Tessa Eagle, University of California Santa Cruz, California, USA teagle@ucsc.edu


My proposed dissertation work highlights social media as digitally-mediated support for neurodivergent individuals. By adopting a critical disability theory lens, I critique the techno-solutionism currently present in digital mental health care. I argue that existing social media platforms can provide community support for neurodivergent individuals to step away from the individualistic approaches currently promoted by much digital mental health technology. These social media-based communities are providing an important service of care and collective knowledge for individuals going through similar experiences to find validation and a sense of agency regarding treatment options. My research will further explore the relationships neurodivergent individuals have had with diagnostic and care systems, as well as ongoing tensions with healthcare providers in both physical and digital spaces.


Much of mental health care places the locus of change on individuals and their actions (e.g., taking medication, talk therapy, meditating) rather than focusing on addressing systemic issues or social support avenues. For many reasons, some individuals cannot access [19, 24, 37] or distrust the medical system [57] and instead have relied on community and low-cost technology-based support to varying levels of success [58]. In this proposed research agenda, I discuss the history and present state of mental health care and social and community-based mental health support for neurodivergent individuals.

Mental health care has a complex and problematic history that is fraught with ongoing ableism and tensions with disabled communities who have endured traumatic experiences and denial of agency at the hands of these systems. Recent work has pushed for the conceptualization of mental health conditions as psychosocial disabilities (e.g., anxiety, depression, etc) [51]. A psychosocial disability stems from diverse mental, cognitive, or emotional experiences that leads to impairment and experienced barriers [51]. Psychosocial disabilities remain stigmatized and our understanding of them is complicated by their potentially invisible or episodic (i.e., relapse periods) [51]. In attempts to address stigma, much technology has been developed for individual and private use [10, 25]. Tensions between the disabled and medical communities form the basis of my argument for peer-based support through informal channels such as social media. For my proposed work, I focus on social-based support for mental health, specifically in neurodivergent (ND) populations. Many neurodivergent individuals are unable to acquire appropriate accommodations and care due to differing diagnostic statuses which lead to difficulties in various aspects of their daily lives. Patient health communities and the benefits of peer support are well-known. Much technology for ND populations has followed the ableist medical view that such technology will “cure” these individuals rather than support them holistically. I discuss patients as experts of their lived experience and the necessity of privileging these experiences to promote autonomy when studying and designing for such populations.


Attention-Deficit Hyperactivity Disorder (ADHD), often diagnosed in childhood, is increasingly discussed on social media, leading some adults to later in life diagnoses or realizations [15]. In the United States, the Individuals with Disabilities Education Act (IDEA) and the Americans with Disabilities Act (ADA) ensures the protection of disabled people [1, 2, 4]. Having a formal diagnosis opens the door for receiving accommodations, treatment and support, a further reason to seek diagnosis beyond peace of mind and self-understanding. Due to the emergence of sub-communities within social networking sites such as Instagram, TikTok, and Twitter, many undiagnosed people are recognizing themselves in informational videos made by creators with ADHD, aiding in self-discovery of their own neurodivergence (Brains and cognitive functioning that diverge from societal norms [64]).

Sharing experiences with people that have gone through similar circumstances is vastly different than the patient-provider relationship, and can help community members find validation, acceptance of diagnosis, improve self-efficacy, and combat feelings of isolation [36, 44, 46]. The internet has allowed for group formation and been utilized within health communities, both on traditional standalone websites as well as on social media. Specialized communities have flourished on social media platforms, with a large number of groups devoted to mental health [5, 49]. These platforms are flexible and can be customized to ft community needs [28]. Individuals or families managing uncommon or rare conditions may come to rely on information and resources shared in OHCs due to insufficient resources provided by their care team [27, 32]. In these cases, patients and caregivers may have to take on the role of becoming an expert in medical knowledge regarding their condition [32]. Peers, whether online or in-person, have come to be seen by many as a valuable source of medical information when dealing with similar health experiences, promoting patients’ self-advocacy [55].

In the wake of the COVID-19 pandemic, many doctors took to social media to combat and teach strategies for users to recognize the massive influx of misinformation surrounding the virus [47, 67]. Research has described the importance of having healthcare providers and other trustworthy professionals on social media to ensure the scientific validity of disseminated information [8, 65]. However, some researchers have expressed concerns around the idea of doctors as influencers and the potential conflicts of interest than can arise from attempts to gain prominence [31]. Meanwhile, some doctors are hyper-aware of the impact they can have on users and the trust they feel toward different medical specialities [31]. Numerous studies express concerns around health misinformation on TikTok and the need for patient education beyond social media as an information source [34, 45, 68].

Participatory Design and Assistive Technology

Support for disability and psychosocial conditions can consist of a variety of systems (e.g., social support, medication, therapy, community-based avenues). Mankoff et al.’s 2010 paper makes the case for the need for assistive technology to be informed by critical disability studies. They note that the Medical Model provides a helpful lens for assistive technology researchers as it forefronts the “helplessness” of disabled individuals and their physical limitations that serve as design considerations that may provide concrete outcomes [38]. Technology designed for neurodivergent populations can be problematic if researchers are unaware of the history and current views within their community of interest for practices they are attempting to implement. A review of technology designed for autistic children found that the majority of the systems focused on teaching social skills and interaction that adhere to neurotypical standards of communication, ignoring that the children may have various other preferred methods of engaging [59]. This focus on correcting behavior fails to promote agency in autistic children and can, in fact, be extremely othering [59]. Not only is neurodivergence under-explored in HCI literature, but there is also a lack of diversity in conditions and age groups studied (with much focusing on autism) [60]. Finally, the authors note that this need of researchers to correct “deficits” contributes to techno-solutionism.

Disability is extremely complex and multifaceted and the lofty technology that is envisioned to “cure” disability can be misguided. Assistive technology and medical devices are life-changing for many [6, 40, 54]. However, technology is not the solution to every problem, and what we as researchers think of as problems in need of a cure may not be classified as such by disabled communities. As we can see, technology for use by disabled people is often created by non-disabled individuals [66]. Much of the work published within ACM venues highlights the benefits to family members of disabled individuals as well as society as a whole that can come from assistive tech relieving some perceived burden [66]. Research in HCI continues to perpetuate the idea that neurodivergent children and individuals are the ones that need to change to ft in society rather than examining and attempting to ease social stigma in order to accept a diverse range of behaviors [59, 66]. Disabled populations are not helpless, and it is crucial to not only give them a voice in ongoing research, but also, to involve them in every stage of the process to determine if certain research is even wanted or needed [66]. While technology can augment treatment or aid in symptom management, it is problematic to uphold technology as having the potential to be a universal remedy. Research and design of assistive technology should empower disabled individuals, something that is near impossible to achieve without direct inclusion of disabled voices.


My proposed work builds upon an initial and ongoing digital ethnography of ADHD communities on social media. To observe naturalistic interactions within informal ADHD communities on social media networks, we follow prior work in ACM by employing digital ethnography [9, 48, 50] to focus on the sub-communities of Instagram, TikTok, and Twitter. While each of these mediums allows for media sharing (i.e., photos and videos with written or spoken commentary), they tend to differ slightly in format and audience. I, therefore, propose looking at the ADHD communities across platforms for comparison. I have been conducting data collection and observations over the past year since Summer 2021 and have one paper under review so far from this data. Data collection happens on average 15-20 hours per week (TikTok - 7 hours, Twitter - 5 hours, and Instagram - 6 hours).

For future planned studies, data will be collected through surveys, interviews with clinicians, content creators and community members, and ethnographic observations of social media community spaces. This work primarily consists of qualitative data and will continue to be analyzed using an iterative and inductive approach following techniques similar to grounded theory, revisiting the data multiple times throughout the coding process [13]. Data will be analyzed for themes to provide insight into the support given and received by members of online ADHD communities as well as existing tensions between members and healthcare systems.


Attempts have been made to establish best practices for handling social media data, such as anonymizing posts and paraphrasing rather than including direct quotes [7, 23]. These considerations are especially important when dealing with sensitive disclosure around topics such as mental health and protecting the anonymity and rights of community members is crucial [12, 18]. Similarly, groups comprised of historically marginalized groups are especially concerned with privacy due to potential for harassment against their community [20].

Following social media ethics guidelines, I will avoid directly quoting posts and comments and exclude usernames outside of mentioning highly followed and well-known accounts posting ADHD-related content.


Throughout my research, I adopt a critical disability perspective that privileges the lived experiences of disabled and neurodivergent individuals. My background is in psychology and human computer interaction, and I have experience working with disabled individuals and people with psychosocial disabilities. I am a neurodivergent cisgender white woman and aim to be continually conscious of the privileges and biases this brings to my work.

Prior Work

My work to this point has focused on evaluating alternative methods for mental health support. There is a general lack of scientific evidence about popular mobile apps for mental health that is unlikely to change in the near future [42, 43, 63]. Randomized controlled trials take years to conduct, in contrast to the fast-moving deployment of industry-designed apps. Furthermore, there is reduced motivation for developers to provide such scientific evidence as mental health apps do not generally require FDA certification as they are often categorized as minimal risk [3, 29]. Apps can also have negative financial effects on users in need of help. Recent work of mine examined user reviews from the Google Play Store left on 40 different mental health apps with differing subscription schemes [22]. We found that three types of negative outcomes stem from the use of a “freemium” model. First, vulnerable users experiencing immediate crisis may download unhelpful or expensive apps. Second, misleading or incomplete descriptions written by app developers can lead to inappropriate treatments and expensive subscriptions. Finally, time-based offers and trials may result in incomplete treatments or unexpected charges.

Even prior to the pandemic, access to mental health care was a continual issue. People face numerous barriers to treatment including, but not limited to cost, provider availability [11], distance to providers, lack of providers, social stigma, and more [19, 30, 41]. Even with insurance coverage, certain rural areas have a limited number of providers, and patients are required to travel long distances to receive care [19]. Not only are people unable to access providers for talk therapy [11], but apps designed to help with mental health are underutilized and often lack implementation of complete validated techniques [33, 62]. My Master’s thesis work outlined the importance of alternative metrics for measuring the value of apps and other technology to support mental health [21]. Developers aiming to evaluate their apps often rely on standardized measures of mental health (e.g., the Patient Health Questionnaire 9-item Depression Inventory [35] or the Generalized Anxiety Disorder 7-item scale [61]) often used in clinical practice. These evaluations overlook experiential reasons for use and the long-term adherence potential of the app. Taking a more holistic view of app use allows us to determine if an app is effective AND if users will exhibit sustained use. By analyzing benefits perceived by users and documented in user reviews left on the Google Play Store, we were able to show the utility of self-report in discovering how apps support users in their goals [21]. While mental health care is clearly a broken system, there are alternative support options to traditional treatment avenues, notably, peer support and online communities. I now turn to a discussion of my current and future work on technology-mediated peer support, specifically for neurodivergent individuals. I approach a discussion of neurodiversity as a member of this community and delineate why community perspectives on research and care solutions are essential to consider.

Ongoing and Future Work

My current work explores social media sub-communities of individuals who identify as having ADHD. I focus on cantering people with lived experiences of ADHD, regardless of medical diagnosis. Recent work has promoted the viewing of lived experiences as valid and legitimate sources of knowledge within healthcare [56]. ADHD diagnosis is time-intensive, expensive, and historically difficult to access for women and people of color, potentially leading to traumatic medical experiences [14, 17, 39]. ADHD can often present comorbidly with other disorders, further complicating diagnosis [16, 26, 53]. The ADHD community acknowledges this difficulty and provides support whether or not one wants to pursue a diagnosis. While a diagnosis can be validating and provide further self-knowledge, identification and disclosure is not a prerequisite for receiving support or finding needed information on social media compared to in-person situations. One Instagram post on this desire for a “label” received likes close to 50,000 and had many in the comment section similarly noting that they simply want to know if and what is different about them or causing their challenges. In following these community norms, by privileging neurodivergent individuals we are able to learn how people provide support in these communities without gatekeeping community membership and to explore any tensions in the community around diagnosis and belonging.

An underlying tension within online ADHD communities stems from prior and current experiences with the medical system. For conditions like ADHD that are understudied in certain demographics the collective group knowledge can potentially be greater than some clinicians that are unfamiliar with varying presentation. Community members discuss the difficulty of the diagnostic process and how the steps required do not set people with ADHD up for success. Prior negative experiences and fear of not being taken seriously may preclude attempts to self-advocate and seek evaluation. However, a diagnosis is typically required to receive accommodations or certain medications, thus the medical community holds the power and authority. Clinical knowledge is always evolving, and it is important to keep and open-mind and dialogue with patients as equal partners rather than dismissing them without taking their concerns seriously. This is especially important for marginalized populations that are less likely to get support even if they want it. The role of healthcare provider is complex, and our goal is not to undermine or critique clinicians that are engaging in patient-centered care, more so we feel there is a larger issue when potential patients are unable to or are afraid of making an initial appointment.

Participation in social media platforms is increasingly common for healthcare providers. While many attempt to debunk misinformation and share educational content, their presence also requires wariness regarding conflicts of interest arising from attempts to gain followers and views [31]. It is important to consider the motivations behind larger accounts created by clinicians, when it is appropriate to bring medical experts into these spaces, and to what extent. Even healthcare providers’ content should be taken with a grain of salt, especially among people with ADHD who have had previous negative medical experiences.

ADHD communities can differ from traditional online health communities in that, while ADHD is a psychosocial disability, many people with ADHD do not have the resources to obtain a formal diagnosis or the support of medication or a clinical care team (as opposed to cancer or autoimmune OHCs, for example). Mental health effects and cannot be disentangled from our overall view of wellbeing, but individuals may be hesitant to apply labels to themselves when it comes to mental health. However, it is important to discuss health as a holistic view of both physical and mental well-being and to recognize mental health conditions as psychosocial disabilities [52]. Mental health care remains inaccessible to many, and despite being a medical issue, is still treated differently than more visible disabilities. People may be forced to seek out self-management solutions such as mental health mobile apps, online support groups, or potentially more harmful routes of self-medication. Technology may help individuals to disclose or accept their psychosocial disabilities, allowing them to gain access or support from people in similar situations. While many people practice self-management out of necessity, digital mental health communities and technologies are a viable alternative to the traditional medical framing of mental health care.

Research Questions

The historical but enduring view of people as being in need of a cure and exclusion of patient agency and opinions may be obscuring the fact that individuals are receiving support from alternative places such as through integration with their daily social media use. Perhaps we should be considering ways in which we can bring support to patients without asking them to complete extra steps when getting even small tasks done can feel overwhelming. The healthcare system and academic focus on individual solutions rather than peer support fails to acknowledge the need and benefits of interdependence and community membership. Informal online health communities have the potential to serve as easily accessible support systems and spaces for self-help seeking. Social media is a fairly stable constant in the lives of many individuals and does not require extra work on the part of the user if health-related content is available in this space they already exist in daily. Mental health apps, while prevalent and somewhat validated, require conscious effort and intrinsic motivation to engage with. Validated interventions have little meaning if users do not engage with them, and the siloing of mental health support on a separate app indicates the view that mental health is only one part of our everyday experience rather than something that affects most of our actions and daily activities.

My proposed dissertation work aims to explore the following questions through digital ethnography and interviews with community members:

Expected Contributions

Through my research I hope to provide support for the validity of peoples’ experiences with self-diagnosis and management of ADHD through knowledge gained from social media communities. One of my goals is to explore and consolidate suggestions for clinicians by community members on things they wish providers told them or knew about diagnosis and management of ADHD, especially in populations that are typically under-diagnosed. A third aim of my work is to investigate community member opinions on the inclusion of clinicians and healthcare providers in online communities for people with ADHD and bet practices for participation in a space that may be wary of such people. I believe I am uniquely qualified to carry out this work as a Neurodivergent HCI researcher with a background in clinical research, enabling me to speak to both sides of the room so to speak.


  1. [n. d.]. Individuals with Disabilities Education Act (IDEA). https://sites.ed.gov/ idea/
  2. ADA. 2021. Introduction to the Americans with Disabilities Act. https://beta. ada.gov/topics/intro-to-ada/
  3. James A. Armontrout, John Torous, Marsha Cohen, Dale E. McNiel, and Renée Binder. 2018. Current Regulation of Mobile Mental Health Applications. Journal of the American Academy of Psychiatry and the Law Online 46, 2 (June 2018), 204–211. https://doi.org/10.29158/JAAPL.003748-18 Publisher: Journal of the American Academy of Psychiatry and the Law Online Section: Regular Articles.
  4. Legal Aid at Work. [n. d.]. Disabilities in Higher Education. https:// legalaidatwork.org/factsheet/disabilities-in-higher-education/
  5. Sairam Balani and Munmun De Choudhury. 2015. Detecting and characterizing mental health related self-disclosure in social media. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems. 1373–1378.
  6. Valéria Baldassin, Helena Eri Shimizu, and Emerson Fachin-Martins. 2018. Computer assistive technology and associations with quality of life for individuals with spinal cord injury: a systematic review. Quality of Life Research 27, 3 (2018), 597–607.
  7. James Baldwin, Teresa Brunsdon, Jotham Gaudoin, and Laurence Hirsch. 2018. Towards a social media research methodology: Defining approaches and ethical concerns. International journal on advances in life sciences 10 (2018).
  8. Corey H Basch, Bhavya Yalamanchili, and Joseph Fera. 2022. # Climate change on TikTok: a content analysis of videos. Journal of community health 47, 1 (2022), 163–167.
  9. Tom Boellstorf, Bonnie Nardi, Celia Pearce, and Tina L Taylor. 2012. Ethnography and virtual worlds. In Ethnography and Virtual Worlds. Princeton University Press.
  10. Andrew D. Carlo, Reza Hosseini Ghomi, Brenna N. Renn, and Patricia A. Areán. 2019. By the numbers: ratings and utilization of behavioral health mobile applications. npj Digital Medicine 2, 1 (June 2019), 1–8. https://doi.org/10.1038/s41746- 019-0129-6 Number: 1 Publisher: Nature Publishing Group.
  11. Christina Caron. 2021. ‘Nobody Has Openings’: Mental Health Providers Struggle to Meet Demand. The New York Times (Feb. 2021). https://www.nytimes.com/ 2021/02/17/well/mind/therapy-appointments-shortages-pandemic.html
  12. Stevie Chancellor, Michael L Birnbaum, Eric D Caine, Vincent MB Silenzio, and Munmun De Choudhury. 2019. A taxonomy of ethical tensions in inferring mental health states from social media. In Proceedings of the conference on fairness, accountability, and transparency. 79–88.
  13. Kathy Charmaz. 2006. Constructing grounded theory: A practical guide through qualitative analysis. sage.
  14. Winston Chung, Sheng-Fang Jiang, Diana Paksarian, Aki Nikolaidis, F Xavier Castellanos, Kathleen R Merikangas, and Michael P Milham. 2019. Trends in the prevalence and incidence of attention-deficit/hyperactivity disorder among adults and children of different racial and ethnic groups. JAMA network open 2, 11 (2019), e1914344–e1914344.
  15. Nicole Clark. 2021. No One’s Ever Talked to Me About This Before. New York Times (May 2021). https://www.nytimes.com/2021/05/24/style/adhd-onlinecreators-diagnosis.html
  16. T Clark, C Feehan, C Tinline, and P Vostanis. 1999. Autistic symptoms in children with attention deficit-hyperactivity disorder. European child & adolescent psychiatry 8, 1 (1999), 50–55.
  17. Tumaini R Coker, Marc N Elliott, Sara L Toomey, David C Schwebel, Paula Cuccaro, Susan Tortolero Emery, Susan L Davies, Susanna N Visser, and Mark A Schuster. 2016. Racial and ethnic disparities in ADHD diagnosis and treatment. Pediatrics 138, 3 (2016).
  18. Munmun De Choudhury, Emre Kiciman, Mark Dredze, Glen Coppersmith, and Mrinal Kumar. 2016. Discovering shifts to suicidal ideation from mental health content in social media. In Proceedings of the 2016 CHI conference on human factors in computing systems. 2098–2110.
  19. N. Douthit, S. Kiv, T. Dwolatzky, and S. Biswas. 2015. Exposing some important barriers to health care access in the rural USA. Public Health 129, 6 (June 2015), 611–620. https://doi.org/10.1016/j.puhe.2015.04.001
  20. Brianna Dym and Casey Fiesler. 2020. Ethical and Privacy Considerations for Research Using Online Fandom Data. Transformative works and cultures 33 (2020).
  21. Tessa Eagle. 2021. “Like Talking to a Person”: User-Perceived Benefits of Mental Health and Wellness Mobile Apps. Master’s Thesis. UC Santa Cruz.
  22. Tessa Eagle, Aman Mehrotra, Aayush Sharma, Alex Zuniga, and Steve Whittaker. 2022. “Money Doesn’t Buy You Happiness”: Exploring Financial Predation in Freemium Mental Health Apps. In Proceedings of the ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW ’22). Association for Computing Machinery.
  23. Casey Fiesler and Nicholas Proferes. 2018. “Participant” perceptions of Twitter research ethics. Social Media+ Society 4, 1 (2018), 2056305118763366.
  24. Blandine French, Elvira Perez Vallejos, Kapil Sayal, and David Daley. 2020. Awareness of ADHD in primary care: stakeholder perspectives. BMC family practice 21, 1 (2020), 1–13.
  25. Sandra Garrido, Chris Millington, Daniel Cheers, Katherine Boydell, Emery Schubert, Tanya Meade, and Quang Vinh Nguyen. 2019. What works and what doesn’t work? A systematic review of digital mental health interventions for depression and anxiety in young people. Frontiers in psychiatry 10 (2019), 759.
  26. Daniel Geller, Carter Petty, Fe Vivas, Jessica Johnson, David Pauls, and Joseph Biederman. 2007. Examining the relationship between obsessive-compulsive disorder and attention-deficit/hyperactivity disorder in children and adolescents: a familial risk analysis. Biological Psychiatry 61, 3 (2007), 316–321.
  27. Tonje Gundersen. 2011. ‘One wants to know what a chromosome is’: the internet as a coping resource when adjusting to life parenting a child with a rare genetic disorder. Sociology of health & illness 33, 1 (2011), 81–95.
  28. Michele P Hamm, Annabritt Chisholm, Jocelyn Shulhan, Andrea Milne, Shannon D Scott, Lisa M Given, and Lisa Hartling. 2013. Social media use among patients and caregivers: a scoping review. BMJ open 3, 5 (2013), e002819.
  29. Center for Devices and Radiological Health. 2019. How to Determine if Your Product is a Medical Device. FDA (Dec. 2019). https://www.fda.gov/medical-devices/ classify-your-medical-device/how-determine-if-your-product-medical-device Publisher: FDA.
  30. M. Courtney Hughes, Jack M. Gorman, Yingqian Ren, Sana Khalid, and Carol Clayton. 2019. Increasing access to rural mental health care using hybrid care that includes telepsychiatry. Journal of Rural Mental Health 43, 1 (2019), 30–37. https://doi.org/10.1037/rmh0000110 Place: US Publisher: Educational Publishing Foundation.
  31. K. C. Ifeanyi. 2022. Your doctor is moonlighting on TikTok as an influencer. https://www.fastcompany.com/90735760/your-doctor-is-moonlightingon-tiktok-as-an-infuencer
  32. Maia Jacobs, Galina Gheihman, Krzysztof Z Gajos, and Anoopum S Gupta. 2019. " I think we know more than our doctors" How Primary Caregivers Manage Care Teams with Limited Disease-related Expertise. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1–22.
  33. Sarah J. Kertz, J. MacLaren Kelly, Kimberly T. Stevens, Matthew Schrock, and Sara B. Danitz. 2017. A Review of Free iPhone Applications Designed to Target Anxiety and Worry. Journal of Technology in Behavioral Science 2, 2 (June 2017), 61–70. https://doi.org/10.1007/s41347-016-0006-y
  34. Wenwen Kong, Shijie Song, Yuxiang Chris Zhao, Qinghua Zhu, Ling Sha, et al. 2021. TikTok as a health information source: assessment of the quality of information in diabetes-related Videos. Journal of Medical Internet Research 23, 9 (2021), e30409.
  35. Kurt Kroenke, Robert L Spitzer, and Janet B W Williams. 2001. The PHQ-9. Journal of General Internal Medicine 16, 9 (Sept. 2001), 606–613. https://doi.org/ 10.1046/j.1525-1497.2001.016009606.x
  36. Dandan Liang, Ruiying Jia, Xiang Zhou, Guangli Lu, Zhen Wu, Jingfen Yu, Zihui Wang, Haitao Huang, Jieyu Guo, and Chaoran Chen. 2021. The effectiveness of peer support on self-efficacy and self-management in people with type 2 diabetes: A meta-analysis. Patient Education and Counseling 104, 4 (2021), 760–769.
  37. Kathrine Bang Madsen, Annette Kjær Ersbøll, Jørn Olsen, Erik Parner, and Carsten Obel. 2015. Geographic analysis of the variation in the incidence of ADHD in a country with free access to healthcare: a Danish cohort study. International journal of health geographics 14, 1 (2015), 1–13.
  38. Jennifer Mankof, Gillian R. Hayes, and Devva Kasnitz. 2010. Disability studies as a source of critical inquiry for the field of assistive technology. In Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility - ASSETS ’10. ACM Press, Orlando, Florida, USA, 3. https://doi.org/10.1145/ 1878803.1878807
  39. Louis S Matza, Clark Paramore, and Manishi Prasad. 2005. A review of the economic burden of ADHD. Cost effectiveness and resource allocation 3, 1 (2005), 1–9.
  40. Birger Mo, Morten Lindbæk, and Sten Harris. 2005. Cochlear implants and quality of life: a prospective study. Ear and hearing 26, 2 (2005), 186–194.
  41. Finiki A. Nearchou, Niamh Bird, Audrey Costello, Sophie Duggan, Jessica Gilroy, Roisin Long, Laura McHugh, and Eilis Hennessy. 2018. Personal and perceived public mental-health stigma as predictors of help-seeking intentions in adolescents. Journal of Adolescence 66 (July 2018), 83–90. https://doi.org/10.1016/j. adolescence.2018.05.003
  42. Martha Neary and Stephen M. Schueller. 2018. State of the Field of Mental Health Apps. Cognitive and Behavioral Practice 25, 4 (Nov. 2018), 531–537. https: //doi.org/10.1016/j.cbpra.2018.01.002
  43. Jennifer Nicholas, Mark Erik Larsen, Judith Proudfoot, and Helen Christensen. 2015. Mobile Apps for Bipolar Disorder: A Systematic Review of Features and Content Quality. Journal of Medical Internet Research 17, 8 (2015), e198. https: //doi.org/10.2196/jmir.4581 Company: Journal of Medical Internet Research Distributor: Journal of Medical Internet Research Institution: Journal of Medical Internet Research Label: Journal of Medical Internet Research Publisher: JMIR Publications Inc., Toronto, Canada.
  44. Craig A Olsson, Mark F Boyce, John W Toumbourou, and Susan M Sawyer. 2005. The role of peer support in facilitating psychosocial adjustment to chronic illness in adolescence. Clinical Child Psychology and Psychiatry 10, 1 (2005), 78–87.
  45. Anjali Om, Bobby Ijeoma, Sara Kebede, and Albert Losken. 2021. Analyzing the quality of aesthetic surgery procedure videos on TikTok. Aesthetic surgery journal 41, 12 (2021), 2078–2083.
  46. Siobhan Bernadette Laura O’Connell, Eden Noah Gelgoot, Paul Henry Grunberg, Joy Schinazi, Deborah Da Costa, Cindy-Lee Dennis, Zeev Rosberger, and Phyllis Zelkowitz. 2021. ‘I felt less alone knowing I could contribute to the forum’: psychological distress and use of an online infertility peer support forum. Health Psychology and Behavioral Medicine 9, 1 (2021), 128–148.
  47. Christian Paz. 2022. When Your Doctor Is on TikTok. https://www.theatlantic. com/politics/archive/2022/01/tiktok-doctors-debunking-pandemic-lies/621346/ Section: Politics.
  48. Celia Pearce. 2011. Communities of play: Emergent cultures in multiplayer games and virtual worlds. MIT press.
  49. Julie Prescott, Amy Leigh Rathbone, and Gill Brown. 2020. Online peer to peer support: Qualitative analysis of UK and US open mental health Facebook groups. Digital Health 6 (2020), 2055207620979209.
  50. Kathryn E Ringland. 2019. A place to play: the (dis) abled embodied experience for autistic children in online spaces. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. 1–14.
  51. Kathryn E. Ringland, Jennifer Nicholas, Rachel Kornfeld, Emily G. Lattie, David C. Mohr, and Madhu Reddy. 2019. Understanding Mental Ill-health as Psychosocial Disability: Implications for Assistive Technology. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility. ACM, Pittsburgh PA USA, 156–170. https://doi.org/10.1145/3308561.3353785
  52. Kathryn E Ringland, Jennifer Nicholas, Rachel Kornfeld, Emily G Lattie, David C Mohr, and Madhu Reddy. 2019. Understanding mental ill-health as psychosocial disability: Implications for assistive technology. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility. 156–170.
  53. Angelica Ronald, Emily Simonof, Jonna Kuntsi, Philip Asherson, and Robert Plomin. 2008. Evidence for overlapping genetic influences on autistic and ADHD behaviours in a community twin sample. Journal of Child psychology and Psychiatry 49, 5 (2008), 535–542.
  54. Yotam Rosner and Amotz Perlman. 2018. The effect of the usage of computer based assistive devices on the functioning and quality of life of individuals who are blind or have low vision. Journal of Visual Impairment & Blindness 112, 1 (2018), 87–99.
  55. Nicole Ruggiano, Karen Whiteman, and Natalia Shtompel. 2016. “If I Don’t Like the Way I Feel With a Certain Drug, I’ll Tell Them.” Older Adults’ Experiences With Self-Determination and Health Self-Advocacy. Journal of Applied Gerontology 35, 4 (2016), 401–420.
  56. Jennifer CH Sebring. 2021. Towards a sociological understanding of medical gaslighting in western health care. Sociology of Health & Illness (2021).
  57. Jennifer C. H. Sebring. 2021. Towards a sociological understanding of medical gaslighting in western health care. Sociology of Health & Illness 43, 9 (Nov. 2021), 1951–1964. https://doi.org/10.1111/1467-9566.13367
  58. Kendall Soucie, Kenzie Tapp, Jasmine Kobrosli, Marissa Rakus, Rachel Katzman, Kristin Schramer, Tanja Samardzic, Noelle Citron, and Peiwen Cao. 2022. “It Wasn’t Until I Took the Reins and Said. . . .” Power and Advocacy in Canadian Women’s Narratives of Polycystic Ovary Syndrome Diagnosis and Treatment. Women’s Reproductive Health (2022), 1–22.
  59. Katta Spiel, Christopher Frauenberger, Os Keyes, and Geraldine Fitzpatrick. 2019. Agency of autistic children in technology research—A critical literature review. ACM Transactions on Computer-Human Interaction (TOCHI) 26, 6 (2019), 1–40.
  60. Katta Spiel and Kathrin Gerling. 2021. The Purpose of Play: How HCI Games Research Fails Neurodivergent Populations. ACM Transactions on Computer Human Interaction 28, 2 (April 2021), 1–40. https://doi.org/10.1145/3432245
  61. Robert L. Spitzer, Kurt Kroenke, Janet B. W. Williams, and Bernd Löwe. 2006. A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7. Archives of Internal Medicine 166, 10 (May 2006), 1092. https://doi.org/10.1001/archinte. 166.10.1092
  62. Katarzyna Stawarz, Chris Preist, Debbie Tallon, Nicola Wiles, and David Coyle. 2018. User Experience of Cognitive Behavioral Therapy Apps for Depression: An Analysis of App Functionality and User Reviews. Journal of Medical Internet Research 20, 6 (2018), e10120. https://doi.org/10.2196/10120 Company: Journal of Medical Internet Research Distributor: Journal of Medical Internet Research Institution: Journal of Medical Internet Research Label: Journal of Medical Internet Research Publisher: JMIR Publications Inc., Toronto, Canada.
  63. John Torous and Adam Haim. 2018. Dichotomies in Digital Mental Health. Psychiatric services (Washington, D.C.) 69, 12 (Dec. 2018), 1204–1206. https: //doi.org/10.1176/appi.ps.201800193
  64. Nick Walker. 2014. Neurodiversity: Some Basic Terms & Defnitions. https: //neuroqueer.com/neurodiversity-terms-and-definitions/
  65. Anthony Yeung, Enoch Ng, and Elia Abi-Jaoude. 2022. TikTok and Attention Deficit/Hyperactivity Disorder: A Cross-Sectional Study of Social Media Content Quality. The Canadian Journal of Psychiatry (2022), 07067437221082854.
  66. Anon Ymous and Judith Good. 2020. “I am just terrified of my future” – Epistemic Violence in Disability Related Technology Research. (2020), 16.
  67. Kaya Yurief. 2020. Doctors turn to Twitter and TikTok to share coronavirus news. https://www.cnn.com/2020/03/31/tech/social-media-doctors-coronavirus/ index.html
  68. David X Zheng, Anne Y Ning, Melissa A Levoska, Laura Xiang, Christina Wong, and Jefrey F Scott. 2021. Acne and social media: A cross-sectional study

About the Authors

Tessa Eagle is a human computer interaction researcher and fourth-year PhD student in Computational Media at UC Santa Cruz with a background in cognitive science, clinical healthcare, and tech. Her research interests include digital mental health, accessibility, and online communities. Her work focuses on alternative support systems for neurodivergent individuals and people with psychosocial disabilities, including community-based avenues for support.