Publications by authors named "Stephen Doogan"
Article Synopsis
- The study aimed to analyze social media data from individuals involved in Alzheimer's disease (AD) to identify obstacles in the patient journey and suggest strategies for improving care.
- Researchers collected and analyzed nearly 226,000 social media posts over 23 years, categorizing the patient journey into three phases: Early Signs, Screening, and Treatment.
- Key findings indicated that anxiety was prevalent throughout all phases, with significant barriers to care access noted in the Screening and Treatment phases, particularly issues related to cost and reluctance to seek care.
Background: Social media data may be especially effective for studying diseases associated with high stigma, such as Alzheimer's disease (AD).
Objective: We primarily aimed to identify issues/challenges experienced by patients with AD using natural language processing (NLP) of social media posts.
Methods: We searched 130 public social media sources between January 1998 and December 2021 for AD stakeholder social media posts using NLP to identify issues/challenges experienced by patients with AD.
Introduction: Online communities contain a wealth of information containing unsolicited patient experiences that may go beyond what is captured by guided surveys or patient-reported outcome (PRO) instruments used in clinical settings. This study described patient experiences reported online to better understand the day-to-day disease burden of ankylosing spondylitis (AS).
Methods: Unguided, English-language patient narratives reported between January 2010 and May 2016 were collected from 52 online sources (e.
Objective: To evaluate the types of experiences and treatment access challenges of patients with psoriatic arthritis (PsA) using self-reported online narratives.
Methods: English-language patient narratives reported between January 2010 and May 2016 were collected from 31 online sources (general health social networking sites, disease-focused patient forums, treatment reviews, general health forums, mainstream social media sites) for analysis of functional impairment and 40 online sources for assessment of barriers to treatment. Using natural language processing and manual curation, patient-reported experiences were categorized into 6 high-level concepts of functional impairment [social, physical, emotional, cognitive, role activity (SPEC-R), and general] and 6 categories to determine barriers to treatment access (coverage ineligibility, out-of-pocket cost, issues with assistance programs, clinical ineligibility, formulary placement/sequence, doctor guidance).