Digital Equity Is an Uphill Struggle

After years of efforts by public interest groups, the federal government made digital equity an explicit goal of infrastructure policy. Originally introduced in 2019 by Patty Murray (WA), the bill was reintroduced in 2021 and then embedded in the Infrastructure and Jobs Act of 2021. Its three programs will fund state digital equity planning ($60M), provide support to states for five years to advance digital equity programs and implement digital equity plans ($1.44B), and $1.25B for a competitive grant program in support of digital equity projects.

A proactive approach to digital equity was at odds with the neo-liberal and techno-utopian policy model pursued by democratic and republican administrations until recently. However, the COVID-19 pandemic drove home the point that digital inequalities continue to be pervasive. First identified almost thirty years ago by the National Telecommunications and Information Administration (NTIA), digital divides have stubbornly persisted. Mitigating them requires a keen understanding of their dynamic nature and a systemic approach toward effective mitigation.

The National Digital Inclusion Alliance defines digital equity as a “condition in which all individuals and communities have the information technology capacity needed for full participation in our society, democracy, and economy. Digital equity is necessary for civic and cultural participation, employment, lifelong learning, and access to essential services.” It operationalizes broadband equity as a state “when all people and communities are able to access and use affordable, high-speed, reliable internet that meets their long-term needs.”

Research commonly distinguishes three levels of digital divides: access, skills, and outcomes. Accelerating change in our increasingly digitally mediated lives opens a fourth, so far largely ignored, new fracture: the ability to adapt to new and emerging technologies and services. Each of these levels sits on the previous ones and they interact with each other. Moreover, digital divides have are heterogeneous, with many shapes and faces. They intersect with other socio-economic factors to form a rugged landscape of digital advantages and disadvantages.

Each level has multiple causes and raises unique challenges. Consequently, striving for digital equity requires differentiated, yet orchestrated responses. In mid-2022, a large fraction of households in the United States do not have access to high-speed Internet connectivity. The two main reasons are lack of infrastructure and affordability of broadband service and the devices needed to access it effectively. A third reason that was historically in play, that users do not see any need for broadband is on the decline.

The historical experience with telecommunications technologies offers a rich menu of policies that worked well to achieve universal service. Reverse auctions are one of the most effective methods to expand infrastructure to unserved, high-cost areas. Multiple firms compete to offer services in an area with the project going to the firm needing the lowest subsidy. Establishment of a sustainable mechanism to support access and affordability is another important element. The lack of such policies is a sign of policy failure rather than a lack of solutions.

Digital skills are critical to turn access to beneficial uses. In part, these skills develop as part of formal education and on-the-job training. Often, they emerge from playful engagement with the technology. Even though younger generations grow up digital, this does not assure they have the requisite skills. Adult and older populations raise additional challenges of developing basic and advanced skills. Digital navigators and programs such as Tech Goes Home, often collaborating with communities, offer models to develop digital skills across age groups.

Access and digital skills are not enough to achieve beneficial outcomes for individuals and communities. This requires additional, complementary efforts. Information technology is highly plastic and can support community wellbeing or to promote division and hatred. Advancing uses that benefit individuals and communities requires a high level of digital literacy that takes such community effects into account as far as possible. It also requires the design of human-centric devices, applications and services that do not exclude.

This takes us to the fourth, emerging level of digital divides. Not only is digital technology changing at an accelerating pace; devices and services increasingly form an invisible infrastructure of our lives (e.g., fitness trackers, face recognition, remote controlled appliances). Consequently, the potential impacts on privacy and security become increasingly opaque. This implies that acquired digital skills will become obsolete faster and require continuous updating. If the opportunities and skills to update knowledge are unevenly distributed, digital equity will suffer.

Achieving and sustaining digital equity requires a new, systemic approach. For example, to harness the benefits of digital technology in K-12 education, providing access and devices is only a first, and not a sufficient, step. Additional changes in the curriculum to emphasize digital skills, modifications in pedagogy to take full advantages of digital technology, training of caretakers, and an increased awareness of harms are all part of a successful digital equity policy.

The components of the digital ecosystem need to align with each other. Federal, state, regional, and local policy need to work together in new ways so that not every community needs to start from nothing. It requires working across functional and organizational boundaries in the private, non-profit, and public sectors. Finally, we need new metrics to assess the interactions between digital technology and community outcomes, such as health, safety and quality of life. Digital equity requires persistent, continuing efforts.

Sources

Bauer, J.M.; Hampton, K.N.; Fernandez, L.; Robertson, C., Overcoming Michigan’s Homework Gap: The Role of Broadband Internet Connectivity for Student Success and Career Outlooks (October 19, 2020). Quello Center Working Paper No. 06-20, Download from: https://ssrn.com/abstract=3714752 or http://dx.doi.org/10.2139/ssrn.3714752.

Hampton, K.N., Robertson, C.T., Fernandez, L., Shin, I., & Bauer, J.M. (2021). How Variation in Internet Access, Digital Skills, and Media Use are Related to Rural Student Outcomes: GPA, SAT, and Educational Aspirations. Telematics and Informatics, 101666, https://doi.org/10.1016/j.tele.2021.101666.

Hampton, K.N. and Shin, I. (2022). Excessive Social Media Use is Less Harmful than Disconnection for the Self Esteem of Rural Adolescents (June 2022). Quello Center Working Paper No. 06, 2022, Available at SSRN: https://ssrn.com/abstract=4136539 or http://dx.doi.org/10.2139/ssrn.4136539.

NDIA, The Words Behind Our Work: The Source for Definitions of Digital Inclusion Terms, https://www.digitalinclusion.org/definitions/, visited 31 July 2022.

van Dijk, J. (2020). The digital divide. Cambridge, UK: Polity Press.

The views articulated are those of the author.

Primary takeaways

Digital inequality shows larger impacts on youth academic performance as compared to time spent on screens.
Digital skills play a significant role in mediating unstructured online engagement (social media use, playing video games, browsing the web) and youth academic, social, and psychosocial development.
Unstructured online engagement and face-to-face social interaction are complementary and continuously interact to create and enhance youth capital outcomes.

A familiar story: concerns of screen time

Today’s discussions of adolescent well-being have coalesced around a clear narrative: teenagers spend too much time online, and their academic performance, mental health, and social lives are deteriorating as a result. A steady stream of academic papers, books, and op-eds, alongside a growing number of policy proposals––school phone bans, age-gated social media use, restrictive screen-time limits––rest on the same underlying claim, aligning with a contemporary, digitized version of the displacement hypothesis:

Screen time, particularly the unstructured, free-time spent on social media, gaming, watching video content, or browsing the web, is said to displace the productive face-to-face activities that build adolescents into capable adults.

The implied and often practiced solution is restriction. In response, this dissertation tested this claim directly, and placed it within the broader context of adolescence.

Across three years, I followed 653 Michigan adolescents from early through late adolescence: in grades 8 or 9 (survey one, 2019) to grades 11 or 12 (survey two, 2022). Notably, these students, studied over time, were part of a broader pooled sample of 5,825 students across the same eighteen highschools. The study window captured the year before and the year after the peak of the COVID-19 pandemic and related lockdown orders, functioning as an unprecedented stress test for theories of adolescent social, academic, and digital life and, importantly, as a benchmark to compare the effects of pandemic-related change and inequality to those effects from screen time alone.

Across four studies of adolescents, consisting of six cross-sectional and longitudinal analyses, findings are not consistent with the displacement narrative, nor the broader concerns about the time youth spend on screens.

Findings are, however, consistent with something the current public and (most) academic discussions have largely overlooked or ignored: the gaps and inequalities that determine whether adolescents can access and use the internet meaningfully in the first place.

What the displacement hypothesis overlooks

Displacement and related research and policy concerning the time young people spend online assumes a “zero-sum” model of adolescent day-to-day time. An hour online is an hour not spent studying, reading, sleeping, or interacting face-to-face (i.e., time spent on more productive or developmentally “better” activity).

Indeed, this makes sense logically. However, as an empirical claim, this model requires time spent online to behave differently from all other ways adolescents allocate time; it must produce uniquely negative outcomes and be inherently harmful across digital contexts, rather than the typical mix of trade-offs corresponding to, and often overlooked among any other social or developmental context.

Yet, online time does not differ from other youth activity. Instead, I find it has a mix of pros, cons, and even some “uniquely digital” benefits which youth utilize for social and academic gains. When I compared unstructured digital media use against traditional face-to-face interaction and activities, both produced similar patterns: some negative associations with academic outcomes, some null, and some positive.

Trade-offs within traditional face-to-face activity (for example, social time with friends and family, or time spent in after-school extracurriculars) are treated as ordinary developmental experiences that must be experienced for the betterment of development. The identical trade-offs involving digital time tend to be overlooked or ignored, and online engagement is perceived as altogether harmful.

A growing body of evidence, including this dissertation, do not support that distinction. Indeed, the developmental context is routinely misread, leaving out the context of the experiences and time spent on digital, as well as face-to-face activities, interactions, existing inequalities, and changes inherent to development. As such, I proposed a novel framework to understand these contexts:

Digital capital exchange

Rather than treating screen time as a unified harm, this dissertation advances an “exchange”-based framework, grounded in James Coleman’s theories of youth capital and digital inequality scholarship, particularly following Eszter Hargittai, Jan van Dijk, and Alexander van Deursen (see this list of all dissertation references for full works).

The core proposition is that adolescents’ online engagement is not an alternative to developmental activity but another, albiet modern domain through which young people accumulate and mobilize online resources––particularly digital skills––that work alongside existing social networks and experiences to be exchanged for human capital (measured as: academic achievement, aspirations, STEM interest) and social capital (peer networks, community participation, extracurricular involvement).

Online time is not the mechanism; instead, it is digital skills that I find to be the most vital component in youth capital exchange and enhancement. Unstructured online engagement contributes to online skills; those skills, accumulated and mobilized alongside existing peer, family, and community networks, translate into the outcomes researchers and parents care about, i.e., academic achievement, aspirations, and face-to-face interaction and social networks.

This digital capital framework treats online and in-person contexts as complementary rather than antagonistic, and it situates adolescents’ digital lives within the structural conditions––connectivity quality, device reliability, autonomy of use––that determine whether exchange can occur at all.

Methods (in brief)

Paper-and-pencil surveys were administered to students in classrooms at two time-points: spring 2019 (N=2,876) and spring 2022 (N=2,949), across the same eighteen predominantly rural Michigan schools, grades 8–12. Official, nationally-ranked standardized reading, writing, and math test scores (PSAT 8/9, PSAT 10, SAT; College Board) were then anonymously linked to students’ survey responses with the help of participating districts.

Cross-sectional path analyses modeled pooled and wave-specific samples (pooled N=5,825); two-wave cross-lagged panel models tested reciprocal, longitudinal relationships on the 653 students who completed both surveys. Multi-group analyses of the cross-lagged panel models compared relationships between girls (N=345) and boys (N=308). All longitudinal models included time-invariant socioeconomic covariates as well as time-varying covariates to reduce omitted-variable bias.

Key findings: an overview

To summarize, to the best of my ability, eight chapters across 376 pages, I present two primary findings:

First: digital inequality predicted larger and more consistent declines in human capital than screen time did.

Unreliable home internet and technology maintenance problems––experiencing and/or dealing with broken or outdated devices and software, restrictive school-issued hardware, issues with connecting to or maintaining internet access––decreased youth GPA and standardized test achievement. And, these effect sizes were substantially larger than any negative direct effect from unstructured digital media use.

Across all four empirical studies, digital inequality emerged as the most substantial predictor of academic and developmental decline.

Second: digital skills mediated the relationship between online time and adolescent academic and social outcomes.

Unstructured digital media use, particularly online gaming and web browsing, predicted higher internet and social media skills for adolescents, which in turn predicted stronger academic achievement and self-efficacy (human capital), and social interaction and extracurricular participation (social capital). The positive indirect effect of screen time through skills offset or exceeded any small negative direct effects across several outcomes (supporting our existing peer-reviewed work: Hales & Hampton, 2025, and which you can read more about here).

These exchange processes were amplified when peer and family networks were modeled alongside digital skills, consistent with the premise that online and offline contexts operate together rather than in competition. The effect was not universal: social media skills amplified rather than offset a negative association with consistency of interest, one of the two subscales of grit. The exchange framework describes a contextual and conditional, domain-specific mechanism, not a blanket defense of time spent online.

Implications

If digital inequality, and not screen time, is the primary predictor of adolescent academic and developmental decline, and still warrants concern regarding access quality and experience even with the broader adoption of digital devices across the United States, the current policy emphasis on restriction is pointed at the wrong target. The evidence supports a different set of priorities.

Stable, reliable home (fast) broadband should be treated as an educational prerequisite rather than a consumer amenity. Unreliable connectivity exerted larger downward pressure on human capital than any measure of screen time, and that pressure intensified during the pandemic-era reliance on digital infrastructure. Technology maintenance, device repair, replacement, technical support, and the flexibility to install software and explore the web autonomously, matters as much as initial access, and school-issued devices that restrict autonomous use appear to hinder skill accumulation rather than support it.

Restrictive parental mediation of internet use was negatively associated with grit and self-efficacy at magnitudes comparable to the positive contributions of face-to-face activity. This challenges the assumption that digital restriction functions protectively. Instructive mediation, teaching adolescents to verify information, navigate platforms critically, and mobilize online resources toward meaningful ends, is the posture the data supports.

Finally, the technical skill-building that occurs through gaming, self-directed exploration, and deep web use is skill-building, not wasted time. Closing the persistent gender gap in these domains likely requires legitimizing technical play for girls, rather than restricting it for everyone.

None of the above is an argument that screen time is benign. It is an argument that screen time is the wrong focus, particularly when studied mostly in isolation. Context matters substantially, whether that is time spent on other activities during adolescence, the period of adolescence itself, digital inequality, resources gained from such online use, and how all such factors interact. The factor that predicts whether a given adolescent can convert online engagement into capital outcomes is structural: access, infrastructure, skills, and the autonomy to use them. These factors are distributed unevenly, and its uneven distribution, not hours logged, is what separates adolescents who thrive from those who fall behind.

The full dissertation is available through Michigan State University’s ProQuest archive, or see the embedded full-text PDF below. I’m happy to share papers, preprints, or the underlying framework with anyone interested and working in this area––don’t hesitate to reach out via my contact form. Thanks for reading.

Tags: Blog Broadband Digital Equity Digital Inequality

Digital Equity Is an Uphill Struggle