakistani Youth: Exploring the Cell Phone Usage Patterns among Teenagers of South Punjab. This study aimed to expound the cell phone usage patterns among teenagers students. The sample was consisted of , 317 boys and 310 girls from various schools, college and university. The studǇ͛s fiŶdiŶgs uŶfold some aspects of gratification acquired by the teenagers for using this technology. It was explored that cell phones have become indispensable for the teenagers. It is one of the effective tools of interaction among teenagers. The cell phone companies have utilized mainstream print and electronic media, by specifically targeted the teenagers for to widen the cell phone usage. The study would conclude that cell phones are a source of satisfaction for the teenagers whether it is for interaction or for fun. The study would unfold the ironic revelation regarding the cell phones utilization that how the users justify their own cell phones usage on the exigency basis while condemn the other usage of cell phones on the charge of misusing.
A study was conducted by Al-Barashdi, Bouazza and Jabur (2014) Smartphone Addiction among University Undergraduates: A literature review. The paper also reviews the relationship between Smartphone addiction among undergraduates and their academic achievement. Finally, significant differences in addiction among undergraduates according to their gender, field of study, parents educational level and family income level will be examined. While some studies have shown gender differences in Smartphone addictive use, others have proved that gender and Smartphone use are not significantly related. A few studies have examined the relationship between addiction and students’ field of study. Some of these have found that humanities students have a higher addiction level than physical science students. The results regarding Smartphone usage and family income had showed contrary indications.
The Internet rapidly developed and came into widespread use in Pakistan in the 20th century, and has since become an established part of daily life. In this modern era of globalization, where people can easily connect with each other by internet, smartphones are one of the most frequently used communication devices which are used by everyone, particularly the early adults are mostly addicted to the usage of smartphones. Where the smartphone addiction facilitates the people in their routine life, at the same time these smartphones, bring them many psychological problems like restlessness, depression and dissatisfaction as well as intervene with their interpersonal relations, at the end of which, the person becomes alone. Moreover, people indulge themselves into different applications of smartphone like Instagram, Facebook, and Google Play Store that does not only badly affect their academic performances but also their relationship with families, peers and relatives. Due to addiction of smartphone and lack of interpersonal face to face interaction, they may feel alone. Furthermore, such positive and negative tendencies of smartphone addiction create the interest to investigate the role of smartphone addiction in our society on majorly influencing factors.
Therefore, the aim of the present study is to examine the smartphone addiction as a predictor of interpersonal relationships and loneliness in university students. Moreover, the present study helps to fulfill that gap, particularly there is limited literature available on smartphone addiction in relation with loneliness and interpersonal relationships.
2.4 Objectives of the study
- To assess the relationship between smartphone addiction, interpersonal relationship and loneliness in university students.
- To examine the role of smartphone addiction as a predictor of interpersonal relationship and loneliness in university students.
- To find the gender differences in smartphone addiction in university students.
- There will be a negative relationship between smartphone addiction and interpersonal relationship in university students.
- There will be a positive relationship between smartphone addiction and loneliness in university students.
- Smartphone addiction will negatively predict the interpersonal relationship in university students.
- Smartphone addiction will positively predict the loneliness in university students.
- Smartphone addiction will be higher in females than males.
3.1 Research Design
A correlational research design was used to assess the smart phone addiction as a predictor of interpersonal relationships and loneliness in university students.
The sample comprised of 100 university students, consisting of both male (n=45) and female (n=55) university students. Sample consisted of final year students of B.S. (Honors) semester 7 and 8, M.Sc semester 3 and 4 and M. Phil semester 3 and 4 and Ph.D. The convenient sampling technique was used to collect the data from The University.
3.2.1 Inclusion Criteria
- Only university students were selected.
- Unmarried Students were selected.
- Final year students of B.S. (Honors), M.Sc, M. Phil and Ph.D were included.
3.2.2 Exclusion Criteria
- Those students who were doing part-time job were excluded.
- Physically disabled students were excluded.
3.3 Operational Definitions
3.3.1 Smart Phone Addiction
The ‘smart phone addiction’ recently has become an important issue in our society. According to the study related to the development of smart phone addiction scale, smart phones also caused symptoms of addiction similar to the effects of the internet including craving, withdrawal, tolerance, daily-life disturbance, and preference of cyberspace-oriented relationship, which were confirmed through the diagnosis (Kwon et al. 2013).
3.3.2 Interpersonal Relationship
Interpersonal relationships are social connections with others. They can be brief or enduring. We experience a variety of interpersonal relationships on a daily basis with family, friends, significant others and people at our workplace (Heaphy & Dutton, 2008). The ISEL-12 yields a total score that describes overall perceived social support, and perceived availability of advice or guidance, empathy, acceptance, concern, and help or assistance, such as material or financial aid and social support (Cohen et al., 1985).
(Russell et at., 1978) indicates, loneliness is an emotionally unpleasant experience. In particular, loneliness has been linked with feelings of general dissatisfaction, unhappiness, depression, anxiety, emptiness, boredom, restlessness and marginality.
3.4 Assessment Measures
Following assessment measures were used in the present study:
i. Smart Phone Addiction Scale – Short Version (SAS-SV)
ii. Interpersonal Support Evaluation List – Short Version (ISEL-SV)
iii. UCLA Loneliness Scale – Version 3
3.4.1 Demographic Information Sheet.
It consisted of general and personal information statements assessing the demographic variables including the information about age, gender, semester or year, family system, duration and frequency of smart phone usage.
3.4.2 Smart Phone Addiction Scale – Short Version.
Smartphone addiction scale (SAS-SV) is a scale for Smartphone addiction that consisted of 10 items with a six-point Likert scale (1: “strongly disagree” and 6: “strongly agree”) based on self-reporting. A Cronbach’s alpha correlation coefficient of 0.91 was obtained for the SAS-SV (Kwon et al. 2013).
220.127.116.11 Pilot testing
Test of the second language version on a small sample (university students) of individuals representative of the target population and native target language speakers was done in order to assess the clarity, appropriateness of wording and acceptability of the translated questionnaire. 10 students age range from 18-28 years were selected for the pilot testing of smartphone addiction scale. The probability convenient sampling technique was used to gather data from the pilot testing sample. The students were approached from a university and were asked to become a part of their research. Consent was taken from the students and demographics were asked. The pilot testing revealed translated construct reliability more accurately and whole scale to give focus to the construct being measured so it was explained in more easy words. Other than that no major changes were made after the pilot study.
18.104.22.168 Interpersonal Support Evaluation List-short Version
A 12-item measure of perceptions of social support. This measure is a shortened version of the original ISEL 40 items. Participants rate each item on 4-point scale ranging from “Definitely True” to “Definitely False”. Following items in this questionnaire 1, 2, 7, 8, 11, 12 are reverse scored. Cronbach’s alpha was calculated as an index of internal consistency, yielding an overall value of 0.83 (Cohen & Hoberman, 1983).
3.4.3 UCLA Loneliness Scale
A 20-item scale designed to measure one’s subjective feelings of loneliness as well as feelings of social isolation. A second set of measures assessed explicit self-labels of loneliness. Examples of such questions are” During your lifetime, how often have you felt lonely?” and “During The past two weeks, how lonely have you felt? Participants rate each item on a scale from 1 (Never) to 4 (Often). Following items in this questionnaire 5, 6, 9, 10, 15, 16, 19, 20 are reverse scored. This measure was highly reliable, in term of internal consistency, coefficient alpha ranging from .89 to .94 (Russell et al., 1978).
3.5 Ethical Consideration
In order to conduct this research, some ethical considerations were kept in mind:
The scales were used after seeking permission from the authors.
An authority letter which explained the nature of the study was presented to the head of the concerned authority for data collection. Thus, prior permission was sought from the concerned authority for data collection.
Informed consent form was taken from the participants and they were briefed about the certain features of the research.
After taking the permission officially from all authentic sources data collection was started, questionnaires were presented to those students who met the required criteria.
Information collected from participants was keep confidential.
The anonymity of all the participants was maintained.
Official support letter by the supervisor and permission for the data selection was taken. After taking the permission by the authorities the data was collected. The authority letter was presented and approved by the heads of the departments of the University. The research identified the inclusion and exclusion criteria. A sample of 100 participants, including 45 males and 55 females was taken from university students. The participants were assured about the full confidentiality of all the information obtained from them. The purpose of the research was explained. The subjects were given demographic information questionnaire (DIQ), Smart Phone Addiction Scale (10 items), Interpersonal Support Evaluation List (18 items) and UCLA Loneliness Scale (20 items). The questionnaires were administered after brief instructions. Approximately 15 – 20 minutes were consumed to administer all three questionnaires. After completion, the questionnaires were taken back and participants were thanked for their cooperation.
3.7 Statistical Analyses
The SPSS will be used to analyze data. In this study, Correlation Pearson Product Moment and Hierarchical Regression analyses were used to determine the relationship and for prediction of smart phone addiction, interpersonal relationship and loneliness in university students. Furthermore, Independent T-Test analysis was used to examine the gender differences in university students.
The results of the current research are presented for smartphone addiction as predictor of interpersonal relationship and loneliness in university students. The data were analyzed in three key steps. In the first step, the reliability analysis was conducted for each scale and Cronbach’s alpha for the scales were reported. In the second step, Pearson Product Moment Correlation was employed to assess the relationships among the study variables that included smartphone addiction, interpersonal relationship and loneliness and demographic variables. The third step, in order to clarify the relationship among predictor and criterion variables further simple linear regression was conducted. Moreover, independent T-test analysis was conducted to examine the gender difference in university students.
4.2 Main Analysis
Pearson Product Moment Correlation was computed to assess the relationship of demographic variables, smartphone addiction, interpersonal relationship and loneliness in university students. The results are shown in table 4.2
In this table 4.2, Results of correlation analysis of demographic variables showed that age was significantly positively correlated with duration of smartphone usage and other study variables and demographics were not affected due to age. Moreover, gender was also significantly positively correlated with smartphone addiction and family system significantly, but negatively correlated with smartphone addiction. The duration of smartphone usage significantly positively correlated with smartphone addiction, interpersonal relationship and loneliness that revealed the important factors influence the study variables.
Further, the result exposed that smartphone addiction significantly positively correlated with loneliness. Our hypothesis related to smartphone addiction and loneliness were approved as a positive relationship was hypothesized among them. Furthermore, the result also revealed that there was a negative correlation between smartphone addiction and interpersonal relationship. Our hypothesis related to smartphone addiction and interpersonal relationship were approved as it was hypothesized that there is a negative relationship between smartphone addiction and interpersonal relationship. The result also revealed that there was a negative correlation between interpersonal relationship and loneliness.
Moreover, these findings suggest that those people who have a higher level of smartphone addiction, have weak interpersonal relationships with others and report high level of loneliness.
4.3 Regression Analysis
As presented in table 4.3. In the first block demographics variables entered, in the second block Smart phone addiction was entered. A hierarchical regression was run to identify the predictor of loneliness. The over all model was significant. Step 1 explained 13 percent of the variance in loneliness. Age (b=.23*) was found a good predictor of interpersonal relationship. In step 2 models explained 11 percent of the variance in the interpersonal relationship. Smartphone addiction (b=.37**) found strong predictor of loneliness.
As presented in table 4.4. In the first block demographics variables entered, in the second block Smart phone addiction was entered. A hierarchical regression was run to identify the predictor of interpersonal relationship. The overall model was significant. Step 1 explained 10 percent of the variance in interpersonal relationship. The duration of smart phone usage (b=.27*) was found a good predictor of interpersonal relationship. In step 2 models explained 11 percent of the variance in the interpersonal relationship. Smartphone addiction (b=.37***) found strong predictor of interpersonal relationship.
4.5 Additional Analysis
Mean differences were explored across different groups of the sample based on the data generated through the demographics of the students. Thus the groups were formulated on the basis of differences in gender such as men and women. For these groups assessed analysis were done through independent sample t- test.
Table 4.5 shows a significant difference between men and women on smartphone addiction it reveals that women are more addicted to smartphone as compared then men. Our hypothesis which states that women are more addicted to smart phone, than men are accepted. The Cohen’s d showed a small effect size.
4.6 Summary of Findings
Following is the summary of the present study findings:
- The gender was positively correlated with smartphone addiction. Furthermore, the duration of smartphone usage was positively correlated with smartphone addiction, interpersonal relationship and loneliness in university students
- There was a positive relationship between smartphone addiction and loneliness in university students. But there was a negative relationship between smartphone addiction and interpersonal relationship with university students.
- Smartphone addiction was highly significant and positively predicted the loneliness and was also significant but negatively predicted the interpersonal relationship in university students.
- Moreover, the finding revealed that there was a higher level of smartphone addiction in woman than men.
The current research was conducted to explore the relationship between Smart phone addiction, interpersonal relationship and loneliness. Loneliness and interpersonal relationship of university students was examined in the current study in terms of mobile phone addiction. When literature is analyzed, the literature has revealed that studies on mobile phone addiction do not have too much background. In addition, studies on mobile phone addiction related to loneliness are quite a few. In this context, this study may be important for the literature.
It was hypothesized that smart phone addiction will be a negative relationship between smartphone addiction and interpersonal relationship in university students. When interpersonal relationship of university student was examined it revealed that it was negatively correlated with smart phone addiction usage(r = -.42**). The results of some studies are similar to the results obtained from this study; a study done by Miller-Ott (2012) examined the use of cell phones and interpersonal relationship. Cell phones were shown to be a source of conflict in relationships when people created rules about when to call/text and over availability and frequency of contact. Arguments over cell phones and arguments regarding cell phone use were identified. Miller-Ott’s research suggests that cell phones are a source of relational conflict, and people do not like limits on their cell phone use. Our hypothesis has been approved and findings are consistent with previous literature.
Further it was hypothesized that smart phone addiction will be a positive relationship with loneliness. The result of this study showed that smart phone addiction positively correlated with loneliness(r = .41**)A study conducted by Kraut et al. (1998).It claimed that pathological use of the new technologies reduces the individual’s social implication in the real world and, as a consequence, his or her psychological well-being, because it produces the kind of isolation, loneliness and depression the individual wants to ease by connecting to the Internet. Chen’s (2006) result indicated heavy mobile phone users meet their friends less. Our hypothesis has been verified and findings are consistent with previous literature.
A hierarchical regression analysis was run for prediction. Hierarchical regression is a way to show if variables of your interest explain a statistically significant amount of variance in your Dependent Variable (DV) after accounting for all other variables. It was hypothesized that Smartphone addiction will negatively predict the interpersonal relationship in university students. A study was conducted by Casey (2012) studied the Linking Psychological Attributes to Smart Phone Addiction, Face-to-Face Communication, Present Absence and Social Capital. Students who reported the greater amount of smart phone used, the higher level of face-to-face communication and present absence they would report. The study also found that the smart phone addiction symptoms are significantly and negatively related to the level of face-to-face communication and positively related to present absence. Our hypothesis has been verified and findings are consistent with previous literature.
A hierarchical regression analysis was run for prediction.it was hypothesized that Smartphone addiction will positively predict the loneliness in university students. Casey (2012) studied the Linking Psychological Attributes to Smart Phone Addiction, Face-to-Face Communication, Present Absence and Social Capital. The results of this study showed that the higher one scored on loneliness and shyness, the higher the likelihood one would be addicted. Furthermore, the most powerful factors affect bonding social capital were gender, grade, and loneliness; while the most powerful factor affecting bridging social capital was face-to-face communication with friends.
An independent t test was conducted to see gender differences in smart phone addiction. It was hypothesis that Smartphone addiction will be higher in females than males. The result of this study indicate that female are more addicted of smart phone as compared to male. The results of some studies are similar to the results obtained from this study (Erözkan, 2004; Karao lu, Av aro lu, & Deniz, 2009; Wiseman, Guttfreund, & Lurie, 1995). In addition, some studies revealed that smart phone usage scores of female students were higher than the scores of male students (Kutlu, 2005).
5.2 Limitations and Suggestions
Following are the limitations and suggestions of the study.
- The sample size was limited due to the short time span of data collection. The quality of the external validity was low. For generalization of the study, large sample size must be taken.
- The Correlation research design was used to study. For further exploration and conformation the research designs like longitudinal or experimental and more rigorous research designs with improved methodology can be used.
- The present study only limited to the educated university students. Moreover, the present study result can be explored by selecting the different samples, like working people, bankers, international export or import companies workers etc.
Following is the implication of the present study;
- The study has implication in universities, social and family settings with the understanding of smartphone addiction and loneliness, its positive and negative effect on student relationships.
- This study gives a good explanation of addictive behavior in itself. Yet there are lots of improvements that can be made. This study can be repeated with different respondents like parents, friends and colleagues. These might be suitable respondents as they are directly affected by one’s behavior and habits; and findings of the study would enlighten the findings of existing studies as well as current research.
- The student also experienced the loneliness due to the every time indulged in smartphones, so in this way there is need to developed the strategies and support relationship in all relatively context through parent, peers and teachers.
- It may be helpful in creating intervention against excessive use of smartphone to enhance the quality of performance and motivate in students.
- With the help of the outcomes of the study, consideration should be given that
smartphone addiction and its negative effects tendencies can reduce in our society by enhancing their abilities and self-confidence or repairing the social networks. With this attempt we may create a protective barrier against rejection sensitivity that make orphans more disturbed and depressive.
- Internet addiction may lead to procrastination, which may further lead to poor academic performance of students. Furthermore, the interpersonal relationships of students are also likely to suffer as time spent online increases. The possible risks of internet addiction and consequences of delaying important academic tasks need be highlighted. Parents, teachers, and members of civil society need to monitor the internet use habits of students.
- This study helps the clinicians as well as social psychologists to deal with the smartphone addiction and loneliness in students.
Smartphone Addiction Among Students – References:
- Andersen, S. M., & Chen, S. (2002). The relational self: an interpersonal social-cognitive theory. Psychological review, 109(4), 619.
- Ali, S., Rizvi, A., & Qureshi, S.M. (2014). Cell Phone Mania and Pakistani Youth: Exploring the Cell Phone Usage Patterns among Teenagers of South Punjab. FWU Journal of Social Sciences, 8(2),42 – 50
- Al-Barashdi, H., Bouazza, A., & Jabur, N. (2014). Smartphone Addiction among University Undergraduates: A literature review
- Booth, R. (1997). Existential loneliness: The other side of the void. The International Journal of Interpersonal Studies, 16(1), 23-32.
- Becker, E. (2007). The denial of death. Simon and Schuster
- Blackham, H. J. (2012). Six existentialist thinkers. Routledge.
- Caplan, S. E. (2006). Relations among loneliness, social anxiety, and problematic Internet use. Cyber Psychology & Behavior, 10(2), 234-242.
- Casey, B. M. (2012). Linking psychological attributes to smart phone addiction, face-to-face communication, present absence and social capital (Doctoral dissertation, The Chinese University of Hong Kong).
- Cacioppo, J. T., & Patrick, W. (2008). Loneliness: Human nature and the need for social connection. WW Norton & Company.
- Carbonell, X., Oberst, U., Beranuy, M. (2013). The cell phone in the twenty-first century: A risk for addiction or a necessary tool? Principles of addiction, 1, 901-909.
- Choliz, M. (2010). Mobile phone addiction: Point of issue. Addiction, 105, 374. Retried on 16, October, 2011 from http://onlinelibrary.wiley.com/doi /10.1111 /j.13600443.2006.01593.x/full
- Enez Darcin, A., Kose, S., Noyan, C. O., Nurmedov, S., Yılmaz, O., & Dilbaz, N. (2016). Smartphone addiction and its relationship with social anxiety and loneliness. Behaviour & Information Technology, 35(7), 520-525.
- Everitt, B. J., Robbins, T. W. (2005). Neural system reinforcement for drug addiction: from actions to habits to compulsion. Nature Neuroscience, 8, 11, 1481-1489.
- Gupta, K. K., Ranjan, A., Bhatnagar, P., Sahu, L. K., & Jain, S. (2016). Multilevel inverter topologies with reduced device count: A review. IEEE Transactions on Power Electronics, 31(1), 135-151
- Gökçearslan, Ş., Mumcu, F. K., Haşlaman, T., & Çevik, Y. D. (2016). Modelling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students. Computers in Human Behavior, 63, 639-649.
- Ha, J. H., Chin, B., Park, D. H., Ryu, S. H., & Yu, J. (2008). Characteristics of excessive cellular phone use in Korean adolescents. CyberPsychology & Behavior, 11(6), 783-784.
- Harvey, J. H., & Pauwels, B. G. (2009). Relationship connection: A redux on the role of minding and the quality of feeling special in the enhancement of closeness. Oxford handbook of positive psychology, 385-392.
- Haverlag, D. (2013). Compulsief gebruik van sociale media op de smartphone. University of Utrecht, Utrecht.
- Huisman, A., Garretsen, H. F. L., & Van Den Eijnden, R. J. J. M. (2000). Problematisch Internetgebruik: een pilot study in Rotterdam. IVO reeks, (2).
- Isaac X. (2008). From Degradation to Redemption. Xlibris Corporation.
- Heinrich, L. M., & Gullone, E. (2006). The clinical significance of loneliness: A literature review. Clinical psychology review, 26(6), 695-718.
- Kim, B. N. (2013). Effect of smart-phone addiction on youth’s sociality development. The Journal of the Korea Contents Association, 13(4), 208-217
- Kwon, M., Kim, D., Choi, J., Gu, X., Hahn, C., Min, J., et al. (2013). Development and validation of a smartphone addiction scale (SAS). PLoS ONE, 8(2), e56936.
- Larson, R., Csikszentmihalyi, M., & Graef, R. (1982). Time alone in daily experience: Loneliness or renewal. Loneliness: A sourcebook of current theory, research and therapy, 40-53
- La Rose, R., & Eastin, M. (2004). A social cognitive theory of internet uses and gratifications: Toward a new model of media attendance. Journal of Broadcasting & Electronic Media, 52, 358-377.
- La Rose, R., Lin, C. A., & Eastin, M. S. (2003). Unregulated internet usage: Addiction, habit, or deficient self-regulation?. Media Psychology, 5(3), 225-253.
- Lo, S. K., Wang, C. C., & Fang, W. (2005). Physical interpersonal relationships and social anxiety among online game players. Cyberpsychology & behavior, 8(1), 15-20.
- Leena, K., Tomi, L., & Arja, R. (2005). Intensity of mobile phone use and health compromising behaviours—how is information and communication technology connected to health- related lifestyle in adolescence?. Journal of adolescence, 28(1), 35-47.
- McLuhan, M. (1964). Understanding media: the extensions of man (1st ed.). New York: McGraw-Hill.
Okazaki, S., & Hirose, M. (2009). Does gender affect media choice in travel information search? On the use of mobile Internet. Tourism Management, 30(6), 794-804.
- Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2011). Habits make smartphone use more pervasive. Personal and Ubiquitous Computing, 0, 1-10.
- Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2012). Habits make smartphone use more pervasive. Personal and Ubiquitous Computing, 16(1), 105-114.
- Pettegrew, L. S., & Day, C. (2015). Smart phones and mediated relationships: The changing face of relational communication. Review of Communication, 15(2), 122-139.
- Peplau, L. A., & Perlman, D. (1982). Perspectives on loneliness. Loneliness: A sourcebook of current theory, research and therapy, 1-20.
- R. Harper (Editors.) Wireless World: Social and Interactional Aspects of the Mobile Age. Godalming aŶd Hiedleďuƌg: “pƌiŶgeƌ Veƌlag, pp. 99‐ϭϭϱ.
- Rush, S. (2011). Problematic use of smartphones in the workplace: An introductory study. Central Queensland University, Rockhampton.
- Salehan, M., & Negahban, A. (2013). Social networking on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29(6), 2632-2639.
- Sattari, K. (2016). THE EFFICACY OF PSYCHO-RELIGIOUS TRAINING ON IMPROVEMENT OF ORGANIZATIONAL BEHAVIOR AND MENTAL HEALTH. Journal of Fundamental and Applied Sciences, 8(4S), 2153-2181.
- Shahsavarani, A. M., Zoghifard, E., Mishamandani, M. E., Mahmoodabadi, M., Mohammadi, A., & Nielsen, P., & Fjuk, A. (2010). The reality beyond the hype: Mobile internet is primarily an extension of pc-based internet. The Information Society, 26(5), 375-382.
- Suedfeld, P. (1982). Aloneness as a healing experience. Loneliness: A sourcebook of current theory, research and therapy, 54-67
- Suedfeld, P. (1987). Extreme and unusual environments. Handbook of environmental psychology, 1, 863-887.
- Snyder, C. R., Lopez, S. J., & Pedrotti, J. T. (2010). Positive psychology: The scientific and practical explorations of human strengths. Sage Publications.
- Sidanius, J., & Pratto, F. (2001). Social dominance: An intergroup theory of social hierarchy and oppression. Cambridge University Press
- Whang, L. S., Lee, S., & Chang, G. (2003). Internet over-users’ psychological profiles: A behavior sampling analysis on internet addiction. CyberPsychology Behavior, 6(2), 143- 150.
- Wayne, S. J., Shore, L. M., & Liden, R. C. (1997). Perceived organizational support and leader- member exchange: A social exchange perspective. Academy of Management journal, 40(1), 82-111.
- Weilenmann, A., & Larsson, C. (2002). Local use and sharing of mobile phones. In Wireless world (pp. 92-107). Springer London.
- Leung, L., & Wei, R. (1999). Who are the mobile phone have-nots? Influences and consequences. New Media & Society, 1(2), 209-226.
- Wood, W., & Neal, D. T. (2007). A new look at habits and the habit-goal interface. Psychological Review, 114(4), 843-863.
- Young, K.S. (1999). Internet addiction: Symptoms, evaluation and treatment. Innovations in Clinical Practice, 17.
- Yan, J., & Sorenson, R. (2006). The effect of Confucian values on succession in family business. Family business review, 19(3), 235-250.