SML is an analytical method that can provide insight into how patients describe their TD symptoms and their feelings about having this disorder. PROs such as the PGIC have been used in clinical trials of approved TD medications, including valbenazine and deutetrabenazine [8,9,10, 16,17,18], and in RE-KINECT, a real-world study of possible TD in which patients were administered the EuroQoL 5-Dimension 5-Level questionnaire, the Sheehan Disability Scale, and a questionnaire about their involuntary movements and the impact of these movements on daily activities [4]. Because the emotions and sentiments of patients (and sometimes caregivers) on social media platforms are unsolicited and unfiltered, SML methods differ from these PROs and offer a more comprehensive context for understanding how patients experience TD and the unmet needs in this therapeutic space. As indicated in the recent FDA guidance on patient engagement for drug development, social media can allow access to difficult-to-reach populations, provide accurate and automatic capture of data, and possibly result in greater self-disclosure by patients [14].
SML is typically used in market research, but with a rigorous approach using health economics and outcomes research (HEOR) methodologies to assess the value proposition for an intervention, it can also guide patient-focused drug development and patient-centered treatment strategies [14, 15]. For example, an SML study of chronic obstructive pulmonary disease found that cough, mucus production, and shortness of breath were the symptoms of greatest concern for patients in terms of disease management [13]. In an SML study of dry eye, patients described the impact on work and other quality-of-life issues in addition to expressing frustration with suboptimal management of their symptoms [12]. By evaluating patient perspectives based on their own words, without any prompting from clinicians/investigators or limitations imposed by clinical trial protocols, these studies were able to gather fresh and unbiased patient perspectives that could complement findings based on more traditional research methods. For clinicians, familiarization with the terms and language used by patients on social media platforms may help guide discussions about symptoms, burden, and treatment options.
In this study, which is the first to apply SML methods to TD, almost all posts were from patients, with a few from caregivers. All posts originated in the United States, with approximately one-third from Twitter. Some assumptions about sex, race, and age group could be made based on photos or content of online posts, but no methods were available to verify demographic or socioeconomic data. However, given the various factors which contribute to the digital divide (e.g., age/generational status, gender, race, income, education) [19, 20], it should be noted that some key populations are probably not represented in this analysis (e.g., homeless patients, elderly patients, patients with intellectual or development disabilities). In addition, patients who are unaware of their TD are unlikely to be discussing their symptoms online and would therefore not be included in this type of study.
The results presented in this study, including how patients describe their TD symptoms and their feelings about those symptoms, are consistent with the types of data that the FDA has indicated as being appropriate for social media sources [14]. Given that TD can be a highly distressing and potentially disabling disorder [1, 21], it was perhaps surprising that 36% of online posts were assessed as neutral (33%) or positive (3%), although discerning the underlying reasons for neutrality or positivity was beyond the scope of this study. It is less surprising that many of the online posts analyzed in this study included negative terms and that 2 of the 3 major themes were “anger” and “insecurity”. Aspects within those themes included expressions of frustration, feelings of being unaccepted by society, and fear of being judged by others. Healthcare providers may help to offset some of these negative emotions by informing patients about the availability of approved TD treatments (e.g., valbenazine and deutetrabenazine) and by providing resources such as the “Talk About TD” website [22] and information for local support groups. Moreover, engaging with patients through social media may foster discussions about TD that can be both educational and supportive. Most importantly, simple follow-up questions about mental well-being during regular visits, coupled with referrals for psychosocial counseling as needed, would help clinicians gain better insights into the experiences of their patients and allow patients to feel that their concerns are being addressed.
Limitations
This study had several limitations worth noting. First, a clinical diagnosis of TD in the users/patients could not be confirmed as TD was self-reported in online posts. Second, patients with TD are a heterogeneous population, but the posts in this report may not reflect the experience of all patients with TD. Additionally, the sample size was small, and as discussed earlier, certain patient populations may have been unable or unwilling to discuss their disease in online forums. Third, online posts often lack detail which may be the result of platform restrictions (e.g., character limits in Twitter). Finally, the perspective of caregivers was under-represented in this study and more research is needed to characterize the burden of TD on caregivers. More research is also needed to further understand the reasons why patients (and caregivers) choose to express their sentiments online and how healthcare providers can address these sentiments.