Social networking time use scale (SONTUS): A new instrument for measuring the time spent on the social networking sites

https://doi.org/10.1016/j.tele.2015.11.002Get rights and content

Highlights

  • New scale has been developed to measure the time use on the SNSs.

  • The scale has good psychometric properties.

  • The scale is very simple to use and administer.

Abstract

One of the key issues plaguing the existing studies on the use of the social networking sites (SNSs) is the lack of a uniform index for measuring the time spent on the sites. The present investigation tries to fill this gap by conceptualizing, developing, and validating a new construct, which we referred to as social networking time use scale (SONTUS). To achieve this, two separate studies were conducted. The data for the first study was collected from 2049 individuals through quota sampling approach. Meanwhile, in this first study, we used exploratory factor analysis to identify the dimension of the SONTUS construct. Findings from this study reveal that SONTUS has five factors with good measurement properties. The main aim of the second study (where we utilized data from 1808 people) is to carry out a confirmatory factor analysis (CFA) and tests three hypothesized models. In addition, it aims to investigate the construct validity of SONTUS; and to achieve this, we used 10 personality and well-being measures, and two theoretically related constructs to SONTUS. The CFA results showed that SONTUS has five factor solution consisting of 29 items and that the model with 5 first-order factors with 1 second-order factor is the most suitable model for the study population. Additionally, the second study provides preliminary evidence for the convergent, predictive, and incremental validity of SONTUS. Overall, the findings from our exploratory (study 1) and confirmatory (study 2) studies shows that SONTUS can be used as a standardized instrument for measuring time spent on sites.

Introduction

For more than a decade, the social networking sites (SNSs) have witnessed a sporadic increase in number and popularity. In fact, as the year passes-by, so is the popularity and number of SNS increases. This is evident in the report of Duggan et al. (2015) and studies conducted by (Ellison et al., 2007, Kuss and Griffiths, 2011, Ryan and Xenos, 2011, Panek et al., 2013, Olufadi, 2015). The SNSs has occupied a central role in the way people communicate and connect with each other; and is been used by people for several reasons (e.g., communication, entertainment, learning, social, emotional etc.). Meanwhile, many authors have described the use of SNSs as beneficial and harmful. However, most of the authors that describes its use as harmful relies on the excessive use (i.e., time committed to the use of the SNSs), which might potentially affect the individual’s work (e.g., performance at work) or health (e.g., addiction); see for example, studies by Shaffer et al., 2004, Griffiths, 2005, Echeburúa and de Corral, 2010. By this way, several authors (e.g., Ross et al., 2009, Ellison et al., 2011, Junco, 2012a, Junco, 2012b) have tried to estimate the amount of time people spend on the SNSs using various methods.

As for the time people spent on SNSs, evidence from the previous studies reveal varying results. For instance, 79% of the participants in a study conducted by Ross et al. (2009) reported spending between 10 and 60 min on Facebook daily. They obtained this result through categorical measure of time. In another study published in 2009, Pempek et al. (2009) asked students to log their daily time spent on Facebook in a diary for 1 week and found that students reported spending an average of 27.93 min per day on weekdays and 28.44 min per day on weekends. Additionally, recent studies by Ellison et al., 2011, Kalpidou et al., 2011, and Junco, 2012a, Junco, 2012b show that students spent around 100 min on the SNSs per day. In a more recent study carried out by Olufadi (2015), the participants in the study spent a substantial amount of time on the sites (M = 175.4, SD = 117.26) per day.

While the previous studies reported above have made great progress in measuring the time spent on the SNSs, their use of different measurement methods is problematic. Indeed, this could be a possible explanation for the variations in the estimates of time spent on the SNSs (as reported earlier). We present in what follows a detailed account of some of the commonly used indices for measuring the time spent on the SNSs and their limitations.

  • (a)

    Categorical measures of time: Ellison et al., 2007, Pierce, 2009, Ross et al., 2009, Memdouh and Taswir, 2013, Wang et al., 2014 and Lien and Cao (2014) are some of the authors that have used this measure. A very important limitation of this approach is that people sometimes give answers they feel will reflect well on them; in addition, because people like to think of themselves as normal or average, the range of answer choices provided when asking for a quantity or a frequency can affect the results. For instance, the survey question developed by Ellison et al. (2007) and used by several authors as a measure of time use on the sites asked the participants to respond to the following question: “on a typical day, about how much time do you spend on Facebook?” The options given are (a) no time at all, (b) less than 10 min, (c) 10–30 min, (d) more than 30 min, up to 1 h. (e) More than 1 h., up to 2 h. (f) More than 2 h, up to 3 h. (g) More than 3 h. It is highly likely we get fewer people picking 3 h or more, than if the choices offered are (a) 1 h or less, (b) 2 h, (c) 3 h, (d) 4 h, (e) 5–6 h, (f) 7 h or more. In fact, only 1.5% of the participants in a study conducted by Valenzuela et al. (2009) reported using the sites for more than 3 h. A possible explanation for this is that the first list of choices makes 3 h sound extreme, while the second list of choices makes it seem typical. Moreover, the alternatives listed may influence the opinion of the respondents as demonstrated above. In other words, the use of categorical choices makes it difficult to include the respondents’ correct choice and may force them into an answer that would not necessarily be a first choice. Additionally, Junco (2012a) reported that the use of categorical choices might reflect an a priori bias on the part of the researcher regarding how much time she believe people spent on the SNSs per day. Lastly, since categorical choices restricts respondents to select from a closed-ended options (which may not reflect and captures respondents’ perceived time of use); this may lead to more introspection about how much actual time is spent on the sites (Junco, 2012a).

  • (b)

    Time spent (in minutes) per day: By this method, participants are asked “how many minutes (per day) do you spend on the sites?” A number of authors (Ellison et al., 2007, Ellison et al., 2011, Junco, 2012a, Junco, 2012b, Kalpidou et al., 2011, Kujath, 2011, Pempek et al., 2009, Ross et al., 2009, Lubis et al., 2012) have employed this method. Unfortunately, this approach may be problematic in the sense that it is difficult to account for the total amount of time spent on the sites. It is also possible that people are unable to estimate the amount of the time they spent on the sites for the day. To be specific, there is variation in the daily time spent on the SNSs; sometimes people have a lot of time, other times they hardly access their SNSs account(s). Thus, there is a need to account for this variation. Moreover, if participants are for example, returning the completed questionnaire (say, in the afternoon or evening), how do we account for the time on sites for the rest of the day (e.g., at night).

  • (c)

    Use of daily/weekly diary: Many authors have employed self-reported daily and or weekly diary in order to measure participants’ time use on SNSs (HERI, 2007, Pempek et al., 2009, Rideout et al., 2010, Jacobsen and Forste, 2011, Junco, 2012a, Olufadi, 2015). One drawback of this approach is how to ensure people are filling the diary at the end of each day (or any time they are required to fill it) and not that they just fill it on the last day and returned. Another obvious limitation of this measurement technique is that respondents may under or overestimate their time use on SNSs; admittedly, this limitation is not peculiar to this approach but any survey that is self-report in nature. We refer readers to Junco (2013) for the details of the limitations of using self-report as a measure of time use on the SNSs.

  • (d)

    Time spent yesterday on the sites: For this measure, the real limitation lies in the possibility of cognitive impairment that may affect respondents’ ability to recall the time spent on the SNSs the previous day. We could not rule out this possibility. An example of authors that employ this measure in their studies is (Junco, 2012a, Junco, 2012b).

The efforts of these authors are helpful as they provide an insight into the time use by the people on the sites, however, it is not enough to capture the dimensionality of this complex construct (i.e., time use on the sites). Several other authors have improved on the limitations highlighted above and have thus presented another view of SNS usage time. Some of these authors have focused on the use of various functionalities of these sites while others have committed their time to the use of these sites for a particular set of activities or specific applications area. For instance, to measure Facebook usage, Joinson (2008) used a list of 28 activities, Pempek et al. (2009) used a list of 25 functionalities, Junco (2012a) used a list of 14 activities, Mazman and Usluel (2010) used a list of 11 educational activities, Xu et al. (2012) used a list of 5 activities, and Valenzuela et al. (2009) used a list of 4 activities. These new approach no doubt represents a major contribution to the operational definitions of SNSs usage, this is because the users task was taken into consideration. In fact, the present study benefitted immensely from their efforts. While their efforts are considered a positive leap in measuring SNSs use time, they can be improved upon. Indeed, this is the goal of the present study.

Furthermore, evidence from the studies reported above showed that using different measures results in different estimates of the time spent on the sites by the people. One major problem however, with the use of such a plethora of different measures of the time spent on the SNSs is the difficulty in comparing the results between different studies. There is therefore a need to have a universal index for measuring the time spent on the SNSs by the people (as suggested in Olufadi (2015)), if we were to (1) compare the results between different studies and (2) study its relationship with any outcome of interest like students’ learning and engagement, the big-five personality inventory, sleeping, anxiety, depression etc.

Another possible explanation for the variations in the estimates of the time people spent on the sites is that most of the previous studies only focused on one of the SNSs. For example, Facebook (Joinson, 2008, Valenzuela et al., 2009, Mazman and Usluel, 2010, Xu et al., 2012, Junco, 2012a, Junco, 2012b, Junco, 2013), WeChat (Lien and Cao, 2014), KakaoTalk (Jo, 2013, Ha et al., 2015), Twitter (Chen, 2011, Hughes et al., 2012, McKinney et al., 2012, Panek et al., 2013), Renren (Li and Chen, 2014). However, recent studies have shown that people subscribed to more than one SNSs platform (Helou et al., 2012, Memdouh and Taswir, 2013, Duggan et al., 2015). For instance, Duggan et al. (2015) reported that more than half of the internet users (52%) use two or more of the following SNSs (Facebook, Twitter, Instagram, Pinterest, and LinkedIn) compared with 42% who did so in 2013. To this end, focusing on only one SNS platform is problematic.

Based on this finding, we have tried to correct the limitation of possible underestimation in the time data collected by using a generic term (SNSs) rather than being specific to one SNSs platform. This is particularly important given that the popularity of SNSs differ by regions. For example, Qzone and Renren are the most popular among the Chinese (CNNIC, 2011, CNNIC, 2013, ResonanceChina, 2013, Wang et al., 2014), whereas, the SNSs platform that are widely used in Korea include KakaoTalk and mobile Facebook (KAA, 2012). In one study by Jo (2013), almost 90% of smartphones users in Korea used KakaoTalk. In addition, findings from the data collected by Wang et al (2014) revealed that Facebook and Twitter were the most popular SNSs in the US; however, recent report from the PEW researchers reveals Facebook, Pinterest, and Instagram as the most popular (Duggan et al., 2015).

Additionally, different SNSs are designed for different purposes and might offer different benefit to their users, thus, SNS-users might be using two or more accounts (as evidenced in the studies by Helou et al., 2012, Memdouh and Taswir, 2013, Duggan et al., 2015) for different purposes. Therefore, being specific to a particular platform would not give us the opportunity of measuring time spent on the other sites. This approach therefore has the advantage of correcting for the underestimation of the time spent on the sites. Moreover, focusing on one SNSs platform cannot allow us to generalize our findings to other SNSs without proper validation, using this generic term (SNSs) corrects for this shortcoming.

To this end, we believe that the use of a generic term (SNSs) rather than being specific to a particular SNS platform (e.g., Twitter) is much more broad and have the advantage of allowing future researchers interested in studying the actual relationship between the time used on the sites (e.g., Facebook and Instagram) and any outcome of interest like wellbeing. Overall, since no attempts has been made in the past to develop a psychometrically tested scale capable of measuring time spent by people on the SNSs, this study is designed to fill this gap.

Firstly, the current study is not concerned about what the people are doing on the site(s) or the benefits and downsides of the time spent on the SNSs as they have been addressed in some of the previous studies. See for example, studies conducted by Valkenburg et al., 2006, Valenzuela et al., 2009, Ross et al., 2009, Kirschner and Karpinski, 2010, Ryan and Xenos, 2011, Wang et al., 2014. Additionally, and as established in the literature, there are different types of SNSs with regard to their primary functions to the users (see Ji et al., 2010). Thus, the relationship between SNSs usage and some outcomes of interest (e.g., wellbeing) may depend on the type of usage. However, our concern is not about studying this relationship but how to measure the time spent on the SNSs by the people. To this end, we have developed a psychometrically tested scale which we termed social networking time use scale (SONTUS) for measuring the time spent by the people on the SNSs. To wrap up this section, we present the debate between the “quality” and “quantity” of the time use on the sites – which is more important?

Section snippets

Using UGT to explain the quality and quantity of time use on SNSs

A theoretical study that is relevant to the conceptual discourse between quality and quantity of time use on SNSs by the people is the uses and gratification theory (UGT) proposed by Katz (1959). Indeed, the UGT could easily explain the use and the reasons people may decide to use a specific platform in a specific place or situations. The knowledge of such will no doubt provide information about the quality or quantity of time use on the sites. For instance, the usefulness of the sites and the

Study 1: exploratory ANALYSIS

This first study aims at designing an exploratory construct validity and reliability analysis of our instrument (SONTUS). This was achieved through the procedures highlighted in the sections that follow. Meanwhile, the desired information in line with the objective of the study was elicited from participants through the design of self-rated questionnaire; and in accordance with Cronbach’s (1971) recommendation on the development of a new scale, we strived to draw representative items from a

Justification for the use of factor analyses

Factor analysis using a principal component analysis (PCA) as extraction method, with varimax rotation, was performed on the 52 items in the draft questionnaire. We present in this section the reasons behind the suitability of the present data for factor analyses. First, the correlation matrix reveals that all variables inter-correlate with at least one other variable at .30, this suggest reasonable factorability. Secondly, the determinant of the correlation matrix for this data was .0031;

Study 2: confirmatory analysis

The data-gathering approach of study 2 were similar to those used in the exploratory study (i.e., study 1). However, in this second study, we distributed 2200 questionnaire, however, only 1808 were useable. The questionnaire we used for this confirmatory study consists of the 29 items we found from the factor analysis in study 1 together with several other standardized measures of personality and wellbeing. The essence of these measures is to carry out further convergent, incremental, and

Validity analyses

In this section, we provide evidence of convergent validity, predictive validity, and incremental validity of SONTUS. For example, when testing its convergent validity, we hypothesized that SONTUS and its five subscales would exhibit convergent validity by showing a modest positive and significant correlations with theoretically related constructs considered in the present study. Furthermore, the predictive validity of SONTUS and its five subscales was assessed by correlating it with some

Discussion

The main objective of the present investigation was to develop a simple, short, and psychometrically sound scale capable of measuring the time spent by the people on the SNSs. To this end, we conceptualized and measured the time use by the people on the SNSs as a multi-dimensional construct consisting of five factors: relaxation and free periods, academic-related periods, public-place-related use, stress-related periods, and motives for use. The validation process we employed using both

Study limitations

To our best knowledge, this is the first attempt at developing a scale (with good measurement properties) for measuring the time spent on the SNSs. Although, the findings are quite promising, this study like many other scientific investigations has some limitations that must be considered when interpreting its results. Firstly, the results of the confirmatory factor analysis reported here should be interpreted with caution. This is because the criteria for judging the goodness-of-fit or

Conclusions

This study reports an exploratory–confirmatory study through a rigorous validation of the proposed measurement instrument. Despite the limitations highlighted in Section 8, the evidence presented here indicates that the scale is a promising instrument for the measurement of time spent on the SNSs, through which researchers can measure and can make important contributions to understanding and predicting how the times spent on the SNSs affect for example, individuals’ wellbeing. Thus, SONTUS can

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      For example, if a participant correctly indicated the pattern at two, three, four, and five squares, and then indicated the incorrect pattern twice at six squares, then their score on the Corsi task was five. The Social Networking Time Use Scale (SONTUS) is a standardized measure used to evaluate the amount of time spent on social networking sites (Olufadi, 2016). The scale was developed in Nigeria and used a large Nigerian sample in both phases of the study (Study 1: Exploratory Analysis, n = 2049; Study 2: Confirmatory Analysis, n = 1808) (Olufadi, 2016).

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