Skip to main content
Download PDF

Implementation processes of social network interventions for physical activity and sedentary behavior among children and adolescents: a scoping review

BMC Public Health volume 24, Article number: 1101 (2024) Cite this article

Abstract

Background

The characteristics of the implementation process of interventions are essential for bridging the gap between research and practice. This scoping review aims to identify the implementation process of social network interventions (SNI) to address physical activity and sedentary behaviors in children and adolescents.

Methods

The scoping review was conducted adhering to the established guidelines. The search was carried out in the ERIC, EBSCO, EMBASE, SCOPUS, and Lilacs databases in April 2023. Social network intervention studies in children and adolescents were included, addressing physical activity or sedentary behaviors. Replicability (TIDieR), applicability (PRECIS-2), and generalizability (RE-AIM) were the explored components of the implementation process. Each component was quantitatively and separately analyzed. Then, a qualitative integration was carried out using a narrative method.

Results

Most SNI were theoretically framed on the self-determination theory, used social influence as a social mechanism, and used the individual typology of network intervention. Overall, SNI had strong replicability, tended to be pragmatic, and three RE-AIM domains (reach, adoption (staff), and implementation) showed an acceptable level of the generalizability of findings.

Conclusions

The analyzed SNI for physical activity and sedentary behaviors in adolescents tended to be reported with high replicability and were conducted pragmatically, i.e., with very similar conditions to real settings. The RE-AIM domains of reach, adoption (staff), and implementation support the generalizability of SNI. Some domains of the principles of implementation strategies of SNI had acceptable external validity (actor, action targets, temporality, dose, and theoretical justification).

Peer Review reports

Background

Dissemination and implementation (D&I) research is a comprehensive approach focused on translating scientific knowledge into practice and policy [1]. D&I science is a field with constant development in terms of theories, frameworks, and methods helpful in bridging the gap between what is known from research and what is implemented in practice. In this process, scientific evidence of the effectiveness of interventions is as crucial as implementing these interventions. Therefore, D&I investigates for whom the scientific evidence could be helpful, in which contexts it would work, and what mechanisms would explain its usefulness [2].

In this regard, and from the D&I research perspective, the exploration of the implementation process places a significant focus on external validity [3]. External validity may be examined by considering different dimensions such as replicability, applicability, and generalizability. Here, replicability analysis focuses on those methodological features reported in sufficient detail so that one can ascertain whether the study may be replicated in a manner similar to the original version [4]. Applicability is understood as an attribute that informs whether the intervention study is closer to “real world” conditions (pragmatic) or idealized conditions (explanatory) [5]. Generalizability refers to the extent to which a study’s findings may translate into practice in settings situations and populations [6].

In the field of social determinants of health-related behavior, interpersonal relationships are the foundation of social network intervention since social network dynamics unfold from social relationships [7]. The associations between social networks and health behaviors are well-established [8,9,10], and particularly for physical activity (PA) and sedentary behavior (SB), the content of social relationships such as social norms, social support, and social influence are the mechanisms that help to explain how social networks affect these behaviors [11,12,13,14,15].

Social network interventions (SNI) have shown a growing interest, and one of its tenets is using network data to accelerate behavior change or improve organizational performance within the network [16]. Four types of SNI have been proposed in the literature: an individual approach aimed to identify leaders to promote behavior change, and three network-based approaches: induction, segmentation, and alteration [16]. The evidence synthesis for social network studies in adolescents indicates that the effectiveness of SNI in changing health-related behaviors has shown promising results in different health outcomes and populations and suggests that the strongest evidence of effectiveness has been for the individual approach [8]. However, implementation elements need to be clarified or provided in detail in this body of literature, including social mechanisms and theoretical foundations [8], since these elements are critical components for D&I science [17] and to understand how social dynamics affect behavior [16]. In addition, the optimal way to apply different SNI approaches in interventions that address health-related behaviors is still unknown [8]. It is necessary to study further SNI characteristics [13, 14], specially describing the complexity and contextual factors that are essential from the D&I perspective, such as personal, cultural, social, environmental factors, among others [18].

Considering the deficient evidence about and the complexity and breadth of the implementation process of SNI, this scoping review aimed to evaluate and synthesize the implementation process of SNI to modify PA and SB in childhood and adolescence. For this purpose and following the suggestion made for evidence synthesis studies for external validity [19], the integration of replicability, applicability, and generalizability, was made recognizing that social intervention are complex and multilevel, and should offer enough detail to apply these implementation strategies in different contexts [20]. For this reason, the typology purposed by Proctor et al. [20] was used to integrate key components of implementation strategies with external validity dimensions. This integration would provide greater clarity of how scientific advances about social network interventions could inform future translation into practice. This integration, and therefore, the characterization of the implementation strategies.

Methods

This scoping review was conducted following the methodological protocols established by the Jhoana Briggs Institute (JBI) [21], whose guides are based on the population, concept, and context framework (PCC) [21]. This review was focused on the population of children and adolescents; the concept used was primary studies of social network interventions in PA and SB. No restrictions were made on the context. The report was elaborated following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) Checklist and Explanation [22]. The implementation process was analyzed exploring different aspects of SNI, including theoretical support, interpersonal relationships fostered in these interventions, types of social network interventions implemented, and how replicable, applicable, and generalizable were the SNI. The scoping review protocol was registered in Open Science Framework as part of the transparency of the study (Registration DOI: https://doi.org/10.17605/OSF.IO/XS3RU).

Eligibility criteria

This scoping review considered social network intervention articles regardless of network intervention strategy. Studies should consider multiple relationships among individuals in the social network and should have PA and SB in children and adolescents in any context as outcome variables. Social network interventions were defined as those studies that intentionally use social network data to generate behavioral changes among individuals within the network. The studies must have measured social relationships and used these measurements to intervene, regardless of the network approach used. Those studies based only on simulated interventions such as agent-based modeling were excluded. Also, following the operational definition of SNI, studies about only on dyadic, or triad relationships were excluded since the design of these types of interventions is not based on network data.

Types of sources

Any primary intervention study was considered regardless of the design or approach used (quantitative, qualitative, or mixed studies).

Search strategy

The search strategy was aimed at locating published studies. The search strategy was not limited by study design, year, region, publication time, or language. Two reviewers were going through the process of identifying the most appropriate terms through an initial search based on previous evidence syntheses. The search strategy was tailored for each database, including all specified keywords and index terms related to PA, SB, and SNI. The reference list of all included sources of evidence was screened for additional studies.

For the complete search, the following electronic databases were used: ERIC, EBSCO, EMBASE, SCOPUS, and Lilacs. The search for information was done in April 2023. For each variable, related terms were used and included physical activity, sport, sedentary behavior, sedentary behaviour, sitting, screen time, screen use, sedentary time, sedentary lifestyle, social network analysis, network intervention, network-based intervention, social network intervention, and friends intervention. The search equation in each database was specified in Supplementary Table S1.

Study/source of evidence election

Once the search was done, the Rayyan bibliographic manager [23] was used to download, organize the bibliography, and eliminate duplicate references. Two reviewers (JP and CA) independently reviewed titles and abstracts for evaluating and selecting evidence, considering the inclusion criteria to select potential review sources. Then, they examined the full text of the studies. Any disagreement between the two reviewers was settled by consensus.

Data extraction

Two reviewers (JP and CA) independently extracted the data from the articles in a template developed following the JBI guidelines [24], and previously pilot-tested. According to the review question, the template was designed with precise information about participants, concept, context, methodology, and essential results. Any disagreement (about 10% for the entire extraction process) was resolved by consensus. The minimum data for the data extraction form included complete citation data (author, year, title, journal), country, participants/population, sample characteristics, outcome variables, approach for social network intervention, context, study-oriented basic theory, the content of fostered interpersonal relationships, details of the intervention process, results (primary and secondary), and conclusions.

The analyzed external validity dimensions included replicability, applicability, and generalizability (Supplementary table S2). Replicability was analyzed with the Template for Intervention Description and Replication tool, TIDieR [25], covering 12 items (Supplementary Table S2). TIDieR score in each item was assessed utilizing 1 = reported and 0 = no reported. The total score of each study was obtained by adding the value of each item, and the score of each item was obtained by adding the value in each study. The Pragmatic-Explanatory Continuum Indicator Summary model, PRECIS-2 [5], was used to evaluate the applicability of the interventions, considering nine items (Supplementary Table S2). Each domain was scored using a 5-point Likert scale: (1) Very explanatory, (2) Rather explanatory, (3) Equally pragmatic and explanatory, (4) Rather pragmatic, (5) Very pragmatic [5]. Generalizability was explored with the reach, effectiveness, adoption, implementation, and maintenance framework (RE-AIM) (Supplementary Table S2) [26]. RE-AIM score in each item was measured as follows: “Not reports = 0”, “Accurate reported = 1”, and “Misreporting = 2”. The percentage of each dimension is reported by applying the following formula (criteria sum * 100/Number of items in each dimension).

Data analysis and presentation

A qualitative analysis of the evidence of the implementation process was carried out using a narrative method. The focus of the present scoping review was the characteristics of the implementation process of the SNI. We did not quantify or measure the effectiveness of the interventions. The process evaluation was analyzed using the TIDieR, PRECIS-2, and RE-AIM tools. The data are represented in tables and graphs with their respective qualitative analyses. As an intent to integrate findings from these three tools, the principles of implementation strategies proposed by Proctor et al. [20]. were used to indicate how replicable, applicable, and generalizable the SNI were in terms of the seven dimensions: actor, the action, action targets, temporality, dose, implementation outcomes, and theoretical justification.

Results

After the search, 755 citations were identified from all databases. After removing duplicates, we screened 403 citations in the title and abstract; five studies met the inclusion criteria for full paper revision [27,28,29,30,31]. After this, two studies were excluded because PA or SB was not measured as the outcome variable in one study [31], and the other was not a SNI [30]. We identified and included three citations found by manual search [32,33,34], and one study was included for the researchers’ knowledge [35]. In total, seven studies were analyzed for this scoping review. Figure 1 shows a flow diagram of publication identification, screening, eligibility assessment, and inclusion.

Fig. 1
figure 1

PRISMA flow diagram illustrating the searching and selection process

Full size image

Characteristics of the studies

The seven studies were published between 2012 and 2022, and six were published in the last six years (from 2017 to 2022), indicating the relative newness of the social network approach to address PA and SB in children and adolescents. All studies were developed in the school context and were conducted in high-income countries: three in England [32,33,34], two in the Netherlands [27, 28], one in the United States [35], and one in Italy [29]. Three studies measured both PA and SB by accelerometry [32,33,34]; four studies measured only PA, three by accelerometry [27,28,29], and the other one by questionnaire [35]. Six studies were conducted using the randomized control trial design; the other used a quasi-experiment design [35]. The age range of the population was 9–16 years old, with a total of 4046 participants in all the studies. Characteristics of the included studies are shown in Table 1.

Table 1 Characteristics of the included studies
Full size table

Interventions details

The length of the interventions varied from 1-week [27, 28] to 10 weeks [32,33,34]. Intervention strategies consisted of forming same-sex groups to obtain rewards related to PA levels of friends by direct and indirect reciprocity, collective and individual levels of PA, and random reward [29], training peer-nominated peers to promote, disseminate information for PA in the classroom [28], serving as support for increase PA and decrease SB [32,33,34], and creating PA-related digital content as vlogs [27] and CDs [35] for classmates. Two studies were conducted only on girls [33, 34]. The intervention model ASSIST (A Stop Smoking in Schools Trial) [36] was adapted to address PA and SB in three studies [32,33,34]. Six out of seven studies were based on individual approaches of SNI [27, 28, 32,33,34,35]. Two studies were effective in increasing PA [29, 35], and one in increasing PA and reducing SB [34]. Characteristics of the SNI are shown in Table 1.

Theoretical support for interventions and social function promoted

All studies reported a theoretical framework. These theories included Self-determination theory (SDT) with Self-persuasion theory (SPT) [28], SDT with planned behavior theory (PBT) [27], diffusion of innovation theory (DOI theory) [32], SDT and DOI theory [33, 34], social cognitive theory (SCT) [35], and social network theory [29]. The most frequent social functions or mechanisms promoted were social influence [27,28,29, 32, 34, 35], followed by social support [32, 33, 35], social norms [27, 29, 37], social modeling [28], and social pressure [29].

Dimensions of external validity

Replicability

The intervention’s replicability was analyzed by TIDieR, and the summary is depicted in Table 2. All studies reported the items “Name”, “Why”, “What procedures”, “What materials”, “Who provided”, “How” and “When and how much”. The less reported items were “Tailoring”, “Modification”, and “How well actual”. The items “Where” and “How well planned” were reported in four and five studies, respectively. The most complete study reported 11/12 items [32], followed by 10/12 items [35]. Two studies reported 9/12 items [27, 28]. The other three reported 8/12 items [29, 33, 34].

Table 2 Summary of TIDieR items described in the analyzed studies
Full size table

Applicability

Precis-2 is a tool that evaluates how pragmatic or explanatory a study is as an indicator of SNI applicability. The nine items were assessed in each study, and the results are shown in Table 3. Very pragmatic items reported were Eligibility, Recruitment, and Primary outcome, all with a mean = 5.0. Rather pragmatic items reported were Flexibility of adherence (mean = 4.7) and Setting (mean = 4.6). Items considered equally pragmatic and explanatory were Flexibility of delivery (mean = 3.7) and Follow-up (mean = 3.1). The items reported as rather explanatory were Organisation (mean = 2.3) and Primary analysis (mean = 2.1). There were no items reported as very explanatory.

Six studies reached a Precis-2 score close to 4 or higher (between 3.8 and 4.3), indicating that these studies were Rather pragmatic [27, 28, 32,33,34,35]. The other study, with a Precis-2 score of 3.3, was classified as equally pragmatic and explanatory [29]. No studies were considered very explanatory, rather explanatory, or very pragmatic. That indicates that social network intervention tends to be pragmatic. The score of each study is compared with the general average of all the studies in each item of Precis-2 (Fig. 2).

Fig. 2
figure 2

PRECIS-2 wheels for the analyzed studies

Full size image
Table 3 Summary of PRECIS-2 scores for the analyzed studies
Full size table

Generalizability

Generalizability was assessed with the RE-AIM tool. In each RE-AIM dimension, a percentage was made according to the number of items reported in each dimension. The analysis by dimensions indicated that the less reported dimension was maintenance (organizational); only one study reported items related to this dimension [29]. Low percentages, under 50%, were reported in the dimensions of effectiveness, adoption (setting), and maintenance (individual). The dimensions of Reach, Adoption (staff), and Implementation had percentages above 50% (see Fig. 3).

Fig. 3
figure 3

Summary of reporting RE-AIM dimensions

Full size image

In each study, the percentage of compliance with each dimension and an average of all the dimensions together were analyzed (see Table 4). The maximum RE-AIM score was 61.2% [34], followed by 55.4% [27], and 51.7% [33]. Only these three studies had a RE-AIM score above 50%. The minimum RE-AIM scores were 26.2% [35] and 29.5% [29]. The other two studies had RE-AIM scores of 38.7% [28] and 46.6% [32].

Table 4 Percentage of completeness report of RE-AIM dimensions in the analyzed studies
Full size table

Integration/intervention details

Following the recommendations for specifying and reporting implementation strategies in intervention studies, the evaluated dimensions of external validity were integrated with the domains specified to operationalize strategies: The actor, the action, action targets, temporality, dose, implementation targets affected, and theoretical justification [20]. Table 5 depicts each domain according to reproducibility, applicability, and generalizability purposes.

Table 5 Domains of implementation strategies for dimensions of external validity of social network intervention studies
Full size table

Discussion

This scoping review aimed to evaluate and synthesize the implementation process of social network interventions to modify physical activity and sedentary behaviors in childhood and adolescence. Several findings were identified in the scoping review and are presented in the following sections. The analyzed SNI for PA and SB have been reported with high replicability (TIDieR), were conducted pragmatically, i.e., with very similar conditions to real settings (PRECIS-2), and the report of some RE-AIM domains support the generalizability of SNI.

Theoretical support for interventions

The most frequent theoretical framework reported in the interventions was the self-determination theory (SDT), used in four out of the seven analyzed studies along with other theories [27, 28, 33, 34]. The SDT is based on intrinsic or autonomous motivation and psychological needs as relation, autonomy, and competence [38]. Recently, a systematic review found that SDT-based interventions improved different health domains [39]. In children and adolescents, the evidence suggests that SDT constructs help to explain physical activity behavior [40].

Diffusion of innovation theory (DOI) was used as a theoretical framework in other social network interventions [32,33,34]. DOI theory is considered relevant for social network interventions [16] since it is helpful to explain how new ideas and practices spread within the social network [41, 42]. Likewise, integrating the theory of social networks with DOI theory has been suggested to improve the implementation of interventions, achieving a comprehensive approach [43]. In the present scoping review, two interventions applied a combination of SDT and DOI theory [33, 34]. However, only the study of Sebire et al. (2018) positively affected PA and SB.

Other theories, such as social cognitive theory (SCT), theory of planned behavior (TPB), and self-persuasion theory (SPT), were used to inform the interventions. However, only one study reported positive effects on PA [35]. However, SCT has been previously used in interventions for PA and obesity with no significant results, and low efficacy [44, 45]. The theoretical support for SNI is required not only for identifying those constructs to intervene during the implementation process and how they interact with each other to influence the outcome of interest but also, more importantly, for helping to explain how patterns of the social system may be modified by fostering or intensifying some social interaction mechanisms to optimize the system behavior. This perspective implies the adoption of the systems lens for using theoretical frameworks for complex interventions [46].

Interpersonal relationships promoted

The social mechanism most promoted in the studies included in this review was social influence, analyzed in all the studies except for the study of Jago et al. [33]. This finding is consistent with what has been pointed out in the literature about the role of social influence in the relationship between health behavior and social networks [47]. The evidence shows that social influence is positively associated with health behaviors in school adolescents [9] and that individual PA levels may result from the influence of friends and peer [12, 14, 15]. The other social mechanisms reported in the studies included social norms, social pressure, social support, and social modeling. The identification of these mechanisms is a key step to define the implementation of strategies [8]. However, it is difficult to determine the actual social mechanisms responsible for behavioral changes due to social networks’ inherent, complex dynamics and their natural evolution [47].

Types of social network interventions

The identification of the social network intervention approach used is an important aspect to understand the implementation process, since each typology of SNI describes different strategies to be implemented [16]. Six out of seven studies were based on individual approaches of SNI. Generally, researchers used friend’s nomination to identify the agents by a network parameter (centrality) and then trained them to implement strategies within the network for behavior change; two of these studies had positive effects [34, 35]. This type of SNI is supported by the most substantial evidence of effectiveness in the adult population [8]. The study that used a social approach based on the specific type of induction and alteration based on reciprocity positively affected the PA level [29]. A review of SNI for health behaviors in adults identified that the social approach, especially induction, was the most frequent SNI typology used [8].

In the present review, two interventions used “closeness centrality”: influence agents closely connected to all other network members [27, 28]. Four interventions used “indegree centrality”: influence agents who received the most nominations or were popular in the network [32,33,34,35]. This strategy is supported by the fact that popularity in social networks has been associated with engagement in health behaviors and significant associations for predicting health behavior [9]. However, the SNI type’s effectiveness for behavior change still requires more research attention.

It is important to note that previous evidence syntheses have also explored PA interventions based on peer-to-peer approaches [48, 49]. Studies analyzed in these reviews applied diverse peer-leadership approaches, where leaders were trained to foster PA among peers. In these studies, the peer leader was identified using different criteria than those applied in SNI, i.e., applying teacher criteria or based on the student’s leadership skills. The difference with these reviews is that our scoping review focuses on those interventions in which sociometric data from networks is used to learn from the community, a particular characteristic of SNI [16]. In other words, the difference lies in the methods used to identify who delivers the strategies. For this review, we strictly adhere to the definition of SNI, in which network information is required to inform the design of the intervention [16].

It is worth noting that four of the seven studies were identified using manual search and previous knowledge of the researchers. This may be explained by the fact that these studies do not include the term of social network intervention in the title or abstract. However, in the methods section, authors describe the procedures that fit with the operational definition of SNI [32,33,34,35].

External validity: replicability

In this scoping review, the replicability of interventions was analyzed by the TIDieR tool, and most of the items were appropriately reported. In general, all the SNI had good replicability scores. However, “Tailoring”, “Modification”, and “How well actual” were the items with the lowest frequency of reporting, crucial aspects for assessing intervention fidelity, adherence, and adverse events. These items are useful to complete the description of the implementation process and should be addressed in future studies. Similar findings about frequencies of complete reports have been documented in overviews of systematic reviews [50, 51]. Even though the analyzed studies had acceptable replicability, more complete and accurate reporting could reduce research waste, improve evidence synthesis, and implementation in other contexts [52].

External validity: applicability

Applicability was assessed with Precis-2; in general, SNI tended to be pragmatic. There were no studies considered rather explanatory or very explanatory. Social network interventions have the particularity of using established networks, in this case, the classrooms. This allows many elements to be pragmatic. In this review, the most pragmatic items were “Eligibility”, “Recruitment”, and “Primary outcome”. At the same time, “Follow-up” tends to be equally pragmatic and explanatory, and “Organisation” and “Primary analysis” tend to be rather explanatory. These results differ from other reviews where “Primary analysis” tends to be more pragmatic [53, 54], and “Eligibility”, “Organisation”, and “Follow-up” tend to be more explanatory in primary health care [53, 54].

In this review, two studies considered pragmatic positively affected PA [34, 35]. However, the most explanatory study also positively improved PA in adolescents in SNI [29]. A systematic review concluded that pragmatic trials were ineffective in improving PA in children [55], and others concluded that more pragmatic studies were associated with smaller increases in PA [56]. It is worth mentioning that in most cases, SNI has aspects that are inevitably considered explanatory in social networks. For instance, although the interventions were implemented in usual school settings, characteristics of the social network of students are not commonly analyzed to inform pedagogical interventions. Therefore, this exploration could be considered explanatory.

External validity: generalizability

Generalizability was assessed with RE-AIM. Overall, three RE-AIM domains (reach, adoption (staff), and implementation) support an acceptable level of the generalizability of findings. The report of the rest of the dimensions needs to be improved, particularly maintenance (organizational). The percentage mean for studies varied from 26.6% [35] to 61.2% [34]. The most reported dimension was reach with 55%, adoption (staff) and implementation both with 57%, and the least reported was maintenance (organizational) with only 2%. Previous systematic reviews have also found that Reach is the dimension where more items are reported in PA school interventions among adolescents [57]. In specific populations, such as indigenous youth, the result was different. A review concluded that the dimensions of reach and implementation were the most poorly reported in PA interventions [58]. However, items could have been better described with more information [57], while the dimension of maintenance is the most poorly reported [59]. In this regard, it has been pointed out that maintenance is one of the most challenging elements for physical activity interventions in schools since it requires the integration of multi-stakeholder perspectives from classroom, school, and policy levels [60].

External validity: integration

All the analyzed studies were conducted in schools, reinforcing the premise that the school setting offers a good opportunity to promote health and prevent disease [61]. In the analyzed SNI studies, students enacted the strategies deployed in their social networks in real-world education settings. Social interactions are the core of SNI. However, students should sometimes receive training to improve their social skills and unfold social mechanisms to promote the intended behaviors. Since social learning skills are part of the learning objective in school settings, SNI fits the requirements for implementation within schools. Although the analyzed studies specify the intervention time, the exposure dose, and other relevant aspects for external validity, social interactions occur naturally during school hours and are not restricted to educational intentions. Therefore, it is a challenge to effectively register the quantity and quality of social interactions that may occur during school days that have yet to be planned within the study. In addition, there is evidence of the effectiveness of SNI in the short and long term (more or less than six months) in some health-related behaviors [8]. All the studies analyzed in the present scoping review had a duration of no more than ten weeks of intervention, and three of them reported positive effects on PA in interventions between 6 and 10 weeks [29, 34, 35]. The SNI for PA and SB tend to be conducted with high external validity in the domains of actor, action targets, temporality, dose, and theoretical justification. The domains of action and implementation outcomes need to be improved in the reports for SNI replicability, applicability, and generalizability.

It is worth indicating that when integrating the three dimensions of external validity according to the domains proposed to describe the implementation of strategies [20], there is a risk of omitting relevant aspects of each intervention. This, added to the need to attend to contextual conditions, as suggested from the systems perspective [18], implies that a reading of the context must be carried out to adapt and contextualize the implementation of the strategies.

The findings of this scoping review contribute to the initiative of whole systems approaches for physical activity promotion [62] because tools such as social network analysis are used to understand systems as a central issue within implementation science [17]. Its application by public health and educational practitioners requires adopting a system approach [46], e.i., embracing the uncertainty and unpredictable nature of the relationship between actions and their consequences. From this perspective, SNI needs to be understood as events within the system [63]. Since schools are complex social systems [64], SNI requires identifying particular social dynamics within the network and being attentive enough to recognize changes produced by the system during the intervention [46]. For instance, the identification of central actors within the social network may be used to activate “leverage points” [65] that generates meaningful changes in the social systems of students [66]. In this regard, integrating context- and practice-based evidence is encouraged. Regarding implications for research, the present review’s findings help identify aspects to be explored in future research. Among these aspects, examining social network mechanisms and studies about the effectiveness and implementation processes of the SNI typologies, for both PA and SB, are elements to study in greater depth. Also, future research should be focused on SNI as a complementary component along with other participatory strategies and system mapping methods to better align with the whole system approach.

This review presents some limitations. First, the researchers used tools to evaluate replicability, applicability, and generalizability. However, this could have been more accurate if the program implementers had participated in the task. Second, all the SNI analyzed were conducted in school settings. The present review did not identify other spheres of socialization, such as neighborhoods, sports teams, churches, and the like. A third limitation is that in this scoping review, and as part of the narrative description of findings about the implementation process, the direction of the effect of the interventions has been mentioned, but not extensively analyzed. This procedure is usually done in systematic reviews of the effectiveness of interventions, as previously conducted in the field of SNI [8]. Among the strengths, integrating the three tools used as dimensions of external validity gave a novel approach to evaluate intervention studies from the D&I research perspective. Also, considering that diverse local circumstances define social network processes, structures, and dynamics, it is challenging to generalize these interventions. In this regard, the present scoping review highlights essential aspects of SNI. Endeavors to scale up SNI must pay special attention in the implementation process to identify these local circumstances responsible for the social dynamics unfolding in the networks.

Conclusions

All the analyzed SNI were theory-driven interventions, and most were based on the combination of SDT with other theories like diffusion of innovation theory, self-persuasion theory, and theory of planned behavior. Other supporting theories were social cognitive theory and social network theory. The most frequent content of the interpersonal relationships or social mechanisms fostered in the studies was social influence, and most of the studies were based on individual approaches of SNI. The analyzed SNI for PA and SB in adolescents tend to be reported with high replicability. These studies were conducted pragmatically, i.e., with very similar conditions to real settings. And the RE-AIM domains of reach, adoption (staff), and implementation support the generalizability of SNI, while the report of the domain of maintenance (organizational) needs to be improved. Some domains of the principles of implementation strategies of SNI had acceptable external validity (actor, action targets, temporality, dose, and theoretical justification). The domains of action and implementation outcomes need to be improved in the reports for SNI replicability, applicability, and generalizability.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

D&I:

Dissemination and implementation research

PA:

Physical activity

SB:

Sedentary behavior

SNI:

Social network intervention

JBI:

Jhoana Briggs Institute

PCC:

Population, concept, and context

TIDieR:

Template for Intervention Description and Replication framework

PRECIS-2:

Pragmatic-Explanatory Continuum Indicator Summary framework

RE-AIM:

Reach, effectiveness, adoption, implementation, and maintenance framework

PRISMA-ScR:

Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews

SDT:

Self-determination theory

SPT:

Self-persuasion theory

PBT:

Planned behavior theory

DOI:

Diffusion of innovation theory

SCT:

Social cognitive theory

References

  1. Brownson RC, Colditz GA, Proctor EK. Dissemination and implementation research in health: Translating science to practice. 3rd ed. New York: Oxford University Press; 2023.

    Book  Google Scholar 

  2. Brownson RC, Shelton RC, Geng EH, Glasgow RE. Revisiting concepts of evidence in implementation science. Implement Sci. 2022;17(1):26. https://doi.org/10.1186/s13012-022-01201-y.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Trinkley K, McNeal D, Fort M, Green L, Huebschmann A. Furthering dissemination and implementation research: paying more attention to external validity through an equity lens. In: Brownson R, Colditz G, Proctor E, editors. Dissemination and implementation research in health: translating science to practice 3rd. New York: Oxford University Press; 2023. pp. 345–70.

  4. Goodman SN, Fanelli D, Ioannidis JPA. What does research reproducibility mean? Sci Transl Med. 2016;8(341):341ps12. https://doi.org/10.1126/scitranslmed.aaf5027.

    Article  PubMed  Google Scholar 

  5. Loudon K, Treweek S, Sullivan F, Donnan P, Thorpe KE, Zwarenstein M. The PRECIS-2 tool: Designing trials that are fit for purpose. Br Med J. 2015;350: h2147. https://doi.org/10.1136/bmj.h2147.

    Article  Google Scholar 

  6. Green LW, Glasgow RE. Evaluating the relevance, generalization, and applicability of research: issues in external validation and translation methodology. Eval Health Prof. 2006;29(1):126–53. https://doi.org/10.1177/0163278705284445.

    Article  PubMed  Google Scholar 

  7. Valente TW. Social networks and health: models, methods, and applications. New York: Oxford University Press; 2010.

  8. Hunter RF, de la Haye K, Murray JM, Badham J, Valente TW, Clarke M, et al. Social network interventions for health behaviours and outcomes: a systematic review and meta-analysis. PLoS Med. 2019;16(9):e1002890. https://doi.org/10.1371/journal.pmed.1002890

    Article  PubMed  PubMed Central  Google Scholar 

  9. Montgomery SC, Donnelly M, Bhatnagar P, Carlin A, Kee F, Hunter RF. Peer social network processes and adolescent health behaviors: a systematic review. Prev Med. 2020;130: 105900. https://doi.org/10.1016/j.ypmed.2019.105900.

    Article  PubMed  Google Scholar 

  10. Prochnow T, Delgado H, Patterson MS, Umstattd Meyer MR. Social network analysis in child and adolescent physical activity research: a systematic literature review. J Phys Act Health. 2020;17:1–11. https://doi.org/10.1123/jpah.2019-0350.

    Article  Google Scholar 

  11. Kim J, Dunn E, Rellinger K, Robertson-Wilson J, Eys M. Social norms and physical activity in American and Canadian contexts: a scoping review. Int Rev Sport Exerc Psychol. 2019;12(1):26–48. https://doi.org/10.1080/1750984X.2017.1354229.

    Article  Google Scholar 

  12. Macdonald-Wallis K, Jago R, Sterne JA. Social network analysis of childhood and youth physical activity: a systematic review. Am J Prev Med. 2012;43(6):636–42. https://doi.org/10.1016/j.amepre.2012.08.021.

    Article  PubMed  Google Scholar 

  13. Mendonça G, Cheng LA, Mélo EN, de Farias Júnior JC. Physical activity and social support in adolescents: a systematic review. Health Educ Res. 2014;29(5):822–39. https://doi.org/10.1093/her/cyu017.

    Article  PubMed  Google Scholar 

  14. Sawka KJ, McCormack GR, Nettel-Aguirre A, Hawe P, Doyle-Baker PK. Friendship networks and physical activity and sedentary behavior among youth: a systematized review. Int J Behav Nutr Phys Act. 2013;10(1): 130. https://doi.org/10.1186/1479-5868-10-130.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Maturo CC, Cunningham SA. Influence of friends on children’s physical activity: a review. Am J Public Health. 2013;103(7):e23-38. https://doi.org/10.2105/AJPH.2013.301366.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Valente TW. Network interventions. Science. 2012;337(6090):49–53. https://doi.org/10.1126/science.1217330.

    Article  CAS  PubMed  Google Scholar 

  17. Neta G, Brownson RC, Chambers DA. Opportunities for epidemiologists in implementation science: a primer. Am J Epidemiol. 2018;187(5):899–910. https://doi.org/10.1093/aje/kwx323.

    Article  PubMed  Google Scholar 

  18. Nilsen P, Bernhardsson S. Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes. BMC Health Serv Res. 2019;19(1):189. https://doi.org/10.1186/s12913-019-4015-3.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Huebschmann AG, Leavitt IM, Glasgow RE. Making health research matter: a call to increase attention to external validity. Annu Rev Public Health. 2019;40(1):45–63. https://doi.org/10.1146/annurev-publhealth-040218-043945.

    Article  PubMed  Google Scholar 

  20. Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8(1): 139. https://doi.org/10.1186/1748-5908-8-139.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Peters M, Godfrey C, McInerney P, Khalil H, Larsen P, Marnie C, et al. Best practice guidance and reporting items for the development of scoping review protocols. JBI Evid Synth. 2022;20(4):953–68. https://doi.org/10.11124/jbies-21-00242.

    Article  PubMed  Google Scholar 

  22. Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Ann Intern Med. 2018;169(7):467–73. https://doi.org/10.7326/M18-0850.

    Article  PubMed  Google Scholar 

  23. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):1–10. https://doi.org/10.1186/S13643-016-0384-4/FIGURES/6.

    Article  Google Scholar 

  24. Peters M, Marnie C, Tricco AC, Pollock D, Munn Z, Alexander L, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth. 2020;18(10):2119–26. https://doi.org/10.11124/jbies-20-00167.

    Article  PubMed  Google Scholar 

  25. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348: g1687. https://doi.org/10.1136/bmj.g1687.

    Article  PubMed  Google Scholar 

  26. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–7. https://doi.org/10.2105/ajph.89.9.1322.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. van Woudenberg TJ, Bevelander KE, Burk WJ, Smit CR, Buijs L, Buijzen M. Testing a social network intervention using vlogs to promote physical activity among adolescents: a randomized controlled trial. Front Psychol. 2020;10:2913. https://doi.org/10.3389/fpsyg.2019.02913.

    Article  PubMed  PubMed Central  Google Scholar 

  28. van Woudenberg TJ, Bevelander KE, Burk WJ, Smit CR, Buijs L, Buijzen M. A randomized controlled trial testing a social network intervention to promote physical activity among adolescents. BMC Public Health. 2018;18(1):542. https://doi.org/10.1186/s12889-018-5451-4.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Proestakis A, di Sorrentino EP, Brown HE, van Sluijs E, Mani A, Caldeira S, et al. Network interventions for changing physical activity behaviour in preadolescents. Nat Hum Behav. 2018;2(10):778–87. https://doi.org/10.1038/s41562-018-0436-y.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Benavides C, Benítez-Andrades JA, Marqués-Sánchez P, Arias N. eHealth intervention to improve health habits in the adolescent population: mixed methods study. JMIR Mhealth Uhealth. 2021;9(2): e20217. https://doi.org/10.2196/20217.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Polman MAA, Beckers D, Burk WJ, Smit CR, Buijzen M, Vink JM, et al. The effect of a multi-component school-based social network intervention on children’s body mass index: a four-arm intervention study. Psychol Health. 2023:1–18. https://doi.org/10.1080/08870446.2023.2179084.

  32. Bell SL, Audrey S, Cooper AR, Noble S, Campbell R. Lessons from a peer-led obesity prevention programme in English schools. Health Promot Int. 2017;32(2):250–9. https://doi.org/10.1093/heapro/dau008.

    Article  PubMed  Google Scholar 

  33. Jago R, Tibbitts B, Willis K, Sanderson E, Kandiyali R, Reid T, et al. Effectiveness and cost-effectiveness of the PLAN-A intervention, a peer led physical activity program for adolescent girls: results of a cluster randomised controlled trial. Int J Behav Nutr Phys Act. 2021;18(1):63. https://doi.org/10.1186/s12966-021-01133-8.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Sebire SJ, Jago R, Banfield K, Edwards MJ, Campbell R, Kipping R, et al. Results of a feasibility cluster randomised controlled trial of a peer-led school-based intervention to increase the physical activity of adolescent girls (PLAN-A). Int J Behav Nutr Phys Act. 2018;15(1):50. https://doi.org/10.1186/s12966-018-0682-4.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Barr-Anderson DJ, Laska MN, Veblen-Mortenson S, Farbakhsh K, Dudovitz B, Story M. A school-based, peer leadership physical activity intervention for 6th graders: feasibility and results of a pilot study. J Phys Act Health. 2012;9(4):492–9. https://doi.org/10.1123/jpah.9.4.492.

    Article  PubMed  Google Scholar 

  36. Campbell SF, Holliday J, Audrey S, Bloor M, Parry-Langdon N, et al. An informal school-based peer-led intervention for smoking prevention in adolescence (ASSIST): a cluster randomised trial. Lancet. 2008;371(9624):1595–602. https://doi.org/10.1016/S0140-6736(08)60692-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Barr-Anderson DJ, Flynn JI, Dowda M, Taverno Ross SE, Schenkelberg MA, Reid LA, et al. The modifying effects of race/ethnicity and socioeconomic status on the change in physical activity from elementary to middle school. J Adolesc Health. 2017;61(5):562–70. https://doi.org/10.1016/j.jadohealth.2017.05.007.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Ryan RM, Deci EL. Self-determination theory: basic psychological needs in motivation, development, and wellness. New York: Guilford; 2017.

  39. Ntoumanis N, Ng JYY, Prestwich A, Quested E, Hancox JE, Thøgersen-Ntoumani C, et al. A meta-analysis of self-determination theory-informed intervention studies in the health domain: effects on motivation, health behavior, physical, and psychological health. Health Psychol Rev. 2021;15(2):214–44. https://doi.org/10.1080/17437199.2020.1718529.

    Article  PubMed  Google Scholar 

  40. Owen KB, Smith J, Lubans DR, Ng JYY, Lonsdale C. Self-determined motivation and physical activity in children and adolescents: a systematic review and meta-analysis. Prev Med. 2014;67:270–9. https://doi.org/10.1016/j.ypmed.2014.07.033.

    Article  Google Scholar 

  41. Rogers EM. Diffusion of innovations. 5 Ed. New York: Free press; 2013.

  42. Valente TW, Davis RL. Accelerating the diffusion of innovations using opinion leaders. Ann Am Acad Political Soc Sci. 1999;566(1):55–67. https://doi.org/10.1177/000271629956600105.

    Article  Google Scholar 

  43. Iqbal M, Zahidie A. Diffusion of innovations: a guiding framework for public health. Scand J Public Health. 2021;50(5):533–7. https://doi.org/10.1177/14034948211014104.

    Article  PubMed  Google Scholar 

  44. Bagherniya M, Taghipour A, Sharma M, Sahebkar A, Contento IR, Keshavarz SA, et al. Obesity intervention programs among adolescents using social cognitive theory: a systematic literature review. Health Educ Res. 2018;33(1):26–39. https://doi.org/10.1093/her/cyx079.

    Article  PubMed  Google Scholar 

  45. Plotnikoff RC, Costigan SA, Karunamuni N, Lubans DR. Social cognitive theories used to explain physical activity behavior in adolescents: a systematic review and meta-analysis. Prev Med. 2013;56(5):245–53. https://doi.org/10.1016/j.ypmed.2013.01.013.

    Article  PubMed  Google Scholar 

  46. Moore GF, Evans RE, Hawkins J, Littlecott H, Melendez-Torres GJ, Bonell C, et al. From complex social interventions to interventions in complex social systems: future directions and unresolved questions for intervention development and evaluation. Evaluation. 2018;25(1):23–45. https://doi.org/10.1177/1356389018803219.

    Article  PubMed  Google Scholar 

  47. Valente TW, Pitts SR. An appraisal of social network theory and analysis as applied to public health: challenges and opportunities. Annu Rev Publ Health. 2017;38(1):103–18. https://doi.org/10.1146/annurev-publhealth-031816-044528.

    Article  Google Scholar 

  48. Christensen JH, Elsborg P, Melby PS, Nielsen G, Bentsen P. A scoping seview of peer-led physical activity interventions involving young people: theoretical approaches, intervention rationales, and effects. Youth Soc. 2020;53(5):811–40. https://doi.org/10.1177/0044118X20901735.

    Article  Google Scholar 

  49. McHale F, Ng K, Taylor S, Bengoechea E, Norton C, O’Shea D, et al. A systematic literature review of peer-led strategies for promoting physical activity levels of adolescents. Health Educ Behav. 2022;49(1):41–53. https://doi.org/10.1177/10901981211044988.

    Article  PubMed  Google Scholar 

  50. Harrison JH, Michael AW, Aidan GC, Amanda DH, Briana KC, James HM, et al. If exercise is medicine, why don’t we know the dose? An overview of systematic reviews assessing reporting quality of exercise interventions in health and disease. Br J Sports Med. 2022;56(12):692. https://doi.org/10.1136/bjsports-2021-104977.

    Article  Google Scholar 

  51. Dijkers MP. Overview of reviews using the template for intervention description and replication (TIDieR) as a measure of trial intervention reporting quality. Arch Phys Med Rehabil. 2021;102(8):1623–32. https://doi.org/10.1016/j.apmr.2020.09.397.

    Article  PubMed  Google Scholar 

  52. Campbell M, Katikireddi SV, Hoffmann T, Armstrong R, Waters E, Craig P. TIDieR-PHP: a reporting guideline for population health and policy interventions. BMJ. 2018;361: k1079. https://doi.org/10.1136/bmj.k1079.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Papagiannopoulou E, Laiou E, Tatsi C, Dimakopoulos G, Ntzani EE, Siamopoulos K, et al. Generalizability of randomized controlled trials in primary health care: applying the PRECIS-2 tool on published protocols. J Eval Clin Pract. 2023;29(2):253–62. https://doi.org/10.1111/jep.13759.

    Article  PubMed  Google Scholar 

  54. Zatzick D, Palinkas L, Chambers DA, Whiteside L, Moloney K, Engstrom A, et al. Integrating pragmatic and implementation science randomized clinical trial approaches: a PRagmatic explanatory Continuum Indicator Summary-2 (PRECIS-2) analysis. Trials. 2023;24(1):288. https://doi.org/10.1186/s13063-023-07313-0.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Finch M, Jones J, Yoong S, Wiggers J, Wolfenden L. Effectiveness of centre-based childcare interventions in increasing child physical activity: a systematic review and meta-analysis for policymakers and practitioners. Obes Rev. 2016;17(5):412–28. https://doi.org/10.1111/obr.12392.

    Article  CAS  PubMed  Google Scholar 

  56. Stecher C, Pfisterer B, Harden SM, Epstein D, Hirschmann JM, Wunsch K, et al. Assessing the pragmatic nature of mobile health interventions promoting physical activity: systematic review and meta-analysis. JMIR Mhealth Uhealth. 2023;11: e43162. https://doi.org/10.2196/43162.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Kennedy SG, Sanders T, Estabrooks PA, Smith JJ, Lonsdale C, Foster C, et al. Implementation at-scale of school-based physical activity interventions: a systematic review utilizing the RE-AIM framework. Obes Rev. 2021;22(7): e13184. https://doi.org/10.1111/obr.13184.

    Article  PubMed  Google Scholar 

  58. Baillie CPT, Galaviz KI, Emiry K, Bruner MW, Bruner BG, Lévesque L. Physical activity interventions to promote positive youth development among indigenous youth: a RE-AIM review. Transl Behav Med. 2017;7(1):43–51. https://doi.org/10.1007/s13142-016-0428-2.

    Article  PubMed  Google Scholar 

  59. McGoey T, Root Z, Bruner MW, Law B. Evaluation of physical activity interventions in youth via the Reach, Efficacy/Effectiveness, adoption, implementation, and maintenance (RE-AIM) framework: a systematic review of randomised and non-randomised trials. Prev Med. 2015;76:58–67. https://doi.org/10.1016/j.ypmed.2015.04.006.

    Article  PubMed  Google Scholar 

  60. Daly-Smith A, Quarmby T, Archbold VSJ, Routen AC, Morris JL, Gammon C, et al. Implementing physically active learning: future directions for research, policy, and practice. J Sport Health Sci. 2020;9(1):41–9. https://doi.org/10.1016/j.jshs.2019.05.007.

    Article  PubMed  Google Scholar 

  61. Kriemler S, Meyer U, Martin E, Sluijs EMFv, Andersen LB, Martin BW. Effect of school-based interventions on physical activity and fitness in children and adolescents: a review of reviews and systematic update. Br J Sports Med. 2011;45(11):923. https://doi.org/10.1136/bjsports-2011-090186.

    Article  CAS  PubMed  Google Scholar 

  62. Baugh Littlejohns L, Near E, McKee G, Rasali D, Naiman D, Faulkner G. A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach? Health Res Policy Sys. 2023;21(1):18. https://doi.org/10.1186/s12961-023-00961-3.

    Article  Google Scholar 

  63. Hawe P, Shiell A, Riley T. Theorising interventions as events in systems. Am J Community Psychol. 2009;43(3–4):267–76. https://doi.org/10.1007/s10464-009-9229-9.

    Article  PubMed  Google Scholar 

  64. Keshavarz N, Nutbeam D, Rowling L, Khavarpour F. Schools as social complex adaptive systems: a new way to understand the challenges of introducing the health promoting schools concept. Soc Sci Med. 2010;70(10):1467–74. https://doi.org/10.1016/j.socscimed.2010.01.034.

    Article  PubMed  Google Scholar 

  65. Meadows D. Leverage points: places to intervene in a system. Hartland, VT: The Sustainability Institute; 1999.

    Google Scholar 

  66. Arango-Paternina C, Watts-Fernández W, Brownson RC. Complex and system thinking in physical education and physical activity promotion. Educ Fis Dep. 2022;41(1):81–105. https://doi.org/10.17533/udea.efyd.e344232.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

The protocol and scoping review was not funded by any agency and was carried out independently by the authors.

Author information

Authors and Affiliations

  1. Instituto de Educación Física, Universidad de Antioquia, Carrera 75 Nº 65-87 - Bloque 45, Medellín, Colombia

    Jose Petro-Petro

  2. Departamento de Cultura Física, Universidad de Córdoba, Montería, Colombia

    Jose Petro-Petro

  3. Research Group on Physical Activity for Health (AFIS), Instituto Universitario de Educación Física y Deportes; Universidad de Antioquia, Ciudadela Robledo, Medellín, Colombia

    Carlos Mario Arango-Paternina, Fredy Alonso Patiño-Villada & Jhon Fredy Ramirez-Villada

  4. Prevention Research Center, Brown School, Washington University, St. Louis, MO, USA

    Ross C. Brownson

  5. Department of Surgery (Division of Public Health Sciences) and Alvin J. Siteman Cancer Center, Washington University School of Medicine; Washington University, St. Louis, MO, USA

    Ross C. Brownson

Authors
  1. Jose Petro-Petro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carlos Mario Arango-Paternina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fredy Alonso Patiño-Villada
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jhon Fredy Ramirez-Villada
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ross C. Brownson
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JP-P and CA-P: Acquisition of data. All authors: analysis and interpretation of data, drafting the article, final approval of the final version of the manuscript, and agreement to be accountable for all aspects of the manuscript.

Corresponding author

Correspondence to Jose Petro-Petro.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Petro-Petro, J., Arango-Paternina, C.M., Patiño-Villada, F.A. et al. Implementation processes of social network interventions for physical activity and sedentary behavior among children and adolescents: a scoping review. BMC Public Health 24, 1101 (2024). https://doi.org/10.1186/s12889-024-18615-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-024-18615-6

Keywords

BMC Public Health

ISSN: 1471-2458

Contact us