Incorporating intersectionality into research design: an example using qualitative interviews

As intersectionality gains more prominence, scholars still face difficulties of incorporating principles of intersectionality into empirical research. Key concepts of intersectionality theory include moving away from additive thinking, relationality, and social constructionism. An important challenge is how to incorporate these concepts into research design. While existing scholarship examines intersectional methodology, most of the focus has been on issues of analysis not data collection. I argue that some of the difficulties in intersectionality scholarship are not just issues of analysis but issues of data collection. In particular, I discuss how scholars can incorporate intersectionality concepts into research design by offering examples from my own research that used qualitative interviews to examine how race and gender influenced neighborhood experiences. I also present the obstacles I encountered in conveying the key concepts of intersectionality into language that is relatable to study participants.     

The ethnosurvey in theory and practice

This article describes a research approach designed to overcome the limitations of federal immigration statistics and to illuminate the social processes underlying aggregate patterns of migration. The principal weaknesses of existing data sources are that they underenumerate and imperfectly measure undocumented migration; they do not reflect the widespread circularity of modern international movements; they omit variables central to the immigration process; and their cross-sectional collection and tabulation precludes the analysis of immigration as a dynamic process. The ethnosurvey is a research design that ameliorates these problems through 5 specific design features: multimethod data collection, representative multisite sampling, multilevel data compilation, life history collection, and parallel sampling. The ethnosurvey design is illustrated by its recent application to study Mexican migration to the US, and empirical evidence is presented to show how it corrects the limitations of federal data on immigration. In spite of its advantages, the ethnosurvey does have several drawbacks. It is costly and requires a substantial investment of professional time. Rather than emphasizing breadth of information, as does a representative sample survey, the ethnosurvey attempts to gather detailed information through intensive analysis of particular communities. The ethnosurvey, because of its costs and professional demands, is hard to implement within a representative sampling framework. For these reasons, the ethnosurvey is best seen as a supplement to other sources of immigration data, providing specialized information on the social processes that underlie the aggregate patterns revealed in national statistics. However, promising results obtained in applying the ethnosurvey to study immigration suggest that it may profitably be applied to investigate other longitudinal social processes as well, such as status attainment, occupational mobility, and residential mobility.     

The construction of communicative (in)competence in autism: a focus on methodological decisions

Research on people diagnosed with autism spectrum disorder (henceforth autism) is often based upon biomedical understanding. Such understanding tends to view the characteristics related to autism diagnosis, such as the lack of or atypical use of speech, as a sign of incompetence that can be reduced as an underlying pathology of an individual. However, little research has explicitly investigated how methodological decisions in research might influence the perception of these characteristics. This paper draws on two separate research cases involving minimally verbal children with autism to examine how methodological decisions in research design, data collection, data analysis, and data interpretation influence the construction of communicative (in)competence in these children. The paper encourages researchers to carefully consider and reflect on the methodological decisions they make throughout the research process.     

Hindsight,foresight and insight: The challenges of longitudinal qualitative research

This paper describes a UK based longitudinal qualitative study following approximately 100 young people over 9 years. It provides an overview of the research design, methods of data collection and analysis as well as reflecting on the strengths and weaknesses of the strategies employed. We focus on the value of a devolved research design, complementary cross-section and temporal analytic approaches and the effects of being involved in a longitudinal study on researchers and participants. The paper aims to contribute to a growing understanding of the practical, ethical and epistemological challenges presented by longitudinal qualitative methods, and highlights those challenges that are specific to this method as well as those which are amplified by this kind of approach.     

Dyadic Research in Marriage and Family Therapy: Methodological Considerations

With training that emphasizes relationship systems, marriage and family therapists are uniquely attuned to interpersonal dynamics, interdependence, and the influence of relationships on individuals’ perceptions, beliefs, and attitudes. While recent statistical advances have contributed to a proliferation of resources designed to introduce researchers to dyadic data analysis, guidelines related to the methodological aspects of dyadic research design have received less attention. Given the potential advantages of dyadic designs for examining couple and family relational and therapeutic processes, the purpose of this article is to introduce marriage and family therapy researchers to dyadic research methodology. Using examples from our own research, we discuss methodological considerations and lessons learned related to sampling, measurement, data collection, and ethics. Recommendations for future dyadic research are provided. Video Abstract     

Overview of the Chicago Study of Elderly Persons at Housing Risk

This chapter presents the basic approach and research design of the Chicago study which was directed at studying homelessness as one of many housing risks of the elderly. Both quantitative and qualititative methods of analysis utilized are described here, while a more detailed explanation of the process can be found in the Appendix. Data sources, sample selection methods, and data collection procedures are described, as well as the approach, methods and statistical tests used in the comparative analysis.     

Some insights related to social network analysis data collection challenges – a research note

This research note discusses opportunities and challenges of using online survey engines for social network analysis (SNA) data collection and assessing sample size and representativeness. The discussion is based on a case study of SNA data collection for a pilot research on health-relevant policy networks in Canada. Our approach demonstrates how to use generic online survey tools in long-term snowball sampling campaigns and how to compute population size estimates through capture–mark–recapture formulas, thus solving a significant methodological challenge of collecting snowball data for unbounded networks.     

Collecting experimental network data from interventions on critical links in workplace networks

This article describes and discusses challenges associated with interventionist network data gathering in organizational settings, with a special focus on dyadic interventions. While pointing out major risks of these approaches, we argue that collecting data in combination with dyadic network alteration methods can enable social network researchers to explore network mechanisms from a new angle and potentially benefit the members of the targeted social networks and the entire collectives, if certain research design and implementation principles are followed. We introduce a facilitated self-disclosure method for strengthening critical dyads in social networks in combination with longitudinal and retrospective network measurement. We assess the participants’ perceptions of the different stages of this process by qualitative interviews. The study illustrates that experimental network data collection includes some extra challenges in addition to the many challenges of observational network data collection but participants also reported practical benefits that would not be gained through observational network surveys alone. The results highlight the importance of early and continuous communication during the data collection process with all research participants, not just the management, and the benefits of sharing more of the preliminary results. The lessons learnt through this study can inform the design of experimental network data collection to prioritize the preferences of the participants and their benefits.     

The Swiss StudentLife Study: Investigating the emergence of an undergraduate community through dynamic,multidimensional social network data

The Swiss StudentLife Study (SSL Study) is a longitudinal social network data collection conducted in three undergraduate student cohorts (N₁ = 226, N₂ = 261, N₃ = 660) in 2016−2019. The main goal of the study was to understand the emergence of informal student communities and their effects on different individual outcomes, such as well-being, motivation, and academic success. To this end, multiple dimensions of social ties were assessed, combining computer-based surveys, social sensors, social media data, and field experiments. The dynamics of these social networks were measured on various time scales. In this paper, we present the design and data collection strategy of the SSL Study. We discuss practical challenges and solutions related to the data collection in four areas that were key to the success of our project: study design, research ethics, communication, and population definition.     

混合研究方法的方法论、研究策略及应用——以消费模式研究为例

近年来,定量定性相结合的研究方法在社会科学中广泛应用,但鲜有研究注意到其方法论含义并科学地选取研究策略。事实上,学术界对于定量定性方法的结合仍有争议,而且不同的结合方法背后的本体论和认识论的含义也不同,对于研究结论的意义和作用也不同。本文以中产阶级消费模式的研究为例,详细阐述了该研究使用混合研究方法的原因、目的、方法论、具体研究策略及其应用。文章使用定量和定性的研究发现说明了混合研究方法如何丰富和深化了研究结论,如何以具有代表性的样本为背景挖掘了消费生活的复杂性和多面性。     

Network Canvas: Key decisions in the design of an interviewer-assisted network data collection software suite

Self-reported social network analysis studies are often complex and burdensome, both during the interview process itself, and when conducting data management following the interview. Through funding obtained from the National Institute on Drug Abuse (NIDA/NIH), our team developed the Network Canvas suite of software – a set of complementary tools that are designed to simplify the collection and storage of complex social network data, with an emphasis on usability and accessibility across platforms and devices, and guided by the practical needs of researchers. The suite consists of three applications: Architect: an application for researchers to design and export interview protocols; Interviewer: a touch-optimized application for loading and administering interview protocols to study participants; and Server: an application for researchers to manage the interview deployment process and export their data for analysis. Together, they enable researchers with minimal technological expertise to access a complete research workflow, by building their own network interview protocols, deploying these protocols widely within a variety of contexts, and immediately attaining the resulting data from a secure central location. In this paper, we outline the critical decisions taken in developing this suite of tools for the network research community. We also describe the work which guides our decision-making, including prior experiences and key discovery events. We focus on key design choices, taken for theoretical, philosophical, and pragmatic reasons, and outline their strengths and limitations.     

The Neighborhood History Calendar: A Data Collection Method Designed for Dynamic Multilevel Modeling

This paper presents a new data collection method, called the Neighborhood History Calendar, designed to collect event histories of community-level changes over time. We discuss the need for and the uses of this method. We describe issues related to the design of instruments, collection of data, and data entry. We provide detailed examples from an application of this method to the study of marriage, contraception, and fertility in rural Nepal. The paper addresses applications of this same technique to other settings and research problems. We also extend the technique to collection of other forms of contextual-history data, including school histories and health service histories. Finally, we discuss how Geographic Information System (GIS) technology can be used to link together multiple sources of contextual-history data.     

Does the online collection of ego-centered network data reduce data quality? An experimental comparison

We analyze whether differences in kind and quality of ego-centered network data are related to whether the data are collected online or offline. We report the results of two studies. In the first study respondents could choose between filling out ego-centered data through a web questionnaire and being probed about their network in a personalized interview. The second study used a design in which respondents were allocated at random to either online or offline data collection. Our results show that the data quality suffers from the online data collection and the findings indicate that this is the consequence of the respondents answering “mechanically”. We conclude that network researchers should avoid to simply copy traditional network items into a web questionnaire. More research is needed about how new design elements specific for web questionnaires can motivate respondents to fill out network questions properly.     

Estimating the reliability and validity of personal support measures: full information ML estimation with planned incomplete data

Egocentered networks are common in social science research. Here, the unit of analysis is a respondent (ego) together with his/her personal network (alters). Usually, several variables are used to describe the relationship between egos and alters.In this paper, the aim is to estimate the reliability and validity of the averages of these measures by the multitrait–multimethod (MTMM) approach. This approach usually requires at least three repeated measurements (methods) of the same variable (trait) for model identification. This places a considerable burden on the respondent and increases the cost of data collection.In this paper, we use a split ballot MTMM experimental design, proposed by Saris (1999), in which separate groups of respondents get different combinations of just two methods. The design can also be regarded as having a planned missing data structure. The maximum likelihood estimation is used in the manner suggested by Allison (1987) of a confirmatory factor analysis model for MTMM-designs specified in Saris and Andrews (1991). This procedure is applied to social support data collected in the city of Ljubljana (Slovenia) in the year 2000.     

Pre-, post-, and longitudinal evaluation of juvenile justice education

This article describes two stages of the Juvenile Justice Educational Enhancement Program's pre-, post-, and longitudinal evaluation research. Pilot studies were used to explore how to design statewide research of pre- and postassessment scores and community reintegration outcomes. Preliminary findings suggest that higher performing educational programs produce greater educational gains as measured by academic achievement tests, credits earned, and pupil progression rates. The findings also indicate that these programs have more students returning to school and lower recidivism rates. Building on the pilot studies, refinements were made to the research designs to enable more comprehensive statewide evaluation. Current research includes collection of pre- and postassessment scores from official sources on approximately 16,000 juvenile justice youths. In addition, a research design has been developed to examine program effectiveness by measuring community reintegration variables. Multiple data sources, including official and self-reported data on family, school, employment, and subsequent crime involvement, will be used in the longitudinal study.     

Changing times: Migrants’ social network analysis and the challenges of longitudinal research

Focusing on migrant social networks, this paper draws upon the sociology of time to incorporate complex notions of temporality into the research process. In so doing, we consider firstly, the challenge of going ‘beyond the snapshot’ in data collection to capture dynamism through time. Secondly, we apply the concepts of timescapes to explore ways of addressing the wider context and the interplay between spatiality, temporality and relationality in migration research. We argue that integrating a mixed methods approach to SNA, crucially including visualisation, can provide a useful methodological and analytical framework to understand dynamics.SNA can also be helpful in bridging the personal and structural dimensions in migration research, by providing a meso level of analysis. However, it is also important to connect the investigation of local and transnational networks with an analysis of the broader social, economic and political contexts in which these take shape; in other words, connecting the micro and the meso with the wider macro level. Drawing upon reflections from our migration research studies, we argue that different combinations of quantitative, qualitative and visual methods do not just provide richer sets of data and insights, but can allow us to better connect conceptualisations – and ontologies – of social networks with specific methodological frameworks.     

Migration in Namibia: Combining Macro and Micro Approaches to Research Design and Analysis1

In adopting a framework that applies both macro and micro variables to the study of migration in Namibia, the analysis of the findings of the Namibia Migration Project emphasizes the utility of combining different scales and methods of data collection in terms of explaining migration dynamics and extending trends and patterns to future scenarios. It is argued that the contextual and explanatory macro factors such as political history, poverty, population, environment, epidemics and culture are crucial to the understanding and interpretation of the micro data collected through the standardized questionnaire survey and the case study material. Equally important is the iterative relationship that the macro/micro approach fosters in the research design and in the analysis of the data between the macro and micro scales of investigation.     

Time matters: the potential and pitfalls of using mixed methods approaches in longitudinal program evaluation

While social programs are often assessed using short-term impact studies, longitudinal designs allow evaluators to capture change over time, identify longer-term outcomes, adapt instruments, and better understand participants in transition. A mixed methods design can be critical in understanding these dynamics; yet there is a lack of literature exploring the practical considerations of planning and conducting qualitative and quantitative data collection and analysis within longitudinal studies. This paper examines two different mixed methods frameworks used in a 5-year evaluation of three youth entrepreneurship programs in East Africa. We show how the evaluation team dealt with unique challenges across methods and over time, and how the design ultimately facilitated a richer understanding of program impacts and processes. Considerations for conducting this type of study are explored, related to the impact of longevity on analysis and research staff. Successfully using a longitudinal mixed methods approach requires researchers to be strategic and reflexive, and work in close collaboration.     

Reflecting on participatory methodologies: research with parents of babies requiring neonatal care

This article concerns a study that examines the attitudes of parents, who have had babies in neonatal care, to sharing their babies’ routinely collected health data for research purposes. A participatory methodology was applied to the design of the study; a group of eleven parents who had all previously had babies in neonatal care were involved in designing a large-scale questionnaire survey. The article addresses the rationale for taking this approach, highlighting how it differs from the more common models of patient and public involvement. It presents the five themes that emerged from parents’ discussion in the course of engaging in the questionnaire design: legitimation, expertise, experiential knowledge, a different epistemology, power and control. How these shaped the design of the survey is employed in this article as a means of providing a commentary on the participatory research process itself. The article concludes by reflecting on whether participatory research can achieve its aims of promoting social justice when used for instrumental purposes such as the refinement of a data collection tool.