Social media use has been increasing apace regardless of geographical and economic boundaries. In particular, its penetration has occurred more rapidly in developing and low-income countries with abounding health and psychological disadvantages. Given the understanding that women are more prone to psychological disorders than men, the current research is an effort to examine social media motives and subsequent effects on the psychological well-being of women social media users in Pakistan. The study is based on an online survey conducted to ascertain as to what extent social media use contributes to women’s psychological well-being or otherwise. The survey recorded responses of 240 women selected through purposive sampling technique. SEM-PLS analysis of the collected data revealed that social media usage plays a meaningful role in women’s psychological health. However, results exposed that Pakistani women, under the traditional patriarchal social pressure, not only have to observe cultural norms in online practices but are also forced to adhere to socially constructed gender roles in online spaces. The mixed results suggest conducting extensive research for a deeper insight into the role of social media in psychological well-being of women in other low-income countries.
Background of the study
Research and conceptual model
Discussion and analysis
Since the emergence of new media technologies, a huge bulk of the literature has touched upon the usage and effects of social media. Nonetheless, specific psychological consequences of social media use remain empirically contested (Pantic, 2014). While examining the overwhelming use of social media, scholars speculated and carried out studies to categorize the pros and cons to gauge whether social media use positively or negatively influences users’ psychological well-being.
A cursory perusal of the available literature highlights that concerns and questions raised by the researchers outnumber the answers provided by the studies. Three recent systematic reviews revealed wide gaps in the literature and identified questions which remain unexplored and unanswered. Best, et al. (2014) concluded with contradictory evidence on the impacts of social media in the context of users’ mental health. Whereas, Erfani and Abedin (2018) pointed out a lack of media and well-being research in developing regions of the world and also pointed out women’s absence in new media and well-being research. Likewise, Lwoga and Sangeda (2018) revealed limited evidence on the long-term contribution of new media communication to well-being in developing countries.
The present article, therefore, examined the effects of social media on the psychological well-being of women in Pakistan — a society that is inherently male-dominated and prone to mental, emotional, and physical abuse of women. In such a state of affairs, women’s mental and emotional disorders and low self-esteem adversely influence their overall well-being. Consequently, they seem to be in search of some activity that offers them escape from the harsh realities of everyday life.
Background of the study
Women’s social positioning in Pakistan
Women worldwide suffer psychological disorders (Mootz, et al., 2019). However, some regions of the world, such as central Asia and southeast Asia, which are deeply patriarchal, face these issues more adversely. In these societies, women lag behind men in all fields of life and remain under-represented, while both religious and cultural forces also mutually contribute to women’s submissive status and low well-being (Urbaeva, 2019).
Similarly, established gender inequalities in Pakistan expose women to culturally inherited biases (Batool and Batool, 2018). The increasing number of harassment and domestic violence cases has included Pakistan among the list of most dangerous countries for women in the world . Women are given a marginalized status and limited fundamental rights of education, health, and employment in the male-dominated society of Pakistan. According to statistics, only 47 percent of female citizens are literate as compared to 71 percent literate male citizens in Pakistan . The mortality rate is also higher among women as evidenced from the fact that every 37 minutes a woman dies during childbearing, indicating limited healthcare facilities for women.
Women constitute 50 percent of the population in Pakistan; however, only 25 percent participate in the labor force and national development. Moreover, oppressive cultural and social norms, domestic violence, and financial dependency further contribute to women’s low well-being (Niaz, 2004); hence women suffer more psychological disorders than men do (Ahmed, et al., 2016).
Women’s social media accessibility and use in Pakistan
Currently, almost 4.5 billion people worldwide have access to the Internet and social media . This technological proliferation has also penetrated in Pakistan, resulting in the increasingly growing use of the Internet and social media platforms. Moreover, the technological transition in Pakistan since the early 1990s with a slow dial-up connection to the recent 4G and Wi-Fi technology has transformed the socialization and interactional patterns and opened up new opportunities for information sharing, resulting in gradual cultural transformation (Mustafa, 2018).
Young people, both men and women use social media quite frequently (Jamil, 2018; Eijaz, 2013); the online spaces in Pakistan however, continue to remain male-dominated. Women are not usually welcomed in the online sphere (Kasana, 2016), thus, only 29 percent of them use new media technologies. According to the Digital Rights Foundation (2017), 45 percent of women in Pakistan face online harassment. Here, it should be borne in mind that several cases are not even reported or registered due to the culturally oppressive compliance to gender roles.
Social media motives
Motivations to use social media differ among individuals. Considering it quite essential to identify the motives for social media use to determine its consequent effects (Valkenburg, et al., 2006), scholars tried to delve deeper into the task (Valenzuela, et al., 2009). Hence, multiple studies were carried out to enlist motives for social media use. These studies mainly identified motives including information and knowledge-seeking; surveillance; entertainment; time-pass; escape; socialization; self-status enhancement; self-exposure; identity establishment; and, utility (Johnson and Kaye, 2004; Shao, 2009; Stafford, et al., 2004). While Sheldon (2008) reported six motives, which are relationship making and maintenance, pastime, being part of a virtual community, fun, coolness, and companionship, Park, et al. (2009) considered socializing, entertainment, self-status seeking, and information as the motives of Facebook use. Recently, scholars also observed that social media is intensively used for socializing, maintaining and strengthening relationships, gaining information, and reducing stress (Basilisco and Cha, 2015).
An extensive review of the literature surfaced the impression that socialization, escapism, personal, emotional, and information motives remained consistent, which were operationalized in varying terms. The present research also relied on these five motives of social media use to examine its effects on the psychological well-being of females in Pakistan.
Irrespective of traditional or new media technologies, socialization has consistently been a major reason for interaction. Scholars commonly mentioned socializing as an essential aspect of social media use (Park, et al., 2009; Sheldon, 2008). However, keeping in touch with friends and family and people at large is also a significant motivation for using social media. According to research, social media use creates a sense of belongingness, connectedness, and companionship and reduces isolation and loneliness, thus resulting in overall well-being (Diomidous, et al., 2016; Erfani and Abedin, 2018). Being a “natural companion” of “native speakers of the digital language” (Palfrey, et al., 2011), the Internet and social media extend friendship circles and keep people connected (Tufekci, 2010). Through social media platforms, people are closely associated with each other, which reduces loneliness (H.-T. Chen and Li, 2017).
Moreover, the feeling of being connected improves relationships and well-being of users. Apart from this, online socialization enhances opportunities for communication and interaction with far-off people. Moreover, mutual sharing brings fruitful results, such as employment and business opportunities (Sanchiz, et al., 2016). Scholars also believe that social media usage improves the quality of life and self-esteem due to new connections and enhanced interaction (J. Chen, et al., 2009).
The concept of escapism has many connotations in terms of revival mechanism and coping with emotional distress to relieve the harmful effects of stressful events on individuals (Stenseng, et al., 2012). The escapism or diversion motive of media use has been explained as an alternate option to get away from a distressful situation by entertaining oneself. This motive involves active engagement in social media to avoid real-life problems and turning to a utopian world (Hastall, 2017).
People use Facebook for escapism, which in fact, reduces life satisfaction (Young, et al., 2017). Previous research termed escapism motive as a psychological disorder as it takes users away from real life (Hassouneh and Brengman, 2014). A recent study also discovered escapism as promoting loneliness (C.-Y. Chen and Chang, 2019). No study was found which explained or presented consequences of online escapism on psychological well-being, so keeping in view the overall effect of escapism it is assumed that in the long run it negatively contributes to one’s psychological well-being.
Personal motives include “status exposure” and identity (Park, et al., 2009) “self-presentation” and “coolness” (Sheldon, 2008). Although personal motives are explained in different terms, the core concept of personal motives indicates the use of social media for maintaining and expressing a positive online image. The study (Bailey, et al., 2013) described the positive effects of online self-exposure on psychological well-being as it promotes users’ confidence and self-esteem. Since social media provide an opportunity to users to establish online profiles according to their desire, users promote best aspects of their personality which enhance their self-esteem (Gonzales and Hancock, 2011) and thus form part of their psychological well-being.
Sharing of personal information is said to be strongly associated with one’s emotions; hence the emotional expression on social media has been widely discussed (Dupré, et al., 2019), and it is still part of the academic debate.
Social media are open platforms where users express their emotions and feelings in multiple ways through pictures, emoticons, posts, and quotes. One of the main reasons for sharing emotional information online is to express feelings and emotions related to an event or an experience. The easiest way to do this is to connect to social media platforms such as Facebook, Twitter, Instagram, or WhatsApp where one gets instant response and gratification (Waterloo, et al., 2018). While explaining the association of emotional motive and psychological well-being, the affective (emotional) well-being, which is an associative component of psychological well-being, has been discussed too (Weinstein, 2018). Both negative and positive emotions are expressed on social media, which leads to mixed effects on users’ psychological well-being.
In the Uses and Gratification research tradition, cognitive use or information-seeking motive of socialization remained central in traditional media use, such as reading newspapers and watching television (Eveland, et al., 2003). Traditional media (radio, television, newspapers) studies proposed cognitive need as an essential motive for media exposure (Norris and Jones, 1998). Scholars observed that cognitive use of media resulted in social behaviours such as political involvement and civic participation (Pasek, et al., 2009).
Likewise, pertaining to new media and informational use, scholars specifically focused on and explored the contours of the informational context of social media in politics (Gil de Zúñiga, et al., 2017). How the informational use of social media leads to or impacts ones psychological well-being did not receive academic attention, though (H. Lee and Choi, 2014). While observing the available evidence in the literature, it is assumed and expected that the informational use of social media can potentially contribute to psychological well-being and lead to better personal growth and enhanced environment handling.
Psychological well-being and social media
The concept of well-being is quite a complex phenomenon that can be defined or gauged in a number of ways. It, however, primarily relates to “optimal psychological experience and functioning” (Ryan and Deci, 2001). In new media research, the concept of well-being was vaguely defined, and multiple indicators of well-being such as happiness, life quality, level of depression, and loneliness, and life satisfaction were used to measure the effects of social media on users’ psychological well-being (Burke and Kraut, 2016; Chae, 2018). Moreover, it was believed that social media use reduced hopelessness and improved personal image (Hogue and Mills, 2019; Park and Baek, 2018).
Despite the use of multiple and diverse indicators of psychological well-being, new media research regarding psychological well-being is still controversial (Best, et al., 2014; Pantic, 2014). The massive growth of social media and prolonged online time motivated the scholars to observe new communication patterns at both individual and social levels to see whether or not the phenomenon contributes to users’ psychological well-being. The results of these studies, however, revealed inconsistent findings. For instance, the time spent on social media negatively influenced psychological well-being (Weinstein, 2018) and increased depression, anxiety, and loneliness (Oberst, et al., 2017). Likewise, frequent users of Facebook reported less life satisfaction and believed that others were happier and more content in their lives (Vogel, et al., 2015). Further, a study reported decreased emotional well-being and reduced life satisfaction among Facebook users (Verduyn, et al., 2017).
In comparison to the research that reported negative effects of social media on users’ psychological well-being, another group of scholars described its positive outcomes, such as the contribution of Facebook friends towards subjective well-being and social assistance (H.E. Lee and Cho, 2018), and reduced loneliness and depression (Nabi, et al., 2013). Moreover, these studies reported that online friends helped with extending connections, which increased and developed chances of positive relationships and contributed to users’ overall well-being (Gonzales and Hancock, 2011). Apart from online friends, other variables such as frequency, rate, and intensity of social media use also indicated a positive effect on users’ well-being (Valkenburg, et al., 2006).
Research and conceptual model
Women’s inclusion in advanced technologies remains a worldwide issue although scholars strongly advocate the role of new media in eliminating gender inequalities and improving women’s lives and well-being (O’Donnell and Sweetman, 2018). Therefore, the initiative of ICT4D (information communication technologies for development) was taken to increase women’s accessibility to technologies to get them a better status in society and to enhance their well-being (Roberts, 2016). However, despite numerous initiatives and technologies for women’s well-being, academic research mainly focused on women’s online self-presentation, body image, and stereotypical presence (Ramsey and Horan, 2018). Very little attention was given to examine the effects of new media on the psychological well-being of women, and unfortunately, no studies addressed the subject explicitly.
There is plentiful academic evidence that substantiates the association of social media use and psychological well-being. Researchers, after an extensive examination of the literature, identified two gaps — the absence of women in new media research related to psychological well-being, and how motives for social media use lead to psychological well-being. Most of the studies mainly measured social media uses in terms of lists of friends and time spent on social media and correlated these two variables with psychological well-being. Further, repeatedly, only happiness, loneliness, life satisfaction, and self-esteem were examined as the measures of psychological well-being.
Thus, to fill the gap, the current research was conducted to examine the effects of social media motives on women’s psychological well-being. The study is based on borrowed theoretical assumptions from Uses and Gratification theory of media and Ryff’s psychological well-being model (Ryff and Keyes, 1995) with six dimensions (autonomy, self-acceptance, personal growth, positive relation, environmental mastery, and purpose in life).
Figure 1: Conceptual framework
Based on the above-stated objective, the following research question and research hypothesis was formulated:
RQ: How do social media motives (socialization; escapism; and personal, emotional, and informational uses) correlate to women’s psychological well-being?
H: Social media motives (socialization; escapism; and personal, emotional, and informational uses) positively correlate to women’s psychological well-being.
Area and context of research
The study was conducted in the federal capital of Pakistan–ICT (Islamabad Capital Territory), which is a culturally diverse city. Being the capital, it is the hub of government offices, educational institutions, diplomatic missions, and many international and national companies. People from across the country and the world reside there for jobs and other purposes. Further, education is one of the main attractions for the general public to come to the city. According to the 2017 census, approximately 4.5 million people populated the city, and 47 percent of them were women.
Research participants of this study were Pakistani female social media users who were employed as university faculty members. Earlier studies mainly focused on the youth of Pakistan while examining the online activities, patterns of usage, and effects of social media (Nasir, et al., 2012; Ahmad, et al., 2016; Mahmood, et al., 2018) and women were wholly ignored in new media research in Pakistan although they actively use social media despite cultural restrictions and limited access to technologies (Zubair, 2016; Qaisrani, et al., 2016). Considering the number of psychological issues among women, it is quite an important area to explore the effects of social media on women’s psychological well-being.
Sample and sample size
A reflective sample of the population (Hair, et al., 2016) was ensured to represent the population and generalize the results (Sekaran and Bougie, 2016). There are multiple suggestions by statisticians for calculating appropriate samples for structural equation modeling, such as 100 and above, though (Bagozzi and Yi, 2012; Hair, et al., 2016). Although the small size (100+) is also considered adequate for PLS-SEM (Goodhue, et al., 2012; Hair, et al., 2016; Marcoulides and Saunders, 2006) to ensure ample and appropriate sample size, the study followed two approaches. The sample size was calculated by path direction (Barclay, et al., 1995). The path direction from IV to DV was (12 paths) calculated 10 times larger to determine the sample size (12*10=120) (Hair, et al., 2011; Marcoulides and Chin, 2013). Further, recommendations of Cohen (1992) were followed to ensure ample sample size and population representation.
The study utilized the purposive sampling technique and selected working women as samples. Since the majority of Pakistani women work in the teaching profession, female teachers from universities were approached. In Islamabad, almost three thousand women are working as faculty members in universities. Their official e-mail addresses were taken from official Web sites, and a questionnaire link was sent to them via e-mail messages.
Part A: Demographic
The first section of the questionnaire recorded demographical information of the respondents, including age, occupation, education, and marital status.
Part B: Social media usage patterns
The second part of the questionnaire measured the trends and patterns of social media usage among women. This part of the instrument recorded online time, frequency of social media usage, number of social media sites with their profiles, and preference for a device for social media use.
Part C: Social media motives (independent variables)
The independent variables of the study included five motives of social media among women: socialization, escapism, information, emotional, and personal. Each motivation had four items.
The socialization motive focused on communication and interaction with friends and family; escapism motive addressed the use of social media for diversion and time-pass; personal motive items centered on individual’s self-presentation and self-credibility and status; emotional motive focused on emotional disclosure, and informational motive addressed the use of social media for academic purposes.
Part D: Psychological well-being
The study utilized a revised version of the well-validated scale of psychological well-being by Ryff (1989) to measure the effects of social media on the psychological well-being of female social media users. The scale comprised six sub-dimensions and 30 items such as Autonomy; Environmental mastery; Positive relations; Purpose in life; Self-acceptance; and, Personal growth.
Autonomy: Being independent with hold on decision-making despite social pressure;
Environment mastery: Knowing and understanding available sources, and choosing and changing the course of action according to the situation;
Positive relations: Having positive and balanced relations with family, friends, and people at large;
Purpose in life: Having a clear and meaningful goal in life and the desire to achieve it;
Self-acceptance: Possessing self-understanding and a realistic view of ones’ personality; and,
Personal growth: Experiencing self-development over time and feeling improvement in self.
A Web-based survey was carried out in 2019, and the online questionnaire link remained available for two months (June and July 2019). Scholars and statisticians suggested online survey mainly because it saves time and financial expenses (Wright, 2005). During these two months, fortnightly reminders were sent, and in total, four reminders were given to respondents to fill out the online questionnaire. Since during statistical analysis, ouliers and missing data is common issue in researcher, therefore, suggestions and recommendations by Hair, et al. (2011) are followed, and 20 percent extra responses were obtained to avoid statistical analysis erorrs. Overall, 240 responses were received for the research.
For the analysis of quantitative data, second-generation statistical analysis technique PLS-SEM (version 3.3.2) was used. PLS-SEM is quite helpful in social sciences research as it not only measures the variables but also configures the errors among or within variables (Chin, 1998). In addition, the measurement model provides a detailed evaluation of the relationship between variables (Kline, 2015). Both confirmatory factor analysis and regression analysis produce reliable results (Grottke, et al., 2018).
Demographics and social media usage
Two hundred and forty females from 30 to 60 years of age participated in the survey. Some 53 percent of them fell between 30 to 40 years of age. Fifty-six percent of the participants had completed 18 years of education, and 73 percent were employed as permanent faculty members in the social sciences and management sciences departments of several universities in the federal capital of Pakistan.
All the participants used social media with minimal variation in frequency and subscription to social networking sites. Ninety percent of the participants accessed social media through the handset and were actively using three to four social networking sites (mostly Facebook, Twitter, Linkedln, and Instagram). On average, they spent 4.5 hours daily on social media exclusively for personal reasons.
Social media motivations
The descriptive analysis was carried out to present the level of motivations for social media use among women participants.
Figure 2: Social media motivations.
According to the results, socialization motive predominates (M=3.78, SD=.73), and further informational (M=3.74, SD=.56), and escapism motives (M=3.24, SD=.88), were found higher among the participants respectively. The mean score of the personal motives (M=2.86, SD=.98), and emotional motives (M=2.64, SD=.95) revealed that these motives have less contribution in social media use among women.
Structural equation modeling (SEM)
Identification and elimination of outliers were performed to ensure results’ accuracy and reliability. Normal distribution of data was tested through the normality test. The obtained value of skewness calculated between 0.169 to -0.724 and the kurtosis ranged from 1.917 to -0.778, which indicated that data were normally distributed. The multi-collinearity was measured by variance inflation factors (VIFs). The endogenous variable psychological well-being with six dimensions was studied in the research. VIF for psychological well-being was 1.729, and the correlation coefficients between exogenous constructs were less than 0.8, which also indicated that there was no multi-collinearity.
The measurement model calculated convergent and discriminant validity. The model observed the variables and described the relationship between them. Convergent validity in social sciences research refers to the relationship of two constructs. The researchers measured the factor-loading of items (see Table 1) and then rechecked the modified factor-loading. We used Cronbach’s alpha value to determine reliability. The obtained Cronbach’s alpha value fell within the values suggested by scholars, i.e., 0.7 (Hair, et al., 2011). In modified factor loading, the obtained values less than 0.7 are deleted. Similarly, the average variance extracted (AVE) was measured, which suggested that the accepted value of AVE was 0.5 (Fornell and Larcker, 1981). The statistical analysis produced satisfactory values of factor-loading, Cronbach’s alpha and AVE, and indicated relevance and reliability.
Table 1: Results of convergent validity. Construct Item Initial model Modified model Cronbach’s alpha Composite reliability Average variance extracted (AVE) Socialization motive SM.1 0.848 0.843 SM.2 0.634 0.647 SM.3 0.817 0.820 0.807 0.866 0.625 SM.4 0.564 Deleted SM.5 0.836 0.836 Escapism motive EM.1 0.827 0.829 0.78 0.867 0.686 EM.2 0.87 0.872 EM.3 0.785 0.779 Personal motive PM.1 0.903 0.901 0.928 0.949 0.823 PM.2 0.931 0.931 PM.3 0.927 0.924 PM.4 0.866 0.871 Emotional motive EM.M1 0.727 0.734 0.813 0.89 0.731 EM.M2 0.895 0.891 EM.M3 0.93 0.928 Information motive IM.1 0.784 0.790 0.795 0.865 0.617 IM.2 0.717 0.721 IM.3 0.862 0.862 IM.3 0.771 0.764 Autonomy Item1 0.739 0.744 0.843 0.895 0.682 Item2 0.87 0.876 Item3 0.886 0.895 Item4 -0.522 Deleted Item5 0.763 0.778 Personal growth Item1 -0.389 Deleted 0.669 0.800 0.502 Item2 0.601 0.614 Item3 0.783 0.785 Item4 0.658 0.664 Item5 0.765 0.757 Purpose in life Item1 0.757 0.755 Item2 0.379 Deleted 0.426 0.688 0.435 Item3 0.69 0.693 Item4 0.642 0.636 Item5 -0.015 Deleted Environment mastery Item1 0.665 0.659 Item2 0.838 0.833 Item3 0.85 0.854 0.731 0.829 0.554 Item4 0.592 0.599 Self-acceptance Item1 0.578 0.574 Item2 0.641 0.643 Item3 0.593 0.59 0.775 0.857 0.602 Item4 0.553 0.555 Positive relations Item1 0.754 0.733 Item2 0.868 0.861 Item3 0.661 0.695 0.729 0.832 0.555 Item4 -0.433 Deleted Item5 0.649 0.678
The discriminant validity tool measured the difference among the constructs. In simple words, the discriminant validity explains to what extent constructs are dissimilar and distinctive from each other. The discriminant validity is measured through multiple methods; however, for the current study, the Hetrotrait-Monotrait ratio of criterion (HTMT) was employed (Henseler, et al., 2014) and results are presented in Table 2. Hair, et al. (2011) suggest that the HTMT values smaller than 0.85 (0.90) mean that the two constructs are distinct. This test further suggested that the constructs measured independently in the model and did not overlap during the measurement (Hair, et al., 2011).
Table 2: Correlation of latent constructs and discriminant validity (HTMT ratio). 1 2 3 4 5 6 7 8 9 10 11 Autonomy 1 Emotional motive 0.277 Environment mastery 0.324 0.642 Escapism motive 0.333 0.278 0.183 Informational motive 0.51 0.226 0.24 0.47 Personal growth 0.364 0.335 0.309 0.15 0.277 Personal motive 0.116 0.662 0.366 0.42 0.153 0.146 Positive relations 0.299 0.405 0.415 0.53 0.459 0.668 0.16 Purpose in life 0.59 0.587 0.643 0.44 0.543 0.662 0.387 0.855 Self-acceptance 0.453 0.239 0.382 0.57 0.545 0.319 0.164 0.54 0.882 Socialization motive 0.316 0.224 0.223 0.45 0.279 0.413 0.436 0.325 0.313 0.251 1
Structural model analysis
For path analysis, the bootstrap approach was performed to examine the relationship and effects of independent variables on dependent variables. The first phase of the path analysis confirmed the level of relationship of social media motives with psychological well-being. The formulated hypotheses were tested through structural equation modeling. According to the research framework in the first model, the combined effects and significance of social media motives on overall psychological well-being were assessed.
The first model (Figure 3) focused on the relationship between social media motives and overall psychological well-being. Since the bootstrapping approach tests confirmed the statistical importance of coefficients and consequently the error of the expected path coefficients (Chin, 1998), the proposed relationship in formulated hypotheses was tested by the bootstrapping approach to evaluate the significance of hypotheses in the model. Figure 1 presents the values of path coefficients with significance (β), p-values, and the R2 values of endogenous constructs.
Figure 3: Path model using a bootstrapping approach for the first model.
The result of the bootstrapping method in Table 3 showed the effect of social media motives on psychological well-being. According to these results, personal motives don’t have significant effects (β = -0.211, p<0.004) on psychological well-being. Although the emotional motives have negative effect on psychological well-being but significant (β =-0.346, p<0.001). According to the statistical analysis, personal and emotional motives had an inverse/negative relationship with psychological well-being. Remaining motives (socialization, escapism and informational) have positive and significant effect on women’s psychological well-being.
To obtain the R2 values, the study utilized the Smart-PLS algorithm function. The adjusted R2 for psychological well-being was 0.523, which indicated that social media motive could explain 52 percent of the variance of psychological well-being. In other words, 52 percent change occurred in overall psychological well-being due to social media motives.
Table 3: Results of the bootstrapping approach for the first model. Paths β SE t-value p-values Results Socialization motive –>PWB 0.223 0.052 4.269 <0.001 Supported Escapism motive –>PWB 0.361 0.066 5.427 <0.001 Supported Personal motive –>PWB -0.211 0.074 2.844 0.004 Not supported Emotional motive –>PWB -0.346 0.055 6.256 <0.001 Supported Informational motive –>PWB 0.263 0.064 4.083 <0.001 Supported
R2 indicated the impact of the independent variable on the dependent variable and highlighted the difference in case an independent construct was omitted from the model. This is also known as the f2 or effect size. The effect size is measured through its standardized values, such as small (f2 ≥ 0.02), medium (f2 ≥ 0.15), and larger (f2 ≥ 0.35) (Cohen, 1992). The effect size values in Table 4 indicated that socialization (0.083) and personal (0.054) motives had insignificant effect on psychological well-being, while escapism motive (0.199), emotional motive (0.163), and informational motive (0.117) had medium effect on psychological well-being.
Table 4: Effect size f2 for the endogenous variable. Exogenous variable Endogenous variable Psychological well-being Socialization motive 0.083 Escapism motive 0.199 Personal motive 0.054 Emotional motive 0.163 Informational motive 0.117
Model I and statistical analysis presented significant effect of social media motives on women’s psychological well-being. However, to examine the effect of social media motive on each sub-dimension of psychological well-being, another path analysis was carried out. Model II identified the aspects of psychological well-being that are influenced by social media motive independently.
Figure 4: Path model using a bootstrapping approach for the second model.
Model II disclosed the effect social media motivations on each sub-dimension of women’s psychological well-being. According to the results (see Table 5) the personal motives don’t have significant effect on women’s autonomy, environment mastery, personal growth and positive relations. Similarly, the informational motives insignificant effect on women’s environment mastery, personal growth and positive relations. However, socialization, emotional and escapism motives have significant effect on women’s different aspects of psychological well-being.
Similar to Model 1, the R2 value of Model II showed predictive capacity of the structural model. The adjusted R2 values were autonomy (0.266), positive relations (0.351), personal growth (0.188), self-acceptance (0.407), environment mastery (0.337), and purpose in life (0.371). R2 values explain changes in dimensions of psychological well-being by social media motive. The highest change occurred in self-acceptance, i.e., 40 percent, followed by purpose in life (37 percent), positive relations 35 percent, environment mastery 33 percent, and autonomy 26 percent. The lowest change occurred in personal growth, i.e., 18 percent.
Table 3: Results of the bootstrapping approach for the second model. Paths β SE t-value p-values Results Socialization motive –>Autonomy 0.201 0.066 3.024 0.001 Supported Socialization motive –>Environment mastery -0.135 0.077 1.757 0.079 Not supported Socialization motive –>Personal growth 0.366 0.072 5.07 0.001 Supported Socialization motive –>Positive relations 0.169 0.062 2.728 0.001 Supported Socialization motive –>Purpose in life 0.179 0.058 3.1 0.001 Supported Socialization motive –>Self-acceptance 0.092 0.049 1.866 0.062 Not supported Escapism motive –>Autonomy 0.136 0.081 1.687 0.092 Not supported Escapism motive –>Environment mastery 0.268 0.065 4.157 0.001 Supported Escapism motive –>Personal growth -0.121 0.073 1.658 0.097 Not supported Escapism motive –>Positive relations 0.364 0.07 5.195 0.001 Supported Escapism motive –>Purpose in life 0.295 0.07 4.217 0.001 Supported Escapism motive –>Self-acceptance 0.46 0.059 7.752 0.001 Supported Personal motive –>Autonomy -0.018 0.094 0.192 0.848 Not supported Personal motive –>Environment mastery -0.062 0.078 0.796 0.426 Not supported Personal motive –>Personal growth -0.038 0.094 0.399 0.69 Not supported Personal motive –>Positive relations -0.051 0.073 0.708 0.479 Not supported Personal motive –>Purpose in life -0.277 0.083 3.341 0.001 Supported Personal motive –>Self-acceptance -0.329 0.071 4.635 0.001 Supported Emotional motive –>Autonomy -0.232 0.079 2.956 0.001 Supported Emotional motive –>Environment mastery -0.498 0.064 7.753 0.001 Supported Emotional motive –>Personal growth -0.273 0.078 3.512 0.001 Supported Emotional motive –>Positive relations -0.349 0.071 4.903 0.001 Supported Emotional motive –>Purpose in life -0.208 0.08 2.59 0.01 Supported Emotional motive –>Self-acceptance -0.02 0.065 0.307 0.759 Not supported Informational motive –>Autonomy 0.292 0.069 4.232 0.001 Supported Informational motive –>Environment mastery 0.008 0.059 0.134 0.894 Not supported Informational motive –>Personal growth 0.098 0.103 0.955 0.340 Not supported Informational motive –>Positive relations 0.13 0.074 1.752 0.080 Not supported Informational motive –>Purpose in life 0.261 0.076 3.421 0.001 Supported Informational motive –>Self-acceptance 0.27 0.075 3.599 0.001 Supported
In Model II, R2 values were calculated to examine the impact of independent variable on the dependent variable. In Model II f2 or effect, size is also measured to explain the level of effect in standardized values, such as small (f2 ≥ 0.02), medium (f2 ≥ 0.15), and larger (f2 ≥ 0.35) (Cohen, 1992). The extended analysis of Model II presented the effect size of each social media motive on all six dimensions of psychological well-being.
According to results, Socialization motive had a close to medium effect on Personal growth (0.129) while the Escapism motive had a medium effect on Positive relations (0.146) and Self-acceptance (0.255). Personal motive only had a noticeable effect on Self-acceptance (0.104) while Emotional motive had a medium effect on Environment mastery (0.237) and Positive relations (0.119).The Informational motive, however, had a small effect on all dimensions of psychological well-being.
Table 6: Effect size f2 for the endogenous variable. Exogenous variable Endogenous variable Autonomy Personal growth Purpose in life Environment mastery Positive relations Self-acceptance Socialization motive 0.043 0.129 0.040 0.022 0.035 0.011 Escapism motive 0.018 0.013 0.099 0.078 0.146 0.255 Personal motive 0.00 0.001 0.069 0.003 0.002 0.104 Emotional motive 0.047 0.058 0.044 0.237 0.119 0.00 Informational motive 0.091 0.009 0.085 0.00 0.02 0.096
Discussion and analysis
Delving into the gap in academic literature, this article provided an in-depth analysis of the effects of social media on Pakistani female users’ psychological well-being.
The social media wave emerged in Pakistan in the mid-2000s, transforming the social, political, and cultural landscape of the country. Interestingly, while Pakistan now stands at number 10 with the title of the emerging Internet economy, gender disparities in technological use and access are still widespread in the country. Unfortunately, reliable data is not available in Pakistan to determine the actual use and penetration of the Internet and social media. There are countless differences in government data and privately conducted surveys. However, higher use of social media is observed regardless of gender, age, and social class (Younus, 2018).
Numerous studies revealed multiple uses and gratification of social media needs (Ali, 2016; Hassan, 2018; Hussain, 2014; Shabib and Fatima, 2012); however, the question as to how these motives lead to women’s psychological well-being remained unanswered.
The results in this pape presented social media motivations among women in turn as socialization, escapism, informational, personal, and emotional. We examined the effects of social media motives on women’s psychological well-being and found an almost 52 percent (R2: 0.523) change in women’s psychological well-being due to social media use. At the first stage, a statistical analysis presented the effect of each motive on overall psychological well-being. Although socialization motives was found higher among participants, results indicated that the escapism motive had a significant effect on psychological well-being of female social media users.
The escapism motive points towards tension release and diversion from routine issues. It indicates that women use social media to get rid of their daily-life problems and to seek pleasure, involving in diverse activities (Krcaburun and Griffiths, 2019), all having positive effects on psychological well-being. Pakistani women reportedly experience depression and mental issues owing to prevalent patriarchal social designs (Shaud and Asad, 2020), so they use social media as an escape from reality. The escapism motive sheds light on the real life of Pakistani women, providing insights into their psychological issues which they are trying to camouflage through social media.
Likewise, the personal motive, which explains disclosure, self-presentation, and objectification, and the emotional motive, which indicates the use of social media for emotional needs, were found less significant. Consequently, the results revealed that the personal and emotional motives both have an inverse relationship with psychological well-being. Although women join social media sites as an escape from the realities of their lives, the cultural norms do not really allow them to disclose their true identities (Hardaker and McGlashan, 2016) and seek emotional guidance. Women are bound to obey culturally inherited norms and not expose or establish their actual personalities (Tsegaye, et al., 2018). Discussion about emotional issues is considered taboo in Pakistan, especially for women, thus refraining them from sharing emotional expressions online (Younas, et al., 2020). Multiple studies suggest that online image and expression lead to improved self-confidence and enhanced well-being (Burke and Kraut, 2016; Erfani, et al., 2016; Kim, 2014; Ko and Kuo, 2009; Naeemi, et al., 2014). Pakistani women, however, are not permitted to seek emotional help, so pent up emotions make them prone to developing mental problems.
According to the results, socialization and informational motives contribute positively to women’s psychological well-being. When women socialize online, the communication process positively influences psychological well-being. Similarly, the informational motive results in better knowledge and information and contributes to psychological well-being of women.
The second phase of the analysis presented the effect of each social media motive on the sub-dimension of psychological well-being. This analysis categorized each sub-dimension of psychological well-being and explained the aspect of psychological well-being that is highly influenced by social media motives.
According to statistical results, Model II showed that the socialization motive positively contributed to women’s psychological well-being. Other dimensions, including autonomy, self-acceptance, positive relations, purpose in life, and personal growth, were also positively and significantly influenced by the socialization motive. Only environmental mastery had the least contribution to psychological well-being. The results indicate that contrary to the socialization opportunities in the socio-cultural setting, online socialization empowers women, helps them develop functional and better relations and improve themselves, and affords them the guidance to achieve their goals in life.
The personal motive that women use social media for self-credibility did not contribute to women’s autonomy, personal growth, positive relations, self-acceptance, purpose in life, and environmental mastery. On the other side, the emotional motive negatively correlated to women’s autonomy, personal growth, positive relations, self-acceptance, purpose in life, and environmental mastery. These results reinforce women’s positioning in low-income patriarchal social structures where, despite technological advancement, women suffer social pressures and cannot always use technologies to improve their well-being (Younas, et al., 2020).
The results of this research point to a positive contribution of social media to women’s psychological well-being in Pakistan. The results of this study contribute to evolving literature regarding women’s social media use in developing regions of the world with respect to leading effects on psychological well-being.
According to the results of this study, social media use has a strong connection with users’ psychological well-being, especially with respect to women users in developing and culturally patriarchal regions of the world. Online time spent in personal activities on social media platforms offers socio-culturally oppressed women a relief and escape from harsh realities of life. Here, it is pertinent to note that this relief is temporary though, yet it has a palpable importance in harmonizing the overall well-being of the social media users.
The findings of this study suggest further research in other low-income countries to better ascertain the positive or negative contribution of new media technologies in empowering women and improving their well-being. The results of this research, aligned with the social positioning and status of women’s well-being in low-income and patriarchal societies in particular, call for more academic research to uncover hidden realities and develop consistent findings on this subject.
About the authors
Iffat Ali Aksar is a Ph.D. Scholar in the Department of Media and Communication Studies in the Faculty of Arts and Social Sciences at the University of Malaya, Malaysia.
E-mail: iffatali101 at gmail dot com
Mahmoud Danaee is a Senior Lecturer in the Department of Social and Preventive Medicine in the Faculty of Medicine at the University of Malaya, Malaysia.
E-mail: mdanaee at um dot edu dot my
Huma Maqsood is a Lecturer in the Faculty of Social Sciences, SZABIST Islamabad, Pakistan.
E-mail: Huma dot maqsood at szabist-isb dot edu dot pk
Amira Firdaus is Deputy Director of the Academic Enhancement & Leadership Development Centre (ADeC) and Senior Lecturer in the Department of Media and Communication Studies in the Faculty of Arts and Social Sciences at the University of Malaya, Malaysia.
E-mail: amira_firdaus at um dot edu dot my
We confirm that the manuscript has been submitted solely to this journal and is not published in the press or submitted elsewhere. Further, we do not have any organizational, institutional, or personal conflict of interest.
S. Ahmad, M. Mustafa, and A. Ullah, 2016. “Association of demographics, motives and intensity of using social networking sites with the formation of bonding and bridging social capital in Pakistan,” Computers in Human Behavior, volume 57, pp. 107–114.
doi: https://doi.org/10.1016/j.chb.2015.12.027, accessed 15 December 2020.
R. Ali, 2016. “Social media and youth in Pakistan: Implications on family relations,” Global Media Journal, volume 14, number 26, at http://www.globalmediajournal.com, accessed 15 December 2020.
R.P. Bagozzi and Y. Yi, 2012. “Specification, evaluation, and interpretation of structural equation models,” Journal of the Academy of Marketing Science, volume 40, number 1, pp. 8–34.
doi: https://doi.org/10.1007/s11747-011-0278-x, accessed 15 December 2020.
J. Bailey, V. Steeves, J. Burkell, and P. Regan, 2013. “Negotiating with gender stereotypes on social networking sites: From ‘bicycle face’ to Facebook,” Journal of Communication Inquiry, volume 37, number 2, pp. 91–112.
doi: https://doi.org/10.1177/0196859912473777, accessed 15 December 2020.
D. Barclay, C. Higgins, and R. Thompson, 1995. “The partial least squares (PLS) approach to casual modeling: Personal computer adoption and use as an illustration,” Technology Studies, volume 2, number 2, pp. 285–309.
R. Basilisco and K.J. Cha, 2015. “Uses and gratification motivation for using Facebook and the impact of Facebook usage on social capital and life satisfaction among Filipino users,” International Journal of Software Engineering and Its Applications, volume 9, number 4, pp. 181–194.
S.A. Batool and S.S. Batool, 2018. “Impact of education on women’s empowerment: Mediational role of income and self-esteem,” Journal of Research and Reflections in Education, volume 12, number 1, pp. 11–24.
P. Best, R. Manktelow, and B. Taylor, 2014. “Online communication, social media and adolescent wellbeing: A systematic narrative review,” Children and Youth Services Review, volume 41, pp. 27–36.
doi: https://doi.org/10.1016/j.childyouth.2014.03.001, accessed 15 December 2020.
M. Burke and R.E. Kraut, 2016. “The relationship between Facebook use and well-being depends on communication type and tie strength,” Journal of Computer-Mediated Communication, volume 21, number 4, pp. 265–281.
doi: https://doi.org/10.1111/jcc4.12162, accessed 15 December 2020.
J. Chae, 2018. “Reexamining the relationship between social media and happiness: The effects of various social media platforms on reconceptualized happiness,” Telematics and Informatics, volume 35, number 6, pp. 1,656–1,664.
doi: https://doi.org/10.1016/j.tele.2018.04.011, accessed 15 December 2020.
C.-Y. Chen and S.-L. Chang, 2019. “Moderating effects of information-oriented versus escapism-oriented motivations on the relationship between psychological well-being and problematic use of video game live-streaming services,” Journal of Behavioral Addictions, volume 8, number 3, pp. 564–573.
doi: https://doi.org/10.1556/2006.8.2019.34, accessed 15 December 2020.
H.-T. Chen and X. Li, 2017. “The contribution of mobile social media to social capital and psychological well-being: Examining the role of communicative use, friending and self-disclosure,” Computers in Human Behavior, volume 75, pp. 958–965.
doi: https://doi.org/10.1016/j.chb.2017.06.011, accessed 15 December 2020.
J. Chen, W. Geyer, C. Dugan, M. Muller, and I. Guy, 2009. “Make new friends, but keep the old: Recommending people on social networking sites,” CHI ’09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 201–210.
doi: https://doi.org/10.1145/1518701.1518735, accessed 15 December 2020.
W.W. Chin, 1998. “The partial least squares approach for structural equation modeling,” In: G.A. Marcoulides (editor). Modern methods for business research. Mahwah, N.J.: Lawrence Erlbaum, pp. 295–336.
J. Cohen, 1992. “A power primer,” Psychological Bulletin, volume 112, number 1, pp. 155–159.
doi: https://doi.org/10.1037/0033-2909.112.1.155, accessed 15 December 2020.
Digital Rights Foundation, 2017. “Measuring Pakistani women’s experiences od online violence: A quantitative research study on gender-based harassment,” at http://digitalrightsfoundation.pk/wp-content/uploads/2017/05/Hamara-Internet-Online-Harassment-Report.pdf, accessed 15 December 2020.
M. Diomidous, K. Chardalias, A. Magita, P. Koutonias, P. Panagiotopoulou, and J. Mantas, 2016. “Social and psychological effects of the Internet use,” Acta Informatica Medica, volume 24, number 1, pp. 66–68.
D. Dupré, G. McKeown, N. Andelic, and G. Morrison, 2019. “Willingness to share emotion information on social media: Influence of personality and social context,” 2018 IEEE Fifth International Conference on Data Science and Advanced Analytics (DSAA).
doi: https://doi.org/10.1109/DSAA.2018.00086, accessed 15 December 2020.
A. Eijaz, 2013. “Impact of new media on dynamics of Pakistan politics,” Journal of Political Studies, volume 20, number 1, pp. 113–130, and at http://pu.edu.pk/images/journal/pols/pdf-files/Abida%20Ejaz_v20_1_2013.pdf, accessed 15 December 2020.
S.S. Erfani and B. Abedin, 2018. “Impacts of the use of social network sites on users’ psychological wellbeing: A systematic review,” Journal of the Association for Information Science and Technology, volume 69, number 7, pp. 900–912.
doi: https://doi.org/10.1002/asi.24015, accessed 15 December 2020.
S.S. Erfani, B. Abedin, and Y. Blount, 2016. “Social support, Social belongingness, and psychological well-being: Benefits of online healthcare community membership,” Pacific Asia Conference on Information Systems Proceedings, at https://aisel.aisnet.org/pacis2016/396/, accessed 15 December 2020.
W.P. Eveland, D.V. Shah, and N. Kwak, 2003. “Assessing causality in the cognitive mediation model: A panel study of motivations, information processing, and learning during campaign 2000,” Communication Research, volume 30, number 4, pp. 359–386.
doi: https://doi.org/10.1177/0093650203253369, accessed 15 December 2020.
C. Fornell and D.F. Larcker, 1981. “Structural equation models with unobservable variables and measurement error: Algebra and statistics,” Journal of Marketing Research, volume 18, number 3, 382–388.
doi: https://doi.org/10.2307/3150980, accessed 15 December 2020.
H. Gil de Zúñiga, T. Diehl, B. Huber, and J. Liu, 2017. “Personality traits and social media use in 20 countries: How personality relates to frequency of social media use, social media news use, and social media use for social interaction,” Cyberpsychology, Behavior, and Social Networking, volume 20, number 9, pp. 540–552.
doi: https://doi.org/10.1089/cyber.2017.0295, accessed 15 December 2020.
A.L. Gonzales and J.T. Hancock, 2011. “Mirror, mirror on my Facebook wall: Effects of exposure to Facebook on self-esteem,” Cyberpsychology, Behavior, and Social Networking, volume 14, numbers 1–2, pp. 79–83.
doi: https://doi.org/10.1089/cyber.2009.0411, accessed 15 December 2020.
D.L. Goodhue, W. Lewis, and R. Thompson, 2012. “Does PLS have advantages for small sample size or non-normal data?” MIS Quarterly, volume 36, number 3, pp. 981–1,001.
doi: https://doi.org/10.2307/41703490, accessed 15 December 2020.
M. Grottke, J.V. Hacker, and C. Durst, 2018. “Which factors determine our online social capital? An analysis based on structural equation modelling,” Australasian Journal of Information Systems, volume 22.
doi: https://doi.org/10.3127/ajis.v22i0.1656, accessed 15 December 2020.
J.F. Hair, C.M. Ringle, and M. Sarstedt, 2011. “PLS-SEM: Indeed a silver bullet,” Journal of Marketing Theory and Practice, volume 19, number 2, pp. 139–152.
doi: https://doi.org/10.2753/MTP1069-6679190202, accessed 15 December 2020.
J.F. Hair, Jr., G.T.M. Hult, C. Ringle, and M. Sarstedt, 2016. A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, Calif.: Sage.
C. Hardaker and M. McGlashan, 2016. “‘Real men don’t hate women’: Twitter rape threats and group identity,” Journal of Pragmatics, volume 91, pp. 80–93.
doi: https://doi.org/10.1016/j.pragma.2015.11.005, accessed 15 December 2020.
K. Hassan, 2018. “Social media, media freedom and Pakistan’s war on terror,” Round Table, volume 107, number 2, pp. 189–202.
doi: https://doi.org/10.1080/00358533.2018.1448339, accessed 15 December 2020.
D. Hassouneh and M. Brengman, 2014. “A motivation-based typology of social virtual world users,” Computers in Human Behavior, volume 33, pp. 330–338.
doi: https://doi.org/10.1016/j.chb.2013.08.012, accessed 15 December 2020.
M.R. Hastall, 2017. “Escapism,” In: P. Rössler (editor). International encyclopedia of media effects. Oxford: Wiley-Blackwell.
doi: https://doi.org/10.1002/9781118783764.wbieme0154, accessed 15 December 2020.
J. Henseler, C.M. Ringle, and M. Sarstedt, 2014. “A new criterion for assessing discriminant validity in variance-based structural equation modeling,” Journal of the Academy of Marketing Science, volume 43, pp. 115–135.
doi: https://doi.org/10.1007/s11747-014-0403-8, accessed 15 December 2020.
J.V. Hogue and J.S. Mills, 2019. “The effects of active social media engagement with peers on body image in young women,” Body Image, volume 28, pp. 1–5.
doi: https://doi.org/10.1016/j.bodyim.2018.11.002, accessed 15 December 2020.
Y. Hussain, 2014. “Social media as a tool for transparency and good governance in the government of Gilgit-Baltistan, Pakistan,” Crossroads Asia Working Paper Series, number 22, at https://www.zef.de/fileadmin/webfiles/downloads/projects/crossroads/publications/xroads_wp22_Hussain.pdf, accessed 15 December 2020.
S. Jamil, 2018. “Politics in a digital age: The impact of new media technologies on public participation and political campaign in Pakistan’s 2018 elections — A case study of Karachi,” Global Media Journal, volume 16, at https://www.globalmediajournal.com/open-access/politics-in-a-digital-age-the-impact-of-new-media-technologies-on-public-participation-and-political-campaign-in-pakistans-2018-el.php?aid=87194, accessed 15 December 2020.
T.J. Johnson and B.K. Kaye, 2004. “Wag the blog: How reliance on traditional media and the Internet influence credibility perceptions of Weblogs among blog users,” Journalism & Mass Communication Quarterly, volume 81, number 3, pp. 622–642.
doi: https://doi.org/10.1177/107769900408100310, accessed 15 December 2020.
M. Kasana, 2016. “Feminisms and the social media sphere,” WSQ: Women’s Studies Quarterly, volume 42, number 3, pp. 236–249.
doi: https://doi.org/10.1353/wsq.2014.0065, accessed 15 December 2020.
H. Kim, 2014. “Enacted social support on social media and subjective well-being,” International Journal of Communication, volume 8, pp. 2,340–2,342, and at https://ijoc.org/index.php/ijoc/article/view/2243, accessed 15 December 2020.
R.B. Kline, 2015. Principles and practice of structural equation modeling. Fourth edition. London: Guilford.
H.-C. Ko and F.-Y. Kuo, 2009. “Can blogging enhance subjective well-being through self-disclosure?” CyberPsychology & Behavior, volume 12, number 1, pp. 75–79.
doi: https://doi.org/10.1089/cpb.2008.0163, accessed 15 December 2020.
K. Krcaburun and M.D. Griffiths, 2019. “Problematic Instagram use: The role of perceived feeling of presence and escapism,” International Journal of Mental Health and Addiction, volume 17, pp. 909–921.
doi: https://doi.org/10.1007/s11469-018-9895-7, accessed 15 December 2020.
H. Lee and J. Choi, 2014. “Motivation, reliance, and diversity of social media use and psychological well-being: A cross-cultural analysis of Korea and the United States,” paper presented at the Seventh World Congress of Korean Studies Conference, at https://www.aks.ac.kr/index.do, accessed 15 December 2020.
H.E. Lee and J. Cho, 2018. “Social media use and well-being in people with physical disabilities: Influence of SNS and online community uses on social support, depression, and psychological disposition,” Health Communication, volume 34, number 9, pp. 1,043–1,052.
doi: https://doi.org/10.1080/10410236.2018.1455138, accessed 15 December 2020.
E.T. Lwoga and R.Z. Sangeda, 2018. “ICTs and development in developing countries: A systematic review of reviews,” Electronic Journal of Information Systems in Developing Countries, volume 85, number 1, e12060.
doi: https://doi.org/10.1002/isd2.12060, accessed 15 December 2020.
Q.K. Mahmood, R. Zakar, and M.Z. Zakar, 2018. “Role of Facebook use in predicting bridging and bonding social capital of Pakistani university students,” Journal of Human Behavior in the Social Environment, volume 28, number 7, pp. 856–873.
doi: https://doi.org/10.1080/10911359.2018.1466750, accessed 15 December 2020.
G.A. Marcoulides and W.W. Chin, 2013. “You write, but others read: Common methodological misunderstandings in PLS and related methods,” In: H. Abdi, W.W. Chin, V. Esposito Vinzi, G. Russolillo, and L. Trinchera (editors). New perspectives in partial least squares and related methods. New York: Springer, pp. 31–64.
doi: https://doi.org/10.1007/978-1-4614-8283-3_2, accessed 15 December 2020.
G.A. Marcoulides and C. Saunders, 2006. “Editor’s comments: PLS: a silver bullet?” MIS Quarterly, volume 30, number 2, pp. iii–ix.
doi: https://doi.org/10.2307/25148727, accessed 15 December 2020.
J.J. Mootz, F. Muhanguzi, B. Greenfield, M. Gill, M.B. Gonzalez, P. Panko, P.O. Mangen, M.L. Weinberg, and K. Khoshnood, 2019. “Armed conflict, intimate partner violence, and mental distress of women in northeastern Uganda: A mixed methods study,” Psychology of Women Quarterly, volume 43, number 4, pp. 457–471.
doi: https://doi.org/10.1177/0361684319864366, accessed 15 December 2020.
S. Mustafa, 2018. “A descriptive study for the impacts of using social media on the studies of university students in Pakistan (A literature review),” European Scientific Journal, volume 14, number 20.
doi: https://doi.org/10.19044/esj.2018.v14n20p18, accessed 15 December 2020.
R.L. Nabi, A. Prestin, and J. So, 2013. “Facebook friends with (health) benefits? Exploring social network site use and perceptions of social support, stress, and well-being,” Cyberpsychology, Behavior, and Social Networking, volume 16, number 10, pp. 721–727.
doi: https://doi.org/10.1089/cyber.2012.0521, accessed 15 December 2020.
S. Naeemi, E. Tamam, S.H. Hassan, and J. Bolong, 2014. “Facebook usage and its association with psychological well-being among Malaysian adolescents,” Procedia — Social and Behavioral Sciences, volume 155, pp. 87–91.
doi: https://doi.org/10.1016/j.sbspro.2014.10.261, accessed 15 December 2020.
S. Nasir, P. Vel, and H. Mateen, 2012. “Social media and buying behaviour of women in Pakistan towards the purchase of textile garments,” Business Management Dynamics, volume 2, number 2, pp. 61–69, and at http://bmdynamics.com/issue_pdf/bmd110262-61-69.pdf, accessed 15 December 2020.
U. Niaz, 2004. “Women’s mental health in Pakistan,” World Psychiatry, volume 3, number 1, pp. 60–62, and at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1414670/, accessed 15 December 2020.
P. Norris and D. Jones, 1998. “Virtual democracy,” International Journal of Press/Politics, volume 3, number 2, pp. 1–4.
doi: https://doi.org/10.1177/1081180X98003002001, accessed 15 December 2020.
U. Oberst, E. Wegmann, B. Stodt, M. Brand, and A. Chamarro, 2017. “Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out,” Journal of Adolescence, volume 55, pp. 51–60.
doi: https://doi.org/10.1016/j.adolescence.2016.12.008, accessed 15 December 2020.
A. O’Donnell and C. Sweetman, 2018. “Introduction: Gender, development and ICTs,” Gender and Development, volume 26, number 2, pp. 217–229.
doi: https://doi.org/10.1080/13552074.2018.1489952, accessed 15 December 2020.
J. Palfrey, U. Gasser, C. Maclay, and G. Beger, 2011. “Digital natives and the three divides to bridge,” at https://www.unicef.org/sowc2011/pdfs/Digital-Natives.pdf, accessed 15 December 2020.
I. Pantic, 2014. “Online social networking and mental health,” Cyberpsychology, Behavior, and Social Networking, volume 17, number 10, pp. 652–657.
doi: https://doi.org/10.1089/cyber.2014.0070, accessed 15 December 2020.
N. Park, K.F. Kee, and S. Valenzuela, 2009. “Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes,” CyberPsychology & Behavior, volume 12, pp. 729–733.
doi: https://doi.org/10.1089/cpb.2009.0003, accessed 15 December 2020.
S.Y., Park and Y.M. Baek, 2018. “Two faces of social comparison on Facebook: The interplay between social comparison orientation, emotions, and psychological well-being,” Computers in Human Behavior, volume 79, pp. 83–93.
doi: https://doi.org/10.1016/j.chb.2017.10.028, accessed 15 December 2020.
J. Pasek, e. more, and D. Romer, 2009. “Realizing the social Internet? Online social networking meets offline civic engagement,” Journal of Information Technology & Politics, volume 6, numbers 3–4, pp. 197–215.
doi: https://doi.org/10.1080/19331680902996403, accessed 15 December 2020.
A. Qaisrani, S. Liaquat, and E.N. Khokhar, 2016. “Socio-economic and cultural factors of violence against women in Pakistan,” Sustainable Development Policy Institute, Working Papers, number 158, at https://think-asia.org/handle/11540/6823, accessed 15 December 2020.
L.R. Ramsey and A.L. Horan, 2018. “Picture this: Women’s self-sexualization in photos on social media,” Personality and Individual Differences, volume 133, pp. 85–90.
doi: https://doi.org/10.1016/j.paid.2017.06.022, accessed 15 December 2020.
T. Roberts, 2016. “Women’s use of participatory video technology to tackle gender inequality in Zambia’s ICT sector,” ICTD ’16: Proceedings of the Eighth International Conference on Information and Communication Technologies and Development, article number 6.
doi: https://doi.org/10.1145/2909609.2909673, accessed 15 December 2020.
R.M. Ryan and E.L. Deci, 2001. “On happiness and human potentials: A review of research on hedonic and eudaimonic well-being,” Annual Review of Psychology, volume 52, pp. 141–166.
doi: https://doi.org/10.1146/annurev.psych.52.1.141, accessed 15 December 2020.
C.D. Ryff, 1989. “Happiness is everything, or is it? Explorations on the meaning of psychological well-being,” Journal of Personality and Social Psychology, volume 57, number 6, pp. 1,069–1,081.
doi: https://doi.org/10.1037/0022-35220.127.116.119, accessed 15 December 2020.
C.D. Ryff and C.L.M. Keyes, 1995. “The structure of psychological well-being revisited,” Journal of Personality and Social Psychology, volume 69, number 4, pp. 719–727.
doi: https://doi.org/10.1037/0022-3518.104.22.1689, accessed 15 December 2020.
E. Sanchiz, F. Ibarra, S. Nikitina, M., Báez, and F. Casati, 2016. “What makes people bond?: A study on social interactions and common life points on Facebook,” 2016 International Conference on Collaboration Technologies and Systems.
doi: https://doi.org/10.1109/CTS.2016.0024, accessed 15 December 2020.
U. Sekaran and R. Bougie, 2016. Research methods for business: A skill building approach. Seventh edition. Chichester: Wiley.
S. Shabib and E. Fatima, 2012. “Social networking Websites:Conduit for women entrepreneurs in Pakistan,” International Journal of Computing and Corporate Research, volume 2, number 5, at http://www.ijccr.com/September2012/2.pdf, accessed 15 December 2020.
G. Shao, 2009. “Understanding the appeal of user-generated media: A uses and gratification perspective,” Internet Research, volume 19, number 1, pp. 7–25.
doi: https://doi.org/10.1108/10662240910927795, accessed 15 December 2020.
S. Shaud and S. Asad, 2020. “Marital adjustment, convergent communication patterns, and psychological distress in women with early and late marriage,” Current Psychology, volume 39, pp. 2,326–2,333.
doi: https://doi.org/10.1007/s12144-018-9936-1, accessed 15 December 2020.
P. Sheldon, 2008. “The relationship between and students’ Facebook use,” Journal of Media Psychology, volume 20, number 2, pp. 67–75.
doi: https://doi.org/10.1027/1864-122.214.171.124, accessed 15 December 2020.
T.F. Stafford, M.R. Stafford, and L.L. Schkade, 2004. “Determining uses and gratifications for the Internet,” Decision Sciences, volume 35, number 2, pp. 259–288.
doi: https://doi.org/10.1111/j.00117315.2004.02524.x, accessed 15 December 2020.
F. Stenseng, J. Rise, and P. Kraft, 2012. “Activity engagement as escape from self: The role of self-suppression and self-expansion,” Leisure Sciences, volume 34, number 1, pp. 19–38.
doi: https://doi.org/10.1080/01490400.2012.633849, accessed 15 December 2020.
M. Tsegaye, K. Drucza, and M. Hailemariam, 2018. “Gender norms, agency and innovation in wheat-based systems and livelihoods: Synthesis report of six community case studies in Pakistan,” at https://repository.cimmyt.org/handle/10883/20003, accessed 15 December 2020.
Z. Tufekci, 2010. “Who acquires friends through social media and why? ‘Rich get richer’ versus ‘seek and ye shall find’,” Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, at https://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/viewFile/1525/1850, accessed 15 December 2020.
J. Urbaeva, 2019. “Opportunity, social mobility, and women’s views on gender roles in central Asia,” Social Work, volume 64, number 3, pp. 207–215.
doi: https://doi.org/10.1093/sw/swz011, accessed 15 December 2020.
S. Valenzuela, N. Park, and K.F. Kee, 2009. “Is there social capital in a social network site? Facebook use and college student’s life satisfaction, trust, and participation,” Journal of Computer-Mediated Communication, volume 14, number 4, pp. 875–901.
doi: https://doi.org/10.1111/j.1083-6101.2009.01474.x, accessed 15 December 2020.
P.M. Valkenburg, J. Peter, and A.P. Schouten, 2006. “Friend networking sites and their relationship to adolescents’ well-being and social self-esteem,” CyberPsychology & Behavior, volume 9, number 5, pp. 584–590.
doi: https://doi.org/10.1089/cpb.2006.9.584, accessed 15 December 2020.
P. Verduyn, O. Ybarra, M. Résibois, J. Jonides, and E. Kross, 2017. “Do social network sites enhance or undermine subjective well-being? A critical review,” Social Issue and Policy Review, volume 11, number 1, pp. 274–302.
doi: https://doi.org/10.1111/sipr.12033, accessed 15 December 2020.
E.A. Vogel, J.P. Rose, B.M. Okdie, K. Eckles, and B. Franz, 2015. “Who compares and despairs? The effect of social comparison orientation on social media use and its outcomes,” Personality and Individual Differences, volume 86, pp. 249–256.
doi: https://doi.org/10.1016/j.paid.2015.06.026, accessed 15 December 2020.
S.F. Waterloo, S.E. Baumgartner, J. Peter, and P.M. Valkenburg, 2018. “Norms of online expressions of emotion: Comparing Facebook, Twitter, Instagram, and WhatsApp,” New Media & Society, volume 20, number 5, pp. 1,813–1,831.
doi: https://doi.org/10.1177/1461444817707349, accessed 15 December 2020.
E. Weinstein, 2018. “The social media see-saw: Positive and negative influences on adolescents’ affective well-being,” New Media & Society, volume 20, number 10, pp. 3,597–3,623.
doi: https://doi.org/10.1177/1461444818755634, accessed 15 December 2020.
K.B. Wright, 2005. “Researching Internet based populations: Advantages and disadvantages of online survey research, online questionnaire authoring software packages, and Web survey services,” Journal of Computer Mediated Communication, volume 10, number 3.
doi: https://doi.org/10.1111/j.1083-6101.2005.tb00259.x, accessed 15 December 2020.
F. Younas, M. Naseem, and M. Mustafa, 2020. “Patriarchy and social media: Women only facebook groups as safe spaces for support seeking in Pakistan,” ICTD2020: Proceedings of the 2020 International Conference on Information and Communication Technologies and Development, article number 11.
doi: https://doi.org/10.1145/3392561.3394639, accessed 15 December 2020.
N.L. Young, D.J. Kuss, M.D. Griffiths, and C.J. Howard, 2017. “Passive Facebook use, Facebook addiction, and associations with escapism: An experimental vignette study,” Computers in Human Behavior, volume 71, pp. 24–31.
doi: https://doi.org/10.1016/j.chb.2017.01.039, accessed 15 December 2020.
K. Younus, 2018. “The power of social media: Negative and positive interpretations,” ISSRA Papers, volume 10, number I, pp. 75&ndask;95, and at https://ndu.edu.pk/issra/issra_pub/articles/issra-paper/ISSRA_Papers_1st_Half_2018/05-THE-POWER-OF-SOCIAL-MEDIA.pdf, accessed 15 December 2020.
S. Zubair, 2016. “Development narratives, media and women in Pakistan: Shifts and continuities,” South Asian Popular Culture, volume 14, numbers 1–2, pp. 19–32.
doi: https://doi.org/10.1080/14746689.2016.1241348, accessed 15 December 2020.
Received 8 July 2020; revised 21 October 2020; revised 6 November 2020; accepted 13 December 2020.
Copyright © 2021, Iffat Ali Aksar, Mahmoud Danaee, Huma Maqsood, and Amira Firdaus. All Rights Reserved.
Effects of social media motivations on women’s psychological well-being in Pakistan
by Iffat Ali Aksar, Mahmoud Danaee, Huma Maqsood, and Amira Firdaus.
First Monday, Volume 26, Number 1 - 4 January 2021