Session: Digital Traces: The Future of Data Collection for Social Work Research (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

All live presentations are in Eastern time zone.

206 Digital Traces: The Future of Data Collection for Social Work Research

Schedule:
Friday, January 22, 2021: 1:15 PM-2:15 PM
Cluster: Adolescent and Youth Development
Speakers/Presenters:
Lauren McInroy, PhD, The Ohio State University, Lauren Reed, PhD, Arizona State University, Jaime Booth, PhD, Https://Www.Socialwork.Pitt.Edu/ and Megan Lindsay Brown, PhD, Arizona State University
Social workers have always been concerned with protecting clients’ vulnerable and private information, challenging power dynamics of research/practitioner and client/participant, and constructing public discourse to leverage advocacy efforts. This roundtable will discuss the use of digital methods and outlets in social work research and advocacy. As stated by Markham (2014), individuals have a relationship to their information and as we seek out this information for research purposes, what do social workers offer beyond other disciplines? Through a discussion of the panel’s prior and ongoing projects, we will illustrate the dilemmas and opportunities of digital technologies. Each panelist will contribute their perspective on how digital technology can be harnessed ethically for research and still take full advantage of emergent technologies. Discussants will interrogate how the research process and the traditions of researcher authority can change to consider digital research processes that are relational and promote equitable data exchange. In a culture saturated with digital traces collected, stored, organized, and distributed for the purposes of surveillance capitalism, how can social work research actively push against the exploitation of information? This type of resistance requires pushing against the techno-utopianism often promoted by the culture of Silicon Valley. The following “proverbs� of Healey (2016) will guide the discussion amongst the panel. First, Information is not wisdom; Convergence is not integrity; and last Transparency is not authenticity.

Presenter 1 considers the lived experiences for women and technology, focusing on ways that online abuse exists in the context of gender-based violence. Her dissertation involved video chat interviews with young adult women, and she triangulated interviews with social media data. Upcoming projects include finding ways to encourage victim service providers to create contentious and ethical streams of service data to advocate for survivors.

Presenter 2 considers the impacts of digital technologies – particularly media production/consumption and niche global communities – the well-being of marginalized youth. She investigates how LGBTQ+ youth build supportive online communities to engage in identity development and foster resilience. She also specializes in digital intervention development and mixed-methods online research – including developing innovative methods for advancing ethical research and collecting complex qualitative data.

Presenter 3 adapted a widely used youth participatory research method for a virtual environment during the coronavirus pandemic. This work demonstrates the challenges of online community-based participatory data collection and the unique opportunity to engage youth participants in the research process using a methodology that has previously been rooted in physical proximity and interaction. She also has written on the ethics of doing online data collection on sexual violence with minors.

Presenter 4 has used mobile technology to engage youth in the mapping of activity spaces in their neighborhood. Youth responded to a brief survey three times a day about how they feel and their perception of the location to map spaces where youth felt supported and where they felt stressed. Data have also examined relationships between ambient stressor and substance use, providing a rationale and pathway forward for intervention at the neighborhood level.

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