Abstract
Emerging adulthood has changed dramatically in the last 30 years, in part due to the widespread adoption of communication technology. Despite studies showing that youth in the United States are communicating with extended family using technology, research on online interactions with non-parental relatives is lacking. Framed by intergenerational solidarity theory, this study identifies subgroups of U.S. emerging adults (N = 532; 18–29 years old) based on eight indicators of connectedness with extended family. Latent class analysis revealed four group: (1) Highly connected (18%), (2) Distant; technologically connected (36%), (3) Close; technologically connected (17%), and (4) Distant (28%). Participants identified cousins and aunts/uncles most frequently as extended family. Results show that 72% of participants are connecting with extended family online, even when they do not feel close to them. Findings support the idea that technology could be the means by which extended family members continue to play a role in the lives of young adults, especially when they are not seeing them frequently in-person.
Keywords: Extended family, Technology, Connectedness, Latent class analysis, Emerging adulthood
Introduction
Family connectedness has been incorporated into prevention research focused on understanding key contributors to positive youth development (Sieving et al., 2017). Further, the widespread accessibility of communication technology as a means of communicating with family has altered the ways in which connectedness can be experienced. In particular, the current generation of emerging adults is distinct in their experience of being fully situated in the digital world for all of their lives, thus, providing a unique perspective on how both online and offline interactions contribute to a sense of connection with family. A wide variety of studies have explored the implications of online connections for nuclear family relationships, but very little research has examined implications for extended family relationships (Vogt, 2020). Using latent class analysis, the current study aims to fill this gap by identifying subgroups of the current generation of emerging adults in their feelings of connectedness with extended family both online and offline.
Emerging Adulthood in Contemporary U.S. Society
In response to historical, economic, and social trends in the contemporary U.S., emerging adults have created increasingly diverse paths to adulthood, resulting in increased complexity during this transitional period (Katsiaficas, 2017). The markers of adulthood just a few decades ago were quite well defined, with objective role transitions such as getting married, having children, and moving out of the family home (Benson & Furstenberg, 2007). Today’s society offers options to prolong educational attainment, to take a “gap year,” to stay in—or return to—the family home, to have children at an older age, or to choose not to have children at all. In 2000, Arnett introduced the concept of “emerging adulthood” that he suggests is reflective of these recent shifts that have been observed in this period of life. Arnett’s conception of emerging adulthood describes this time in generally positive terms—as a time of exploration and opportunity as young people move beyond the dependency of adolescence but have not yet assumed all the responsibilities of adulthood. Arnett (2000) described emerging adulthood as a time of possibility and optimism about the future, emphasizing the psychosocial aspects of development over objective markers. Arnett’s (2015) conception of emerging adulthood includes five main features: identity exploration, instability, self-focus, feeling “in-between,” and possibilities/optimism.
Because some youth still achieve the traditional markers at young ages, the various ways that youth navigate the transition to adulthood have broadened and become more complex (Katsiaficas, 2017). These social and economic shifts have also had a significant impact on the family life cycle. For example, parents are now finding themselves taking an active parenting role for longer than in the past, and relationships between emerging adults and their parents often need to be renegotiated, such as financial arrangements and expectations when living together (Copp et al., 2017). Young people today are opting to delay the attainment of many of these traditional milestones of adulthood, which do not hold the same significance they once did (Benson & Furstenberg, 2007).
One of the unique characteristics of today’s emerging adults is that they are the first generation to be fully integrated with the internet (Turner, 2015). Emerging adults are voracious users of communication technology. Eighty-nine percent of all U.S. adults are online (Pew Research Center, n.d.a); it is estimated that close to 100% of 18 to 29 year olds in the U.S. own a cell phone and close to 100% use it for texting at least once a week (Pew Research Center, n.d.b). Eighty-eight percent of 18 to 29 year olds in the U.S. are using social-networking sites (Pew Research Center, n.d.c). These numbers are in stark contrast to 1996, when only 19% of the U.S. adult population was using email, and 1997, when less than one quarter of the U.S. adult population was using the internet at all (Pew Research Center, 1999).
While parents facilitate opportunities to connect between younger children and their extended family, this function becomes less prominent as children age and begin to develop their own relationships with family members separate from their parents (Geurts & van Tilburg, 2015). The integration of communication technology within families means that any young person with a connection to the internet can interact with other family members autonomously. The adoption of communication technology means that these traditional definitions should be reexamined and researchers should explore how contact extends beyond geographic limitations; researchers have called for studies that look at the use of communication technology for supporting intergenerational ties (Fingerman et al., 2012).
Emerging Adults and Extended Family Relationships
Considerable research on the family life of emerging adults has focused on the parent–child relationship (Tariq et al., 2021). As a result, researchers have called for more studies to examine the role and impact of the extended family network on emerging and young adults, particularly using samples that are racially and socioeconomically diverse (Aquilino, 2006; Mills et al., 2001). Children receive assistance from non-parental relatives, both as practical support, such as housing and food, and as psychological support, such as emotional stability and a sense of identity (Bernardi, 2011). Further, a sense of connectedness between youth and both parental and non-parental adults has been associated with positive social, academic, and health-related behaviors in youth (Sieving et al., 2017). Although research on the impact of extended family members on child development is limited, results have shown that extended family involvement can be a protective factor, for example, against externalizing behaviors in children in foster care (Bai et al., 2016). Research has shown an increase in feelings of family cohesion and adaptability as youth move from adolescence into emerging adulthood, reflecting their perception of the functioning of the broader family system rather than just one dyadic relationship (Parra et al., 2015). Colaner et al. (2021) reported on the relational maintenance behaviors of godparents in their communication with emerging adult kin, revealing the associations between the behaviors of assurances, social networks, and self-disclosure and relational closeness. Specifically, communication reaffirming commitment to the relationship and sharing of self, along with spending time within the same network of family and friends, supported the development of closeness in the relationship. During a period of life when youth are increasingly becoming independent from parents, extended family support may play a particularly important role in maintaining connections with family while supporting their transition to adulthood (Claes et al., 2001).
Research on U.S. emerging adults and extended relatives such as aunts, uncles, and cousins, is scarce. In their book, “Aunting,” Ellingson and Sotirin (2010) described in-depth interviews and written narratives on experiences with aunts; college students were the predominant written narrative authors. These youth described a range of roles that aunts play in their lives, including aunts as maternal figures, role models and mentors, kin keepers, and distant actors in the same system. Some research has suggested that aunts act as moderators and mediators of the parent–child relationship for LGBTQ youth coming out to their families (Grafsky et al., 2018). While aunts and uncles play a variety of roles and may live geographically close or distant, the frequency of contact between aunts/uncles and nieces/nephews has been shown to be low; between 22.5% (nephews) and 42.9% (nieces) of the predominantly emerging adult participants interviewed by Milardo (2010) described biannual or less frequent contact with their aunts/uncles. This finding may reflect the tendency of U.S. families to gather only at significant national holidays, such as Thanksgiving, and religious celebrations, such as Christmas. Langer and Ribarich (2007) hypothesized that older extended relatives, such as aunts and uncles, who do not marry have a unique opportunity to be more active in the lives of younger family members.
Research on emerging adults’ relationships with grandparents is also sparse, particularly for samples of emerging adults not enrolled in college (Aquilino, 2006). Research on emerging adults and grandparents has suggested that youth have fairly strong feelings of closeness and, to a lesser extent, similarity with their grandparents, particularly maternal grandparents (Mills et al., 2001). Oliver and Cheff (2014) found that grandparents were significant sources of logistical and emotional support even for homeless young women who had difficult relationships with their parents and immediate family members. More recently, research has shown that grandparents can play an important role in mentoring their emerging adult grandchildren, positively impacting identity synthesis (Michałek-Kwiecień, 2022).
Similarly, Vogt (2020) analyzed biological interviews with three generations of families in Norway, including emerging adults who were transitioning into adulthood. Analysis of these qualitative data resulted in a typology of extended family roles along the two dimensions of “Involvement,” exemplified by “degree of emotional or practical caring/engagement” and “Interaction,” exemplified by “frequency of meetings, contact, communication” (Vogt, 2020, p. 1239). The quadrants associated with these dimensions were described as “Inspirational: providing advice, serving as a role model,” Sharing: support and help in everyday life, Detached: little/no contact or involvement, and Distanced: some contact but little or no emotional or practical caring/engagement” (Vogt, 2020, p.1239). Vogt (2020) did not distinguish between online and offline interactions, including both types of contact in describing interaction between family members. The distinction between these modalities serves as a foundational point of the current study.
Use of Technology with Extended Family
The integration of communication technology into everyday family life has introduced new opportunities for geographically distant family members to interact, both one-on-one and in social contexts, especially for today’s emerging adults who spend less time physically at home than when they were younger. Adolescence and emerging adulthood represent developmental periods of learning how to be independent from parents, and studies have shown that this process is reflected in online communication, in addition to in-person communication (Chen & Katz, 2009). We know some about how college students are interacting with parents online. However, a comprehensive look at how emerging adults are using communication technology with family more broadly is lacking.
Despite research showing that youth are reporting online contact with extended family, there is a significant gap in our understanding of online connections between emerging adults and non-parental relatives. Stephenson-Abetz and Holman (2012) found that most of the participants in their study were Facebook friends with parents and extended family members. Some research suggests that telephone communication between emerging adults and their grandparents is associated with how youth perceive the role and importance of grandparents (Rempusheski et al., 2012). However, these studies are just beginning to explore how emerging adults are connecting with non-parental family members, and researchers of emerging adults frequently use only college student samples (Aquilino, 2006). Technology has enabled families to communicate in novel ways that help to bridge the geographic distance that is increasingly present in a highly mobile society, but the implications of those opportunities to connect online are not fully understood.
Theoretical Framework
Intergenerational Solidarity Theory
This study is primarily based on Bengtson and Roberts’ (1991) Intergenerational Solidarity Theory (IGS). Bengtson and Roberts’ (1991) IGS has been described as the “gold standard” for understanding intergenerational relationships and is a well-established framework for exploring family obligations and support in an intergenerational context (Silverstein et al., 2010). Because emerging adulthood is a time when youth are developing unique relationships with extended family members—separate from their parents—intergenerational solidarity is particularly suited to research that explores these extended family relationships (Geurts & van Tilburg, 2015).
Intergenerational solidarity theory describes the dimensions that explain how intergenerational transfer of critical resources, values, and capacity occurs. As a part of this intergenerational cycle, there is a “renegotiation of the balance between continuity and innovation over time…” (Bengtson & Oyama, 2007, p. 4). Participants in younger generations make choices about what family values and resources will be moved forward, for example. At the same time, there is resource exchange that occurs between the generations, most clearly illustrated in the form of help to both younger and older family members. This bi-directional resource exchange and renegotiation is informed by levels of affect, interaction, agreement, and obligation within family relationships. A fundamental component of this intergenerational cycle is the opportunity to connect with extended family members. In the current study, this intergenerational framework has been applied to extended family relationships more broadly. The same dimensions that pertain to resource exchange from one generation to another (i.e., opportunities for interaction, contact, feelings, similarities, and support) can also be relevant within the same generation.
IGS is defined by six dimensions that contribute to this intergenerational cycle (Bengtson & Roberts, 1991): (1) structural solidarity (opportunities for interaction); (2) associational solidarity (active contact and interactions); (3) affectual solidarity (feelings or affect); (4) consensual solidarity (similarities); (5) functional solidarity (support given and received); and (6) normative solidarity (beliefs about family obligations). A brief definition of each of the six dimensions is included in Table 1. The current study utilizes four of the dimensions of IGS: structural, associational, affectual, and consensual solidarity.
Table 1.
Dimensions of Intergenerational Solidarity Theory (Bengtson & Roberts, 1991, p. 857)
| Dimension | Nominal definition |
|---|---|
| Structural solidarity | Opportunity structure for intergenerational relationships reflected in number, type, and geographic proximity of family members |
| Associational solidarity | Frequency and patterns of interaction in various types of activities in which family members engage |
| Affectual solidarity | Type and degree of positive sentiment held about family members, and the degree of reciprocity of these sentiments |
| Consensual solidarity | Degree of agreement on values, attitudes, and beliefs among family members |
| Functional solidarity [not utilized in the current studies] | Degree of helping and exchanges of resources |
| Normative solidarity [not utilized in the current studies] | Strength of commitment to performance of familial roles and to meeting familial obligations (familism) |
Social Identity Theory: Identification with Family
In addition to IGS, the concept of identification with family from Social Identity Theory was used to conceptualize the current study. IGS focuses primarily on intergenerational dyadic relationships within the family (e.g., how much support one gets from a particular family member, or pair of family members that share the same role, such as parents). Feelings of belonging and membership identification are not captured within IGS, and come from social identity theory, which states that a person’s sense of group membership impacts their feelings of pride and self-esteem (Tajfel & Turner, 1979). The concept of identification with family used in these studies is based on research by Brown et al. (1986), who identified self-awareness as a key component of group identity. Awareness of family membership could be expected to impact—and be impacted by—both passive and active connections with extended family. As children transition through adolescence and into adulthood, their sense of family membership has been found to increase, while their feelings of closeness to parents plateau, supporting the idea that feelings of family membership and family closeness are distinct constructs that may have unique implications for young people in this developmental period (Tsai et al., 2013).
Application of Theoretical Assumptions
IGS espouses a number of theoretical assumptions; three established assumptions have provided a foundation for the current study:
Structural solidarity is a precursor of associational solidarity. The "opportunity structure for family intergenerational interaction will enable (or constrain) frequencies and types of association and resource exchanges" (Bengtson & Roberts, 1991, p. 861).
Consensual solidarity (degree of agreement between family members) is independent of affectual and associational solidarity.
Family members act independent from each other within each solidarity dimension, i.e., solidarity is an individual manifestation, not dyadic.
Bengtson and Roberts’ (1991) IGS was chosen for this project in part because it provides a comprehensive view of adult family relationships and because it captures not only the interactions between family members, but also the potential to connect. Traditionally, interpretation of structural solidarity has been limited to a focus on physical proximity, number of family members, and the health of family members. However, as noted by Milardo (2010), family members who live near each other may not have strong ties, and vice versa. The current study adapts IGS by breaking structural and associational solidarity into two distinct types of connection: in-person and using technology. In addition to the structural and associational solidarity dimensions, affectual solidarity is included because it measures the degree of closeness that each participant feels toward their extended family members. Consensual solidarity contributes by assessing the extent to which each participant feels similar to extended family members, which is a concept that is closely tied to identification with family. While the concepts of family obligation and support are related to associational and structural solidarity, the IGS dimensions of normative and functional solidarity were not included in the current study in order to focus more directly on the dimensions relating to communication and affect.
Current Study
The research aim for the current study was to develop a typology of U.S. emerging adults’ extended family relationships and the connectedness experienced by emerging adults in those relationships. Researchers have hypothesized that society is moving beyond the “confines of the shrinking nuclear family” to make more and better use of extended kin (Bengtson et al., 2002, p. 162). Yet research on extended family relationships is scarce, especially for emerging adults. The current study was designed to fill specific gaps in our understanding of emerging adults in a broad family context.
There has been a lack of consensus in measuring family connectedness in online environments, such as social media (Tariq et al., 2021). Further, despite research suggesting that emerging adults are connecting with family members online, no studies have explored distinctions between having the opportunity/infrastructure (passive, structural solidarity) to connect and the frequency of connection (active, associational solidarity). Using intergenerational solidarity theory as a conceptual framework, the current study defines connectedness as encompassing multiple concepts, including identification with family, and consensual, affectual, associational (in-person and using technology), and structural (in-person and using technology) solidarity. If structural and associational solidarity is a conduit for interactions to occur, e.g., transfer of resources or increasing emotional closeness, then operationalizing these dimensions to include connectedness beyond physical proximity may better reflect the ways in which interactions occur in contemporary society.
Methods
Procedure
Upon receiving approval from the Institutional Review Board, participants were recruited from Amazon Mechanical Turk (MTurk) in late 2017 to complete a 25-min online survey and were paid $0.75 upon survey completion. MTurk is an online labor market that connects employers with workers who complete short term online tasks, such as surveys. In order to maximize the quality of the data, workers were required to have an MTurk reputation score of 95% or higher, which has been shown to have a positive impact on data quality (Peer et al., 2014). MTurk workers build their reputation score by completing tasks that are accepted by the creator of that task.
Participants provided demographic information and answered questions about their well-being and sense of identification with family. Participants then identified up to twelve family members who have “played a role, either positive or negative” in their life “during the past year,” categorized those family members as either “immediate” or “extended” family using a “drag-and-drop” feature, and answered questions about their interactions closeness, and similarity with each extended family member. This name generating technique was based on Widmer’s (2010) recommended methodology. Data for this study included only those participants who identified at least one extended family member as playing a role in their life over the past year; analyses include only data collected for those people that the participant identified as an “extended family member.”
Participants
Participants were 18–29 year old adults living in the U.S. (Table 2; N = 532; M age = 25.89 years, SD = 2.53). Inclusion criteria required participants to have at least one living extended family member. Participants were primarily White (70.9%), female (65.4%), married or living with a partner (61.3%), employed (85.9%), and partially or completely financially independent from their parents (93.2%). Approximately half of the participants earned less than $40,000 per year (53.4%) and had children of their own (42.5%). The college-going status of the participants was closely divided between (1) enrolled in school (32.1%), (2) not enrolled in school and had not attained a 4-year baccalaureate degree (32.1%), and (3) not enrolled in school and had earned a 4-year baccalaureate degree (35.5%).
Table 2.
Demographic Information of Participants (n = 532)
| n | % | |
|---|---|---|
| Race/Ethnicity | ||
| White or Caucasian | 377 | 70.9 |
| Youth of Color | 151 | 28.4 |
| Other/missing/do not know/prefer not to answer | 4 | 0.8 |
| Gender | ||
| Female | 348 | 65.4 |
| Male | 182 | 34.2 |
| Other/missing | 2 | 0.4 |
| Marital status | ||
| Single, never married | 190 | 35.7 |
| Separated or divorced | 16 | 3.0 |
| Married | 224 | 42.1 |
| Living together but not married | 102 | 19.2 |
| Parenthood status | ||
| Yes, have children or are expecting | 226 | 42.5 |
| No, do not have children | 303 | 57.0 |
| Missing | 3 | 0.6 |
| Employment status | ||
| Employed full-time | 346 | 65.0 |
| Employed part-time | 111 | 20.9 |
| Not employed | 75 | 14.1 |
| Financial independence from parents | ||
| Fully or almost fully supported by parents | 36 | 6.8 |
| Partially independent from parents | 179 | 33.6 |
| Completely independent from parents | 317 | 59.6 |
| Residential status (vis-à-vis parents) | ||
| Yes, have lived with a parent majority of the last 12 months | 156 | 29.3 |
| No, have not lived with a parent majority of the last 12 months | 376 | 70.7 |
| Annual income | ||
| Less than $25,000 | 143 | 26.9 |
| $25,000-$39,999 | 141 | 26.5 |
| $40,000-$59,999 | 136 | 25.6 |
| $60,000 or more | 111 | 20.9 |
| Missing | 1 | 0.2 |
| Education | ||
| High school degree or less | 66 | 12.4 |
| Some college | 206 | 38.8 |
| 4-year college graduate | 203 | 38.2 |
| Post-graduate training, e.g., Master’s, Ph.D | 57 | 10.7 |
| School status | ||
| Enrolled in school (could be post-graduate) | 170 | 32.1 |
| Does not have 4-year degree and not in school | 171 | 32.1 |
| Earned 4-year degree and not in school | 189 | 35.5 |
| Missing | 2 | 0.3 |
Measures
Structural Solidarity In-person
Structural solidarity in-person was measured by asking participants about their geographic proximity to each extended family member on a six-point Likert-type scale from 0 (Less than 1 h) to 5 (5 or more hours). The mean score for driving distance was 1.99, which equates to 2–3 h. High/low structural solidarity in-person was dichotomized based on a threshold score of within 2 h’ drive or closer for at least 50% of identified extended family members (adapted from Silverstein & Bengtson, 1997; van der Pers et al., 2015).
Structural Solidarity Using Technology
Structural solidarity using technology was measured by asking participants how frequently they were connected to each extended family member using six different technologies using a seven-point Likert scale from 0 (Not connected) to 6 (Daily or several times a week) for the following six technologies: Voice calls; Texting; Email; Social media; Online games; Video (α = 0.98). This measure was dichotomized based on breadth (connected with at least 50% of extended family members) and depth (using at least three technologies). This approach is supported by Media Multiplexity Theory, which posits that people with stronger relationships will use more channels to communicate (Haythornthwaite, 2005).
Associational Solidarity In-person
Associational solidarity in-person was measured by asking participants how frequently they saw each family member during the last 12 months, using a six-point Likert-type scale from 1 (Not at all) to 6 (Several times a week). The mean score for associational solidarity in-person was 3.03 (SD = 1.44). High/low associational solidarity in-person was dichotomized based on the threshold score of seeing at least 50% of identified extended family members at least monthly (Cheng et al., 2015; Milardo, 2010).
Associational Solidarity Using Technology
Associational solidarity using technology was measured based on frequency of interaction and number of family members with whom they connect (see “Structural solidarity using technology”). High/low associational solidarity using technology was dichotomized based on the threshold score of having monthly or more frequent contact with at least 50% of identified extended family members using at least one form of technology. Raw mean scores for associational solidarity were as follows: Voice calls (M = 3.24; SD = 1.62), Texting (M = 3.73; SD = 1.66); Email (M = 2.68; SD = 1.58); Social media (M = 3.74; SD = 1.67); Online games (M = 3.39; SD = 1.72); Video (M = 3.29; SD = 1.61).
Affectual Solidarity
Affectual solidarity was measured using one question from Gronvold (1988), adapted to apply to extended family members: “Taking everything into consideration, how close do you feel is the relationship between you and this family member?” using a six-point Likert-type scale from 1 (Not at all close) to 6 (Very close). The mean score for affectual solidarity was 3.82 (SD = 1.60). High/low consensual solidarity was dichotomized based on a threshold score of “4” or higher with at least 50% of identified extended family members.
Consensual Solidarity
Participants responded to the following question for each extended family member: “How similar are you to this person in your opinions and values about life?” using a six-point Likert-type scale from 1 (Not at all similar) to 6 (Very similar, Giarusso et al., 2004). The mean score for consensual solidarity was 3.65 (SD = 1.54). High/low consensual solidarity was dichotomized based on a threshold score of “4” or higher for at least 50% of extended family members (adapted from Guo et al., 2012).
Size of Extended Family Network
Participants identified from one to 12 extended family members who “played a role, either positive or negative, in [their lives] over the past year.” The average number of identified extended family members per participant was 3.64 (SD = 3.16).
Identification with Family
Participants responded to two statements measuring their awareness of membership in their family adapted from the Awareness subscale of Brown et al.’s (1986) Group Identification Scale: “I am a person who identifies with my family” and “I am a person who sees myself as belonging to my family” (a = 0.93). Participants responded using a 6-point Likert-type scale from 1 (Strongly disagree) to 6 (Strongly agree). A mean score (M = 4.58) was used to calculate perceived identification with family and then dichotomized at the threshold score of “4” or higher.
Data Analysis Plan
First, descriptive statistics were computed using SPSS v22.0.0.0. Second, a latent class analysis was conducted to create a typology based on extended family network size, identification with family, and all measures of solidarity. Latent class enumeration and measurement model building were conducted in Mplus v8, using the estimator Maximum Likelihood with robust standard errors (MLR). A systematic process was used to determine the potential range of classes, beginning with a one-class solution, and adding additional classes until the model did not converge. Model selection was determined using three recommended measures: Fit, parsimony, and interpretability (Collins & Lanza, 2010). Optimal solutions should have the lowest Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size adjusted BIC values, and a significant bootstrapped Likelihood Ratio Test (BLRT; Collins & Lanza, 2010; Masyn, 2013). The parsimony principal directs the researcher to select the least complicated model with adequate absolute fit (Masyn, 2013). Finally, interpretability refers to the degree of conceptual clarity between the classes (Geiser, 2013). Because of the lack of independence between the indicators of structural solidarity using technology and associational solidarity using technology, the analytical model accounted for not meeting the assumption of conditional independence between those variables.
The dataset included very little missing demographic data (< 0.6%). Missingness for the solidarity indicators prior to dichotomization ranged from 0 to 10.3%. Missingness for the solidarity indicators after dichotomization ranged from 0 to 1.9%. Missing data for the latent class analysis was addressed using full information maximum likelihood (FIML).
Results
Participants identified a total of 2475 family members as “extended family” that had “played a role” in their life over the past year, including aunts/uncles (30.5%), cousins (29.9%), in-laws (14.7%), grandparents (8.5%), niblings (5.1%), friends (2.1%), godparents/kin (1.5%), and others (e.g., step- or half-relatives, coworkers; 7.7%). The average age of extended family members was 42.5 years (SD = 19.43; range = 0—97). The age distribution of extended family members can be found in Fig. 1.
Fig. 1.
Age distribution of extended family members (in years)
Correlation coefficients were calculated for all variables, using the average score per participant across all the extended family members they identified (Table 3). Results showed moderate, positive relationships between structural solidarity in-person and associational solidarity in-person, and associational solidarity in-person and using technology. Moderate-to-strong positive relationships were found between associational solidarity using technology and affectual solidarity, and between associational solidarity using technology and consensual solidarity.
Table 3.
Pearson’s r correlations between variables (n = 532)
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
|---|---|---|---|---|---|---|---|---|
| 1. Age | 1 | 0.013 | −0.049 | −0.089* | −0.098* | −0.063 | −0.017 | 0.019 |
| 2. Structural Solidarity In-Person | 1 | 0.450*** | 0.072 | 0.030 | 0.036 | −0.041 | −0.038 | |
| 3. Associational Solidarity In-Person | 1 | 0.434*** | 0.357*** | 0.291*** | -0.099* | −0.114** | ||
| 4. Associational Solidarity Using Technology | 1 | 0.537*** | 0.523*** | -0.093* | 0.165*** | |||
| 5. Affectual Solidarity | 1 | 0.752*** | 0.006 | 0.300*** | ||||
| 6. Consensual Solidarity | 1 | −0.107* | 0.253*** | |||||
| 7. Size of Extended Family | 1 | 0.068 | ||||||
| 8. Family Identity | 1 |
*p < 0.05 **p < 0.01 ***p < 0.001
A review of the fit indices (Table 4) determined the 4-class solution as optimal for the latent class analysis (LCA). Although the lowest AIC value was the 5-class solution, the lowest BIC and Adjusted BIC values were found in the 4-class solution. The Lo-Mendell-Rubin Adjusted Likelihood Ratio Test (Adj. LMR) became non-significant at the 4-class solution, and the BLRT for both the 4- and 5-class solutions were significant. The 4-class solution was considered optimal because of the overall fit and using the principle of parsimony. Results from the LCA showed a range in probabilities of class membership for the eight indicators from 0.01 to 0.99 (Table 5). These probabilities reflect the likelihood of class membership based on being in the “High” group for each binary indicator, e.g., having “High structural solidarity.”
Table 4.
Fit indices used to identify optimal model
| Model | AIC | BIC | Adjusted BIC | Entropy | Adjusted LMR p | Bootstrapped LRT p |
|---|---|---|---|---|---|---|
| 1 class | 7300.36 | 7338.85 | 7310.28 | – | – | – |
| 2 class | 7029.29 | 7106.27 | 7049.13 | 0.71 | < 0.001 | < 0.001 |
| 3 class | 6953.90 | 7069.37 | 6983.66 | 0.65 | < 0.01 | < 0.001 |
| 4 class | 6906.69 | 7060.65 | 6946.38 | 0.66 | 0.153 | < 0.001 |
| 5 class | 6865.31 | 7057.76 | 6914.91 | 0.67 | < 0.001 | < 0.001 |
| 6 class | Not identified |
Table 5.
Probabilities of Class Membership, Indicating High Solidarity (95% CI)
| Class 1 (n = 98) | Class 2 (n = 190) | Class 3 (n = 91) | Class 4 (n = 153) | |
|---|---|---|---|---|
| Structural solidarity in-person |
0.50 (0.33–0.67) |
0.39 (0.26–0.52) |
0.37 (0.23–0.55) |
0.41 (0.19–0.66) |
| Structural solidarity using technology |
0.97 (0.85–1) |
0.92 (0.66–0.99) |
0.97 (0.89–0.99) |
0.23 (0.13–0.38) |
| Associational solidarity in-person |
0.99 (0.54–1) |
0.52 (0.39–0.66) |
0.66 (0.51–0.79) |
0.56 (0.28–0.80) |
| Associational solidarity using technology |
0.99 (0.95–1) |
0.89 (0.65–0.97) |
0.96 (0.86–0.99) |
0.23 (0.07–0.53) |
| Affectual solidarity |
0.73 (0.46–0.89) |
0.01 (0-0.82) |
0.97 (0.04–1) |
0.13 (0.05–0.32) |
| Consensual solidarity |
0.66 (0.43–0.84) |
0.05 (0.01–0.26) |
0.71 (0.51–0.85) |
0.30 (0.18–0.45) |
| Identification with family |
0.27 (0.16–0.42) |
0.19 (0.12–0.28) |
0.43 (0.30–0.58) |
0.17 (0.09–0.29) |
| Mean | ||||
| Count of identified extended family members | 6.53 | 2.97 | 2.58 | 6.69 |
Figure 2 provides a graphical depiction of the 4-class solution, including binary indicators, the count indicator of average number of extended family members identified, and the sample size for each class. The classes that emerged from the latent class analysis describe groups of emerging adults with varying levels of extended family connectedness and sizes of extended family networks (Table 6).
Fig.2.
Probability of class membership by indicators
Table 6.
Description of classes
| Class 1 | Class 2 | Class 3 | Class 4 | |
|---|---|---|---|---|
| “Highly connected” | “Distant; technologically connected” | Close; “technologically connected” | “Distant” | |
| M Age (SD) | 26.0 (2.4) | 25.8 (2.6) | 26.1 (2.2) | 25.8 (2.6) |
| Extended family size | Large | Small | Small | Large |
| Interaction | High in-person and technology | High technology | High technology | Low technology |
| Emotional closeness and similarity | * | Distant, not similar | Close | Distant |
| Identification with family | Not useful for determining class separation* | |||
| Structural solidarity in-person | Not useful for determining class separation* |
*Probabilities were not significant
Class 1, labeled as “Highly connected,” is characterized by a large and tight-knit extended family network. Although these participants comprise a relatively small class size (n = 98), these participants were distinguished as being the only class that had a high likelihood of frequent in-person interaction with extended family.
Class 2, labeled as “Distant; technologically connected” represents the most participants (n = 190). This class is distinguished by the lowest likelihood of having feelings of closeness and similarity with extended family members. These participants may not have frequent in-person contact with their extended family but they appear to maintain their relationships through technology. Members of this group identified fewer extended family members on average (2.97) than Classes 1 and 4, but keep in touch with these family members, using technology to maintain connection.
Class 3, labeled as “Close; technologically connected,” is distinguished by feelings of closeness and frequent connection using technology, with a lower likelihood than Class 1 (“Highly connected”) of having in-person interactions. Participants in this class (n = 91) feel close and somewhat similar to their small number (2.58) of extended family members; those relationships are primarily maintained through technology and not through frequent in-person contact.
Class 4, labeled as “Distant” represents the second-largest group of participants (n = 153). The portrait drawn of these respondents is that of an independent group of emerging adults who may or may not see their large network (6.69) of extended family members frequently, and do not feel close to most of them nor have much connection to them using technology.
No significant differences between classes were found by age, race, residential status, financial independence, annual income, employment status, school status, and marital status. Differences between classes were found by gender, X2 (3, N = 532) = 12.5, p = 0.05, such that males were more likely to be represented in Class 2 (Distant; technologically connected) and less likely to be represented in Class 4 (Distant) than females.
Discussion
This study increases our understanding of the family members that U.S. emerging adults consider as playing a part in their lives and the connectedness they experience with these extended family members, emotionally, in-person, and using technology. Results reveal that extended family members do continue to play a role in the lives of emerging adults, even after they have attained a number of markers of adulthood and have begun to build families of their own; the most commonly reported relationships were aunts/uncles, cousins, and in-laws. Findings provide further evidence of connections between emerging adults and their extended family members specifically via technology. These online interactions occur regardless of how emotionally close the emerging adults may feel with their extended family.
Despite Vogt (2020) not viewing their typology as resulting in four categories, results from this latent class analysis provides evidence that the two dimensions of Interaction and Involvement, broadly defined, plus the resulting quadrants, can be found in a larger sample as well. Vogt’s (2020) “Sharing” quadrant fits well with the “Class 1: Highly connected” emerging from these data. This finding of frequent in-person and online contact is particularly notable considering that these participants also had the highest average number of extended family members at 6.69. It is unclear from these analyses is whether the large extended family network is in addition to a substantive immediate family network, or possibly compensating for a small immediate family. Future research that accounts for the size of one’s immediate family could help shed light on the significance of extended family size within one’s overall family network.
Vogt’s (2020) “Inspirational” quadrant fits with the “Class 3: Close; technologically connected” group from these data. These families reveal a smaller group of extended family relationships in which the emerging adult feels close and connects through technology, but not as frequently in person. This group might also be similar to the description provided by Riley and Riley (1993) who described extended family as “remaining dormant” until needed, meaning that the means to communicate is there as needed. However, the pervasive use of social media provides a means for family members to passively stay connected in the “everyday” life of other family members, in ways they were unable to do in previous generations. These connections do not replace in person interactions but do provide an alternative way to maintain contact.
The “Distant” quadrant from Vogt’s (2020) study fits with the “Class 2: Distant; technologically connected” group in this study, characterized by high technology connections but not feeling particularly close or involved with that family member. That they are least likely to feel close or similar to their extended family suggests that they may have attained or sustained some measure of independence or separation from their family, perhaps through beginning their own family and developing their own social networks, values, and beliefs. It is notable that males were overrepresented in this class, suggesting that utilization of technology may serve other functions than emotional support, such as planning or information sharing.
Finally, the “Detached” group in Vogt’s (2020) study relates to the “Class 4: Distant” group in this study, characterized by low involvement both online and offline, and lack of emotional closeness in these relationships. It is possible that this class includes emerging adults who have attained a high degree of independence from their family. It is also possible that the sheer number of significant extended family members makes the relationship maintenance required to achieve “High affectual solidarity” burdensome. What is unclear from these data is why these participants identified a large number of extended family who have played a role in their life but with whom they do not feel close or have frequent interaction, and how these family members continue to play a role in their life, if they are not interacting frequently in-person or using technology. One possible answer is that the ritual of connecting over major holidays provides a potent reminder of family connectedness. Some people place tremendous value on family rituals associated with holidays. This class may represent a group that values those events and does not hold expectations for more frequent interactions beyond those celebrations and events.
What is clear from these results is that emerging adults are highly likely to be connecting with many extended family members using multiple technology environments; taken together, three of the classes (“Highly connected,” “Distant; technologically connected,” and “Close; technologically connected”) comprised nearly three quarters (72%) of the sample. This finding makes sense given the prevalence of social media and texting, the ease with which one can become connected using social media, the flexibility in a/synchronicity of popular technologies, and the prominent role that technology plays in the lives of emerging adults. Geographic distance was not a defining characteristic of any of the classes. Individuals not having the opportunity to see extended family members in person may still feel close to them using technology. Results show that most emerging adults are connected with their extended family members using technology, even when they do not interact with them frequently in-person. In contrast with past generations, however, aunts/uncles, grandparents, and emerging adults today have powerful new tools that could facilitate both direct and indirect communication.
Results showed the significance of emerging adults connecting with relatives in the same age group. The largest group of extended family members represented those people between the ages of 20 and 29 years; nearly 40% (39.6%) of identified extended family members were between the ages of 20 and 29 or 50 and 59. These individuals are not siblings and parents, but more likely cousins, aunts, and uncles. In a period of life where peer relationships are important, the idea that a cousin can be both a family member and a friend is intriguing. Presumably the cousin relationship does not carry the same significance, tension, and potential complications as a sibling relationship. Yet cousins that are also in emerging adulthood share multiple points of intersection with each other, e.g., family dynamics, heritage, the challenges of transitioning to adulthood. Cousins are more likely to be geographically distant than immediate family members, which has implications for how communication technology facilitates these relationships. Cousins in a similar age range are also likely to already be using the same kinds of technology as their emerging adult relatives, requiring little extra work to communicate in online spaces.
During a transitional period when young people are building their independence from parents and reaching traditional markers of adulthood, they are also beginning to take responsibility for maintaining connections with extended family as an adult in their own right. It was not surprising that the top four family roles included parents and siblings. However, the prominence of cousins and aunts/uncles—and relative lack of prominence of grandparents—may depart from conventional wisdom. These findings could be at least partially explained by the number of potential cousins and aunts/uncles with which one could be connected. For example, we would anticipate that the sheer number of cousins in a emerging adults' life would be more than siblings (exponentiated by both parents having their own multiple siblings). These findings emphasize the need for future research into these unique family relationships.
Theoretical Implications
Intergenerational Solidarity Theory distinguishes between the opportunities to interact, or structural solidarity, and the actual interactions themselves, associational solidarity. In many studies structural solidarity has been measured as geographic proximity, usually in miles/kilometers or hours’ driving time. The findings in the current study provide support for considering interactions that occur in-person and those that occur using technology as separate phenomena, with different opportunities, expectations, and barriers. For example, the “Highly connected” class was distinguished primarily by the high likelihood of frequent in-person contact, whereas the “Distant” class was distinguished primarily by its low likelihood of contact using technology. The distinction between in-person contact and interactions using technology is especially relevant given the high geographic mobility of contemporary U.S. society and of this age group in particular.
The distinction between structural solidarity using technology and associational solidarity using technology was less clear in the results; in general, the high likelihood of having high structural solidarity using technology was accompanied by the high likelihood of having high associational solidarity using technology. One explanation for why this finding would be different using technology than in-person is that there needs to be multiple factors in place for in-person contact, e.g., coordination, cost, means of transportation. In contrast, given the widespread use of communication technology overall, the opportunity to connect via technology may be as simple as clicking a button to invite someone to use a particular application. It is also likely that when two people are connected using at least one form of technology (e.g., email) then the barrier to connect using other forms of technology is reduced significantly because (1) both people are already using communication technology in some way, and (2) they each have a direct address or other contact information for the other person on which to build additional access points. Similar to the relationship between where one lives and the frequency of in-person contact, there is a potential relationship between having some connection using technology and having frequent interactions using technology.
Findings from the current study did not provide support for complementing IGS with the concept of identification with family, which was not found as a distinguishing factor between classes. This finding might be considered surprising as it is reasonable to expect that one’s feelings of belonging and perceptions of family membership would be related to contact with family and feelings of closeness. However, it is notable that the average score for the identification with family variable was quite high for the entire sample, so it is possible that the operationalization of this indicator was not sufficiently sophisticated to capture variations in perceptions of family identity. Future research should examine how we define and measure family identity and how feelings of family membership and belonging intersect with the intergenerational solidarity dimensions.
Limitations and Strengths
While the current study has extended our understanding of emerging adults and their connectedness with extended family, it has limitations. These data were collected prior to the COVID-19 pandemic, which altered family communication patterns. The role of extended family in our lives is greatly influenced by culture; this study looks specifically at a U.S. sample and does not distinguish between sub-cultures or distinguish between immigrant communities with the U.S. Dichotomization of variables means that complexity in the original responses is lost. Also, utilizing a threshold of 50% of extended family to achieve high solidarity for the indicators used in the latent class analysis means that more nuanced variations of solidarity were not taken into consideration. Finally, communication technology is constantly changing and can be categorized in a number of different ways. The distinctions between technological devices and online environments is frequently shifting. For example, social media can facilitate indirect and passive communication, but also expedite instant messaging in real time. Researchers need to continue to explore how best to structure measures to capture the complexities of technology use while also maintaining a user-friendly experience for study participants.
In addition to these limitations, the current study has strengths. First, despite being predominantly white and female, analyses were conducted using a participant sample that includes both college-going and non-college-going youth in the U.S., which has been a critique of studies on youth in the past (Aquilino, 2006). While there has been no published research on differences specific to technology use with extended family members, some research has found that differences exist in family identity and in technology use with parents (Hessel & Dworkin, 2017). Second, the study design allowed participants themselves to identify which individuals should be categorized as “extended family,” rather than arbitrarily classifying extended family members based on their role. Finally, it reconceptualized IGS to better fit contemporary communication methods by separating in-person and online contact.
Conclusion
Findings from this study fill some of the gaps in our understanding of how U.S. youth are connecting with these family members and also points toward future research that could further our knowledge about the kinds of family relationships that help youth navigate the path to adulthood. Three key findings should be emphasized. First, participants reported having a family network that includes a diverse range of relationship roles, with the most frequent being cousin, parent, sibling, and aunt/uncle. Second, nearly three quarters of the participants who identified at least one extended family member as playing a role in their life are likely to be connecting with extended family using technology, even when they do not feel particularly close to them; contact using technology could be the means by which extended family members continue to play a role in the lives of emerging adults, especially when they are not seeing them frequently in-person. Finally, this study supports treating the Intergenerational Solidarity Theory concepts of structural and associational solidarity in-person as separate and distinct from structural and associational solidarity using technology, providing a foundation for future family communication research more closely aligned with contemporary methods of family communication.
Acknowledgements
This work was supported by the Minnesota Agricultural Experiment Station.
Data Availability
The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Conflict of interest
The author has no relevant financial or non-financial interests to disclose. The author has no competing interests to declare that are relevant to the content of this article. The author certifies that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The author has no financial or proprietary interests in any material discussed in this article.
Ethical Approval
The questionnaire and methodology for this study was approved by the Institutional Review Board of the University of Minnesota (STUDY00001904).
Informed Consent
Informed consent was obtained from all individual participants included in the study.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- Aquilino WS. Family relationships and support systems in emerging adulthood. In: Arnett JJ, Tanner JL, editors. Emerging adults in America: Coming of age in the 21st century. American Psychological Association; 2006. pp. 193–217. [Google Scholar]
- Arnett JJ. Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist. 2000;55(5):469–480. doi: 10.1037//0003-066X.55.5.469. [DOI] [PubMed] [Google Scholar]
- Arnett JJ. Emerging adulthood: The winding road from the late teens through the twenties. 2. Oxford University Press; 2015. [Google Scholar]
- Bai GJ, Leon SC, Garbarino J, Fuller AK. The protective effect of kinship involvement on the adjustment of youth in foster care. Child Maltreatment. 2016;21(4):288–297. doi: 10.1177/1077559516669043. [DOI] [PubMed] [Google Scholar]
- Bengtson VL, Biblarz TJ, Roberts RE. How families still matter: A longitudinal study of youth in two generations. Cambridge University Press; 2002. [Google Scholar]
- Bengtson, V. L., & Oyama, P. S. (2007). Intergenerational solidarity and conflict. In Intergenerational solidarity: Strengthening economic and social ties. United Nations. Retrieved April 24, 2022 from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.476.6909&rep=rep1&type=pdf
- Bengtson VL, Roberts REL. Intergenerational solidarity in aging families: An example of formal theory construction. Journal of Marriage and Family. 1991;53(4):856–870. doi: 10.2307/352993. [DOI] [Google Scholar]
- Benson J, Furstenberg FF. Entry into adulthood: Are adult role transitions meaningful markers of adult identity. In: MacMillan R, editor. Constructing adulthood: Agency and subjectivity in the life course. Elsevier Science; 2007. pp. 199–224. [Google Scholar]
- Bernardi L. A mixed-methods social networks study design for research on transnational families. Journal of Marriage and Family. 2011;73(4):788–803. doi: 10.1111/j.1741-3737.2011.00845.x. [DOI] [Google Scholar]
- Brown R, Condor S, Mathews A, Wade G, Williams J. Explaining intergroup differentiation in an industrial organization. Journal of Occupational Psychology. 1986;59:273–286. doi: 10.1111/j.2044-8325.1986.tb00230.x. [DOI] [Google Scholar]
- Chen Y-F, Katz JE. Extending family to school life: College students’ use of the mobile phone. International Journal of Human-Computer Studies. 2009;67(2):179–191. doi: 10.1016/j.ijhcs.2008.09.002. [DOI] [Google Scholar]
- Cheng YP, Birditt KS, Zarit SH, Fingerman KL. Young adults’ provision of support to middle-aged parents. Journals of Gerontology Series B Psychological Sciences and Social Sciences. 2015;70(3):407–416. doi: 10.1093/geronb/gbt108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Claes M, Lacourse E, Bouchard C, Luckow D. Adolescents’ relationships with members of the extended family and non-related adults in four countries: Canada, France, Belgium and Italy. International Journal of Adolescence and Youth. 2001;9(2–3):207–225. doi: 10.1080/02673843.2001.9747877. [DOI] [Google Scholar]
- Colaner C, Elkhalid A, Butauski M, Bish A, Nelson L, Rick J. Communicatively constructing godparenthood: Relational maintenance and relational closeness. Journal of Family Communication. 2021;21(2):107–117. doi: 10.1080/15267431.2021.1903901. [DOI] [Google Scholar]
- Collins LM, Lanza ST. Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. Wiley; 2010. [Google Scholar]
- Copp JE, Giordano PC, Longmore MA, Manning WD. Living with parents and emerging adults' depressive symptoms. Journal of Family Issues. 2017;38(16):2254–2276. doi: 10.1177/0192513X15617797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ellingson LL, Sotirin PJ. Aunting: Cultural practices that sustain family and community life. Baylor University Press; 2010. [Google Scholar]
- Fingerman KL, Sechrist J, Birditt K. Changing views on intergenerational ties. Gerontology. 2012;59(1):64–70. doi: 10.1159/000342211. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Geiser C. Data analysis wtih Mplus. The Guilford Press; 2013. [Google Scholar]
- Geurts T, van Tilburg T. Grandparent-grandchild relationships. In: Wright JD, editor. International Encyclopedia of the Social & Behavioral Sciences. 2. Elsevier; 2015. pp. 336–340. [Google Scholar]
- Giarrusso R, Feng D, Bengtson VL. The intergenerational stake phenomenon over 20 years. Annual Review of Gerontology & Geriatrics. 2004;24(1):55–76. doi: 10.1891/0198-8794.24.1.55. [DOI] [Google Scholar]
- Grafsky L, Hickey K, Nguyen HN, Wall JD. Youth disclosure of sexual orientation to siblings and extended family. Family Relations. 2018;67:147–160. doi: 10.1111/fare.12299. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gronvold R. Measuring affectual solidarity. In: Mangen D, Bengtson V, Landry P, editors. Measurement of intergenerational relations. Sage; 1988. pp. 74–97. [Google Scholar]
- Guo M, Chi I, Silverstein M. The structure of intergenerational relations in rural China: A latent class analysis. Journal of Marriage and Family. 2012;74(5):1114–1128. doi: 10.1111/j.1741-3737.2012.01014.x. [DOI] [Google Scholar]
- Haythornthwaite C. Social networks and internet connectivity effects. Information Communication and Society. 2005;8(2):125–147. doi: 10.1080/13691180500146185. [DOI] [Google Scholar]
- Hessel, H., & Dworkin, J. (2017, November). Different paths: Comparing college-going and noncollege youth. Poster presented at the National Council on Family Relations, Orlando.
- Katsiaficas D. “I know I’m an adult when … I can care for myself and others”: The role of social responsibilities in emerging adulthood for community college students. Emerging Adulthood. 2017;5(6):392–405. doi: 10.1177/2167696817698301. [DOI] [Google Scholar]
- Langer N, Ribarich M. Aunts, uncles-nieces, nephews: Kinship relations over the lifespan. Educational Gerontology. 2007;33(1):75–83. doi: 10.1080/03601270600894279. [DOI] [Google Scholar]
- Masyn KE. Latent class analysis and finite mixture modeling. In: Little TD, editor. The Oxford handbook of quantitative methods (1st edition) Oxford University Press; 2013. p. 551. [Google Scholar]
- Michałek-Kwiecień J. The mentoring relationship with the closest grandparent and identity processes among emerging adult grandchildren in Poland: The role of perceived grandparents’ perspective taking. Journal of Adult Development. 2022 doi: 10.1007/s10804-022-09429-0. [DOI] [Google Scholar]
- Milardo RM. The forgotten kin: Aunts and uncles. Cambridge University Press; 2010. [Google Scholar]
- Mills TL, Wakeman MA, Fea CB. Adult grandchildren’s perceptions of emotional closeness and consensus with their maternal and paternal grandparents. Journal of Family Issues. 2001;22(4):427–455. doi: 10.1177/019251301022004003. [DOI] [Google Scholar]
- Oliver V, Cheff R. The social network: Homeless young women, social capital, and the health implications of belonging outside the nuclear family. Youth & Society. 2014;46(5):642–662. doi: 10.1177/0044118X12448801. [DOI] [Google Scholar]
- Parra A, Oliva A, del Reina MC. Family relationships from adolescence to emerging adulthood: A longitudinal study. Journal of Family Issues. 2015;36(14):2002–2020. doi: 10.1177/0192513X13507570. [DOI] [Google Scholar]
- Peer E, Vosgerau J, Acquisti A. Reputation as a sufficient condition for data quality on Amazon mechanical Turk. Behavior Research Methods. 2014;46(4):1023–1031. doi: 10.3758/s13428-013-0434-y. [DOI] [PubMed] [Google Scholar]
- Pew Research Center. (1999). The Internet news audience goes ordinary. Retrieved April 24, 2022 from: http://people-press.org/report/72/the-internet-news-audience-goes-ordinary
- Pew Research Center. (n.d.). Mobile fact sheet. Retrieved April 24, 2022 from: http://www.pewinternet.org/fact-sheet/mobile/
- Pew Research Center. (n.d.). Internet/Broadband fact sheet. Retrieved April 24, 2022a from: http://www.pewinternet.org/fact-sheet/internet-broadband/
- Pew Research Center. (n.d.). Social media fact sheet. Retrieved April 24, 2022b from: http://www.pewinternet.org/fact-sheet/social-media/
- Rempusheski VF, Haigh KM, Davidson LM. College students’ perceptions of their grandparents and communication technology use. Journal of Intergenerational Relationships. 2012;10:370–385. doi: 10.1080/15350770.2012.726600. [DOI] [Google Scholar]
- Riley MW, Riley JW. Connections: Kin and cohort. In: Bengtson VL, Achenbaum WA, editors. The changing contract across generations. Aldine De Gruyter; 1993. pp. 169–189. [Google Scholar]
- Sieving RE, McRee A, McMorris BJ, Shlafer RJ, Gower AL, Kapa HM, Beckman KJ, Doty JL, Plowman SL, Resnick MD. Youth-adult connectedness: A key protective factor for adolescent health. American Journal of Preventive Medicine. 2017;52(3S3):S275–S278. doi: 10.1016/j.amepre.2016.07.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Silverstein M, Bengtson VL. Intergenerational solidarity and the structure of adult child-parent relationships in American families. American Journal of Sociology. 1997;103(2):429–460. doi: 10.1086/231213. [DOI] [Google Scholar]
- Silverstein M, Gans D, Lowenstein A, Giarrusso R, Bengtson VL. Older parent-child relationships in six developed nations: Comparisons at the intersection of affection and conflict. Journal of Marriage and Family. 2010;72:1006–1021. doi: 10.1111/j.1741-3737.2010.00745.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Stephenson-Abetz J, Holman A. Home is where the heart is: Facebook and the negotiation of “old” and “new” during the transition to college. Western Journal of Communication. 2012;76(2):175–193. doi: 10.1080/10570314.2011.654309. [DOI] [Google Scholar]
- Tajfel H, Turner J. An integrative theory of intergroup conflict. In: Austin WG, Worchel S, editors. The social psychology of intergroup relations. Brooks-Cole; 1979. pp. 33–47. [Google Scholar]
- Tariq A, Saez DM, Khan SR. Social media use and family connectedness: A systematic review of quantitative literature. New Media & Society. 2021;24(3):814–832. doi: 10.1177/14614448211016885. [DOI] [Google Scholar]
- Tsai KM, Telzer EH, Fuligni AJ. Continuity and discontinuity in perceptions of family relationships from adolescence to young adulthood. Child Development. 2013;84(2):471–484. doi: 10.1111/j.1467-8624.2012.01858.x. [DOI] [PubMed] [Google Scholar]
- Turner A. Generation Z: Technology and social interest. Journal of Individual Psychology. 2015;71(2):103–113. doi: 10.1353/jip.2015.0021. [DOI] [Google Scholar]
- van der Pers M, Mulder CH, Steverink N. Geographic proximity of adult children and the well-being of older persons. Research on Aging. 2015;37(5):524–551. doi: 10.1177/0164027514545482. [DOI] [PubMed] [Google Scholar]
- Vogt KC. The extended family in transitions to adulthood: A dynamic approach. Journal of Youth Studies. 2020;23(9):1234–1248. doi: 10.1080/13676261.2019.1663799. [DOI] [Google Scholar]
- Widmer ED. Family configurations: A structural approach to family diversity. Ashgate; 2010. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.