Investigating the relationship between place, social networks, and social capital for emerging adults: Study design and methods

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As such, place-based interventions are an increasingly accepted mainstay in public health, with a particular focus on disadvantaged communities. Health and wellbeing outcomes in these communities are influenced by access to interpersonal and organisational supports, among other ecological influences. This is particularly the case for emerging adults, who may have less ability to move between spaces to seek supports. In this paper we present the research design and methods of a study that aims to explore the relationship between community, social networks, and social capital, for emerging adults (aged 18–25) living in two Australian communities. Methods The study takes a mixed-methods approach combining a novel use of ego social network analysis with interpretative phenomenological analysis, compared across areas of contrasting geographic location and socioeconomic status. Discussion Prevention efforts which focus on place to improve health first need to examine the role of place in the lives of populations. Exploring the ways in which emerging adults interact with, and experience, their communities and support resources may shed light on structural and systemic issues which have long existed, but which have been recently highlighted on a global scale. Further, it may provide context for the way emerging adults seek health and other supports from local services, larger organisations, or other avenues. Emerging adults social networks place social capital bonding capital bridging capital linking capital social support ecological systems Figures Figure 1 Figure 2 Contributions to the Literature This protocol gives a detailed description of a non-routine comparative analysis across communities of contrasting socioeconomic advantage, an approach not commonly taken in social network research. This study will contribute to theoretical debates regarding the intersection of social structure (networks), individual agency (accessing social capital), and context (place of residence). The data collection will provide insight into how community, health, and support services across two areas of contrasting socioeconomic advantage are used and experienced by emerging adults, and how this impacts their health, wellbeing, and daily life. This knowledge could support the design or improvement of local services and resources. Background The ways in which people move through the world, and the relationships and resources which can facilitate or hinder this movement, is a topic of perpetual interest in public health and other related fields. In Australia, as with the rest of the world, access to healthcare, employment, education, and other fundamental human rights – collectively referred to as the social determinants of health – play a pivotal role in shaping individuals’ physical health, quality of life, and socioemotional wellbeing over the life course ( 1 – 3 ). The social determinants are inherently interdependent, each influencing the others in complex ways that ultimately impact both individual and population health outcomes. For example, educational attainment can directly influence opportunities for employment, which can in turn affect income levels and access to quality healthcare ( 4 ). While the importance of the social determinants of health has long been acknowledged, their significance was further highlighted by the COVID-19 pandemic. The effects of the pandemic drew attention to growing disparities in housing, food, education, and employment access across communities, and highlighted the impact of these disparities on population health and wellbeing ( 1 , 5 , 6 ). Evidence suggests these disparities disproportionately impacted those from already marginalised communities, including racial or ethnic minorities, those of low socioeconomic status, women and, notably, emerging adults – young people between the ages of 18 and 25 ( 5 – 10 ). This is a life stage in which people often explore the world and themselves, and emerging adults face frequent and turbulent changes to their self-image, their relationships, their knowledge, and their work ( 11 ). Prior to the pandemic, emerging adults were more likely to be unemployed, underemployed, or precariously employed than older adults, with many of them undertaking casual work ( 9 , 12 ). In fact, people in this age range made up nearly 40 per cent of Australia’s casual workforce in the years prior to the outbreak of COVID-19, and during the initial stages of the pandemic casual employees made up two thirds of all job losses in Australia ( 13 , 14 ). As such, emerging adults experienced more significant disruptions to employment as a result of the pandemic than older adults which, combined with the associated financial stress, resulted in a negative effect on their health and wellbeing ( 15 – 17 ). Given the multitude of societal and structural factors which influence health and wellbeing, it follows that where one lives can have a great impact on one’s ability to thrive ( 18 , 19 ). Place of residence has been linked to numerous outcomes such as physical health, depressed mood, and mortality ( 20 , 21 ). In some instances, wellbeing has been positively correlated with the presence of freely available green spaces, as well as being negatively correlated with a higher presence of housing disrepair ( 22 ). Moreover, the presence and quality of accessible infrastructure, such as stores and other places where people assemble, can have an impact on everyday wellbeing. These places, as with anywhere people interact, are subject to the constant and ever-changing interplay of human and non-human actors who can help or hinder the flourishing of others in these settings ( 23 ). While the impact of neighbourhood deprivation and place effects have been evidenced throughout the literature, there is some question as to the mechanism of influence; individual factors, or place of residence itself ( 21 ). This uncertainty exists in part due to the entwined relationship between place of residence and socioeconomic factors ( 21 ). Those with limited resources often cannot afford to live in more affluent or resource-rich areas, while living in these areas can also determine potential for upward or social mobility ( 24 ). It is therefore helpful to explore the connection between individuals and their neighbourhoods using a lens which accounts for the multitude of relationships which influence emerging adults in their day-to-day lives. One method of exploring and accounting for the complex relationships between individuals, their neighbourhoods, and other factors is the ecological theory of nested systems, also referred to as ecological systems theory ( 25 ). This theory understands influences on individuals as interacting, relational, complex systems which are reciprocally impacted by those who are impacted by them ( 25 – 27 ). Importantly, ecological systems theory accounts for points in time (through reference to the chronosystem), which allows for the consideration of major life events and disturbances, times of transition, and other temporal influences ( 28 ). This framework emphasises interrelationships at all levels, from the most immediate social environment to the broader sociocultural factors that influence an individual’s life. How emerging adults are connected to their local context informs the development of their social networks ( 28 , 29 ). These networks of relationships accumulate social capital which influences many aspects of health and wellbeing, from social support and education to loneliness and self-rated health ( 30 – 32 ). At its core, social capital refers to the resources, such as knowledge or social support, one can access through interpersonal interactions and community participation ( 33 ). For the purposes of this study, we focus on three types of social capital: bonding, bridging, and linking. Bonding capital refers to the relationships between people who share similarities, particularly those that result in close emotional relationships ( 34 – 36 ). Shallower, horizontal relationships with others in different groups to your own that allow you to bridge gaps in information or access are known as bridging capital ( 33 – 35 ). Finally, vertical relationships between people that are characterised by inherent power or authority gradients are referred to as linking capital ( 32 – 35 ). While there is consensus about the kinds of relationships which comprise bonding and bridging capital, there is some debate as to what constitutes linking capital ( 33 ). For example, some studies have drawn on the concept of linking capital to describe voting participation and other political interactions ( 37 – 40 ) whereas others see it as the interactions between people and institutional representatives such as bankers, police officers, doctors, and psychologists; relationships which have the ability to influence access to potentially life changing information and services on a direct, personal level ( 33 , 41 – 43 ). It is the latter conceptualisation which most closely aligns with the ecological and public health framing of this study. From the literature reviewed, a picture of influential and cyclical relationships between place of residence, social networks, and social capital is built for people across the lifespan, particularly when looking at individuals’ ability to not only survive, but also to thrive ( 28 , 29 , 33 , 44 ). It shines a light on the need to understand the supports and resources available to emerging adults in place( 16 , 45 ), as well as detailing some theoretical contradictions regarding the conceptualisations of social capital ( 21 , 33 ). Methods/Design Study aim and research questions This study aims to explore relationship between place of residence, social networks, and available or accessed social capital through the lived experience of emerging adults. To this end, this study will address the following questions: How do the social networks of emerging adults differ depending on the relative advantage or disadvantage of their place of residence? What types of social capital are available to emerging adults according to their social networks and place of residence? a. How, and under what conditions, do emerging adults access the social capital available to them? How do emerging adults experience their social networks within the context of their place of residence? Study context This study will be conducted in Melbourne, Australia. Metropolitan Melbourne was subject to the world’s longest lockdown periods during the height of the COVID-19 lockdown periods in 2020 and 2021 ( 46 ). During this time young people reported higher levels of anxiety and depression than others ( 47 ), and many communities faced challenges which highlighted the complex interplay of social network connections, social capital, health, and contextual vulnerabilities ( 48 ). This study received approval by the Victoria University Human Research Ethics Committee (VUHREC - HRE23-122). Study design A mixed methods comparative design will enable a comprehensive exploration of the lived experience of the relationship between place, social networks and social capital of emerging adults. To surface and understand lived experience, we draw on the ontological and epistemological tenets of social constructionism, which argues that the ‘reality’ of emerging adulthood is constructed through social interaction with people, values, and structures (49,50). Emerging adults form knowledge about the world through interactions that are socially and culturally situated and therefore require research methods designed to elicit such knowledge (shaped by social context) ( 50 , 51 ). Mixed-methods designs are often deployed in the investigation of complex, multi-faceted phenomena such as those which involve multiple intersecting spheres of influence ( 52 , 53 ). This study will examine the interrelationships between four constructs (place, networks, social capital, and emerging adulthood). It therefore necessitates the use of both quantitative and qualitative methods in order to create a comprehensive picture of the experiences and networks of emerging adults. To further examine the role of ‘place’, there will be a comparative component to the study. The mixed methods design will be implemented in two communities, allowing for a cross case comparative analysis of the role of place in the social networks of emerging adults. Sample The two communities of comparison, or local government areas (LGAs), chosen for this study are the City of Brimbank (an LGA in Melbourne’s west) and the City of Bayside (in Melbourne’s southeast). These communities were chosen based on their Socio-Economic Indexes for Areas (SEIFA) score. This score is generated using data gathered from the Australian national census ( 54 , 55 ). These LGAs not only are on opposite sides of the metropolis, they also sit at opposite ends of the SEIFA index ( 55 ). Figure 1 provides a visual representation of the aforementioned LGAs, with colours corresponding to their specific SEIFA index scores ( 56 ). Investigating contrasting LGAs will allow for a comparison of participants of similar socioeconomic statuses in contrasting communities. This approach builds on studies such as Browne-Yung et al (2013), which compared low-income participants living in contrasting socio-economic Australian suburbs approximately 40 kilometres apart. This study found that service providers, particularly medical practitioners, featured much more prominently in the social and health supports accessed by those living in lower socio-economic suburbs. Similarly, investigating geographically distinct and socioeconomically contrasting LGAs would allow for an exploration into service availability, the availability of different forms of capital (including different operationalisations of linking capital), and a direct comparison of similar individuals in different environments. Focusing on a single LGA could inadvertently result in the measurement of just the effects of socioeconomic status, rather than place. Additionally, support and other services are often found within LGA bounds, and therefore focus on a single LGA would limit the ability to examine differences in available capital in place. Participants and Recruitment This study aims to recruit emerging adults from both Brimbank and Bayside. Participants will be aged between 18 and 25, as per the definition of emerging adulthood, and will have lived within their current LGA for a minimum of a year. This is to minimise the possible effects of relocation, and to emphasise any place effects on participant networks and experiences. Guided by qualitative analysis standards, the proposed study will aim to recruit approximately 5 participants per LGA, as qualitative studies often reach data saturation once n = 10–20 ( 57 – 59 ). Purposeful criterion sampling will be employed, in which participants will be selected based on whether they meet criteria relevant to the research questions ( 58 ). These criteria include age ( 18 – 25 ), location (living in one of the two LGAs of inquiry), and duration of residence (minimum of one year in their current LGA). These criteria were chosen to ensure an accurate examination of the networks of emerging adults and the role place plays in these networks, while limiting extraneous variables related to displacement and isolation. Participants will be recruited through a combination of physical and online advertising. This advertising will be targeted to relevant local hubs (such as universities, libraries, and neighbourhood houses) as well as youth-focused newsletters and online fora. During the recruitment process prospective participants will be provided with a plain language information sheet, as well as a consent form reiterating their rights and expectations within the research process. Their suitability to participate in the study (as per participation requirement criteria) will be assessed during a pre-interview screening telephone call. At this point, participants will have the chance to ask any questions they have regarding the study, the research process, and their rights and expectations. Upon participants having a clear understanding of the study they will have the chance to provide verbal consent, as well as complete a digital consent form. Participants will be consenting to take part in two interviews, the process of which is detailed later in this paper. Participants will receive a $ 40 gift card after the completion of each interview (process outlined below) in recognition of their time. Financial incentives have been effectively used to reduce participant drop off during time-intensive research, as well as facilitating the involvement of marginalised participants who otherwise might not be able to take part ( 60 ). Data collection Phased semi-structured interviews will be used to obtain data, as they will provide participants greater confidentiality than other qualitative methods, such as focus groups ( 61 ). While surveys can be used to obtain information about social network data, they are not well suited to studies that privilege participants’ lived experiences. Semi-structured interviews are especially conducive to the proposed research as they allow for the inclusion of some closed-answer or other quantifiable questions ( 62 ). These interviews will be carried out in two parts: As shown in Fig. 2 , data collection and analysis will take place over three time points. Time one will involve data collection and immersion in Brimbank. During this time, participants from this LGA will take part in a social network interview, followed by a lived experience interview (as detailed later in this paper). Social network data will be preliminarily analysed to inform and adapt the lived experience interview. Following the conclusion of the lived experience interview, all data from the participant will be analysed. This process will be repeated for each Brimbank participant, after which point cross case analysis will be implemented; network maps and qualitative codes from each participant will be compared and contrasted in order to discern any experiential similarities or differences and build an LGA profile Once all data from Brimbank has been analysed, the data collection and immersion process will be repeated at Time two in Bayside, including cross-case analysis. At the completion of Time one and Time two there will exist two composite datasets: a Brimbank LGA profile and a Bayside LGA profile. These will then be comparatively analysed to tease out similarities and differences which may be the result of place-based factors. This phased approach to data collection will allow for the acquisition of detailed data regarding the structural nature of the social networks of young people, as well as provide important context as to what is otherwise a singular point-in-time data set ( 63 , 64 ). This greater context will build a more in-depth understanding of the interrelationship between place, social networks, social capital, and emerging adulthood than would otherwise be gleaned from a more singular approach. Such practice has the added benefit of an in-built participant validation, or member check, system in which interviewees can make changes to their network maps after the fact. This allows for a more co-created knowledge acquisition which centres the voices of emerging adults ( 65 ). Instrument Design Given the phased nature of this study, two semi-structured interview schedules were created: one comprising questions designed to elicit the ego social networks of participants (hereafter, the E-SNA protocol) and one comprising open-ended questions designed to elicit the experiences of participants navigating the relationship between place, social networks, and social capital (hereafter, the Lived Experience Protocol). A pilot study was conducted on a small sample of emerging adults living in Melbourne (n = 3) in order to fine tune both the interview guides and processes. The final procedure and materials outlined in this paper are the result of this testing. E-SNA Protocol Creation A five-domain interview schedule including 51 questions was created for use in the social network interview detailed later in this paper. These questions, informed by the literature as well as consultation with experts in the field and refined through piloting, are designed to generate the ego social networks of participants. The five domains included in this protocol are detailed in Table 1 . Table 1 E-SNA Protocol domains Domain Name Domain Description Example Question Structural Name Generators Questions which focus on the role of those within participant’s networks ( 66 ) Who do you speak to in your family? Social Capital Name Generators Questions which focus on the content of the exchange between participant and network member (alter) ( 66 ). Who do you share secrets with? Social Capital Organisation Generator Questions which focus on the content of the exchange between participant and organisations within their network, Are you involved with any organisations which provide you with health or other specialised advice? Name Interpreters Questions exploring the attributes of the alters within a network ( 66 ) What is the alter’s suburb of residence? Organisation Interpreters Questions exploring the attributes of the organisations within a network. Where is the organisation located? Along with these five domains, the social capital name and organisation generators shown in Table 1 consist of three subdomains based on the kinds of support that could be provided by network alters: emotional support, tangible support, and informational support. These subdomains illustrate the kinds of support which have been found to be important to youths and young adults, and which are present among conceptualisations of social and other capitals ( 66 , 67 ). In this context, emotional support refers to trusted positive relationships, tangible support refers to direct and practical ways of helping, and informational support refers to the provision of information or advice ( 67 ). Lived Experience Protocol Creation A four-domain interview schedule comprising 10 questions was loosely created for use in the phenomenological lived experience interview detailed later in this paper. These questions were designed to explore the experiences of emerging adults living in the Melbourne LGAs of Brimbank and Bayside paying particular attention to their social networks and, by virtue of this, their access to (and operationalisation of) social capital. Although a guideline has been created, questions within will be personalised and adapted depending on the outcome of each participant’s initial E-SNA interview. For example, if a the alters in a participant’s network are largely located outside of the participant’s home LGA, this may be explored during the lived experience interview. The four domains included in this protocol, centred around the concepts outlined in this study’s research questions, were informed by the literature and consultations with discipline experts, and refined through piloting. The domains outlined in the lived experience protocol are detailed in Table 2 . Table 2 Lived Experience Protocol Domains Domain Name Domain Description Example Question Place Questions which focus on the experience of living in their current LGA What is it like to live in [suburb of residence]? Emerging Adulthood Questions exploring the experience of becoming an adult Can you give me an example of a relationship that has changed since you became an adult? Social Capital and Support Questions exploring the helpfulness of relationships found in participants’ network maps Tell me about a time you’ve needed help from a person or organisation in your map. Factors Influencing Support Access Questions exploring social capital activation and reciprocity What influences the likelihood of you helping a person or organisation in your network when asked? Data analysis Recordings of each interview will be transcribed to enable both qualitative and quantitative analysis. Interview One: E-SNA Interview The first semi-structured interview will be informed by ego social network research and will employ a mix of traditional and novel social network analytic techniques. Ego social network analysis (E-SNA) is often used to explore the availability of social capital within networks and is therefore well suited to answering the research questions (Borgatti et al., 2013; Lin, 2005). This is in contrast with whole network analysis, which maps the relationships between all people within a context, such as a company or school ( 75 ). In both instances SNA is informed, in part, by theories of social capital ( 76 – 78 ). This field highlights the everyday or consistent social interactions such as those had with parents, friends, employers, or support services ( 79 , 80 ). Traditional social network analytic techniques such as name generators (open ended questions designed to elicit the names of people in a participant’s life), name interpreters (questions which gather demographic and other information about those in participants’ networks), and position generators (questions gathering data about the role, position, or utility of people previously identified) will be included in the interview schedule ( 75 , 76 ). Along with these traditional SNA techniques, this study will implement a novel analytical approach, akin to the standard resource and position generator explorations used to explore hierarchical relationships and access to social capital-related resources ( 66 , 76 ). Position generators explore the societal position of network actors by defining actors by their careers, while resource generators explore the availability of particular tangible resources from individuals within a network (for example, access to a car). In contrast, the current study proposes to integrate the two to explore hierarchical relationships with service providers and other organisations which influence the lives of emerging adults, as well as the availability of specific types of support from those (both interpersonal and organisational) within a network. For example, although participants may not have consistent contact with the same doctor, they may have consistent contact with the same medical clinic. As such, their health or willingness to seek medical treatment may be influenced by their overall experience with the clinic, and whether they feel they are supported by that organisation (or those working within its systems). During this initial interview social network software will be used create on-the-fly network maps. Doing this will allow participants to provide feedback in real time and will bring a spirit of collaboration to the interviews which does not always exist. These maps will be used two-fold; as a visual way to create conversation in the lived experience interviews, and as part of the quantitative social network analyses. Interview Two: Lived Experience Interview Traditional social network analysis does not necessarily allow for the investigation of exosystemic or field influences on relationships, however, the inclusion of qualitative data collection and analysis allows for such nuance to be obtained. Therefore, the second interview will utilise the network maps generated in interview one as a prompt for open-ended, phenomenological questions. The use of this visual may allow for relational patterns to be noticed and explored and enabling participants to provide more nuanced answers about the interaction between their place of residence, personal/professional and institutional relationships, and the ways in which they accrue or access social capital. Given the small sample size and the focus on individual experiences, data from the lived experience interviews will be analysed using interpretative phenomenological analysis (IPA), which is a method of qualitative analysis focusing on the way participants make sense of their social world ( 59 ). Table 3 describes in detail how the data collection and analysis methods will address the research questions which are the focus of this study. Table 3 How chosen methods address research questions RQ Question Data and Analysis 1 Do the social networks of emerging adults differ depending on the relative advantage or disadvantage of their place of residence? - Semi-structured interviews (n = 5 in each community) will generate data regarding the personal and support relationships of emerging adults. -The networks of emerging adults will be analysed using SNA. -The data from each community will be analysed separately and then compared to examine similarities and differences according to place of residence. 1.1 Do the social networks of emerging adults differ according to their size, quality, and diversity? -Data will include the number of people, supports, and institutions (alters) within participants’ networks. -Demographic data for participants and their alters will allow network diversity to be explored. -SNA will be used to examine the structural characteristics of networks -Participants’ experiences of their relationships will be gathered through semi-structured interview to explore network quality 2 What types of social capital are available to emerging adults according to their social networks and place or residence? -Semi-structured interviews (n = 5 in each community), will be analysed according to the three forms of social capital. -The way these forms of capital are present in each place-based subset of participants will be compared via SNA 2.1 How, and under what conditions, do emerging adults access the social capital available to them? -Semi-structured interviews (n = 5 in each community) will explore the way relationships are created, and social capital is accessed. -IPA will be used to explore the conditions in which participants access social capital. -Themes will be drawn from data from each community and then compared to examine similarities and differences according to place of residence. 3 How do emerging adults experience their social networks within the context of their place of residence? -IPA will be used to explore the impact of the lived experience of emerging adults and their social networks. Rigour and generalisability An integral part of qualitative research, and specifically IPA, is a focus on reflexivity. Creating and maintaining a continuous, consistent, process of research self-reflection allows for the recognition and restriction of personal experiences which may impact the research process ( 81 , 82 ). IPA, and other constructionist research, gives rise to personal contextual understandings of a given phenomenon. While such in-depth research is generally conducted on smaller samples, the process of analysis uncovers a wealth of data which can inform similar contexts ( 83 ). During the piloting process several time and feasibility constraints were highlighted (for example, unpredictable recruitment time). Given this, and the compounding influences from this study being undertaken as part of a PhD it is therefore unfeasible to extend the participant pool. However, the previously mentioned analyses will allow for logical inferences to be made regarding the relationship between place, social networks, and social capital for emerging adults ( 84 ). Discussion Emerging adults ( 18 – 25 ) have been disproportionately disadvantaged by the COVID-19 pandemic; a time in our recent history in which the importance of social networks, access to social capital, and connection to community was reinforced in health and public policy, and throughout the media. Understanding the way emerging adults experience and interact with their networks and local communities could illuminate systemic or structural factors which may help and/or harm the trajectory of their lives. Including health, support, and other organisations in an ego social network model may provide more explicit insight into where and how, and to what end, organisations exist in the networks of emerging adults. There are some challenges in the practical implementation of this study. Most notably, there is the feasibility of creating network maps in real time while being able to effectively conduct research interviews. Related to this, there is the feasibility of analysing these maps prior to conducting the second interviews with the same emerging adults. This process was tested and refined during the piloting phase. It is worth noting that participants may sometimes forget members of their networks ( 75 ). The presentation of individual network maps during the second interview will function as a second chance for participants to ensure they have reported everyone they feel should be included, as well as a prompt for the interview proper. In this way the study benefits from an in-built member checking system, as well as providing greater context to the network data ( 64 , 65 ). Social network analysis has been used within mixed-methods research designs to increasingly great effect across multiple disciplines ( 63 , 64 ). This study seeks to build off, and learn from, such studies whilst bringing a novel twist to the way ego social networks are considered within a local Australian milieu. As well, the focus on emerging adults will provide important context to the way relationships with individuals and organisations are being navigated and experienced by those who are beginning to interact with complex societal systems and renegotiate their relationships with themselves and others. This increased contextual understanding may shed light on the impact and efficacy of local health or support organisations and interventions. Abbreviations E-SNA Ego social network analysis SNA Social network analysis SEIFA Socio-economic indexes for areas IPA Interpretative Phenomenological Analysis LGA Local government area Declarations Ethics approval and consent to participate This study received ethics approval from the Victoria University Human Research Ethics Committee (VUHREC): HRE23-122. No participation has occurred as this study has not yet occurred. Consent for publication Not applicable Availability of data and materials Not applicable Competing interests The authors declare that they have no competing interests. Funding The authors received no funding to complete this article. Authors’ contributions EF, TR, and AM designed the study. EF led the writing of the manuscript. TR and AM contributed to the writing of the manuscript, providing critical feedback on all drafts. All authors read and approved the final manuscript. Acknowledgements This study design was developed with input and guidance from Dr Dan Chamberlain at La Trobe University. Author’s information (optional) Institute for Health and Sport, Victoria University, Melbourne, Australia.Erin Fitzpatrick, Therese Riley & Amy Mowle enAble Institute for Health Science, Curtin University, Perth, Australia Amy Mowle Corresponding Author Correspondence to Erin Fitzpatrick, [email protected] or [email protected] References Green H, Fernandez R, MacPhail C. Well-being and social determinants of health among Australian adults: A national cross-sectional study. Health Soc Care Community. 2022;30(6):2025–430. Wilkinson R, Marmot M. Social determinants of health: the solid facts. 2nd ed. Regional Office for Europe: World Health Organization; 2003. p. 31. World Health Organization. World Health Organization. 2023 [cited 2022 Oct 30]. Social determinants of health. Available from: https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1 Kawachi I, Adler NE, Dow WH. Money, schooling, and health: Mechanisms and causal evidence. N Y Acad Sci. 2010;1186(1):56–68. 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Interpretative phenomenological analysis: Theory, method and research. 1st ed. London: SAGE; 2012. p. 225. In J. Introduction of a pilot study. Korean J Anesthesiol. 2017;70(6):601–5. Majid MAA, Othman M, Mohamad SF, Lim S. Piloting for interviews in qualitative research: Operationalization and lessons learnt. Int J Acad Res Bus Soc Sci. 2017;7(4):1073–80. Malmqvist J, Hellberg K, Möllås G, Rose R, Shevlin M. Conducting the pilot study: A neglected part of the research process? Methodological findings supporting the importance of piloting in qualitative research studies. Int J Qual Methods. 2019;18. Turner DW. Qualitative interview design: A practical guide for novice investigators. Qual Rep. 2010;15(3):754–60. Golzar J, Noor S, Tajik O. Convenience sampling. Int J Educ Lang Stud. 2022;1(2):72–7. Shakir M, ur Rahman A. Conducting pilot study in a qualitative inquiry: Learning some useful lessons. J Posit Sch Psychol. 2022;6(10):1620–4. Borgatti SP, Everett MG, Johnson JC. Analyzing social networks. 1st ed. SAGE; 2013. Lin N. A network theory of social capital. Handbook on Social Capital. Oxford University Press; 2005. Lee M. Bringing the best of two worlds together for social capital research in education: Social network analysis and symbolic interactionism. Educ Res. 2014;43(9):454–64. Robins G. A tutorial on methods for the modeling and analysis of social network data. J Math Psychol. 2013;57:261–74. Borgatti SP, Halgin DS. On network theory. Organ Sci. 2011;1–14. Singh S. How should we study relational structure? Critically comparing the epistemological positions of social network analysis and field theory. Sociology. 2019;53(4):762–78. Dowling M. From Husserl to van Manen. A review of different phenomenological approaches. Int J Nurs Stud. 2007;44:131–42. Johnson JL, Adkins D, Chauvin S. A review of the quality indicators of rigor in qualitative research. Am J Pharm Educ. 2020;84(1):7120. Moon K, Blackman D. A guide to understanding social science research for natural scientists. Conserv Biol. 2014;28(5):1167–77. Polit DF, Beck CT. Generalization in quantitative and qualitative research: Myths and strategies. Int J Nurs Stud. 2010;47:1451–8. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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2","display":"","copyAsset":false,"role":"figure","size":455320,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7625138/v1/e1bdb7c6387a1ed42ee823a7.png"},{"id":94988315,"identity":"1bd3308c-0580-47fa-9728-e23301cf0c73","added_by":"auto","created_at":"2025-11-03 07:08:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1532210,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7625138/v1/8fb7aef7-d38e-443d-b544-b3eabcd03bd0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigating the relationship between place, social networks, and social capital for emerging adults: Study design and methods","fulltext":[{"header":"Contributions to the Literature","content":"\u003cul\u003e\n \u003cli\u003eThis protocol gives a detailed description of a non-routine comparative analysis across communities of contrasting socioeconomic advantage, an approach not commonly taken in social network research.\u003c/li\u003e\n \u003cli\u003eThis study will contribute to theoretical debates regarding the intersection of social structure (networks), individual agency (accessing social capital), and context (place of residence).\u003c/li\u003e\n \u003cli\u003eThe data collection will provide insight into how community, health, and support services across two areas of contrasting socioeconomic advantage are used and experienced by emerging adults, and how this impacts their health, wellbeing, and daily life. This knowledge could support the design or improvement of local services and resources.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eThe ways in which people move through the world, and the relationships and resources which can facilitate or hinder this movement, is a topic of perpetual interest in public health and other related fields. In Australia, as with the rest of the world, access to healthcare, employment, education, and other fundamental human rights \u0026ndash; collectively referred to as the social determinants of health \u0026ndash; play a pivotal role in shaping individuals\u0026rsquo; physical health, quality of life, and socioemotional wellbeing over the life course (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The social determinants are inherently interdependent, each influencing the others in complex ways that ultimately impact both individual and population health outcomes. For example, educational attainment can directly influence opportunities for employment, which can in turn affect income levels and access to quality healthcare (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). While the importance of the social determinants of health has long been acknowledged, their significance was further highlighted by the COVID-19 pandemic. The effects of the pandemic drew attention to growing disparities in housing, food, education, and employment access across communities, and highlighted the impact of these disparities on population health and wellbeing (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEvidence suggests these disparities disproportionately impacted those from already marginalised communities, including racial or ethnic minorities, those of low socioeconomic status, women and, notably, emerging adults \u0026ndash; young people between the ages of 18 and 25 (\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). This is a life stage in which people often explore the world and themselves, and emerging adults face frequent and turbulent changes to their self-image, their relationships, their knowledge, and their work (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Prior to the pandemic, emerging adults were more likely to be unemployed, underemployed, or precariously employed than older adults, with many of them undertaking casual work (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In fact, people in this age range made up nearly 40 per cent of Australia\u0026rsquo;s casual workforce in the years prior to the outbreak of COVID-19, and during the initial stages of the pandemic casual employees made up two thirds of all job losses in Australia (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). As such, emerging adults experienced more significant disruptions to employment as a result of the pandemic than older adults which, combined with the associated financial stress, resulted in a negative effect on their health and wellbeing (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGiven the multitude of societal and structural factors which influence health and wellbeing, it follows that where one lives can have a great impact on one\u0026rsquo;s ability to thrive (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Place of residence has been linked to numerous outcomes such as physical health, depressed mood, and mortality (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In some instances, wellbeing has been positively correlated with the presence of freely available green spaces, as well as being negatively correlated with a higher presence of housing disrepair (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Moreover, the presence and quality of accessible infrastructure, such as stores and other places where people assemble, can have an impact on everyday wellbeing. These places, as with anywhere people interact, are subject to the constant and ever-changing interplay of human and non-human actors who can help or hinder the flourishing of others in these settings (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile the impact of neighbourhood deprivation and place effects have been evidenced throughout the literature, there is some question as to the mechanism of influence; individual factors, or place of residence itself (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This uncertainty exists in part due to the entwined relationship between place of residence and socioeconomic factors (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Those with limited resources often cannot afford to live in more affluent or resource-rich areas, while living in these areas can also determine potential for upward or social mobility (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). It is therefore helpful to explore the connection between individuals and their neighbourhoods using a lens which accounts for the multitude of relationships which influence emerging adults in their day-to-day lives. One method of exploring and accounting for the complex relationships between individuals, their neighbourhoods, and other factors is the ecological theory of nested systems, also referred to as ecological systems theory (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This theory understands influences on individuals as interacting, relational, complex systems which are reciprocally impacted by those who are impacted by them (\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Importantly, ecological systems theory accounts for points in time (through reference to the chronosystem), which allows for the consideration of major life events and disturbances, times of transition, and other temporal influences (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). This framework emphasises interrelationships at all levels, from the most immediate social environment to the broader sociocultural factors that influence an individual\u0026rsquo;s life.\u003c/p\u003e\u003cp\u003eHow emerging adults are connected to their local context informs the development of their social networks (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). These networks of relationships accumulate social capital which influences many aspects of health and wellbeing, from social support and education to loneliness and self-rated health (\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). At its core, social capital refers to the resources, such as knowledge or social support, one can access through interpersonal interactions and community participation (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). For the purposes of this study, we focus on three types of social capital: bonding, bridging, and linking. Bonding capital refers to the relationships between people who share similarities, particularly those that result in close emotional relationships (\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Shallower, horizontal relationships with others in different groups to your own that allow you to bridge gaps in information or access are known as bridging capital (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Finally, vertical relationships between people that are characterised by inherent power or authority gradients are referred to as linking capital (\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). While there is consensus about the kinds of relationships which comprise bonding and bridging capital, there is some debate as to what constitutes linking capital (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). For example, some studies have drawn on the concept of linking capital to describe voting participation and other political interactions (\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) whereas others see it as the interactions between people and institutional representatives such as bankers, police officers, doctors, and psychologists; relationships which have the ability to influence access to potentially life changing information and services on a direct, personal level (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). It is the latter conceptualisation which most closely aligns with the ecological and public health framing of this study.\u003c/p\u003e\u003cp\u003eFrom the literature reviewed, a picture of influential and cyclical relationships between place of residence, social networks, and social capital is built for people across the lifespan, particularly when looking at individuals\u0026rsquo; ability to not only survive, but also to thrive (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). It shines a light on the need to understand the supports and resources available to emerging adults in place(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), as well as detailing some theoretical contradictions regarding the conceptualisations of social capital (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e"},{"header":"Methods/Design","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy aim and research questions\u003c/h2\u003e\u003cp\u003eThis study aims to explore relationship between place of residence, social networks, and available or accessed social capital through the lived experience of emerging adults.\u003c/p\u003e\u003cp\u003eTo this end, this study will address the following questions:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHow do the social networks of emerging adults differ depending on the relative advantage or disadvantage of their place of residence?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat types of social capital are available to emerging adults according to their social networks and place of residence?\u003c/p\u003e\u003cp\u003ea. How, and under what conditions, do emerging adults access the social capital available to them?\u003c/p\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHow do emerging adults experience their social networks within the context of their place of residence?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy context\u003c/h3\u003e\n\u003cp\u003eThis study will be conducted in Melbourne, Australia. Metropolitan Melbourne was subject to the world\u0026rsquo;s longest lockdown periods during the height of the COVID-19 lockdown periods in 2020 and 2021 (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). During this time young people reported higher levels of anxiety and depression than others (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), and many communities faced challenges which highlighted the complex interplay of social network connections, social capital, health, and contextual vulnerabilities (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e This study received approval by the Victoria University Human Research Ethics Committee (VUHREC - HRE23-122).\u003c/p\u003e\n\u003ch3\u003eStudy design\u003c/h3\u003e\n\u003cp\u003eA mixed methods comparative design will enable a comprehensive exploration of the lived experience of the relationship between place, social networks and social capital of emerging adults. To surface and understand lived experience, we draw on the ontological and epistemological tenets of social constructionism, which argues that the \u0026lsquo;reality\u0026rsquo; of emerging adulthood is constructed through social interaction with people, values, and structures (49,50). Emerging adults form knowledge about the world through interactions that are socially and culturally situated and therefore require research methods designed to elicit such knowledge (shaped by social context) (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMixed-methods designs are often deployed in the investigation of complex, multi-faceted phenomena such as those which involve multiple intersecting spheres of influence (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). This study will examine the interrelationships between four constructs (place, networks, social capital, and emerging adulthood). It therefore necessitates the use of both quantitative and qualitative methods in order to create a comprehensive picture of the experiences and networks of emerging adults.\u003c/p\u003e\u003cp\u003eTo further examine the role of \u0026lsquo;place\u0026rsquo;, there will be a comparative component to the study. The mixed methods design will be implemented in two communities, allowing for a cross case comparative analysis of the role of place in the social networks of emerging adults.\u003c/p\u003e\n\u003ch3\u003eSample\u003c/h3\u003e\n\u003cp\u003eThe two communities of comparison, or local government areas (LGAs), chosen for this study are the City of Brimbank (an LGA in Melbourne\u0026rsquo;s west) and the City of Bayside (in Melbourne\u0026rsquo;s southeast). These communities were chosen based on their Socio-Economic Indexes for Areas (SEIFA) score. This score is generated using data gathered from the Australian national census (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). These LGAs not only are on opposite sides of the metropolis, they also sit at opposite ends of the SEIFA index (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Figure\u0026nbsp;1 provides a visual representation of the aforementioned LGAs, with colours corresponding to their specific SEIFA index scores (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eInvestigating contrasting LGAs will allow for a comparison of participants of similar socioeconomic statuses in contrasting communities. This approach builds on studies such as Browne-Yung et al (2013), which compared low-income participants living in contrasting socio-economic Australian suburbs approximately 40 kilometres apart. This study found that service providers, particularly medical practitioners, featured much more prominently in the social and health supports accessed by those living in lower socio-economic suburbs. Similarly, investigating geographically distinct and socioeconomically contrasting LGAs would allow for an exploration into service availability, the availability of different forms of capital (including different operationalisations of linking capital), and a direct comparison of similar individuals in different environments. Focusing on a single LGA could inadvertently result in the measurement of just the effects of socioeconomic status, rather than place. Additionally, support and other services are often found within LGA bounds, and therefore focus on a single LGA would limit the ability to examine differences in available capital in place.\u003c/p\u003e\n\u003ch3\u003eParticipants and Recruitment\u003c/h3\u003e\n\u003cp\u003eThis study aims to recruit emerging adults from both Brimbank and Bayside. Participants will be aged between 18 and 25, as per the definition of emerging adulthood, and will have lived within their current LGA for a minimum of a year. This is to minimise the possible effects of relocation, and to emphasise any place effects on participant networks and experiences.\u003c/p\u003e\u003cp\u003eGuided by qualitative analysis standards, the proposed study will aim to recruit approximately 5 participants per LGA, as qualitative studies often reach data saturation once n\u0026thinsp;=\u0026thinsp;10\u0026ndash;20 (\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Purposeful criterion sampling will be employed, in which participants will be selected based on whether they meet criteria relevant to the research questions (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). These criteria include age (\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22 CR23 CR24\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), location (living in one of the two LGAs of inquiry), and duration of residence (minimum of one year in their current LGA). These criteria were chosen to ensure an accurate examination of the networks of emerging adults and the role place plays in these networks, while limiting extraneous variables related to displacement and isolation.\u003c/p\u003e\u003cp\u003eParticipants will be recruited through a combination of physical and online advertising. This advertising will be targeted to relevant local hubs (such as universities, libraries, and neighbourhood houses) as well as youth-focused newsletters and online fora. During the recruitment process prospective participants will be provided with a plain language information sheet, as well as a consent form reiterating their rights and expectations within the research process. Their suitability to participate in the study (as per participation requirement criteria) will be assessed during a pre-interview screening telephone call. At this point, participants will have the chance to ask any questions they have regarding the study, the research process, and their rights and expectations. Upon participants having a clear understanding of the study they will have the chance to provide verbal consent, as well as complete a digital consent form. Participants will be consenting to take part in two interviews, the process of which is detailed later in this paper. Participants will receive a \u003cspan\u003e$\u003c/span\u003e40 gift card after the completion of each interview (process outlined below) in recognition of their time. Financial incentives have been effectively used to reduce participant drop off during time-intensive research, as well as facilitating the involvement of marginalised participants who otherwise might not be able to take part (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData collection\u003c/h2\u003e\u003cp\u003ePhased semi-structured interviews will be used to obtain data, as they will provide participants greater confidentiality than other qualitative methods, such as focus groups (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). While surveys can be used to obtain information about social network data, they are not well suited to studies that privilege participants\u0026rsquo; lived experiences. Semi-structured interviews are especially conducive to the proposed research as they allow for the inclusion of some closed-answer or other quantifiable questions (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). These interviews will be carried out in two parts:\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"541\" height=\"300\"\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e, data collection and analysis will take place over three time points. Time one will involve data collection and immersion in Brimbank. During this time, participants from this LGA will take part in a social network interview, followed by a lived experience interview (as detailed later in this paper). Social network data will be preliminarily analysed to inform and adapt the lived experience interview. Following the conclusion of the lived experience interview, all data from the participant will be analysed. This process will be repeated for each Brimbank participant, after which point cross case analysis will be implemented; network maps and qualitative codes from each participant will be compared and contrasted in order to discern any experiential similarities or differences and build an LGA profile Once all data from Brimbank has been analysed, the data collection and immersion process will be repeated at Time two in Bayside, including cross-case analysis. At the completion of Time one and Time two there will exist two composite datasets: a Brimbank LGA profile and a Bayside LGA profile. These will then be comparatively analysed to tease out similarities and differences which may be the result of place-based factors.\u003c/p\u003e\u003cp\u003eThis phased approach to data collection will allow for the acquisition of detailed data regarding the structural nature of the social networks of young people, as well as provide important context as to what is otherwise a singular point-in-time data set (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). This greater context will build a more in-depth understanding of the interrelationship between place, social networks, social capital, and emerging adulthood than would otherwise be gleaned from a more singular approach. Such practice has the added benefit of an in-built participant validation, or member check, system in which interviewees can make changes to their network maps after the fact. This allows for a more co-created knowledge acquisition which centres the voices of emerging adults (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eInstrument Design\u003c/h3\u003e\n\u003cp\u003e Given the phased nature of this study, two semi-structured interview schedules were created: one comprising questions designed to elicit the ego social networks of participants (hereafter, the E-SNA protocol) and one comprising open-ended questions designed to elicit the experiences of participants navigating the relationship between place, social networks, and social capital (hereafter, the Lived Experience Protocol).\u003c/p\u003e\u003cp\u003eA pilot study was conducted on a small sample of emerging adults living in Melbourne (n\u0026thinsp;=\u0026thinsp;3) in order to fine tune both the interview guides and processes. The final procedure and materials outlined in this paper are the result of this testing.\u003c/p\u003e\n\u003ch3\u003eE-SNA Protocol Creation\u003c/h3\u003e\n\u003cp\u003eA five-domain interview schedule including 51 questions was created for use in the social network interview detailed later in this paper. These questions, informed by the literature as well as consultation with experts in the field and refined through piloting, are designed to generate the ego social networks of participants. The five domains included in this protocol are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eE-SNA Protocol domains\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDomain Description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExample Question\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStructural Name Generators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions which focus on the role of those within participant\u0026rsquo;s networks (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWho do you speak to in your family?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Capital Name Generators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions which focus on the content of the exchange between participant and network member (alter) (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWho do you share secrets with?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Capital Organisation Generator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions which focus on the content of the exchange between participant and organisations within their network,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAre you involved with any organisations which provide you with health or other specialised advice?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName Interpreters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions exploring the attributes of the alters within a network (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhat is the alter\u0026rsquo;s suburb of residence?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrganisation Interpreters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions exploring the attributes of the organisations within a network.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhere is the organisation located?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAlong with these five domains, the social capital name and organisation generators shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e consist of three subdomains based on the kinds of support that could be provided by network alters: emotional support, tangible support, and informational support. These subdomains illustrate the kinds of support which have been found to be important to youths and young adults, and which are present among conceptualisations of social and other capitals (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). In this context, emotional support refers to trusted positive relationships, tangible support refers to direct and practical ways of helping, and informational support refers to the provision of information or advice (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eLived Experience Protocol Creation\u003c/h2\u003e\u003cp\u003eA four-domain interview schedule comprising 10 questions was loosely created for use in the phenomenological lived experience interview detailed later in this paper. These questions were designed to explore the experiences of emerging adults living in the Melbourne LGAs of Brimbank and Bayside paying particular attention to their social networks and, by virtue of this, their access to (and operationalisation of) social capital. Although a guideline has been created, questions within will be personalised and adapted depending on the outcome of each participant\u0026rsquo;s initial E-SNA interview. For example, if a the alters in a participant\u0026rsquo;s network are largely located outside of the participant\u0026rsquo;s home LGA, this may be explored during the lived experience interview. The four domains included in this protocol, centred around the concepts outlined in this study\u0026rsquo;s research questions, were informed by the literature and consultations with discipline experts, and refined through piloting. The domains outlined in the lived experience protocol are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eLived Experience Protocol Domains\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDomain Description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExample Question\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions which focus on the experience of living in their current LGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhat is it like to live in [suburb of residence]?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmerging Adulthood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions exploring the experience of becoming an adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCan you give me an example of a relationship that has changed since you became an adult?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Capital and Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions exploring the helpfulness of relationships found in participants\u0026rsquo; network maps\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTell me about a time you\u0026rsquo;ve needed help from a person or organisation in your map.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactors Influencing Support Access\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestions exploring social capital activation and reciprocity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhat influences the likelihood of you helping a person or organisation in your network when asked?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eRecordings of each interview will be transcribed to enable both qualitative and quantitative analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eInterview One: E-SNA Interview\u003c/h2\u003e\u003cp\u003eThe first semi-structured interview will be informed by ego social network research and will employ a mix of traditional and novel social network analytic techniques. Ego social network analysis (E-SNA) is often used to explore the availability of social capital within networks and is therefore well suited to answering the research questions (Borgatti et al., 2013; Lin, 2005). This is in contrast with whole network analysis, which maps the relationships between all people within a context, such as a company or school (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). In both instances SNA is informed, in part, by theories of social capital (\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). This field highlights the everyday or consistent social interactions such as those had with parents, friends, employers, or support services (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Traditional social network analytic techniques such as name generators (open ended questions designed to elicit the names of people in a participant\u0026rsquo;s life), name interpreters (questions which gather demographic and other information about those in participants\u0026rsquo; networks), and position generators (questions gathering data about the role, position, or utility of people previously identified) will be included in the interview schedule (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlong with these traditional SNA techniques, this study will implement a novel analytical approach, akin to the standard resource and position generator explorations used to explore hierarchical relationships and access to social capital-related resources (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). Position generators explore the societal position of network actors by defining actors by their careers, while resource generators explore the availability of particular tangible resources from individuals within a network (for example, access to a car). In contrast, the current study proposes to integrate the two to explore hierarchical relationships with service providers and other organisations which influence the lives of emerging adults, as well as the availability of specific types of support from those (both interpersonal and organisational) within a network. For example, although participants may not have consistent contact with the same doctor, they may have consistent contact with the same medical clinic. As such, their health or willingness to seek medical treatment may be influenced by their overall experience with the clinic, and whether they feel they are supported by that organisation (or those working within its systems).\u003c/p\u003e\u003cp\u003eDuring this initial interview social network software will be used create on-the-fly network maps. Doing this will allow participants to provide feedback in real time and will bring a spirit of collaboration to the interviews which does not always exist. These maps will be used two-fold; as a visual way to create conversation in the lived experience interviews, and as part of the quantitative social network analyses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eInterview Two: Lived Experience Interview\u003c/h2\u003e\u003cp\u003eTraditional social network analysis does not necessarily allow for the investigation of exosystemic or field influences on relationships, however, the inclusion of qualitative data collection and analysis allows for such nuance to be obtained. Therefore, the second interview will utilise the network maps generated in interview one as a prompt for open-ended, phenomenological questions. The use of this visual may allow for relational patterns to be noticed and explored and enabling participants to provide more nuanced answers about the interaction between their place of residence, personal/professional and institutional relationships, and the ways in which they accrue or access social capital.\u003c/p\u003e\u003cp\u003eGiven the small sample size and the focus on individual experiences, data from the lived experience interviews will be analysed using interpretative phenomenological analysis (IPA), which is a method of qualitative analysis focusing on the way participants make sense of their social world (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e describes in detail how the data collection and analysis methods will address the research questions which are the focus of this study.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eHow chosen methods address research questions\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRQ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuestion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eData and Analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDo the social networks of emerging adults differ depending on the relative advantage or disadvantage of their place of residence?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e- Semi-structured interviews (n\u0026thinsp;=\u0026thinsp;5 in each community) will generate data regarding the personal and support relationships of emerging adults.\u003c/p\u003e\u003cp\u003e-The networks of emerging adults will be analysed using SNA.\u003c/p\u003e\u003cp\u003e-The data from each community will be analysed separately and then compared to examine similarities and differences according to place of residence.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDo the social networks of emerging adults differ according to their size, quality, and diversity?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-Data will include the number of people, supports, and institutions (alters) within participants\u0026rsquo; networks.\u003c/p\u003e\u003cp\u003e-Demographic data for participants and their alters will allow network diversity to be explored.\u003c/p\u003e\u003cp\u003e-SNA will be used to examine the structural characteristics of networks\u003c/p\u003e \u003cp\u003e-Participants\u0026rsquo; experiences of their relationships will be gathered through semi-structured interview to explore network quality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhat types of social capital are available to emerging adults according to their social networks and place or residence?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-Semi-structured interviews (n\u0026thinsp;=\u0026thinsp;5 in each community), will be analysed according to the three forms of social capital.\u003c/p\u003e \u003cp\u003e-The way these forms of capital are present in each place-based subset of participants will be compared via SNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHow, and under what conditions, do emerging adults access the social capital available to them?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-Semi-structured interviews (n\u0026thinsp;=\u0026thinsp;5 in each community) will explore the way relationships are created, and social capital is accessed.\u003c/p\u003e\u003cp\u003e-IPA will be used to explore the conditions in which participants access social capital.\u003c/p\u003e\u003cp\u003e-Themes will be drawn from data from each community and then compared to examine similarities and differences according to place of residence.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHow do emerging adults experience their social networks within the context of their place of residence?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-IPA will be used to explore the impact of the lived experience of emerging adults and their social networks.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003eRigour and generalisability\u003c/h2\u003e\u003cp\u003eAn integral part of qualitative research, and specifically IPA, is a focus on reflexivity. Creating and maintaining a continuous, consistent, process of research self-reflection allows for the recognition and restriction of personal experiences which may impact the research process (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIPA, and other constructionist research, gives rise to personal contextual understandings of a given phenomenon. While such in-depth research is generally conducted on smaller samples, the process of analysis uncovers a wealth of data which can inform similar contexts (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). During the piloting process several time and feasibility constraints were highlighted (for example, unpredictable recruitment time). Given this, and the compounding influences from this study being undertaken as part of a PhD it is therefore unfeasible to extend the participant pool. However, the previously mentioned analyses will allow for logical inferences to be made regarding the relationship between place, social networks, and social capital for emerging adults (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eEmerging adults (\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22 CR23 CR24\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) have been disproportionately disadvantaged by the COVID-19 pandemic; a time in our recent history in which the importance of social networks, access to social capital, and connection to community was reinforced in health and public policy, and throughout the media. Understanding the way emerging adults experience and interact with their networks and local communities could illuminate systemic or structural factors which may help and/or harm the trajectory of their lives. Including health, support, and other organisations in an ego social network model may provide more explicit insight into where and how, and to what end, organisations exist in the networks of emerging adults.\u003c/p\u003e\u003cp\u003eThere are some challenges in the practical implementation of this study. Most notably, there is the feasibility of creating network maps in real time while being able to effectively conduct research interviews. Related to this, there is the feasibility of analysing these maps prior to conducting the second interviews with the same emerging adults. This process was tested and refined during the piloting phase. It is worth noting that participants may sometimes forget members of their networks (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). The presentation of individual network maps during the second interview will function as a second chance for participants to ensure they have reported everyone they feel should be included, as well as a prompt for the interview proper. In this way the study benefits from an in-built member checking system, as well as providing greater context to the network data (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Social network analysis has been used within mixed-methods research designs to increasingly great effect across multiple disciplines (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). This study seeks to build off, and learn from, such studies whilst bringing a novel twist to the way ego social networks are considered within a local Australian milieu. As well, the focus on emerging adults will provide important context to the way relationships with individuals and organisations are being navigated and experienced by those who are beginning to interact with complex societal systems and renegotiate their relationships with themselves and others. This increased contextual understanding may shed light on the impact and efficacy of local health or support organisations and interventions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eE-SNA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEgo social network analysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSNA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSocial network analysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSEIFA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSocio-economic indexes for areas\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIPA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterpretative Phenomenological Analysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLGA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLocal government area\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study received ethics approval from the Victoria University Human Research Ethics Committee (VUHREC): HRE23-122. No participation has occurred as this study has not yet occurred.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors received no funding to complete this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eEF, TR, and AM designed the study. EF led the writing of the manuscript. TR and AM contributed to the writing of the manuscript, providing critical feedback on all drafts. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThis study design was developed with input and guidance from Dr Dan Chamberlain at La Trobe University.\u003c/p\u003e\n\u003cp\u003eAuthor\u0026rsquo;s information (optional)\u003c/p\u003e\n\u003cp\u003eInstitute for Health and Sport, Victoria University, Melbourne, Australia.Erin Fitzpatrick, Therese Riley \u0026amp; Amy Mowle\u003c/p\u003e\n\u003cp\u003eenAble Institute for Health Science, Curtin University, Perth, Australia Amy Mowle\u003c/p\u003e\n\u003cp\u003eCorresponding Author\u003c/p\u003e\n\u003cp\u003eCorrespondence to Erin Fitzpatrick, [email protected] or [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGreen H, Fernandez R, MacPhail C. Well-being and social determinants of health among Australian adults: A national cross-sectional study. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://methods.sagepub.com/book/social-network-analysis-for-ego-nets/\u003c/span\u003e\u003cspan address=\"https://methods.sagepub.com/book/social-network-analysis-for-ego-nets/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScales PC, Boat A, Pekel K. Defining and measuring social capital for young people: A practical review of the literature on resource-full relationships. Bill \u0026amp; Melinda Gates Foundation: Search Institute; 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith JA, Flowers P, Larkin M. Interpretative phenomenological analysis: Theory, method and research. 1st ed. London: SAGE; 2012. p. 225.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIn J. Introduction of a pilot study. 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Conserv Biol. 2014;28(5):1167\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePolit DF, Beck CT. Generalization in quantitative and qualitative research: Myths and strategies. Int J Nurs Stud. 2010;47:1451\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Emerging adults, social networks, place, social capital, bonding capital, bridging capital, linking capital, social support, ecological systems","lastPublishedDoi":"10.21203/rs.3.rs-7625138/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7625138/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePlace effects have long been understood to influence health and wellbeing outcomes. As such, place-based interventions are an increasingly accepted mainstay in public health, with a particular focus on disadvantaged communities. Health and wellbeing outcomes in these communities are influenced by access to interpersonal and organisational supports, among other ecological influences. This is particularly the case for emerging adults, who may have less ability to move between spaces to seek supports. In this paper we present the research design and methods of a study that aims to explore the relationship between community, social networks, and social capital, for emerging adults (aged 18\u0026ndash;25) living in two Australian communities.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study takes a mixed-methods approach combining a novel use of ego social network analysis with interpretative phenomenological analysis, compared across areas of contrasting geographic location and socioeconomic status.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDiscussion\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrevention efforts which focus on place to improve health first need to examine the role of place in the lives of populations. Exploring the ways in which emerging adults interact with, and experience, their communities and support resources may shed light on structural and systemic issues which have long existed, but which have been recently highlighted on a global scale. Further, it may provide context for the way emerging adults seek health and other supports from local services, larger organisations, or other avenues.\u003c/p\u003e","manuscriptTitle":"Investigating the relationship between place, social networks, and social capital for emerging adults: Study design and methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 02:20:02","doi":"10.21203/rs.3.rs-7625138/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9edca00c-7cf9-4a7f-ab41-b4de2d3a96c9","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-02T16:38:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 02:20:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7625138","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7625138","identity":"rs-7625138","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}