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Social media platforms are rich and dynamic spaces where individuals communicate on a person-to-person level and to broader audiences. These platforms provide a wealth of publicly available data that can shed light on the lived experiences of people from numerous clinical populations. Twitter can be used to examine individual expressions and community discussions about specific characteristics (e.g., motor skills, burnout) associated with a diagnostic group. These data are useful for understanding the perspectives of a diverse, international group of self-advocates representing a wide range of clinical populations. Here, we provide a framework for how to harvest data from Twitter through their free, academic researcher application programming interface access using Python, a free, open-source programming language. We also provide a sample data set harvested using this framework and a set of analyses on these data specifically related to motor differences in neurodevelopmental conditions. This framework offers a cost-effective and flexible means of harvesting and analyzing Twitter data. Researchers should utilize these resources to advance our understanding of the lived experiences of clinical populations through social media platforms and to determine the critical questions that are of most importance to improving quality of life.

Little is known about adults' experiences with developmental coordination disorder (DCD; sometimes also referred to as dyspraxia). Social media is an accessible opportunity for those who identify as dyspraxic or as having DCD to provide valuable insight into the lifespan impact of this condition on functional ability, participation, compensatory strategies, and well-being. We used the Twitter research application programming interface to identify users who self-identified with the keywords Developmental Coordination Disorder, #DCD, #dyspraxic (or # dyspraxia), or clumsy in their profile descriptions between October 10 and November 10, 2021. During that period, 818 tweets were harvested with 524 remaining after removing duplicates (e.g., multiple promotions of a single resource) and unrelated tweets. They were labeled according to motor differences ("general motor, coordination, fine motor skills, oral motor skills, manual dexterity, driving, gross motor skills, movement pain and fatigue, posture and balance, and lower extremity"); functional impact ("advocacy/awareness, support for others, resources, information, and education, intervention, accommodation, and work"); or other related topics ("stimming and sensory, co-occurrence and diagnostic overlap, cognitive, social and communication speech, and emotional and mental health"). The DCD/dyspraxic community has clearly identified a lifelong impact of motor differences across multiple contexts. DCD/dyspraxic Twitter users shared compensatory strategies that could help others, and offered insight into their experience of co-occurring conditions and cognitive/emotional sequelae of motor challenges.

Despite a growing awareness of the prevalence of motor differences in the autistic community, their functional impact is poorly understood. Social media offers the ideal setting to observe this discourse in a less-contrived setting than lab-based structured interviews. The aims of the present study were (a) to determine the proportion of Twitter users who self-identify as autistic and dyspraxic/having developmental coordination disorder, relative to autistic alone, and (b) to identify common themes emerging from two moderated chat threads with motor-related prompts. Using the Twitter research application programming interface, we harvested data from users' public profiles and tweets containing terms related to autism and developmental coordination disorder within a 1-month time period. We also harvested data from two #AutChat threads related to motor skills, which included 151 tweets from 31 unique autistic users (two with co-occurring developmental coordination disorder). Of these tweets, 44 were explicitly about motor differences, while the remainder consisted of discussion topics more loosely associated with motor skills. The following common themes were quantified: manual dexterity, lower extremity, oral motor, gross motor, posture, balance, stimming, movement pain, and coordination. Together, these findings indicate that motor differences are highly recognized and discussed among autistic individuals but are not overtly integrated into their identities at the same rate.