The role of digital status in adult child–parent relationships in European comparative perspective

Authors:
Bence Völgyi Faculty of Humanities and Social Sciences, University of Pécs, Hungary

Search for other papers by Bence Völgyi in
Current site
Google Scholar
Close
,
Katalin Füzér Faculty of Humanities and Social Sciences, University of Pécs, Hungary

Search for other papers by Katalin Füzér in
Current site
Google Scholar
Close
,
Fruzsina Albert HUN-REN Centre for Social Sciences and Semmelweis University, Hungary

Search for other papers by Fruzsina Albert in
Current site
Google Scholar
Close
, and
Dávid Erát Faculty of Humanities and Social Sciences, University of Pécs, Hungary

Search for other papers by Dávid Erát in
Current site
Google Scholar
Close
Open access
Get eTOC alerts
Rights and permissions Cite this article

The increasing significance of technology-mediated social interactions gives rise to optimistic expectations that digitalisation leads to various overwhelmingly positive outcomes in all walks of life. Our study relies on the European Social Survey 10th wave data (2020–22) to investigate the role of digital status in the relationship between adult children and parents in 30 countries. We found media multiplexity in adult child–parent relationships to be coupled in interesting and partly counterintuitive ways with our novel measure of digital status that captures digital skills and the outcomes of ICT use. The country-specific binary logistic regression models revealed that digital skills and the emotional benefits of ICT use have a central role in using new and old technologies, whereas a positive practical outcome of ICT use decreased the frequency of adult child–parent contact. By shaping the opportunities of doing family digitally, the skills and outcomes aspects of digital status have independent roles in a key segment of intergenerational relationships of adult family members.

Abstract

The increasing significance of technology-mediated social interactions gives rise to optimistic expectations that digitalisation leads to various overwhelmingly positive outcomes in all walks of life. Our study relies on the European Social Survey 10th wave data (2020–22) to investigate the role of digital status in the relationship between adult children and parents in 30 countries. We found media multiplexity in adult child–parent relationships to be coupled in interesting and partly counterintuitive ways with our novel measure of digital status that captures digital skills and the outcomes of ICT use. The country-specific binary logistic regression models revealed that digital skills and the emotional benefits of ICT use have a central role in using new and old technologies, whereas a positive practical outcome of ICT use decreased the frequency of adult child–parent contact. By shaping the opportunities of doing family digitally, the skills and outcomes aspects of digital status have independent roles in a key segment of intergenerational relationships of adult family members.

Introduction

Digitalisation has transformed life domains in such a comprehensive manner that concepts and measures are needed to grasp this increasingly independent aspect of our lives. Two kinds of literature have provided frameworks to capture the digital transformation with implications for where individuals, social groups and organisations stand. The digital divides literature, on the one hand, has offered the perspective of positioning actors along the three dimensions of digital connectivity, digital skills and digital benefits/damages studying how social groups and individuals maintain, improve or, for that matter, worsen their social, economic or educational positions and how countries rank in terms of their digital readiness (DiMaggio and Hargittai, 2001; Norris, 2001; Hargittai, 2002; Dimaggio et al, 2004; van Deursen and Helsper, 2015; Robinson et al, 2020a; 2020b). On the other hand, digital capital research (Selwyn, 2004; Morgan, 2010; Seale, 2013; Roberts and Townsend, 2016; Ragnedda, 2018; Ragnedda et al, 2020; Calderón Gómez, 2021; Tőkés, 2021) and scholarship on techno capital or e-capital (Rojas et al, 2004; Gilbert, 2010; Straubhaar et al, 2012; Carlson and Isaacs, 2018) have offered the perspective of positioning actors in terms of their capital profile, inserting the increasingly vital digital resources aspect into the conventional triad of economic, social and cultural capitals (Bourdieu, 2005; Park, 2017; Merisalo and Makkonen, 2022; Füzér et al, 2023).

In contrast to these two categories of the literature, the digital status approach advanced in this article positions individuals in the larger social setting by building a measure ultimately destined to complement basic socioeconomic status measures such as education, occupation, income and so on. Digital status captures the transformative impact of digitalisation, the differentiated leveraging of online and digital practices that not only reinforces existing inequalities but creates a new dimension, that of ‘digital stratification’ (Ragnedda et al, 2023). Our digital status measure assesses both the digital literacy levels of individuals or groups and illuminates different benefits of information and communication technology (ICT) use. This enables a comparative analysis of measured individuals and groups, positioning them within the digital hierarchy of society. While there is a substantial body of literature dedicated to examining the benefits or outcomes of internet use, frequently the findings lack generalisability or the measures employed fail to capture the multifaceted aspects of benefits (Helsper et al, 2015). Our methodology effectively presents a range of benefits, including both practical and emotional dimensions, thereby providing novel evidence elucidating various positive impacts arising from ICT use. Consequently, our methodological approach doesn’t exclusively favour digital natives (Selwyn, 2009; Hargittai, 2010) or early adopters (Rogers, 2003; Ortega Egea et al, 2007), who are often perceived as the ‘winners’ in the digital realm. Instead, our measure is also sensitive to those who, despite potential deficiencies in digital skills, might experience more positive impacts of ICT on their lives and social relationships. Besides its potential to further our understanding of the positioning of actors vis-à-vis the instrumental domains of wealth, power, reputation and the expressive domains of physical health, mental health and life satisfaction (Pena-López and Sánchez-Santos, 2017; Fox et al, 2023), digital status is also a key aspect of conducting interpersonal relationships. In particular, our research asks what role digital status plays in the contact multiplexity of family relations by shaping the opportunities of doing family digitally.

The connection between digital skills and online communication has been the focus of several studies in the past, but most prior research has focused on adolescents’ use of ICT. Whether digital skills enhance (Livingstone and Helsper, 2007; Areepattamannil and Khine, 2017; Scherer et al, 2017; Cino et al, 2023; Zhang et al, 2023) or undermine (Hinostroza et al, 2015; Correa, 2016) adolescents’ online communication is debated. It has been widely recognised that the increased use of social media, messaging and video calling (technology-assisted communication) has changed how individuals communicate even with their closest family members, that is, how they maintain their relationships. Especially when living geographically apart, technology can help maintain these ties but it might also assist the everyday micro coordination of family tasks. Each new medium seems to have complemented and not replaced prior media forms, thus families ‘increase their overall frequency of communication as each new technology [is] introduced’ (Wilding, 2006: 131). Media multiplexity theory (MMT, Haythornthwaite, 2005), which is rooted in communications theory and social network analysis, claims that people use multiple forms of communication (various forms of ICTs) to maintain their strong ties and the more channels they use and the more frequently they do so, the higher quality their relationship is. MMT originally claims that tie strength is the driver of media use; for example, strong ties requiring a significant amount of time and energy are often maintained via various communication channels but ties are also shaped by media use – for instance, additional communication channels may strengthen a relationship as well (Haythornthwaite, 2002; Ledbetter, 2021). Another important prediction of MMT, especially in light of the relational impact of the COVID-19 pandemic, is that changes in the availability of various forms of communication have a more profound impact on weak ties, while strong ties suffer less disruption (Ledbetter, 2021).

However, there seems to be a cultural difference between people living in individualistic versus collectivistic cultures. In individualistic cultures the interests of the individual are more important than those of the group, promoting a nuclear family structure in which children are brought up to be able to stand on their feet alone, leave the parental home early and not necessarily keep close ties (if at all) with parents. In collectivistic cultures, in contrast, the interests of the group are more important than those of the individual and these societies sustain extended families, belonging to which is perceived by its members as a given, a major source of their identity, resulting in mutually interdependent family relations (Hofstede et al, 2010). Those in individualist cultures seem to rely more on ICTs to feel close to their loved ones while the emotional connections of those in collectivist cultures are not so dependent on such interactions (Hofstede et al, 2010). Such differences can be mostly observed between countries, but in multicultural societies, within-country variance is also significant.

Barajaki et al (2018) examined long-distance family relations and hypothesised that relational closeness was correlated with both ICT use frequency as well as variety and that relational closeness would be positively associated with both. They found that increased relational closeness was significantly associated with ICT use frequency and that relational closeness is a positive predictor of ICT frequency, but could not find proof of the link with ICT variety. Balayar and Langlais (2021) tested the impact of online and offline interactions on the quality of family relationships. Their sample population is limited to undergraduate students and their results are inconclusive but their analyses revealed that individuals scoring high in collectivism report that spending time face-to-face is associated with higher relationship closeness and love, particularly with parents. Barakji et al (2018) included culture when analysing how relational closeness is linked to the use of information and communication technologies (ICTs) to maintain long-distance family relationships.

From among a larger set of research questions that follow about how digital status and doing family are connected, our study focuses on understanding the contact frequency and multiplexity aspect of adult child–parent relationships.

Data, methods and research questions

To investigate the connection between digital status and adult child–parent relationships, we used data from the 10th wave of the European Social Survey (ESS) conducted between 2020–2022 (European Social Survey European Research Infrastructure) which provided a set of variables on digital skills and outcomes as well as on the means and frequency of contact between children and their parents. As we were interested in the contact frequency of adult children and their parents, all analyses were restricted to the sample of respondents (N=39,969) between the ages of 18 and 65 for 30 European countries.

Our digital status measure consisted of three digital skills variables and two proxies for positive outcomes. The degree of agreement that online and mobile communication makes people feel closer to one another worked as a proxy for emotional outcome, whereas the degree of agreement that online and mobile communication makes it easy to coordinate and manage activities worked as a proxy for practical outcome. Unlike in the conventional digital divide framework, we omitted the first, access divide from the digital status tool. This decision was based on the prevalence of ICT coverage in Europe which minimises exclusion of individuals without access, leading to negligible impact on digital status.

The first pillar in constructing digital status is digital skills, also known as the second digital divide that is critical to the success of ICT use and is influenced by factors such as age, residence and several socioeconomic criteria (Hargittai, 2010; van Deursen and van Dijk, 2011; van Deursen et al, 2016; Hargittai et al, 2019; Robinson et al, 2020a). Regarding digital skills, the ESS asked about the level of familiarity (on a 1–5 scale, where higher values indicated higher familiarity) with preference settings, advanced search, and PDF documents. These survey instruments for measuring Internet skills were derived from a comprehensive 27-item questionnaire developed and tested by Hargittai (2005). Later, shorter item lists were proposed to measure digital skills using variables that can assess these skills independently of an individual’s basic demographic and socioeconomic status (Hargittai and Hsieh, 2012). As these three skill variables were found to be highly correlated in all examined countries in our ESS datasets (see online supplement for country-specific correlations), we opted to create a simple index representing digital skills on a 1–5 scale (higher values indicate greater skill) by averaging the three original skill items.

The other two pillars of digital status focused on the perceived usefulness of ICT use in managing and maintaining social relationships and online activities. Numerous studies have suggested that ICT and social network sites help sustain and deepen relationships (Pew Research Center, 2010; Szabo et al, 2019). These technologies enhance accessibility, foster frequent and sustained communication, and contribute to the maintenance of relationships with family and friends (Katz and Rice, 2002; van Deursen and Helsper, 2015; Hartanto et al, 2020; Li et al, 2022). Reflecting on these previous studies, we conceptualised the second pillar of the digital status tool as the emotional outcome of ICT use which was measured by the degree of agreement that online and mobile communication makes people feel closer to one another. The third pillar of the digital status tool measured the practical outcome of ICT use. Previous measurement tools and surveys, such as those conducted by Zillien and Hargittai (2009) and van Deursen and Helsper (2015), have revealed various positive and capital-enhancing outcomes resulting from different modes of ICT use. In contrast to emotional outcome, the practical outcome of ICT use captures a generalised sense of effectiveness in conducting interactions and is measured by the degree of agreement that online and mobile communication makes it easy to coordinate and manage activities. The emotional and practical outcome variables were employed as separate dimensions in their original form as 0–10 scales (with higher values indicating higher positive emotional or practical positivity) because only a low level of correlation existed between them and vis-a-vis the skill items. This approach was also supported by dimension reduction solutions (exploratory factor analysis)1 in an attempt to create factors from the original skills and outcomes variables. Loadings clearly showed that while the three skill variables loaded onto one factor, the two outcome variables formed separate dimensions, thus forcing them together would result in inconsistent results (calculations available from authors).

To illustrate country-level heterogeneity without sample selection bias in our later models of adult child and parent contact frequency, Figure 1 presents the means of the three indices for all respondents aged 18–65 (N=39,969). In the case of the first pillar, the highest average digital skills index was observed for Finland (4.12) and the lowest for Latvia (2.99). The European average skill (calculated with weights that correct for population size and sampling errors) was 3.48. Countries with above-average skills included mostly nations from Northern (Finland, Norway, Sweden), Western (Switzerland, the Netherlands, the UK, Ireland) and Central-Eastern Europe (Austria, Poland, Hungary, Slovakia, Czechia). Except for France and Iceland, below-average nations came from mostly Southern and Eastern Europe.

The figure shows the estimated means of the three variables, namely the skill index, the emotional outcome and the practical outcome measures, with countries ordered in descending order along the skill index. A notable feature is that an ordering along the skill index does not result in visible patterns along the other two variables, suggesting that they are different dimensions at least to a considerable degree.
Figure 1:

Estimated means of the three independent variables, full sample

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 (N=39,969). Countries are in descending order by their respective skill index value. Lines indicate the 95 per cent confidence interval.

Regarding emotional and practical outcomes, there was no visible correlation between them and the skill index (as illustrated by the fact that ordering by the skill index did not result in a similar ordering along the outcomes), indicating that skills and outcomes grasp different dimensions of our digital lives. The European average emotional outcome was 6.54, with the highest values observed in Czechia (7.65) and Greece (7.62), and the lowest in Germany (5.32). Both the below-average and above-average groups were heterogeneous in terms of regionality (for example, the former consists of Montenegro, France, Poland, Switzerland, Austria, Estonia, Serbia and Germany). Finally, the mean European practical outcome was 7.82, with the lowest value in Montenegro (6.56) and the highest in Norway (8.54). Above- and below-average groups were again very heterogeneous.

To analyse how digital skills, emotional outcome and practical outcome affected the frequency of contact between adult children and their parents, we selected a subsample of adult children (18–65) with relevant information on a parent, designated as their biological parent who was still alive, or the one whose birthday was most recent at the time of the interview. Our final sample consisted of N=26,675 respondents (9,915 had no parent in the dataset; 3,369 had missing data on at least one main dependent2 or control variable (see Table 1) from the original N=39,969 respondents aged 18–65).

Table 1:

Variable summary table: controls, main independents and dependent variables

Type Variable
Controls Gender Male
Female
Gender of parent Father
Mother
Disclose intimate matters None
1–3 person(s)
4 or more persons
Educational attainment Primary or lower
Secondary
Tertiary
Physical distance Living together
30 minutes or less
31–60 minutes
61 minutes or more
Emotional distance Not close
Close
Age of respondent Mean and SD
Age of parent Mean and SD
Main independents Skill index Mean and SD
Emotional outcome (0–10) Mean and SD
Practical outcome (0–10) Mean and SD
Dependents In-person contact Less than weekly
At least weekly
Contact via voice call Less than weekly
At least weekly
Contact via video call Less than weekly
At least weekly
Contact via messaging Less than weekly
At least weekly

Regarding the main dependent variables, we examined four forms of contact, namely, the frequency of in-person contact, voice calls, video calls and messaging (Figure 2). The ESS10 questionnaire contained the following wording for each of these items. G28: How often do you speak with {him/her} in person? Please only include occasions where you are physically in the same location; G29: How often do you speak with {him/her} such that you can see each other on a screen?; G30: How often do you speak with {him/her} using a phone or other device? Please include calls you make or receive, but exclude calls where you see each other on a screen; G31: How often do you communicate in writing with each other via text, email or messaging apps? While the original contact variables were measured on a 1–7 scale (where 1 indicated several times a day and 7 never), due to country-level variability and the often rarely chosen ends of the scale, we dichotomised the dependent variables to reflect whether the adult children contacted their parent at least weekly or less frequently than weekly.

The second figure shows the estimated percentage of frequent (defined as at least weekly) contact via in-person meetings, voice calls, video calls and messaging. All types of contacts show considerable variability between countries, which implies that communication with a parent differs across the nations of Europe and therefore, a country-specific modelling approach is warranted. The percentage of frequent in-person contact ranged from 22 per cent (Finland) to 86.9 per cent (North Macedonia); for voice calls it was between 38 per cent (Finland) and 83.1 per cent (Greece), for video calls it was between 4.3 per cent (Finland) and 29.8 per cent (Serbia), and finally for messaging, it was between 13.7 per cent (Bulgaria) and 51.6 per cent (Spain).
Figure 2:

Estimated percentage of frequent (at least weekly) contact with parents

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval.

As several other factors can be associated with contact frequency, we included a wide range of control variables. First, we added variables related to the respondents, namely, their age (in years), gender, highest level of education (primary or lower, secondary or tertiary), and core discussion network size – that is, the number of persons they can discuss intimate matters with (none, one to three persons, or four or more persons). Second, we included the gender and age of the parent they reported about. Third, we chose indicators that represent physical and emotional closeness to the parent. The former was measured by travel distance from living together to living more than an hour away from each other, and the latter was a dichotomised variable (from a 1–5 scale to close or not close) which represented subjective emotional closeness. Descriptive statistics for the samples used are presented in the online supplement.

The hypotheses motivating our study on the connection between digital status and adult child–parent relationship were the following:

  1. H1: The skills aspect of digital status is positively correlated with the frequency of technology-mediated contact (voice calls, video calls and messaging) between adult children and parents.
  2. H2: The emotional outcome aspect of digital status is positively correlated with the frequency of technology-mediated contact (voice calls, video calls and messaging) between adult children and parents.
  3. H3: The practical outcome aspect of digital status is positively correlated with the frequency of technology-mediated contact (voice calls, video calls and messaging) between adult children and parents.
  4. H4: The strength of the correlation between digital status (skills and outcomes) and the frequency of technology-mediated contact (voice calls, video calls and messaging) depends on physical distance from the parent; it is strongest in the case of far-distance residence, weakest in the case of co-residence.

To model how our main dependent variables affected contact frequency, we employed country-specific binary logistic regression models for all outcomes. We started by fitting models using the three main dependents with controls, followed by models where we interacted the main independents with each other (all two-way interactions examined separately) and checked possible higher-order (squared) effects.3 While a multilevel approach was also considered, we opted for simpler country-specific models due to the absence of country-level hypotheses and the relatively low number of countries, which can bias results for logistic models causing errors and false conclusions (see Snijders and Bosker, 1999; Bryan and Jenkins, 2016; Ali et al, 2019). In the discussion of the results, we rely on the average marginal effects of the main dependents from the fitted models, as they are unbiased and therefore enable group comparisons (see Mood, 2010, for a comprehensive methodological discussion). All presented data and detailed models with fit statistics (pseudo-R-squared statistics and area-under-the-curve values) are available in the online supplement.

Results

Looking first at H1 on the correlation of the skills aspect of digital status with the frequency of contact between adult children and parents, our findings in Figure 3 show the average marginal effect (AME) of a 1 scale-point increase in the digital skill of adult children on the probability of frequent contact with parents.

The third figure shows the average marginal effects of the skill index on frequent contact with parent. The notable feature of the figure is that messaging emerges as the most affected way of communication, with other avenues only rarely showing statistical significance.
Figure 3:

AME of digital skill index (1–5) on frequent contact (at least weekly) with parent

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval. Dotted line indicates zero effect. Values in grey indicate non-significant effects (p > 0.05).

For in-person contact, we found that out of the 29 nations, only North Macedonia had a mild positive correlation (+4.09 per cent per scale point), so we concluded that digital skills were not related to personal contact frequency between adult children and their parents. For voice calls we found that 8 countries had a significant correlation, 7 displayed a positive one (from +2.79 per cent in Greece to +6.20 per cent in Slovakia), and interestingly, digital skills had a negative correlation with contact frequency via voice calls (–5.60 per cent per scale point), although the lower bound of the effect was close to zero. For video calls, we found that digital skills had a significant correlation in 6 countries, in 4 of those (Portugal, North Macedonia, Ireland, Greece) positive and in 2 negative (Slovakia, Germany). Positive correlation ranged from +4.36 per cent (North Macedonia) to +1.93 per cent (Greece). While the negative correlation for Germany is minor (–1.18 per cent), Slovakia’s is more substantial (–4.14 per cent). For messaging, we found that digital skills had a strong correlation with the frequency of messaging, as higher skills had a positive, significant effect in 17 nations. The strongest correlation was observed in North Macedonia (+9.41 per cent per skill point) and the weakest in Germany (+3.10 per cent).

With regard to H1, we concluded that in the domain of adult child and parent contacts, the skill aspect of digital status was positively and strongly correlated with frequent messaging in most European countries. Frequent contact via voice calls was less strongly but still significantly correlated with digital skills in a number of countries, whereas a positive correlation for video calls was observed in four countries only. H1 therefore was partially upheld.

Considering, second, H2 on the correlation of the positive emotional outcome aspect of digital status with the frequency of contact between adult children and parents, our findings in Figure 4 show the average marginal effect (AME) of a 1 scale-point increase in the positive emotional outcome of adult children on the probability of frequent contact with parents.

The fourth figure depicts the average marginal effects of the emotional outcome variable on frequent contact with parent. Effects are generally not significant, with messaging being the most affected form of communication.
Figure 4:

AME of positive emotional outcome (0–10) on frequent contact (at least weekly) with parent

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval. Dotted line indicates zero effect. Values in grey indicate non-significant effects (p > 0.05).

Emotional benefit was slightly correlated with in-person contact frequency, voice call and video call frequency with parents. A significant, negative correlation was observed for in-person contact frequency in the case of Montenegro (–4.92 per cent), Hungary (–2.42 per cent) and Greece (–1.54 per cent), and a positive in France (+1.27 per cent). For voice calls, positive emotional outcome displayed a correlation in four countries (Austria, France, Germany and Greece), ranging from +2.08 per cent (Austria) to +1.12 per cent (Germany). Stronger emotional benefit also significantly correlated with video call frequency in five countries (Greece, Ireland, Montenegro, the Netherlands and Sweden), the connection ranging from +3.91 per cent (Montenegro) to +1.55 per cent (Greece). Finally, stronger emotional benefit was significantly correlated with the frequency of messaging in 9 nations (Bulgaria, Finland, Germany, Greece, Montenegro, Poland, Portugal, Serbia and Spain). The weakest of these was observed in Germany (+0.99 per cent) and the strongest in Montenegro (+3.93 per cent).

With regard to H2, we concluded that in the domain of adult child and parent contacts, the emotional benefit aspect of digital status was positively and strongly correlated with frequent messaging (via various platforms) in the nine European countries where the connection was significant. Frequent contact via voice calls and video calls was less strongly but still significantly correlated with emotional benefit in a smaller number of countries (in five countries for video calls, and four countries for voice calls). H2 therefore was partially upheld.

Looking, third, at H3 on the correlation of the positive practical outcome aspect of digital status with the frequency of contact between adult children and parents, our findings in Figure 5 show the average marginal effect (AME) of a 1 scale-point increase in the positive practical outcome of adult children on the probability of frequent contact with parents.

The fifth figure shows the average marginal effects of the practical outcome variable on frequent contact with parents. A notable feature of this analysis is that most effects are either non-significant or negative.
Figure 5:

AME of positive practical outcome (0–10) on frequent contact (at least weekly) with parent

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval. Dotted line indicates zero effect. Values in grey indicate non-significant effects (p > 0.05).

Compared to emotional benefit, stronger practical benefit was mostly negatively correlated with the various media of communication. Stronger practical benefit was associated with less frequent in-person contact in 5 countries, with the strongest negative correlation observed in Cyprus (–3.20 per cent), and the weakest in Sweden (–1.86 per cent). For voice calls, we observed a negative correlation in two countries and a positive correlation in another pair of countries (Greece with –2.66 per cent, Sweden with –3.24 per cent, Italy with +2.16 per cent and Lithuania with +3.69 per cent, respectively). For video calls, interestingly, stronger practical benefit was associated with lower frequency of video calls in 9 nations (from –5.24 per cent in Montenegro to –0.76 per cent in Germany), whereas higher frequency was observed only in France (+1.89 per cent). Finally, for messaging, practical benefit was correlated significantly in three countries only (Bulgaria with –0.50 per cent, Montenegro with –5.24 per cent, and Slovakia with –3.32 per cent), where it decreased the probability of at least weekly contact between an adult child and their parent.

With regard to H3, we concluded that in the domain of adult child and parent contacts, the practical outcome aspect of digital status was negatively and strongly correlated with frequent video calls in nine European countries, a pattern that was observable for messaging in three countries. H3 therefore was rejected.

We also looked at higher-order effects between each of the three aspects of digital status and the frequency of contact via relevant media.

In six countries, we found a significant squared effect for digital skills on the frequency of voice calls with parents (Figure 6). For Belgium, the effect was negative and stronger towards the 3–4 range of the digital skill scale. For four countries (Great Britain, Hungary, Latvia and Poland), the positive effect had a reverse U-shape, which implies that the positive effect is stronger when digital skill increases towards the middle (more average) skill level but the positive effect weakens at high skill levels. For Montenegro, the reverse U-shape had an earlier peak, at around skill level 2.

The sixth figure shows squared effects of the skill index on contact via voice calls for six countries. As described, the figure shows visible reverse U-shaped patterns (with steeper rises for Hungary and Latvia), except for Belgium, where a regular U-shaped pattern emerged.
Figure 6:

AME of digital skill index (1–5) on frequent contact (at least weekly) with parents via voice calls, higher-order effects

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval. Dotted line indicates zero effect. All effects are significant (p < 0.05).

In six countries (Figure 7), emotional benefit had a significant squared term. In five of these (Belgium, Cyprus, the UK, Iceland and Serbia), the negative effect of emotional benefit on the probability of frequent contact via video calls has a U-shape: it is stronger at medium/ upper-medium levels of emotional benefit, and weaker at the lower and upper ends. Slovakia’s case is unique: the AME of emotional benefit is non-significant at the lowest (0) level, but grows positive and stronger towards values of 8–9, where it stagnates.

The penultimate figure shows the squared effects of emotional outcomes on frequent video calls with parent. From the six presented countries, five show a U-shaped pattern of negative effects, with Slovakia presenting a positive, increasing effect – with low levels of emotional outcome being non-significant.
Figure 7:

AME of emotional outcome (0–10) on frequent contact (at least weekly) with parent via video calls, higher-order effects

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval. Dotted line indicates zero effect. Values in grey indicate non-significant effects (p > 0.05).
The final figure shows the squared effect of the practical outcome variable on frequent video calls with parent. All countries follow a negative U-shaped trend, with all except Italy having a non-significant effect at low practical outcome levels.
Figure 8:

AME of positive practical outcome (0–10) on frequent contact (at least weekly) with parent via video calls, higher-order effects

Citation: Families, Relationships and Societies 13, 2; 10.1332/20467435Y2024D000000026

Source: ESS, wave 10 (2020), respondents aged 18–65 with a parent. Lines indicate the 95 per cent confidence interval. Dotted line indicates zero effect. Values in grey indicate non-significant effects (p > 0.05).

Finally, we found a significant quadratic effect in the case of practical benefit and the frequency of contacts via video calls for five countries (Figure 8). For all of these nations, the effect is U-shaped – weaker at low and high levels of practical outcome and stronger towards the middle. In the case of Austria, the UK, Greece and Lithuania, the effect at the lowest values of practical benefit (0–1) is non-significant at p < 0.05.

Last, in response to H4 on the extent to which the strength of correlation between the skills and outcomes aspects of digital status, and the frequency of technology-mediated contact (voice calls, video calls and messaging) depended on physical distance from the parent, we proceeded by fitting interaction models. The proposed interaction between the main independents and physical distance, measured in travel time to parent, was not corroborated by our results (available in the online supplement). Although we did not find evidence for the notion that the effect of digital skills, practical benefit and emotional benefit differed according to physical distance, and there was also a possibility that the lack of a significant interaction resulted from low country-specific sample sizes, we could nevertheless conclude that, regardless of physical distance, the two important factors in adult child–parent contacts were digital skills and a positive emotional outcome of online and mobile communication.

Discussion and conclusion

Our results largely confirm a fundamental insight of the two digitalisation literatures invoked in our study, namely the understanding that digital skills and the outcomes of digital practices, let them be emotional or practical, are independent dimensions shaping the digital position of social actors. Our digital status measure revealed that doing family digitally means very different practices in a key area of family relations, that is, in how adult children keep contact with their parents.

Our findings further supported the positive relationship between digital skills and online communication, confirming this relationship in the context of adult child–parent contact frequency. Among the various forms of contact analysed, messaging was most influenced by digital skills, with a positive and significant average marginal effect observed across 17 European nations.

When conceptualising digital status, our objective was to create a measurement tool that – in addition to digital skills – included practical and emotional outcomes without favouring digital natives or early adopters. Prior studies have noted the importance of social outcomes of ICT use, and within this, they have explored topics such as network building, social capital, or online dating (van Dijk, 2005; Boase et al, 2006; van Deursen and Helsper, 2015; Scheerder et al, 2017). Due to data availability limitations, we were only able to focus on one element of social outcomes, namely emotional benefits. In line with expectations, within the domain of adult child and parent contacts, the emotional outcome aspect of digital status showed a positive and strong correlation with frequent messaging in the nine European countries where this connection was significant. Furthermore, frequent contact via voice calls and video calls was less strongly but still significantly correlated with a positive emotional outcome in a smaller number of countries (in five for video calls and four for voice calls). In summary, the results suggest that the first two pillars of digital status, specifically emotional outcomes and digital skills, positively influence the frequency of adult child–parent contact.

A more surprising correlation was found in the case of the third pillar of digital status. Contrary to our hypothesis, positive practical outcomes, capturing a generalised sense of effectiveness in conducting interactions, had an overall negative impact on adult child–parent contact frequency. The practical benefit element of digital status showed a negative and strong correlation with frequent video calls in nine European countries. This pattern was also observed for messaging in three countries. One potential explanation for this counterintuitive result might be connected to findings in previous research which has indicated that individuals with higher social status, who occupy a digitally advantageous position and employ ICT effectively, are more likely to use ICTs for materially beneficial or capital-enhancing purposes and less inclined to use them primarily for communication via social networking platforms (van Deursen and van Dijk, 2014; Correa, 2016). In this context, a higher practical benefit score could potentially explain decreased contact frequency. Although our study does not provide a definitive answer to this set of questions, it serves as a valuable foundation for potential avenues of exploration in future research. The results of this study also indicated that the two outcome pillars, emotional and practical, captured the relationship between digital status and adult child–parent contact frequency in a divergent manner, underpinning the claim that the concept of digital status offers a viable framework for exploring the ever-widening landscape of outcomes of ICT use.

The prime limitation of our study is that the measure of digital status employed in the analysis was conditioned by data availability in the 10th wave of ESS, a restriction especially evident in the case of proxies for digital outcomes. When compared to more nuanced solutions for grasping digital outcomes, which explicitly ask respondents to give their opinion on a scale ranging from an obviously negative outcome to a clearly positive outcome, in a relevant domain (for example, Pew Research Center, 2010), we encounter the constraints in ESS10 posed by the two measures of digital practices as proxies of positive outcomes exclusively. For instance, in contrast with ESS10, which asked, on the one hand, whether online and mobile communication brought people closer to one another, and on the other hand, made interpersonal coordination easier, the Pew Research Centre (2010) asked US respondents in 2010 to position themselves on several scales ranging from negative to positive outcomes. Measures included scales ranging from the negative extreme ‘new technology makes life more complicated’ to the positive ‘new technology makes life easier’; or from ‘new technology makes people more isolated’ to ‘new technology makes people closer to their friends and family’; likewise from ‘new technology makes people waste too much time’ to ‘new technology allows people to use their time more efficiently’ (Pew Research Centre, 2010: 26). This obvious limitation of ESS10 notwithstanding, the concept and the empirical operationalisation of digital status, we claim, is worth exploring further in the context of various other datasets.

Our analyses relied on the insight of media multiplexity theory that the use of multiple channels of communication, contact multiplexity, strengthens ties by increasing contact frequency. Our findings did reveal that the frequency of technology-mediated contact (voice calls, video calls and messaging) between adult children and parents shows great cross-country variance in Europe and is closely tied especially to the skills but also to the emotional benefit aspect of digital status. These findings put media multiplexity into the wider context of how digitalisation, captured by individual-level variance in digital status, enables or disables actors to conduct personal relationships in key private life domains.

Notes

1

Exploratory factor analysis is a method that aims to reduce a large set of variables to so-called factors that represent underlying constructs based on the association between the examined variables (see Fabrigar and Wegener, 2012, for both a discussion on basic concepts and application). Loadings represent the extent to which each original variable contributes to (or is associated with) a proposed factor – higher factor loadings imply a stronger relationship between the original variable and the factor.

2

Respondents from Czechia had to be omitted entirely as all respondents had missing values on one of the control variables.

3

Effects are considered to be higher-order if the non-categorical explanatory variable is included in its original and squared (or other polynomial) form, which enables the modelling of possibly more complex effects.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Data availability statement

Data and materials are located at http://pea.lib.pte.hu/handle/pea/44824.

Conflict of interest

The authors declare that there is no conflict of interest.

References

  • Ali, A., Ali, S., Khan, S.A., et al (2019) Sample size issues in multilevel logistic regression models, PLOS ONE, 14(11): e0225427. doi: 10.1371/journal.pone.0225427

    • Search Google Scholar
    • Export Citation
  • Areepattamannil, S. and Khine, M.S. (2017) Early adolescents’ use of information and communication technologies (ICTs) for social communication in 20 countries: examining the roles of ICT-related behavioral and motivational characteristics, Computers in Human Behavior, 73: 26372. doi: 10.1016/j.chb.2017.03.058

    • Search Google Scholar
    • Export Citation
  • Balayar, B. and Langlais, M. (2021) Technology makes the heart grow fonder? A test of media multiplexity theory for family closeness, Social Sciences, 10(1): 25. doi: 10.3390/socsci10010025

    • Search Google Scholar
    • Export Citation
  • Barakji, F., Maguire, K.C., Reiss, H., et al (2018) Cultural and transnational influences on the use of information communication technologies in adult long-distance family relationships: an extension of media multiplexity theory, Journal of Family Communication, 19(1): 3046. doi: 10.1080/15267431.2018.1530675

    • Search Google Scholar
    • Export Citation
  • Boase, J., Horrigan, J.B., Wellman, B., et al (2006) The Strength of Internet Ties: The Internet and E-mail Aid Users in Maintaining Their Social Networks and Provide Pathways to Help when People Face big Decisions, Washington, DC: The Pew Internet and American Life Project.

    • Search Google Scholar
    • Export Citation
  • Bourdieu, P. (2005) The Social Structures of the Economy, Cambridge: Polity.

  • Bryan, M.L. and Jenkins, S.P. (2016) Multilevel modelling of country effects: a cautionary tale, European Sociological Review, 32(1): 322. doi: 10.1093/esr/jcv059

    • Search Google Scholar
    • Export Citation
  • Calderón Gómez, D. (2021) The third digital divide and Bourdieu: bidirectional conversion of economic, cultural, and social capital to (and from) digital capital among young people in Madrid, New Media & Society, 23(9): 253453. doi: 10.1177/1461444820933252

    • Search Google Scholar
    • Export Citation
  • Carlson, A. and Isaacs, A.M. (2018) Technological capital: an alternative to the digital divide, Journal of Applied Communication Research, 46(2): 24365. doi: 10.1080/00909882.2018.1437279

    • Search Google Scholar
    • Export Citation
  • Cino, D., Lacko, D., Mascheroni, G., et al (2023) Predictors of children’s and young people’s digital engagement in informational, communication, and entertainment activities: findings from ten European countries, Journal of Children and Media, 17(1): 3754. doi: 10.1080/17482798.2022.2123013

    • Search Google Scholar
    • Export Citation
  • Correa, T. (2016) Digital skills and social media use: how internet skills are related to different types of Facebook use among ‘digital natives’, Information, Communication & Society, 19(8): 1095107. doi: 10.1080/1369118x.2015.1084023

    • Search Google Scholar
    • Export Citation
  • DiMaggio, P. and Hargittai, E. (2001) From the ‘digital divide’ to ‘digital inequality’: studying internet use as penetration increases, Working Papers 47, Princeton, NJ: Princeton University, School of Public and International Affairs.

  • DiMaggio, P., Hargittai, E., Celeste, C., et al (2004) Digital inequality: from unequal access to differentiated use, in K. Neckerman (ed) Social Inequality, New York, NY: Russell Sage Foundation, pp 355400.

    • Search Google Scholar
    • Export Citation
  • European Social Survey European Research Infrastructure (ESS ERIC) (2023) ESS10 integrated file, edition 3.2 [data set]. Sikt – Norwegian Agency for Shared Services in Education and Research. doi: 10.21338/ess10e03_2

    • Search Google Scholar
    • Export Citation
  • Fabrigar, L.R. and Wegener, D.T. (2012) Exploratory Factor Analysis, New York, NY: Oxford University Press.

  • Fox, S., Taylor, C., Evans, C., et al (2023) The positional effects of education on social capital in the UK, International Journal of Sociology, 53(4): 26182. doi: 10.1080/00207659.2023.2227457

    • Search Google Scholar
    • Export Citation
  • Füzér, K., Völgyi, B., Erát, D., et al (2023) Global digital peripheries: the social capital profile of low‐adopter countries, Social Inclusion, 11(3): 22538. doi: 10.17645/si.v11i3.6808

    • Search Google Scholar
    • Export Citation
  • Gilbert, M. (2010) Theorizing digital and urban inequalities, Information, Communication & Society, 13(7): 100018. doi: 10.1080/1369118x.2010.499954

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. (2002) Second-level digital divide, First Monday, ISSN 1396-0466, https://firstmonday.org/ojs/index.php/fm/article/download/942/864?inline=1.

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. (2005) Survey measures of web-oriented digital literacy, Social Science Computer Review, 23(3): 3719. doi: 10.1177/0894439305275911

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. (2010) Digital na(t)ives? Variation in internet skills and uses among members of the ‘net generation’, Sociological Inquiry, 80(1): 92113. doi: 10.1111/j.1475-682x.2009.00317.x

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. and Hsieh, Y.P. (2012) Succinct survey measures of web-use skills, Social Science Computer Review, 30(1): 95107. doi: 10.1177/0894439310397146

    • Search Google Scholar
    • Export Citation
  • Hargittai, E., Piper, A.M. and Morris, M.R. (2019) From internet access to internet skills: digital inequality among older adults, Universal Access in the Information Society, 18(4): 88190. doi: 10.1007/s10209-018-0617-5

    • Search Google Scholar
    • Export Citation
  • Hartanto, A., Yong, J.C., Toh, W.X., et al (2020) Cognitive, social, emotional, and subjective health benefits of computer use in adults: a 9-year longitudinal study from the Midlife in the United States (MIDUS), Computers in Human Behavior, 104: 106179. doi: 10.1016/j.chb.2019.106179

    • Search Google Scholar
    • Export Citation
  • Haythornthwaite, C. (2002) Strong, weak, and latent ties and the impact of new media, The Information Society, 18(5): 385401. doi: 10.1080/01972240290108195

    • Search Google Scholar
    • Export Citation
  • Haythornthwaite, C. (2005) Social networks and internet connectivity effects, Information, Communication & Society, 8(2): 12547. doi: 10.1080/13691180500146185

    • Search Google Scholar
    • Export Citation
  • Hinostroza, J.E., Matamala, C., Labbé, C., et al (2015) Factors (not) affecting what students do with computers and internet at home, Learning, Media and Technology, 40(1): 4363. doi: 10.1080/17439884.2014.883407

    • Search Google Scholar
    • Export Citation
  • Hofstede, G., Hofstede, G.J. and Minkov, M. (2010) Cultures and Organizations: Software of the Mind: Intercultural Cooperation and Its Importance for Survival, 3rd edn, New York, NY: McGraw-Hill.

    • Search Google Scholar
    • Export Citation
  • Katz, J. and Rice, R. (2002) Social Consequences of Internet Use. Access, Involvement, and Interaction, Cambridge: MA: MIT Press. doi: 10.2307/1556636

    • Search Google Scholar
    • Export Citation
  • Ledbetter, A.M. (2021) Media multiplexity theory: explaining tie strength and technology use, Engaging Theories in Interpersonal Communication, 3rd edn, New York, NY Routledge.

    • Search Google Scholar
    • Export Citation
  • Li, C., Ning, G., Xia, Y., et al (2022) Does the internet bring people closer together or further apart? The impact of internet usage on interpersonal communications, Behavioral Sciences, 12(11): 425. doi: 10.3390/bs12110425

    • Search Google Scholar
    • Export Citation
  • Livingstone, S. and Helsper, E. (2007) Gradations in digital inclusion: children, young people and the digital divide, New Media & Society, 9(4): 67196. doi: 10.1177/1461444807080335

    • Search Google Scholar
    • Export Citation
  • Merisalo, M. and Makkonen, T. (2022) Bourdieusian e-capital perspective enhancing digital capital discussion in the realm of third level digital divide, Information Technology & People, 35(8): 23152. doi: 10.1108/itp-08-2021-0594

    • Search Google Scholar
    • Export Citation
  • Mood, C. (2010) Logistic regression: why we cannot do what we think we can do, and what we can do about it, European Sociological Review, 26(1): 6782. doi: 10.1093/esr/jcp006

    • Search Google Scholar
    • Export Citation
  • Morgan, B. (2010) New literacies in the classroom: digital capital, student identity, and third space, The International Journal of Technology, Knowledge, and Society, 6(2): 22140. doi: 10.18848/1832-3669/cgp/v06i02/56094

    • Search Google Scholar
    • Export Citation
  • Norris, P. (2001) Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide, Communication, Society and Politics, Cambridge: Cambridge University Press. doi: 10.1017/CBO9781139164887

    • Search Google Scholar
    • Export Citation
  • Ortega Egea, J.M., Recio Menéndez, M. and Román González, M.V. (2007) Diffusion and usage patterns of internet services in the European Union, Information Research, 12(2).

    • Search Google Scholar
    • Export Citation
  • Park, S. (2017) Digital Capital, London: Palgrave Macmillan. doi: 10.1057/978-1-137-59332-0

  • Pena-López, J.A. and Sánchez-Santos, J.M. (2017) Individual social capital: accessibility and mobilization of resources embedded in social networks, Social Networks, 49: 111. doi: 10.1016/j.socnet.2016.11.003

    • Search Google Scholar
    • Export Citation
  • Pew Research Center (2010) Millennials: A Portrait of Generation Next. Confident. Connected. Open to Change, Washington, DC: Pew Research Center, www.pewresearch.org/wp-content/uploads/sites/3/2010/10/millennials-confident-connected-open-to-change.pdf.

    • Search Google Scholar
    • Export Citation
  • Ragnedda, M. (2018) Conceptualizing digital capital, Telematics and Informatics, 35(8): 236675. doi: 10.1016/j.tele.2018.10.006

  • Ragnedda, M., Muschert, G.W. and Ruiu, M.L. (2023) Digital stratification: class, status group and party in the age of the internet, in W. Housley, A. Edwards, R. Beneito-Montagut and R. Fitzgerald (eds) The SAGE Handbook of Digital Society, London: Sage, pp 1934. doi: 10.4135/9781529783193

    • Search Google Scholar
    • Export Citation
  • Ragnedda, M., Ruiu, M.L. and Addeo, F. (2020) Measuring digital capital: an empirical investigation, New Media & Society, 22(5): 793816. doi: 10.1177/1461444819869604

    • Search Google Scholar
    • Export Citation
  • Roberts, E. and Townsend, L. (2016) The contribution of the creative economy to the resilience of rural communities: exploring cultural and digital capital, Sociologia Ruralis, 56(2): 197219. doi: 10.1111/soru.12075

    • Search Google Scholar
    • Export Citation
  • Robinson, L., Schulz, J., Blank, G., et al. (2020a) Digital inequalities 2.0: legacy inequalities in the information age, First Monday. doi: 10.5210/fm.v25i7.10842

    • Search Google Scholar
    • Export Citation
  • Robinson, L., Schulz, J., Dunn, H.S., et al. (2020b) Digital inequalities 3.0: Emergent inequalities in the information age, First Monday. doi: 10.5210/fm.v25i7.10844

    • Search Google Scholar
    • Export Citation
  • Rogers, E.M. (2003) Diffusion of Innovations, 5th edn, New York: Free Press.

  • Rojas, V., Roychowdhury, D., Okur, O., et al. (2004) Beyond access: cultural capital and the roots of the digital divide, in E.P. Bucy and J.E. Newhagen (eds) Media Access: Social and Psychological Dimensions of New Technology Use, Mahwah, NJ: Lawrence Erlbaum Associates.

    • Search Google Scholar
    • Export Citation
  • Scheerder, A., van Deursen, A. and van Dijk, J. (2017) Determinants of internet skills, uses and outcomes. A systematic review of the second- and third-level digital divide, Telematics and Informatics, 34(8): 160724. doi: 10.1016/j.tele.2017.07.007

    • Search Google Scholar
    • Export Citation
  • Scherer, R., Rohatgi, A. and Hatlevik, O.E. (2017) Students’ profiles of ICT use: identification, determinants, and relations to achievement in a computer and information literacy test, Computers in Human Behavior, 70: 48699. doi: 10.1016/j.chb.2017.01.034

    • Search Google Scholar
    • Export Citation
  • Seale, J. (2013) When digital capital is not enough: reconsidering the digital lives of disabled university students, Learning, Media and Technology, 38(3): 25669. doi: 10.1080/17439884.2012.670644

    • Search Google Scholar
    • Export Citation
  • Selwyn, N. (2004) Reconsidering political and popular understandings of the digital divide, New Media & Society, 6(3): 34162. doi: 10.1177/1461444804042519

    • Search Google Scholar
    • Export Citation
  • Selwyn, N. (2009) The digital native – myth and reality, Aslib Proceedings, 61(4): 36479. doi: 10.1108/00012530910973776

  • Snijders, T. and Bosker, R. (1999) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, London: Sage Publishers.

    • Search Google Scholar
    • Export Citation
  • Straubhaar, J., Tufekci, Z., Spence, J., et al (2012) Digital Inequity in the Austin Technopolis – An Introduction. doi: 10.7560/728714-002

    • Search Google Scholar
    • Export Citation
  • Szabo, A., Allen, J., Stephens, C., et al (2019) Longitudinal analysis of the relationship between purposes of internet use and well-being among older adults, The Gerontologist, 59(1): 5868. doi: 10.1093/geront/gny036

    • Search Google Scholar
    • Export Citation
  • Tőkés, G.E. (2021) Digitális egyenlőtlenségek és digitális tőkemegoszlás Romániában, Információs Társadalom, 21(3): 109. doi: 10.22503/inftars.xxi.2021.3.5

    • Search Google Scholar
    • Export Citation
  • van Deursen, A. and van Dijk, J. (2011) Internet skills and the digital divide, New Media & Society, 13(6): 893911. doi: 10.1177/1461444810386774

    • Search Google Scholar
    • Export Citation
  • van Deursen, A.J. and van Dijk, J.A. (2014) The digital divide shifts to differences in usage, New Media & Society, 16(3): 50726. doi: 10.1177/1461444813487959

    • Search Google Scholar
    • Export Citation
  • van Deursen, A.J.A.M. and Helsper, E.J. (2015) The third-level digital divide: who benefits most from being online?, Communication and Information Technologies Annual. Studies in Media and Communications, 10:2953. doi: 10.1108/S2050-206020150000010002

    • Search Google Scholar
    • Export Citation
  • van Deursen, A.J.A.M., Helsper, E.J. and Eynon, R. (2016) Development and validation of the Internet Skills Scale (ISS), Information, Communication & Society, 19(6): 80423. doi: 10.1080/1369118X.2015.1078834

    • Search Google Scholar
    • Export Citation
  • van Dijk, J. (2005) The Deepening Divide: Inequality in the Information Society, Thousand Oaks, CA: Sage. doi: 10.4135/9781452229812

  • Wilding, R. (2006) ‘Virtual’ intimacies? Families communicating across transnational contexts, Global Networks 6(2): 12542. doi: 10.1111/j.1471-0374.2006.00137.x

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., Cao, H., Zhang, W., et al (2023) How digital skills influence on digital participation in China? The mediating roles of online interpersonal communication and online immersion, Sage Open, 13(4): 21582440231218786. doi: 10.1177/21582440231218786

    • Search Google Scholar
    • Export Citation
  • Zillien, N. and Hargittai, E. (2009) Digital distinction: status-specific types of internet usage, Social Science Quarterly, 90(2): 27491. doi: 10.1111/j.1540-6237.2009.00617.x

    • Search Google Scholar
    • Export Citation
  • Figure 1:

    Estimated means of the three independent variables, full sample

  • Figure 2:

    Estimated percentage of frequent (at least weekly) contact with parents

  • Figure 3:

    AME of digital skill index (1–5) on frequent contact (at least weekly) with parent

  • Figure 4:

    AME of positive emotional outcome (0–10) on frequent contact (at least weekly) with parent

  • Figure 5:

    AME of positive practical outcome (0–10) on frequent contact (at least weekly) with parent

  • Figure 6:

    AME of digital skill index (1–5) on frequent contact (at least weekly) with parents via voice calls, higher-order effects

  • Figure 7:

    AME of emotional outcome (0–10) on frequent contact (at least weekly) with parent via video calls, higher-order effects

  • Figure 8:

    AME of positive practical outcome (0–10) on frequent contact (at least weekly) with parent via video calls, higher-order effects

  • Ali, A., Ali, S., Khan, S.A., et al (2019) Sample size issues in multilevel logistic regression models, PLOS ONE, 14(11): e0225427. doi: 10.1371/journal.pone.0225427

    • Search Google Scholar
    • Export Citation
  • Areepattamannil, S. and Khine, M.S. (2017) Early adolescents’ use of information and communication technologies (ICTs) for social communication in 20 countries: examining the roles of ICT-related behavioral and motivational characteristics, Computers in Human Behavior, 73: 26372. doi: 10.1016/j.chb.2017.03.058

    • Search Google Scholar
    • Export Citation
  • Balayar, B. and Langlais, M. (2021) Technology makes the heart grow fonder? A test of media multiplexity theory for family closeness, Social Sciences, 10(1): 25. doi: 10.3390/socsci10010025

    • Search Google Scholar
    • Export Citation
  • Barakji, F., Maguire, K.C., Reiss, H., et al (2018) Cultural and transnational influences on the use of information communication technologies in adult long-distance family relationships: an extension of media multiplexity theory, Journal of Family Communication, 19(1): 3046. doi: 10.1080/15267431.2018.1530675

    • Search Google Scholar
    • Export Citation
  • Boase, J., Horrigan, J.B., Wellman, B., et al (2006) The Strength of Internet Ties: The Internet and E-mail Aid Users in Maintaining Their Social Networks and Provide Pathways to Help when People Face big Decisions, Washington, DC: The Pew Internet and American Life Project.

    • Search Google Scholar
    • Export Citation
  • Bourdieu, P. (2005) The Social Structures of the Economy, Cambridge: Polity.

  • Bryan, M.L. and Jenkins, S.P. (2016) Multilevel modelling of country effects: a cautionary tale, European Sociological Review, 32(1): 322. doi: 10.1093/esr/jcv059

    • Search Google Scholar
    • Export Citation
  • Calderón Gómez, D. (2021) The third digital divide and Bourdieu: bidirectional conversion of economic, cultural, and social capital to (and from) digital capital among young people in Madrid, New Media & Society, 23(9): 253453. doi: 10.1177/1461444820933252

    • Search Google Scholar
    • Export Citation
  • Carlson, A. and Isaacs, A.M. (2018) Technological capital: an alternative to the digital divide, Journal of Applied Communication Research, 46(2): 24365. doi: 10.1080/00909882.2018.1437279

    • Search Google Scholar
    • Export Citation
  • Cino, D., Lacko, D., Mascheroni, G., et al (2023) Predictors of children’s and young people’s digital engagement in informational, communication, and entertainment activities: findings from ten European countries, Journal of Children and Media, 17(1): 3754. doi: 10.1080/17482798.2022.2123013

    • Search Google Scholar
    • Export Citation
  • Correa, T. (2016) Digital skills and social media use: how internet skills are related to different types of Facebook use among ‘digital natives’, Information, Communication & Society, 19(8): 1095107. doi: 10.1080/1369118x.2015.1084023

    • Search Google Scholar
    • Export Citation
  • DiMaggio, P. and Hargittai, E. (2001) From the ‘digital divide’ to ‘digital inequality’: studying internet use as penetration increases, Working Papers 47, Princeton, NJ: Princeton University, School of Public and International Affairs.

  • DiMaggio, P., Hargittai, E., Celeste, C., et al (2004) Digital inequality: from unequal access to differentiated use, in K. Neckerman (ed) Social Inequality, New York, NY: Russell Sage Foundation, pp 355400.

    • Search Google Scholar
    • Export Citation
  • European Social Survey European Research Infrastructure (ESS ERIC) (2023) ESS10 integrated file, edition 3.2 [data set]. Sikt – Norwegian Agency for Shared Services in Education and Research. doi: 10.21338/ess10e03_2

    • Search Google Scholar
    • Export Citation
  • Fabrigar, L.R. and Wegener, D.T. (2012) Exploratory Factor Analysis, New York, NY: Oxford University Press.

  • Fox, S., Taylor, C., Evans, C., et al (2023) The positional effects of education on social capital in the UK, International Journal of Sociology, 53(4): 26182. doi: 10.1080/00207659.2023.2227457

    • Search Google Scholar
    • Export Citation
  • Füzér, K., Völgyi, B., Erát, D., et al (2023) Global digital peripheries: the social capital profile of low‐adopter countries, Social Inclusion, 11(3): 22538. doi: 10.17645/si.v11i3.6808

    • Search Google Scholar
    • Export Citation
  • Gilbert, M. (2010) Theorizing digital and urban inequalities, Information, Communication & Society, 13(7): 100018. doi: 10.1080/1369118x.2010.499954

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. (2002) Second-level digital divide, First Monday, ISSN 1396-0466, https://firstmonday.org/ojs/index.php/fm/article/download/942/864?inline=1.

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. (2005) Survey measures of web-oriented digital literacy, Social Science Computer Review, 23(3): 3719. doi: 10.1177/0894439305275911

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. (2010) Digital na(t)ives? Variation in internet skills and uses among members of the ‘net generation’, Sociological Inquiry, 80(1): 92113. doi: 10.1111/j.1475-682x.2009.00317.x

    • Search Google Scholar
    • Export Citation
  • Hargittai, E. and Hsieh, Y.P. (2012) Succinct survey measures of web-use skills, Social Science Computer Review, 30(1): 95107. doi: 10.1177/0894439310397146

    • Search Google Scholar
    • Export Citation
  • Hargittai, E., Piper, A.M. and Morris, M.R. (2019) From internet access to internet skills: digital inequality among older adults, Universal Access in the Information Society, 18(4): 88190. doi: 10.1007/s10209-018-0617-5

    • Search Google Scholar
    • Export Citation
  • Hartanto, A., Yong, J.C., Toh, W.X., et al (2020) Cognitive, social, emotional, and subjective health benefits of computer use in adults: a 9-year longitudinal study from the Midlife in the United States (MIDUS), Computers in Human Behavior, 104: 106179. doi: 10.1016/j.chb.2019.106179

    • Search Google Scholar
    • Export Citation
  • Haythornthwaite, C. (2002) Strong, weak, and latent ties and the impact of new media, The Information Society, 18(5): 385401. doi: 10.1080/01972240290108195

    • Search Google Scholar
    • Export Citation
  • Haythornthwaite, C. (2005) Social networks and internet connectivity effects, Information, Communication & Society, 8(2): 12547. doi: 10.1080/13691180500146185

    • Search Google Scholar
    • Export Citation
  • Hinostroza, J.E., Matamala, C., Labbé, C., et al (2015) Factors (not) affecting what students do with computers and internet at home, Learning, Media and Technology, 40(1): 4363. doi: 10.1080/17439884.2014.883407

    • Search Google Scholar
    • Export Citation
  • Hofstede, G., Hofstede, G.J. and Minkov, M. (2010) Cultures and Organizations: Software of the Mind: Intercultural Cooperation and Its Importance for Survival, 3rd edn, New York, NY: McGraw-Hill.

    • Search Google Scholar
    • Export Citation
  • Katz, J. and Rice, R. (2002) Social Consequences of Internet Use. Access, Involvement, and Interaction, Cambridge: MA: MIT Press. doi: 10.2307/1556636

    • Search Google Scholar
    • Export Citation
  • Ledbetter, A.M. (2021) Media multiplexity theory: explaining tie strength and technology use, Engaging Theories in Interpersonal Communication, 3rd edn, New York, NY Routledge.

    • Search Google Scholar
    • Export Citation
  • Li, C., Ning, G., Xia, Y., et al (2022) Does the internet bring people closer together or further apart? The impact of internet usage on interpersonal communications, Behavioral Sciences, 12(11): 425. doi: 10.3390/bs12110425

    • Search Google Scholar
    • Export Citation
  • Livingstone, S. and Helsper, E. (2007) Gradations in digital inclusion: children, young people and the digital divide, New Media & Society, 9(4): 67196. doi: 10.1177/1461444807080335

    • Search Google Scholar
    • Export Citation
  • Merisalo, M. and Makkonen, T. (2022) Bourdieusian e-capital perspective enhancing digital capital discussion in the realm of third level digital divide, Information Technology & People, 35(8): 23152. doi: 10.1108/itp-08-2021-0594

    • Search Google Scholar
    • Export Citation
  • Mood, C. (2010) Logistic regression: why we cannot do what we think we can do, and what we can do about it, European Sociological Review, 26(1): 6782. doi: 10.1093/esr/jcp006

    • Search Google Scholar
    • Export Citation
  • Morgan, B. (2010) New literacies in the classroom: digital capital, student identity, and third space, The International Journal of Technology, Knowledge, and Society, 6(2): 22140. doi: 10.18848/1832-3669/cgp/v06i02/56094

    • Search Google Scholar
    • Export Citation
  • Norris, P. (2001) Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide, Communication, Society and Politics, Cambridge: Cambridge University Press. doi: 10.1017/CBO9781139164887

    • Search Google Scholar
    • Export Citation
  • Ortega Egea, J.M., Recio Menéndez, M. and Román González, M.V. (2007) Diffusion and usage patterns of internet services in the European Union, Information Research, 12(2).

    • Search Google Scholar
    • Export Citation
  • Park, S. (2017) Digital Capital, London: Palgrave Macmillan. doi: 10.1057/978-1-137-59332-0

  • Pena-López, J.A. and Sánchez-Santos, J.M. (2017) Individual social capital: accessibility and mobilization of resources embedded in social networks, Social Networks, 49: 111. doi: 10.1016/j.socnet.2016.11.003

    • Search Google Scholar
    • Export Citation
  • Pew Research Center (2010) Millennials: A Portrait of Generation Next. Confident. Connected. Open to Change, Washington, DC: Pew Research Center, www.pewresearch.org/wp-content/uploads/sites/3/2010/10/millennials-confident-connected-open-to-change.pdf.

    • Search Google Scholar
    • Export Citation
  • Ragnedda, M. (2018) Conceptualizing digital capital, Telematics and Informatics, 35(8): 236675. doi: 10.1016/j.tele.2018.10.006

  • Ragnedda, M., Muschert, G.W. and Ruiu, M.L. (2023) Digital stratification: class, status group and party in the age of the internet, in W. Housley, A. Edwards, R. Beneito-Montagut and R. Fitzgerald (eds) The SAGE Handbook of Digital Society, London: Sage, pp 1934. doi: 10.4135/9781529783193

    • Search Google Scholar
    • Export Citation
  • Ragnedda, M., Ruiu, M.L. and Addeo, F. (2020) Measuring digital capital: an empirical investigation, New Media & Society, 22(5): 793816. doi: 10.1177/1461444819869604

    • Search Google Scholar
    • Export Citation
  • Roberts, E. and Townsend, L. (2016) The contribution of the creative economy to the resilience of rural communities: exploring cultural and digital capital, Sociologia Ruralis, 56(2): 197219. doi: 10.1111/soru.12075

    • Search Google Scholar
    • Export Citation
  • Robinson, L., Schulz, J., Blank, G., et al. (2020a) Digital inequalities 2.0: legacy inequalities in the information age, First Monday. doi: 10.5210/fm.v25i7.10842

    • Search Google Scholar
    • Export Citation
  • Robinson, L., Schulz, J., Dunn, H.S., et al. (2020b) Digital inequalities 3.0: Emergent inequalities in the information age, First Monday. doi: 10.5210/fm.v25i7.10844

    • Search Google Scholar
    • Export Citation
  • Rogers, E.M. (2003) Diffusion of Innovations, 5th edn, New York: Free Press.

  • Rojas, V., Roychowdhury, D., Okur, O., et al. (2004) Beyond access: cultural capital and the roots of the digital divide, in E.P. Bucy and J.E. Newhagen (eds) Media Access: Social and Psychological Dimensions of New Technology Use, Mahwah, NJ: Lawrence Erlbaum Associates.

    • Search Google Scholar
    • Export Citation
  • Scheerder, A., van Deursen, A. and van Dijk, J. (2017) Determinants of internet skills, uses and outcomes. A systematic review of the second- and third-level digital divide, Telematics and Informatics, 34(8): 160724. doi: 10.1016/j.tele.2017.07.007

    • Search Google Scholar
    • Export Citation
  • Scherer, R., Rohatgi, A. and Hatlevik, O.E. (2017) Students’ profiles of ICT use: identification, determinants, and relations to achievement in a computer and information literacy test, Computers in Human Behavior, 70: 48699. doi: 10.1016/j.chb.2017.01.034

    • Search Google Scholar
    • Export Citation
  • Seale, J. (2013) When digital capital is not enough: reconsidering the digital lives of disabled university students, Learning, Media and Technology, 38(3): 25669. doi: 10.1080/17439884.2012.670644

    • Search Google Scholar
    • Export Citation
  • Selwyn, N. (2004) Reconsidering political and popular understandings of the digital divide, New Media & Society, 6(3): 34162. doi: 10.1177/1461444804042519

    • Search Google Scholar
    • Export Citation
  • Selwyn, N. (2009) The digital native – myth and reality, Aslib Proceedings, 61(4): 36479. doi: 10.1108/00012530910973776

  • Snijders, T. and Bosker, R. (1999) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, London: Sage Publishers.

    • Search Google Scholar
    • Export Citation
  • Straubhaar, J., Tufekci, Z., Spence, J., et al (2012) Digital Inequity in the Austin Technopolis – An Introduction. doi: 10.7560/728714-002

    • Search Google Scholar
    • Export Citation
  • Szabo, A., Allen, J., Stephens, C., et al (2019) Longitudinal analysis of the relationship between purposes of internet use and well-being among older adults, The Gerontologist, 59(1): 5868. doi: 10.1093/geront/gny036

    • Search Google Scholar
    • Export Citation
  • Tőkés, G.E. (2021) Digitális egyenlőtlenségek és digitális tőkemegoszlás Romániában, Információs Társadalom, 21(3): 109. doi: 10.22503/inftars.xxi.2021.3.5

    • Search Google Scholar
    • Export Citation
  • van Deursen, A. and van Dijk, J. (2011) Internet skills and the digital divide, New Media & Society, 13(6): 893911. doi: 10.1177/1461444810386774

    • Search Google Scholar
    • Export Citation
  • van Deursen, A.J. and van Dijk, J.A. (2014) The digital divide shifts to differences in usage, New Media & Society, 16(3): 50726. doi: 10.1177/1461444813487959

    • Search Google Scholar
    • Export Citation
  • van Deursen, A.J.A.M. and Helsper, E.J. (2015) The third-level digital divide: who benefits most from being online?, Communication and Information Technologies Annual. Studies in Media and Communications, 10:2953. doi: 10.1108/S2050-206020150000010002

    • Search Google Scholar
    • Export Citation
  • van Deursen, A.J.A.M., Helsper, E.J. and Eynon, R. (2016) Development and validation of the Internet Skills Scale (ISS), Information, Communication & Society, 19(6): 80423. doi: 10.1080/1369118X.2015.1078834

    • Search Google Scholar
    • Export Citation
  • van Dijk, J. (2005) The Deepening Divide: Inequality in the Information Society, Thousand Oaks, CA: Sage. doi: 10.4135/9781452229812

  • Wilding, R. (2006) ‘Virtual’ intimacies? Families communicating across transnational contexts, Global Networks 6(2): 12542. doi: 10.1111/j.1471-0374.2006.00137.x

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., Cao, H., Zhang, W., et al (2023) How digital skills influence on digital participation in China? The mediating roles of online interpersonal communication and online immersion, Sage Open, 13(4): 21582440231218786. doi: 10.1177/21582440231218786

    • Search Google Scholar
    • Export Citation
  • Zillien, N. and Hargittai, E. (2009) Digital distinction: status-specific types of internet usage, Social Science Quarterly, 90(2): 27491. doi: 10.1111/j.1540-6237.2009.00617.x

    • Search Google Scholar
    • Export Citation
Bence Völgyi Faculty of Humanities and Social Sciences, University of Pécs, Hungary

Search for other papers by Bence Völgyi in
Current site
Google Scholar
Close
,
Katalin Füzér Faculty of Humanities and Social Sciences, University of Pécs, Hungary

Search for other papers by Katalin Füzér in
Current site
Google Scholar
Close
,
Fruzsina Albert HUN-REN Centre for Social Sciences and Semmelweis University, Hungary

Search for other papers by Fruzsina Albert in
Current site
Google Scholar
Close
, and
Dávid Erát Faculty of Humanities and Social Sciences, University of Pécs, Hungary

Search for other papers by Dávid Erát in
Current site
Google Scholar
Close

Content Metrics

May 2022 onwards Past Year Past 30 Days
Abstract Views 211 211 15
Full Text Views 223 223 183
PDF Downloads 164 164 133

Altmetrics

Dimensions