Facebook usage and quality of life of individuals with visual impairments

Abstract

The aim of the present study was to examine the impact of Facebook usage on the quality of life of individuals with visual impairment while also investigating the impact of Facebook communication in comparison with face-to-face communication on quality of life. Ninety-two adult users of Facebook with visual impairment, of whom 46 lived in Greece and 46 lived abroad, participated in this study. Regarding Facebook usage, a questionnaire which investigated the frequency of various aspects of Facebook activity and Facebook communication as well as face-to-face communication was used in this study. Regarding quality of life, the Satisfaction with Life Scale, a single-item happiness scale, and the Beck Depression Inventory were employed to evaluate three different indicators of quality of life. Participants’ quality of life was relatively high. Findings showed that face-to-face communication with friends was a significant predictor of quality of life, while neither Facebook communication nor Facebook usage correlated with any of the indicators of quality of life investigated.

Keywords

Depression Facebook happiness life satisfaction quality of life social networking sites visual impairment

Introduction

It is estimated that visual impairment affects 285 million people globally (Pascolini & Mariotti, 2011). Visual impairment may negatively affect social interaction due to the fact that face-to-face communication includes non-verbal cues, to which individuals with visual impairment do not have access to (Meza-de-Luna et al., 2019). This phenomenon is supported by research results which suggest that vision loss is linked to less social participation (Mick et al., 2018) and that young people with visual impairment prefer activities which involve less social interaction (Gold et al., 2010). Notably, individuals with visual impairment may feel lonely or isolated even when they are living with others (Hinds et al., 2003).

Thanks to technology, more social networks have become available to individuals with visual impairment (Gerber, 2003). Even before social networking websites became popular, individuals with visual impairment used the internet to socialize by keeping in touch with friends and by meeting new people (Gold et al., 2010), a habit that carried on after their introduction (van der Geest et al., 2014). Equal participation online is not always achieved as assistive technology is not always compatible with the newer features of the websites individuals with impairment wish to use (Söderström, 2013). Nevertheless, online interaction offers many advantages to individuals with visual impairment. It removes non-verbal cues and gives them the opportunity to choose the time, the manner, the audience, and the circumstances under which they will disclose their disability while allowing them to showcase their capabilities to challenge pre-existing disability stereotypes (Bowker & Tuffin, 2002; Okonji & Aryal, 2016). Consequently, online communication can take place on equal terms (Gur & Rimmerman, 2017).

The social influence model states that preference for a communication channel depends on both the attitudes toward the channel and the features of it, which are not entirely objectively determined, but socially constructed as well. That is, individuals tend to be influenced by the perceptions and attitudes people around them have for the features of these channels (Fulk et al., 1987, 1990). Contrary to popular belief, communication on social network sites does not limit face-to-face communication, but actually reinforces it (Dienlin et al., 2017; Pacheco et al., 2018). Evidently, many weak connections would be lost without the advantages they offer (Ellison & boyd, 2013; Ellison et al., 2007; Quainoo et al., 2021). Some individuals with visual impairment feel that online interaction enhanced their social participation and helped them fight negative feelings of loneliness and isolation (Okonji et al., 2015). Furthermore, people with visual impairment feel a greater sense of community nowadays compared to the past (Gerber, 2003).

In a recent study, Crossland et al. (2014) found that one of the main reasons individuals with visual impairment used mobile devices, like smartphones and tablets, was to access the internet, while one of their most used apps was Facebook. People with disabilities believe that the internet can foster social inclusion while removing the social stigma associated with disability (Guo et al., 2005). In a pilot study, Brinkley and Tabrizi (2013) found that individuals with visual impairment used social network sites more than other types of websites, while 7 out of 10 indicated a preference for Facebook, as did their sighted participants.

According to Ellison and boyd (2013),

A social network site is a networked communication platform in which participants 1) have uniquely identifiable profiles that consist of user-supplied content, content provided by other users, and/or system-provided data; 2) can publicly articulate connections that can be viewed and traversed by others; and 3) can consume, produce, and/or interact with streams of user generated content provided by their connections on the site. (p. 158)

The profile includes information about the age, the location, and the interests of the user and also a picture of them (boyd & Ellison, 2007). This information can be used to discover other users and formulate new connections (Ellison & boyd, 2013). These connections form the social network of the user (Ellison & boyd, 2013). Users can communicate with public messages called “comments” or private messages (boyd & Ellison, 2007; Ellison & boyd, 2013). Communication and content sharing are the primary motivators for using social network sites, while the public “comments” have the advantage of allowing the user to communicate with not just his network, but the networks of other users as well (Ellison & boyd, 2013). As a result, a modern network may consist of people who have never met and will never meet (Sweet et al., 2019).

Out of all social network sites, Facebook is the one recognized by researchers as the most popular (Giannakos et al., 2013; Luaran et al., 2014). Facebook was introduced in 2004 as a social network site for Harvard University students only, but became gradually accessible to all from 2005 (boyd & Ellison, 2007). Today, only a valid e-mail address is needed to create a Facebook account (Cain, 2008), and Facebook is mainly used as a habitual pastime (Giannakos et al., 2013; Papacharissi & Mendelson, 2011). The status-update feature, where a user is encouraged to post his current thoughts, and the comments that ensue are at the heart of Facebook (Ellison & boyd, 2013; Fox et al., 2013). Another key feature is Facebook groups, which can be deployed as support groups (Steadman & Pretorius, 2014).

Even though social network sites were designed without taking disability into account, they are increasingly being used by people with disabilities (Enajeh et al., 2018). The most popular social network site for people with disability (Asuncion et al., 2012; Raghavendra et al., 2012) and for people with visual impairment (Brinkley & Tabrizi, 2013; Martiniello et al., 2012; Vashistha et al., 2015), specifically, is Facebook. It is considered one of the most accessible social network sites by users with disability and has offered them a degree of access that was not possible in other social network sites before (Asuncion et al., 2012; Quainoo et al., 2021). However, it is worth noting that individuals with congenital visual impairment have been more satisfied with Facebook compared to individuals with adventitious impairment (Quainoo et al., 2021). Even though Facebook still presents accessibility challenges to individuals with visual impairment (Babu, 2014; S. M. Lee et al., 2014; Nobre et al., 2018; Quainoo et al., 2021), the cooperation between its creators and the American Foundation of the Blind (Enajeh et al., 2018) showed its commitment to ameliorate. Moreover, Facebook provides information about accessibility in its help center (Facebook, n.d.) and a page about new accessibility features where feedback by users is welcome (Facebook Accessibility, 2012).

People with disabilities have other people with disabilities in their list of friends, while only 1 out of 2 participate in Facebook groups related to disability (Shpigelman & Gill, 2014). When they do participate, they share common experiences, societal concerns, and information about disability issues as well as policies that concern them (Stetten et al., 2019). In a case study, the majority of members in a Facebook group for people with visual impairment were found not to actively participate in it by posting (Caran et al., 2016). However, it was suggested that members may have been expressing their emotional support to each other by liking posts (Caran et al., 2016). The beneficial aspects of Facebook support groups, despite the lack of active participation, have been proved in other cases as well (Steadman & Pretorius, 2014).

Facebook usage can affect an individual. According to Schalock et al. (2002), the eight indicators of quality of life are interpersonal relations, personal development, social inclusion, rights, self-determination, material, and physical and emotional well-being. It is emotional well-being which can be examined through indicators such as self-concept, happiness, satisfaction, and mental health when an individual is asked to appraise their life (Schalock et al., 2002). Positive posts prevail on Facebook and that tends to spread positive emotions, like happiness, to its users, especially when the post viewed was shared by someone whom they consider a strong tie, that is, a close connection (Lin & Utz, 2015). However, Sagioglou and Greitemeyer (2014) found that users seemed to be in a negative mood right after using Facebook, even though they tended to predict that Facebook usage would make them feel good. Facebook posts can give the impression that others are happier (Chou & Edge, 2012), so it is not surprising that intense Facebook usage has been correlated to negative social comparison, which in turn has been related to negative self-perception (de Vries & Kühne, 2015).

Research results around the effects of Facebook usage on quality of life are not consistent. Research shows that intense Facebook usage is associated with higher life satisfaction (Valenzuela et al., 2009) and also that more time spent on Facebook is associated with lower life satisfaction (Kross et al., 2013). Interestingly, even certain aspects of Facebook usage can affect quality of life. The number of Facebook friends has been found to be positively related to life satisfaction (Nabi et al., 2013). In addition, receiving personal messages from Facebook friends who are considered strong ties enhances subjective well-being (Burke & Kraut, 2016).

Even the way a person uses Facebook may affect their well-being. Passive usage of social network sites has been linked to lower subjective well-being (Chen et al., 2016; Wang et al., 2018). Passive usage can promote envy which has a negative impact on affective well-being (Verduyn et al., 2015) and depression (Tandoc et al., 2015). However, Facebook usage in general is not directly related to depression (Jelenchick et al., 2013) and passive usage can actually lessen depression, if it does not evoke feelings of envy (Tandoc et al., 2015).

The research reviewed above does not take users with disability into account. No studies that examined the relation between Facebook usage and the quality of life of people with disability in general or visual impairment specifically were found during this literature review. Admittedly, the focus of studies concerning individuals with disabilities has been on social network site activity and issues of accessibility. Consequently, this study will attempt to respond to the gap detected in the literature to explore the relation between Facebook usage and the quality of life of individuals with visual impairment as well as the possible benefits social media has for these individuals.

The aims of the present study are to investigate (a) the impact of participants’ personal characteristics on their quality of life based on three indicators: happiness, life satisfaction, and depression; (b) the impact of the frequency of Facebook use on the quality of life of users with visual impairment; and (c) the extent of the impact of face-to-face communication versus communication through Facebook on the quality of life of Facebook users with visual impairment.

Method

Participants

The sample consisted of 92 active Facebook users with visual impairment (43 females and 49 males) whose age ranged from 18 to 70 (Μ = 37.9, SD = 12.02). Forty-six were residents of Greece and 46 lived abroad, of whom 19 lived in the United States while the rest lived in various other countries (Germany, United Kingdom, Australia, Argentina, Albania, Belgium, Brazil, India, Ireland, Cyprus, Malaysia, Montenegro, Nepal, Pakistan, Poland, Romania, Serbia, Jamaica, Czech Republic, Finland). According to their self-assessment about their vision status, 62 had blindness (visual acuity < 20/400) and used Braille or screen-reading software for reading, while 30 had low vision (20/200 > visual acuity > 20/400) and used low-vision aids to read. Regarding the age at onset of visual impairments, vision loss occurred congenitally for 43 participants and adventitiously for 49. It is worth mentioning that vision loss was present at birth or occurred during infancy for 64 participants. Concerning educational attainment, 13 participants held a postgraduate degree and 40 a graduate degree, 33 were secondary education graduates, 3 had completed junior high school, and 3 had completed elementary school. In terms of mobility, 26 reported complete independent mobility, 32 high independent mobility being able to move independently most of the time, and 34 low independent mobility being few times able to move independently.

Instruments

In the present study, a questionnaire, which consisted of scales and items that have already been used to evaluate social network site usage in the existing literature, was employed to measure Facebook usage (Dienlin et al., 2017; Hayes et al., 2015; S. Y. Lee, 2014; Nabi et al., 2013; Shpigelman & Gill, 2014; Utz & Breuer, 2017; Viluckiene & Ruškus, 2017). Quality of life can neither be easily defined nor measured (Schalock et al., 2002; Smart, 2001). Participants’ quality of life was estimated through three indicators: life satisfaction, happiness, and depression. The scales employed to measure them were the Satisfaction with Life Scale (SWLS; Diener et al., 1985), a one-item happiness scale (Papadopoulos et al., 2015), and the Beck Depression Inventory (Beck et al., 1961).

Facebook usage

Α 32-item questionnaire was used to evaluate Facebook usage (see Appendix 1). It included four open-ended questions (Q1–Q4) about the number of Facebook friends (Nabi et al., 2013; Shpigelman & Gill, 2014), the number of close and weak ties among them (S. Y. Lee, 2014; Nabi et al., 2013; Utz & Breuer, 2017), and the duration of weekly Facebook usage (Hayes et al., 2015; Shpigelman & Gill, 2014). Two items (Q5 and Q6) measured Facebook group participation related to personal interests or impairment on a 4-point Likert-type scale (1 = strongly disagree, 2 = disagree, 3 = agree, and 4 = strongly agree).

The questionnaire included two sets of items which evaluated face-to-face communication (Q7, Q9, Q11) and Facebook communication (Q8, Q10, Q12), respectively. Each item measured the frequency of communication with (a) family, (b) friends, and (c) acquaintances either face-to-face or on Facebook using a 5-point Likert-type scale (0 = never, 1 = once a month, 2 = once a week, 3 = a few times a week, and 4 = daily) (Dienlin et al., 2017). Finally, a 20-item subscale (Q13–Q32) measured the frequency of Facebook activity. The scale was based on the adaptation of Viluckiene and Ruškus (2017) of a scale developed by Burke et al. (2010). The items measured the frequency of various Facebook activities such as “Receiving comments,” “Commenting on posts of others,” “Updating personal profile,” and “Sharing information” on a 5-point Likert-type scale (0 = never, 1 = once a month, 2 = once a week, 3 = a few times a week, and 4 = daily). Concerning the reliability of this subscale, Cronbach’s alpha coefficient for Facebook activity was computed to be .85.

Life satisfaction

The SWLS, which includes five items, was employed to measure life satisfaction on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree) (Diener et al., 1985). The scale appraises an individual’s personal cognitive judgment for their life overall and a score of 20 out of 35 is considered neutral (Diener et al., 1985; Pavot & Diener, 1993). Cronbach’s alpha coefficient regarding life satisfaction was .88 for the present study.

Happiness

A single-item scale used by Papadopoulos et al. (2015) was employed to measure happiness. A similar scale has been previously used in research (Kef, 2002; Kef et al., 2000) based on the Cantril Scale (Cantril, 1965). Participants were asked to respond on an 11-point scale ranging from 0 (none) to 10 (a great deal) to the question “How happy do you feel.”

Depression

Beck’s Depression Inventory (BDI) in its full 21-item form, where each item pertains to a behavioral manifestation of depression, was employed to measure depression (Beck et al., 1961). Each item includes four statements which reflect the degree of the severity of the manifestation ranging from neutral to severe and participants are to choose the one that best describes their attitude at the present time (Beck et al., 1961). Scores of 0–9 on the BDI indicate minimal depressive symptoms, scores of 10–16 indicate mild depressive symptoms, scores of 17–29 indicate moderate depressive symptoms, and scores of 30–63 indicate severe depressive symptoms (Farinde, 2013). For the general population, people with no clinical history of depression, a score of 21 or over is indicative of depression (Farinde, 2013). Cronbach’s alpha coefficient was .87 for the present study.

Procedure

The participants of this study were recruited through Facebook groups about visual impairment via posts. The posts were published by the researchers and included a link to a Google form which included the questionnaire in either Greek or English depending on the language used on each group. The link was posted on three Greek and three global Facebook groups. More specifically, the link was posted once on each Greek Facebook group on an interval of 10 days to act as a reminder for those who wished to participate as the groups shared members and three times at different times of day on each of the global Facebook groups to ensure that the majority of members and members from different parts of the world would see it, due to the high number of participants in those groups. It is worth noting that the Greek groups focused on themes of technology and accessibility, while the global groups were employed as more traditional support groups and meeting places. As is evident, each participant completed the questionnaire on their own without the presence of the researchers, while the researchers’ Facebook accounts and e-mail addresses were available to them in case they needed guidance or further information.

Statistical analysis

The total score computed from the 20 items measuring the frequency of Facebook activity was used on subsequent analysis. To determine the predictors of quality of life, a Pearson (r) correlation analysis took place to examine whether the score of each indicator of quality of life (life satisfaction, happiness, and depression) correlated with any other variables. Then, the variables that showed a significant or close to significant correlation with life satisfaction, happiness, and/or depression were used as predictors in three separate linear multiple regression analysis with life satisfaction, happiness, and depression as the dependent variable to define the predictors of each indicator.

Results

The mean of the range of participants’ Facebook friends was 874.34 (SD = 998.38). The mean of close ties was 61.34 (SD = 159.06), while the mean of weak ties was 576.72 (SD = 984.94). As far as time spent on Facebook, the mean of hours of use per week was 16.69 (SD = 19.95). Concerning quality of life, the mean of participants’ score on SWLS was 24.35 (SD = 7.02) indicating that the participants were slightly satisfied with their life (Pavot & Diener, 1993) and the mean of their happiness was 7.21 (SD = 2.31) indicating the participants were happy, while the participants’ scores on BDI ranged from 0 to 39 (M = 9.19, SD = 8.73). According to their scores, 58 participants reported minimal symptoms, 18 mild symptoms, 13 moderate symptoms, and 3 severe symptoms of depression. Even assuming all of the participants belong to the general population and lack a history of clinical depression, 11 reported considerable symptoms of depression having scored 21 or higher on the scale (Farinde, 2013).

Table 1 presents the Pearson (r) correlation coefficients between the three indicators of participants’ quality of life and their personal characteristics. To fully investigate the correlation between participants’ personal characteristics and their quality of life, a new variable was computed to evaluate the years since the onset of visual impairments. Table 2 presents the Pearson (r) correlation coefficients between the three indicators of participants’ quality of life and Facebook usage. Table 3 presents the Pearson (r) correlation coefficients between the three indicators of participants’ quality of life and the means of communication they used, face-to-face or through Facebook, with each of their relations.

Table 1.

Correlation coefficients between indicators of quality of life and personal characteristics.

	Life satisfaction	Happiness	Depression
Age	−.094	−.166	.153
Vision status	−.198⁺	−.206*	.168
Age at onset of visual impairments	−.195	−.087	.221*
Years since onset of visual impairments	.125	−.051	−.101
Educational level	.084	−.104	.014
Independent mobility	.179	.106	−.083

p < .06, *p < .05.

Table 2.

Correlation coefficients between indicators of quality of life and Facebook usage.

	Life satisfaction	Happiness	Depression
Number of friends (Q1)	.116	.155	.013
Number of strong ties (Q2)	−.014	−.021	.121
Number of weak ties (Q3)	.046	.079	.116
Hours of use per week (Q4)	.048	.142	−.019
Participation in groups for people with visual impairments (Q5)	−.066	−.050	.073
Participation in groups for interests (Q6)	−.011	−.114	.065
Frequency of Facebook activity (Q13–Q32)	.159	.120	.091

Table 3.

Correlation coefficients between indicators of quality of life and means of communication.

	Life satisfaction	Happiness	Depression
Face-to-face communication with friends (Q7)	.234*	.299**	−.299**
Facebook communication with friends (Q8)	−.001	−.008	.037
Face-to-face communication with family (Q9)	.068	.141	−.183
Facebook communication with family (Q10)	.117	.063	−.030
Face-to-face communication with acquaintances (Q11)	.123	.197	−.169
Facebook communication with acquaintances (Q12)	−.017	.046	−.017

p < .05, **p < .01.

The linear multiple regression analysis for life satisfaction (Table 4) produced an adjusted R² of .069 (F = 4.358, p < .05). Face-to-face communication with friends was a significant predictor of life satisfaction (b = .224, p < .05).

Table 4.

Linear multiple regression analysis for variables as predictors of life satisfaction.

Variables	B	SE	Beta	t	p
Vision status	−2.765	1.510	−.186	−1.831	.070
Face-to-face communication with friends	1.374	0.622	.224	2.207	.030

Adjusted R² = .069.

Bold value indicates the significance of p < .05.

The linear multiple regression analysis for happiness (Table 5) produced an adjusted R² of .105 (F = 6.365, p < .01). Face-to-face communication with friends was a significant predictor of happiness as well (b = .288, p < .01), while vision status was a close to significant predictor (b = −.190, p = .059).

Table 5.

Linear multiple regression analysis for variables as predictors of happiness.

Variables	B	SE	Beta	t	p
Vision status	−0.934	0.489	−.190	−1.911	.059
Face-to-face communication with friends	0.584	0.201	.288	2.899	.005

Adjusted R² = .105.

Bold value indicates the significance of p < .01.

Concerning depression, the linear multiple regression analysis (Table 6) produced an adjusted R² of .104 (F = 6.295, p < .01). Face-to-face communication with friends was a significant predictor of depression (b = −.276, p < .01).

Table 6.

Linear multiple regression analysis for variables as predictors of depression.

Variables	B	SE	Beta	t	p
Age at onset of visual impairments	0.111	0.060	.187	1.867	.065
Face-to-face communication with friends	−2.111	0.764	−.276	−2.764	.007

Adjusted R² = .104.

Bold value indicates the significance of p < .01.

Since face-to-face communication with friends turned out to be a significant predictor of all indicators of quality of life investigated, another Pearson (r) correlation analysis took place to examine the possible relation between face-to-face communication and communication through Facebook. No significant correlation was found between face-to-face communication with friends and communication with them on Facebook. A significant association was found between face-to-face and Facebook communication with family (r = .219, p < .05) and face-to-face and Facebook communication with acquaintances (r = .427, p < .01). Participants who tended to communicate more with their family and acquaintances in real life tended to also communicate with them more on Facebook.

Discussion

Participants’ quality of life is relatively high as they self-reported a slight satisfaction with their lives and a quite high feeling of happiness, while 63% of the participants reported almost no symptomatology of depression. Older individuals with visual impairment have reported a similar level of life satisfaction (Good et al., 2008) and individuals with visual impairment of all ages have reported similar levels of happiness (Papadopoulos et al., 2015; Kef, 2002) in studies where the same or similar measurements of life satisfaction and happiness were used. Moreover, a similar percentage of participants with visual impairment showed no symptomatology of depression based on BDI scores in a study of Papadopoulos, Papakonstantinou, et al. (2014).

Regarding the relation between participants’ personal characteristics and their quality of life, few significant correlations were found. Participants’ vision status correlated with happiness and their age at onset of visual impairments correlated with depression. Vision status also had a close to significant correlation with life satisfaction. The linear multiple regression analysis showed that vision status was a close to significant predictor of happiness, while age at onset of visual impairments was not a significant predictor of depression. Previous research findings concerning the relation between personal characteristics and quality of life of individuals with visual impairment are contradictory. Although Matsuguma et al. (2018) reported no relation between vision status and happiness and Papadopoulos, Papakonstantinou, et al. (2014) no relation between age at onset of visual impairments and depression, Papadopoulos, Paralikas, et al. (2014) reported that the age at onset of visual impairments was a significant predictor of depression.

In the present study, no relation between Facebook usage and participants’ quality of life was found. These results are corroborated by studies on sighted individuals. Nabi et al. (2013) found no effect of frequency of Facebook use on life satisfaction. Verduyn et al. (2015) found no effect of either active or passive Facebook usage on life satisfaction. Arampatzi et al. (2018) found no association between the hours spent on social networking sites and happiness and Jelenchick et al. (2013) no association between social network site use and depression. Nonetheless, intense Facebook usage has been negatively as well as positively linked to life satisfaction in other studies (Kross et al., 2013; Valenzuela et al., 2009). Time spent on Facebook has been associated with depression (Wright et al., 2013). Furthermore, a negative correlation between passive use of social networking sites and subjective well-being was found, when measured by indicators such as life satisfaction and happiness (Chen et al., 2016).

Face-to-face communication with friends turned out to be a significant predictor of all three indicators of quality of life. Specifically, frequent communication with friends in real life predicted higher levels of life satisfaction and happiness as well as lower levels of depression. On the contrary, no associations between face-to-face communication with family or acquaintances and quality of life were found. As far as sighted individuals are concerned, there is research which corroborates our findings (P. S. Lee et al., 2011) and research which contradicts them (Dienlin et al., 2017). Yet, Werner-Seidler et al. (2017) similarly found that frequent communication with friends was associated with less symptoms of depression, while the frequency of communication with family was not.

As far as communication through Facebook is concerned, no associations between Facebook communication with friends, family, or acquaintances and quality of life were found in the present study. According to Rodríguez-Pose and von Berlepsch (2014), informal interaction and trust, two main aspects of social capital, are related to happiness. This could explain the absence of association between Facebook communication and quality of life as informal interaction on Facebook may lack the foundation of trust needed to affect quality of life. Furthermore, perceived social support has been connected to quality of life through a negative correlation with depression (Gençöz & Özlale, 2004). It is possible that since online communication fosters weak-tie connections (Ellison & boyd, 2013; Ellison et al., 2007; Quainoo et al., 2021), communication on Facebook does not foster trust which would make users feel that social support would be available if needed. Conversely, research on sighted individuals showed that communication on social networking sites had a long-term positive effect on life satisfaction (Dienlin et al., 2017). Moreover, Burke and Kraut (2016) reported that not Facebook communication per se, but direct personal communication on Facebook is associated with improved quality of life.

Individuals with visual impairment tend to report that they use social networking sites to keep in touch with their peers (Fuglerud et al., 2012). In the present study, communicating with friends in real life had no correlation with communicating with them on Facebook. However, face-to-face communication with family and face-to-face communication with acquaintances were correlated with Facebook communication with family and Facebook communication with acquaintances, respectively. Taking the points of the social influence model into consideration (Fulk et al., 1987, 1990), we could hypothesize that Facebook usage was common among the families of the participants so it was a preferred channel of communication among them and that they furthermore perceived Facebook as an ideal channel to keep in contact with weaker ties. Communication channels reinforce each other as far as sighted individuals are concerned (Dienlin et al., 2017). In addition, Facebook can play a role in the maintenance or extension of social connections even if that is not the intent of the users (Papacharissi & Mendelson, 2011).

In conclusion, this study attempted to fill the gap in the literature on Facebook and quality of life concerning individuals with visual impairment. The findings of the present research showed that face-to-face communication with friends had a significant effect on participants’ quality of life, whereas communication through Facebook had no association with it. These findings suggest that Facebook communication cannot replace face-to-face communication, as the second plays an essential role on the quality of life of individuals with visual impairment. Thus, face-to-face communication is essential for the emotional well-being of individuals with visual impairment.

Future research investigating the effect of Facebook usage on the quality of life of individuals with visual impairment should include personality traits like self-esteem or locus of control as moderators like studies on sighted individuals have done. Social networking sites are an integral part of modern life and will remain so. Individuals should know the effect they can have on them and adjust their activity accordingly to get the most out of their Facebook use as well as ameliorate their well-being. Facebook is a social network and, as Fowler and Christakis (2008) reported, happiness is a collective phenomenon which can spread in a social network from one to another.

Limitations

The present research was only based on self-report and lacked observation of actual online behavior which may have allowed for more objective measurements. The questionnaire measuring Facebook usage consisted of items which were self-constructed by authors of previous studies allowing for disadvantages of reliability and validity. However, Cronbach’s alpha coefficient regarding the subscale measuring frequency of Facebook activity showed good reliability. Regarding quality of life, it was evaluated through emotional well-being, while other relevant indicators, as determined by Schalock et al. (2002), such as social inclusion were not examined in this research.

Footnotes

Appendix

Appendix 1.

Facebook usage questionnaire.

Q1	How many friends do you have on Facebook?
Q2	How many of your friends on Facebook do you consider strong ties?
Q3	How many of your friends on Facebook do you consider weak ties?
Q4	For how many hours a week do you use Facebook?
Q5	I participate in Facebook groups for people with visual impairment.
Q6	I participate in Facebook groups for people with the same interests as mine.
Q7	How often do you communicate with your friends in real life (face-to-face)?
Q8	How often do you communicate with your friends on Facebook including via messenger?
Q9	How often do you communicate with your family members in real life (face-to-face)?
Q10	How often do you communicate with your family members on Facebook including via messenger?
Q11	How often do you communicate with your acquaintances in real life (face-to-face)?
Q12	How often do you communicate with your acquaintances on Facebook including via messenger?
Q13	How often do you receive comments?
Q14	How often do you comment on posts of others?
Q15	How often do you receive “Likes”?
Q16	How often do you give “Likes”?
Q17	How often do you send private messages?
Q18	How often do you receive private messages?
Q19	How often do you receive invitations to play games?
Q20	How often do you play games?
Q21	How often do you share information?
Q22	How often do you adjust/update your personal profile?
Q23	How often do you visit profiles of others?
Q24	How often do you post material (e.g., videos/photos)?
Q25	How often do you watch photos, videos, and posts?
Q26	How often do you read articles and other info?
Q27	How often do you organize events?
Q28	How often do you offer topic for conversation?
Q29	How often do you participate in themed discussions?
Q30	How often do you send Facebook membership invitations to unknown people?
Q31	How often do you send Facebook membership invitations to offline friends, acquaintances?
Q32	How often do you conduct commercial activities?

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Katerina Gkatzola

Konstantinos Papadopoulos

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