A systematic review and narrative synthesis of the relationship between social support and binge drinking among adolescents and emerging adults

Citation: Villar, E.; Martínez-López, Z.; Mayo, M.E.; Braña, T.; Rodríguez, M.; Tinajero, C. A Systematic Review and Narrative Synthesis of the Relationship between Social Support and Binge Drinking among Adolescents and Emerging Adults. Youth 2022,2, 570–586. https:// doi.org/10.3390/youth2040041 Academic Editors: Diego Gomez-Baya, Nora Wiium, Denisse Manrique-Millones and Margarida Gaspar de Matos Received: 20 September 2022 Accepted: 27 October 2022 Published: 2 November 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Systematic Review A Systematic Review and Narrative Synthesis of the Relationship between Social Support and Binge Drinking among Adolescents and Emerging Adults Eva Villar 1,* , Zeltia Martínez-López 1, M. Emma Mayo 1, Teresa Braña 2, Mauro Rodríguez 2 and Carolina Tinajero 1 1 Department of Developmental and Educational Psychology, Faculty of Psychology, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain 2Department of Social Psychology, Basic Psychology and Methodology, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain *Correspondence: evavillar[email protected] Abstract: Binge drinking (BD) is a high-risk pattern of alcohol consumption that is remarkably prevalent among teenagers and emerging adults. This pattern is thought to alter social networks, affecting access to social support (SS), which is considered essential for adjustment during transitional periods and may in turn play a proactive role against risk behaviors. In this review, we aim to synthesize the available data on the relationship between BD and SS in teenagers and emerging adults. Therefore, a search on three electronic databases was conducted (Web of Science, PsycInfo and PubMed). Articles were screened using eligibility criteria in line with the investigation question and the methodological quality of the studies were reported. Data were analyzed using a narrative synthesis approach. Cross-sectional and longitudinal data suggested that SS is associated with the onset, frequency, and intensity of BD; this relation varies with age, gender, and source of support (family or peers). From developmental and socio-cognitive points of view, the following conclusions were reached: (a) effects beyond the detrimental consequences of BD must be considered in order to interpret the data, and (b) social support should be taken into consideration in intervention strategies. Keywords: binge drinking; personal social network; individual social capital; social support; adolescence; emerging adulthood 1. Introduction The consumption of alcohol and other drugs is a major challenge in many countries due to the impact on individual health and well-being [ 1 ]. In particular, binge drinking (BD) has received much attention as it is considered a high-risk pattern of alcohol consumption [ 2 , 3 ]. BD is defined as the intake of four or more drinks in women (five or more drinks in men) within approximately two hours, at least once during the previous month, leading to a blood alcohol concentration of at least 0.08 g/dL [4,5]. The currently available data indicate a high prevalence of this drinking pattern, particularly among adolescents (12 to 18 years old) and emerging adults (18 to 25 years old). In a survey conducted in the USA, 34.3% of emerging adults reported BD in the previous month [ 6 ]. In European countries, one out of three youngsters aged 15 to 24 years reported frequent BD (at least once a week) in the previous year [ 7 ]. Despite BD being traditionally more prevalent among males, recent reports suggest that this gender difference may be fading [ 8 ]. In fact, BD is nowadays recognized as a normative rite of passage for adolescents and emerging adults in general [9]. Various consequences of BD in adolescents and emerging adults, both at the individual level and in interpersonal relationships, have been identified [ 3 , 10 , 11 ], and the BD pattern of alcohol consumption is thought to have more severe outcomes than regular Youth 2022,2, 570–586. https://doi.org/10.3390/youth2040041 https://www.mdpi.com/journal/youth Youth 2022,2571 consumption [ 12 ]. Furthermore, an early onset age is considered a risk factor for long term consequences and has been associated with a higher probability of developing a substance use disorder in adulthood [13]. The outcomes most frequently experienced by binge drinkers pertain to the social domain [ 14 – 16 ]. Some issues typically considered within this category include neglected obligations, disruption of family relationships, and regretting something that has been said or done [ 3 , 12 , 17 ]. As these consequences are considered inherently interactive, they are likely to alter personal social networks, affecting role performance and perceived access to social support (SS) [ 18 ] and, in turn, negatively affecting the protective role of SS in regard to unhealthy behavior, particularly alcohol consumption. 1.1. Social Support as Derived from Personal Social Networks Social networks are defined as a set of social relationships in which the members maintain stable interactions [ 19 ]. The functionality of these networks (e.g., regulation and control of behavior) will be conditioned by structural (e.g., density, homogeneity) and interactional (e.g., level of integration, frequency of contact or reciprocity) properties, as well as by certain personal characteristics (e.g., gender, age, socioeconomic status) [ 20 – 22 ]. A sub-network of significant others, denominated the personal social network, is usually distinguished, as the presence of this group is expected to enhance health and well-being. Sub-networks involving different types of relationships (e.g., family or friends) have also been independently examined [19]. Individual social capital comprises the set of rules, norms, obligations, relationships of reciprocity and trust, social structures and institutional services that members of a social network can access [ 23 , 24 ] and through which these social networks are expanded [ 22 ]. These resources, which vary depending on the relationship (e.g., family, school), enable network members to achieve various communal and personal goals [ 25 ] and impact their development, health and well-being [26,27]. SS is one of the main derivations of individual social capital [ 28 ]. It has been conceived as the perception or experience of resources provided by others, leading to the sense that one is esteemed, valued and forms part of a social network of mutual assistance [ 29 ]. The term thus encompasses two different psychosocial dimensions: a behavioral dimension (supportive actions provided or received) and a cognitive dimension (perceived availability of support) [ 30 ]. Perceived SS has been assessed from both a global perspective (in terms of general availability and satisfaction with support) [ 31 ], by considering its functionality (i.e., specific provisions, such as emotional, social integration or esteem support) [ 32 ] and by taking into account its relational base (regarding different sources, such as family or friends, who provide, or could provide, support) [ 33 ]. This theoretical framework is depicted in Figure 1. 1.2. Social Support during Adolescence and Emerging Adulthood The size and composition of personal social network vary throughout the lifetime of an individual and have been considered, from a developmental perspective, in relation to the prominence of certain personal goals and normative life events [ 19 ]. Thus, during adolescence and emerging adulthood, the number and diversity of social relationships usually increases; the time spent and the frequency of interactions with the family diminish, while time shared with peers increases [ 34 , 35 ]. During this period, gathering knowledge and information becomes a salient goal, and transitional changes are experienced (physical maturation, establishing autonomy and personal identity, dealing with new responsibilities and demands). All of these changes are potential opportunities to acquire new attributes and abilities, but can also be threats to well-being, making individuals more susceptible to engage in risk behaviors such as BD [36]. Youth 2022,2572 Youth 2022, 2, FOR PEER REVIEW 3 Figure 1. Theoretical Relationship Between the Targeted Variables. 1.2. Social Support during Adolescence and Emerging Adulthood The size and composition of personal social network vary throughout the lifetime of an individual and have been considered, from a developmental perspective, in relation to the prominence of certain personal goals and normative life events [19]. Thus, during adolescence and emerging adulthood, the number and diversity of social relationships usually increases; the time spent and the frequency of interactions with the family diminish, while time shared with peers increases [34,35]. During this period, gathering knowledge and information becomes a salient goal, and transitional changes are experienced (physical maturation, establishing autonomy and personal identity, dealing with new responsibilities and demands). All of these changes are potential opportunities to acquire new attributes and abilities, but can also be threats to well-being, making individuals more susceptible to engage in risk behaviors such as BD [36]. SS plays an essential role in adjustment during transitional periods of development. It is thought to act by enhancing one’s sense of belonging, self-worth and security, as well as by moderating the appraisal of situations as threatening and also increasing self-confidence to cope with such situations [20,37]. During adolescence and emerging adulthood, a change in the preponderance of the main sources of support is generally observed. The incidence of family support decreases, due to the increased autonomy and independence of young adults [38]. The opposite pattern is observed regarding the relationship with peers, which has greater influence during adolescence and declines towards the end of emerging adulthood [39], mainly through processes of peer selection and socialization [40]. On the other hand, women have been shown to receive and demand more SS than their male counterparts [41]. Social relationships are considered key factors in modulating alcohol consumption during adolescence and emerging adulthood, representing a focal point for research in the field of health [42–45]. In recent years, the protective role of SS has drawn the attention of researchers [46]. Conversely, as previously mentioned, personal social network can also be affected by drinking behavior, suggesting a reciprocal influence between consumption and SS [18]. The present review aims to offer a comprehensive vision of the data and interpretations currently available regarding the bidirectional relationship between SS and BD. Hence, the following objectives were established: Figure 1. Theoretical Relationship Between the Targeted Variables. SS plays an essential role in adjustment during transitional periods of development. It is thought to act by enhancing one’s sense of belonging, self-worth and security, as well as by moderating the appraisal of situations as threatening and also increasing self-confidence to cope with such situations [ 20 , 37 ]. During adolescence and emerging adulthood, a change in the preponderance of the main sources of support is generally observed. The incidence of family support decreases, due to the increased autonomy and independence of young adults [ 38 ]. The opposite pattern is observed regarding the relationship with peers, which has greater influence during adolescence and declines towards the end of emerging adulthood [ 39 ], mainly through processes of peer selection and socialization [ 40 ]. On the other hand, women have been shown to receive and demand more SS than their male counterparts [41]. Social relationships are considered key factors in modulating alcohol consumption during adolescence and emerging adulthood, representing a focal point for research in the field of health [ 42 – 45 ]. In recent years, the protective role of SS has drawn the attention of researchers [ 46 ]. Conversely, as previously mentioned, personal social network can also be affected by drinking behavior, suggesting a reciprocal influence between consumption and SS [ 18 ]. The present review aims to offer a comprehensive vision of the data and interpretations currently available regarding the bidirectional relationship between SS and BD. Hence, the following objectives were established: (I) to explore the relationships between SS and BD, and (II) to analyze whether the aforesaid relationships (when identified) vary depending on the type of social bonds (family, peers) and the developmental stage. 2. Materials and Methods This systematic review followed the Preferred Reporting items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 47 ]. The Web of Science (WoS), PsycInfo and PubMed databases were consulted, through the advanced search option in the fields “All fields” and/or “Topic” (in “all databases” in the WoS). The original search was performed between November and December 2019, and it was regularly updated through search alerts created in the databases. No time frame was included in the search, in order to capture studies ranging from early theoretical elaborations and empirical research to the most recent contributions. This approach is also consistent with the fact that BD is a recent phenomenon, defined at the beginning of the century [4]. The search expressions used-[“Binge Drinking” OR “Heavy Episodic Drinking”] AND “Social Support”-yielded the following number of hits in each database: 244 in the WoS, 144 in PsycInfo, and 132 in PubMed. The initial total was 522, but 289 entries were finally retained after duplicates were removed. The titles and abstracts of the 289 entries Youth 2022,2573 were read, and documents were preselected according to the inclusion/exclusion criteria listed in Table 1. In this regard, the listed exclusion criteria were established in order to stablish the generalizability of our findings, which led us to discard 99 documents. In total, 68 documents were preselected and read in full before being included in or excluded from the final review. Although the focus of the present review was the relationship between SS and BD, studies involving the relationships between both the personal social network and individual social capital and BD were retained, as they may be valuable for interpreting the relationship(s) being explored. No studies on received SS were found. Two team members independently and blindly screened, preselected and then finally selected the documents. Inter-rater reliability, measured using Cohen’s Kappa coefficient, was intermediate (k = 0.56) during the preselection stage and high (k = 0.75) during the selection stage. All disagreements during the pre-selection and selection phases were resolved through discussion, and consensus was reached by all authors of the review. Table 1. Eligibility Criteria for the Screening of Documents. Inclusion Criteria Exclusion Criteria The BD-SS relation must be addressed in the document. The sample should consist of adolescents (12 to 18 years old) and/or emerging adults (18 to 25 years old). The articles must be written in English, Spanish, French or Portuguese. Participants with any psychiatric or physical diagnosis. Population under difficult circumstances (violence, pregnancy, COVID-19, etc.). The methodological quality was assessed using a template created as a synthesis of the Joanna Briggs Institute Critical Appraisal Tool for Qualitative Research and for Crosssectional Studies [ 48 , 49 ], as well as the NIH Quality Assessment Tool for Observational Cohort and Cross-sectional Studies [ 50 ]. The studies were categorized as intermediate (44%), high (28%) and low quality (28%). The main study limitations were the lack of control of potential confounding variables and failure to obtain representative samples. Finally, 26 documents (25 empirical studies, 1 critical review [ 18 ]) that met the eligibility criteria were selected after detailed, critical screening. After a manual search process, 1 article was added to the list. This process is depicted in a flow diagram (Figure 2). In the final phase (data extraction), according to the PRISMA guidelines, the main empirical results were summarized in a table. To this end, a matrix was created with the following variables: authors, publication year, quality of the study, measures, and results (see Table 2in Results section). The possibility of performing a meta-analysis was considered, yet the characteristics of the studies included in the systematic review did not allow us to do it. Therefore, a narrative synthesis was used, to gather the information on the findings and designs of the reviewed studies. Theoretical contributions were also synthetized and integrated in the text. The whole process was conducted using the Covidence systematic review software (https://www.covidence.org/, accessed on 28 October 2022), the screening and information selection tool selected by Cochrane as the standard production platform for Cochrane Reviews. The complete protocol was registered at PROSPERO (CRD42020184639). Youth 2022,2574 Youth 2022, 2, FOR PEER REVIEW 5 Figure 2. Flow Diagram of the Preselection and Selection Phases. In the final phase (data extraction), according to the PRISMA guidelines, the main empirical results were summarized in a table. To this end, a matrix was created with the following variables: authors, publication year, quality of the study, measures, and results (see Table 2 in Results section). The possibility of performing a meta-analysis was considered, yet the characteristics of the studies included in the systematic review did not allow us to do it. Therefore, a narrative synthesis was used, to gather the information on the findings and designs of the reviewed studies. Theoretical contributions were also synthetized and integrated in the text. The whole process was conducted using the Covidence systematic review software (https://www.covidence.org/, accessed on 28 October 2022), the screening and information selection tool selected by Cochrane as the standard production platform for Cochrane Reviews. The complete protocol was registered at PROSPERO (CRD42020184639). 3. Results Here we provide a brief description of the studies analyzed (see details in Table 2). Most (62%) of the documents were published after 2010 and, of these, 25% were published in the last five years (2016-21). Only 11% of the articles were published before 2004 and none were published before 2000, reflecting the recent and increasing interest in the topic. Figure 2. Flow Diagram of the Preselection and Selection Phases. 3. Results Here we provide a brief description of the studies analyzed (see details in Table 2). Most (62%) of the documents were published after 2010 and, of these, 25% were published in the last five years (2016-21). Only 11% of the articles were published before 2004 and none were published before 2000, reflecting the recent and increasing interest in the topic. This trend is particularly notable in the US, where most of the studies were performed (55%). 3.1. Measures Regarding how the variables of interest for this review were evaluated, most of the studies (85%) used a single item reflecting both frequency and quantity of drinks or two items (e.g., “On average, how many days per week do you drink alcohol?” and “On a typical day when you drink, on average, how many drinks do you have?”) combined in an index in order to identify BD. The AUDIT-C [ 51 ] and the Time-Line Follow Back (TLFB) [ 52 ] were the standardized measures used to detect BD. The time frame during which BD was evaluated ranged from 1 week and lifetime, with “the last 30 days” being the most frequent interval (30%). Studies that applied a wider time window (e.g., last year, lifetime) mainly focused on adolescence, a developmental stage during which BD is less frequent than in Youth 2022,2575 emerging adulthood. As for the differentiation of cut-off points in males and females, they were only considered in 40% of the studies included in the present review. Personal social network and individual social capital were measured through diverse indexes, such as network composition and individual popularity. Finally, among those studies addressing perceived SS, more than half used a variable number of ad hoc items (between 1 and 5) to measure participants’ appraisals of global availability of support (e.g., “How much do you feel that your parents care about you”? or “How easy or difficult is it to get help from friends if you need it”?). The Multidimensional Scale of Perceived Social Support (MSPSS) [ 53 ] was the most commonly used scale in those studies that used standardized measures. The MSPSS is a 12-item instrument that measures perceived availability of SS from different sources (e.g., family, friends, and significant other). The other instruments used in the different studies identified aspects such as perceived availability of diverse provisions (e.g., emotional, social integration or esteem support) [54–56] and sources [57] of support and/or satisfaction with the support [58,59]. All the studies reviewed focused on the possible protective role of SS against BD. The findings of the various studies are presented below. The studies were generally organized in relation to the type of approach to SS (personal social network, individual social capital and perceived SS), developmental stage and sources of support (teacher, family and peers). 3.2. BD and Personal Social Networks Regarding research on the relationship between BD and personal social network, five studies were identified; all of these reported statistically significant relationships between different network properties and BD both in adolescents and in emerging adults. In particular, in adolescents, the number of groups of friends was associated with a greater likelihood of participation in BD [ 60 ], while mainly male composition of personal social network was associated with a higher frequency of BD, especially among boys [61]. During emerging adulthood, belonging to a social network that includes peers considered drinking buddies increases the risk of BD, and a high incidence of BD in the network has been shown to be a significant predictor of individual BD frequency [ 62 ]. Furthermore, Lorant & Nicaise (2015) [ 63 ] computed the effective size of university students’ personal networks as an index of social capital (number of alters minus average number of ties of each contact to other contacts) and found that it negatively predicted BD frequency in emerging adults; the same result was obtained for gender heterophily (i.e., cross-gender relationships), while popularity positively predicted BD. Special consideration should be given to the research conducted by Hahm et al. (2012) [ 64 ], who carried out a longitudinal study in which a sample was tracked from adolescence to emerging adulthood. Low levels of heterogeneity of the personal network (proportion of friends who were not in the same school or grade) and the presence of alcohol-using peers led to a higher frequency of BD during adolescence, although this effect decreased throughout the study period. The opposite trend was observed for popularity, which had an increasingly important impact on BD and was particularly relevant during emerging adulthood. 3.3. BD and Individual Social Capital We identified two articles addressing the relationship between individual social capital and BD. One of these explored the aforementioned relationship in adolescents [ 65 ], measuring both trust in people and community participation, but did not obtain significant results. However, Weitzman and Chen (2005) [ 66 ] found significant associations between BD and other indexes of individual social capital for emerging adults. Thus, these authors reported that as the level of individual social capital increased (e.g., time spent volunteering), the probability of university students participating in BD decreased. In addition, individual social capital was found to be a significant predictor of the onset of a binge-drinking pattern in first-year students and BD frequency throughout the university period. Youth 2022,2576 3.4. BD and Perceived Social Support Finally, perceived SS was measured globally in three of the studies identified [58,67,68] ; none of these reported any significant relationship between perceived SS and BD. Indeed, neither perceived availability nor satisfaction with SS were significant predictors of BD [58,68]. Several studies have specifically explored the relationship between BD and perceived SS from family during adolescence. Five of these [ 56 , 69 – 72 ] reported a significant and negative relationship, so that high/moderate levels of familiar support were associated with lower probability of and/or frequency of BD. Of special mention is the study by Wiley (2014) [ 56 ], in which perceived parental closeness (i.e., support provision of social integration) was specifically measured and different BD trajectories were established in a sample of adolescents (between 15 and 18 years old). Measurement of the level of social integration differentiated participants who reported infrequent BD (with higher levels of SS) from those who either maintained a constant moderate level of BD or developed a more frequent consumption. The lack of statistical significance in the relationship between family support and BD observed in the remaining two studies with samples of adolescents [ 57 , 59 ] may be due to the mean age of the study participants (17 and 16.6 years old, respectively), which was higher than in the previously mentioned studies. Indeed, in a study following a sample from adolescence to emerging adulthood, Aseltine and Gore (2000) [ 69 ] found an interaction between age and perceived support, in relation to BD frequency. This pattern is consistent with the results of the five identified studies with samples of emerging adults [ 55 , 73 – 76 ]. These studies examined the relationship between family support and BD intensity and/or frequency, and the relationship was not found to be statistically significant in any of them. Regarding perceived SS from peers, four studies reported a positive and significant relationship between this dimension and BD as globally evaluated, in both high school students [ 69 ] and university students [ 77 , 78 ]. This relationship can also be recognized in the research regarding specific support provisions, as in the study by Czyzewska & McKenzie (2016) [ 54 ], which evaluated emotional support from peers. In a study focused on perceived esteem, Tinajero et al. (2019) [ 55 ] noted a curvilineal relationship between this dimension and BD frequency, with an increase in acceptance linked to increasing rates of consumption, followed by a stable level of acceptance at intermediate levels of BD, and a subsequent decline. Table 2. Synthesis of Characteristics and Key Findings of Included Studies. Authors Sample Characteristics Measures/Intervention Findings Personal social network Reifman et al. (2006) [62]1 Wave 1/3: 274 first-year university students (63.5% women) from US. Wave 3/3 (1 year later): 43% of the original sample (73.9% women). Social network: network drinking (1 item), drinking buddies (1 item) BD (2 items): number of binge-drinking episodes (4+/5+ drinks) during the past two weeks. Percentage of drinking buddies in Wave 1 predicted own alcohol misuse at Wave 2. High average levels of network BD were a significant predictor of individuals’ BD Hahm et al. (2012) [64]2 7966 adolescents (11–18 years; 54% women females) from US. Followed for 7 years (3 waves). Social Network: heterogeneity (2 items), popularity (Bonacich centrality) and density (reciprocity in the nomination). Alcohol using peers (1 item) BD (1 item): frequency of consumption of 5+drinks in a row over the past 12 months. Lower group heterogeneity and socialization with alcohol using peers were associated with higher frequency of BD at Wave 1. This effect decreased over time. High popularity had a significant effect on the frequency of BD, that grew over time. Density had no association with BD. Youth 2022,2577 Table 2. Cont. Authors Sample Characteristics Measures/Intervention Findings Zarzar et al. (2012) [60]1 891 adolescents in Brazil (15–19 years, 59% women). Social network: “Groups and networks” domain of the Integrated Questionnaire for the Measurement of Social Capital (friendship network characteristics and number of groups of friends) a. BD: AUDIT-C (frequency of consumption of 5+ drinks on one occasion) b. Women who valued school friends more than those from hobbies were less likely to report BD. Women who valued school friends less than those from church were less likely to report BD. Female students who reported that the most important group of friends were from school (as opposed to friends from church) had higher odds of BD. Male students with more than 2 groups of friends were more likely to report BD. Lorant & Nicaise (2015) [63]2 478 first-year college students of Psychology (n = 253) and engineering (n = 234) from Belgium. Social network: popularity, gender-heterophily (Krackhardt E-I index), and heterogeneity. BD (1 item): frequency of consumption of 6+ drinks in the previous year. High popularity was associated with higher binge-drinking frequency. High levels of network heterogeneity and cross-gender relationships negatively predicted BD. Grard et al. (2018) [61]2 10,932 adolescents (between 14 and 16 years old) from six European cities. Social Network: Coleman index (same sex/other sex friendships) and school gender balance. BD (1 dichotomous item): frequency of occasions of 5+drinks (at least two) in the last month. Boys and girls in male-majority schools were more frequent binge drinkers. Other-sex friendship was associated with more BD among girls. Individual social capital Lundborg (2005) [65]2 1346 adolescents (between 12 and 18 years old) from Sweden. Social capital: trust (1 dichotomous item) and community participation (10 items). BD (1 dichotomous item): intake of 4+ drinks during the past month. Neither trust nor social participation predicted the probability of BD. Weitzman & Chen (2005) [66]1 27,687 college students (18–24 years, 53.44% women) from US. Social capital: average daily time committed to volunteering in the past 30 days. BD (1 item): frequency of consumption of 4+/5+ drinks in the past two weeks. Students with higher social capital showed lower odds of BD. Individual social capital negatively predicted uptake BD among freshman and frequency of BD in college. Social Support Aseltine &Gore (2000) [69]1 Wave 1/5: 1208 adolescents (from 14 to 16 years old, 57% women) from US. Wave 5/5 (9 years later): 69% of the original sample (from 22 to 25 years). Perceived SS from family (3 items) and friends (2 items) from the Perceived Social Support Scale c. BD (1 item): frequency of occasions of 5+ drinks on one occasion, during the last week/month. Statistically significant and negative effect of PSS from parents on BD. This effect decreased over time. PSS from friends was positively associated with BD. Youth 2022,2578 Table 2. Cont. Authors Sample Characteristics Measures/Intervention Findings Von Ah et al. (2004) [68]3 161 college students (mean age = 19.7; 73,3% women) from US. Perceived availability of and satisfaction with SS: Social Support Questionnaire d. BD (1 item): frequency of consumption of 5+ drinks in the last 30 days and 6 months. PSS (availability/satisfaction) did not predict frequency of BD. Windle (2004) [57]3 1049 adolescents (mean age = 17.3, 51.9% women) from US. Perceived SS from Family: Perceived Social Support Scale c. BD (1 item): frequency of consumption of 6+ drinks over the past 6 months Perceived SS from family did not predict BD. Springer et al. (2006) [71]2 930 adolescents (mean age = 15, 48% women) from El Salvador. Perceived SS from parents: 7 items based on the Multidimensional Scale of Perceived Social Support e. BD (1 dichotomous item): intake of 5+ drinks in the past 30 days. For women, PSS from parents was a predictor of BD: low levels in this index multiplied by 3 the chances of BD. Ichiyama et al. (2009) [73]1 863 first-year college students (between 18 and 19 years old, 63% women) from the US. 347 included in an intervention program. Parent Based Intervention designed to increase parental support. BD (1 item): frequency of consumption of 4+/5+ drinks on one occasion, during the last two weeks. There was no significant intervention effect. Piko & Kovács (2010) [59]2 881 adolescents (mean age = 16.6, 46% women) from Hungary. Perceived SS from mother and father: Measures of Perceived Social Support f. BD (1 item): frequency of consumption of 5+ drinks on one occasion in the past three months. Perceived parental support did not predict BD. Pearson & Wilkinson (2013) [70]3 13,140 adolescents (mean age = 15.9, 53.1% women) from US. Perceived SS from family (5 items). BD (1 dichotomous item): intake of 5+ drinks during the previous year. Perceived family support predicted BD. Schwinn & Schinke (2014) [75]2 400 young adults (mean age = 17.3, 54% women) from US. Perceived SS from family: Multidimensional Scale of Perceived Social Support e. BD (1 item): frequency of consumption of 5+ + drinks on one occasion for the past 30 days. PSS from family did not predict BD. Zhao (2013) [76]1 140 graduate students (mean age = 27.61, SD=5.76, 73% women) from US. Perceived SS from family, friends and significant other: Multidimensional Scale of Perceived Social Support e. BD (2 items): frequency of consumption of 5+ drinks at least once in the previous year. PSS was not correlated with BD. PSS was not a predictor of the type of drinker (abstainers, social drinkers, moderate drinkers, binge drinkers, and problematic drinkers). Youth 2022,2585 55. Tinajero, C.; Cadaveira, F.; Rodríguez, M.S.; Páramo, M.F. Perceived social support from significant others among binge drinking and polyconsuming Spanish university students. Int. J. Environ. Res. Public Health 2019,16, 4506. [CrossRef] [PubMed] 56. Wiley, L.C. Alcohol Use Trajectories & the Transition from Adolescence into Young Adulthood: An Examination of Crime, Sex, and Gender. Ph.D. Thesis, OhioLINK Electronic Theses and Dissertations Center, Akron, OH, USA, 2014. Available online: https://etd.ohiolink.edu/rws_etd/send_file/send?accession=akron1395770516&disposition=attachment (accessed on 28 October 2022). 57. Windle, M. Suicidal Behaviors and alcohol use among adolescents: A developmental psychopathology perspective. Alcohol.-Clin. Exp. Res. 2004,28, 29S–37S. [CrossRef] 58. Haardörfer, R.; Windle, M.; Fairman, R.T.; Berg, C.J. Longitudinal changes in alcohol use and binge-drinking among young-adult college students: Analyses of predictors across system levels. Addict. Behav. 2020,112, 106619. [CrossRef] 59. Piko, B.F.; Kovács, E. Do parents and school matter? Protective factors for adolescent substance use. Addict. Behav. 2010 ,35, 53–56. [CrossRef] 60. Zarzar, P.M.; Jorge, K.O.; Oksanen, T.; Vale, M.P.; Ferreira, E.F.; Kawachi, I. Association between binge drinking, type of friends and gender: A cross-sectional study among Brazilian adolescents. BMC Public Health 2012,12, 257. [CrossRef] 61. Grard, A.; Kunst, A.; Kuipers, M.; Richter, M.; Rimpela, A.; Federico, B.; Lorant, V. Same-Sex Friendship, School Gender Composition, and Substance Use: A Social Network Study of 50 European Schools. Subst. Use Misuse 2018 ,53, 998–1007. [CrossRef] [PubMed] 62. Reifman, A.; Watson, W.K.; McCourt, A. Social networks and college drinking: Probing processes of social influence and selection. Personal. Soc. Psychol. Bull. 2006,32, 820–832. [CrossRef] [PubMed] 63. Lorant, V.; Nicaise, P. Binge drinking at university: A social network study in Belgium. Health Promot. Int. 2015 ,30, 675–683. [CrossRef] [PubMed] 64. Hahm, H.C. Binge drinking trajectories from adolescence to young adulthood: The effects of peer social network. Subst. Use Misuse 2012,47, 745–756. [CrossRef] [PubMed] 65. Lundborg, P. Social capital and substance use among Swedish adolescents-An explorative study. Soc. Sci. Med. 2005 ,61, 1151–1158. [CrossRef] 66. Weitzman, E.R.; Chen, Y.Y. Risk modifying effect of social capital on measures of heavy alcohol consumption, alcohol abuse, harms, and secondhand effects: National survey findings. J. Epidemiol. Community Health 2005,59, 303–309. [CrossRef] 67. Stickley, A.; Koyanagi, A.; Roberts, B.; Murphy, A.; Kizilova, K.; McKee, M. Male solitary drinking and hazardous alcohol use in nine countries of the former Soviet Union. Drug Alcohol Depend. 2015,150, 105–111. [CrossRef] 68. von Ah, D.; Ebert, S.; Ngamvitroj, A.; Park, N.; Kang, D.H. Predictors of health behaviours in college students. J. Adv. Nurs. 2004 , 48, 463–474. [CrossRef] 69. Aseltine, R.H.; Gore, S.L. The variable effects of stress on alcohol use from adolescence to early adulthood. Subst. Use Misuse 2000 , 35, 643–668. [CrossRef] 70. Pearson, J.; Wilkinson, L. Erratum: Family relationships and adolescent well-being: Are families equally protective for same-sex attracted youth? J. Youth Adolesc. 2013,42, 1494–1496. [CrossRef] 71. Springer, A.; Parcel, G.; Baumler, E.; Ross, M. Supportive social relationships and adolescent health risk behavior among secondary school students in El Salvador. Soc. Sci. Med. 2006,62, 1628–1640. [CrossRef] [PubMed] 72. Walsh, S.D.; Kolobov, T.; Harel-Fisch, Y. Parenting behaviors as moderators of the relationship between immigrant status and alcohol se among adolescents in Israel. J. Fam. Issues 2021,42, 1195–1216. [CrossRef] 73. A Ichiyama, M.; Fairlie, A.M.; Wood, M.D.; Turrisi, R.; Francis, D.P.; E Ray, A.; A Stanger, L. A randomized trial of a parent-based intervention on drinking behavior among incoming college freshmen. J. Stud. Alcohol Drugs 2009 ,16, 67–76. [CrossRef] [PubMed] 74. Ryabov, I. Relation of peer effects and school climate to substance use among Asian American adolescents. J. Adolesc. 2015 ,42, 115–127. [CrossRef] 75. Schwinn, T.M.; Schinke, S.P. Alcohol use and related behaviors among late-adolescent urban youths: Peer and parent influences. J. Child Adolesc. Subst. Abus. 2014,23, 58–64. [CrossRef] 76. Zhao, T.T. Personality factors, life orientation factors, and alcohol use patterns in graduate students. Ph.D. Thesis, Adler School of Professional Psychology, Chicago, IL, USA, 2013. 77. Fruehwirth, J.C.; Gorman, B.L.; Perreira, K.M. The effect of social and stress-related factors on alcohol use among college students during the COVID-19 pandemic. J. Adolesc. Health 2021,69, 557–565. [CrossRef] 78. Seid, A.K. Social interactions, trust and risky alcohol consumption. Health Econ. Rev. 2016,6, 3. [CrossRef] 79. Grootaert, C.; Narayan, D.; Jones, V.N.; Woolcook, M. Measuring Social Capital, an Integrated Questionnaire; The World Bank: Washington, DC, USA, 2003. 80. Procidano, M.E.; Heller, K. Measures of perceived social support from friends and from family: Three validation studies. Am. J. Community Psychol. 1983,11, 1–24. [CrossRef] 81. Sarason, I.G.; Levine, H.M.; Basham, R.B.; Sarason, B.R. Assessing social support: The social support questionnaire. J. Personal. Soc. Psychol. 1983,44, 127–139. [CrossRef] 82. Turner, R.J.; Marino, F. Social support and social structure: A descriptive epidemiology. J. Health Soc. Behav. 1994 ,35, 193–212. [CrossRef] 83. Rodríguez, M.S.; Martínez-López, Z.; Tinajero, C.; Guisande, M.A.; Páramo, M.F. Adaptación española de la Escala de Aceptación Percibida (PAS) en estudiantes universitarios. Psicothema 2012,24, 483–488. Youth 2022,2586 84. Cohen, S.; Mermelstein, R.; Kamarck, T.; Hoberman, H.M. Measuring the functional components of social support. In Social Support: Theory, Research and, Applications; Martinus Nijhoff: The Hague, The Netherlands, 1985; pp. 73–94. 85. Brutovská, M.; Orosová, O.; Kalina, O. Gender, normative beliefs and alcohol consumption among university students. In Psychology Applications & Developments; Pracana, C., Ed.; InScience Press: Lisboa, Portugal, 2014; pp. 67–75. 86. Benenson, J.F. Gender differences in social networks. J. Early Adolesc. 1990,10, 472–495. [CrossRef] 87. Gençer, H. Group Dynamics and Behaviour. Univers. J. Educ. Res. 2019,7, 223–229. [CrossRef] 88. Pascarella, E.T.; Goodman, K.M.; Seifert, T.A.; Tagliapietra-Nicoli, G.; Park, S.; Whitt, E.J. College student binge drinking and academic achievement: A longitudinal replication and extension. J. Coll. Stud. Dev. 2007,48, 715–727. [CrossRef] 89. Piazza-Gardner, A.K.; Barry, A.E.; Merianos, A.L. Assessing drinking and academic performance among a nationally representative sample of college students. J. Drug Issues 2016,46, 347–353. [CrossRef] 90. Porter, S.R.; Pryor, J. The effects of heavy episodic alcohol use on student engagement, academic performance, and time use. J. Coll. Stud. Dev. 2007,48, 455–467. [CrossRef] 91. Kuntsche, E.; Knibbe, R.; Gmel, G.; Engels, R. Why do young people drink? A review of drinking motives. Clin. Psychol. Rev. 2005,25, 841–861. [CrossRef] 92. Arnett, J.J. Emerging adulthood: A theory of development from the late teens through the twenties. Am. Psychol. 2000 ,55, 469–480. [CrossRef] 93. Reboussin, B.A.; Song, E.Y.; Wolfson, M. Social Infl uences on the Clustering of Underage Risky Drinking and Its Consequences in Communities. J. Stud. Alcohol Drugs 2012,73, 890–898. [CrossRef] 94. Lapsley, D.; Hardy, S.A. Identity Formation and Moral Development in Emerging Adulthood. In Emerging Adulthood Series. Flourishing in Emerging Adulthood: Positive Developmental during the Third Decade of Life; Oxford University Press: Oxford, UK, 2017. 95. Andersen, A.; Holstein, B.E.; Due, P. School-related risk factors for drunkenness among adolescents: Risk factors differ between socio-economic groups. Eur. J. Public Health 2007,17, 27–32. [CrossRef] 96. Borawski, E.A.; Ievers-Landis, C.E.; Lovegreen, L.D.; Trapl, E.S. Parental monitoring, negotiated unsupervised time, and parental trust: The role of perceived parenting practices in adolescent health risk behaviors. J. Adolesc. Health 2003,33, 60–70. [CrossRef] 97. Wiersma, J.D.; Fischer, J.L.; Cleveland, H.H.; Reifman, A.; Harris, K.S. Selection and socialization of drinking among young adult dating, cohabiting, and married partners. J. Soc. Pers. Relatsh. 2010,28, 182–200. [CrossRef] 98. Kuntsche, E.; Nic Gabhainn, S.; Roberts, C.; Windlin, B.; Vieno, A.; Bendtsen, P.; Hublet, A.; Tynjälä, J.; Välimaa, R.; Dankulincová, Z.; et al. Drinking motives and links to alcohol use in 13 European countries. J. Stud. Alcohol Drugs 2014 ,75, 428–437. [CrossRef] [PubMed]