Patient Concerns and Perceptions Regarding Biologic Therapies in Ankylosing Spondylitis: Insights From a Large‐Scale Survey of Social Media Platforms

Dzubur, Eldin; Khalil, Carine; Almario, Christopher V.; Noah, Benjamin; Minhas, Deeba; Ishimori, Mariko; Arnold, Corey; Park, Yujin; Kay, Jonathan; Weisman, Michael H.; Spiegel, Brennan

doi:10.1002/acr.23600

Cited by 32 publications

(24 citation statements)

References 25 publications

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“…Patients tend to be hopeful, but they have mixed feelings about bDMARDs, including a sense of anxiety and hopelessness ( 23 ). In an analysis of AS patient discussions on social media, patients voiced uncertainty about starting or continuing bDMARD therapy, and the uncertainty manifested chiefly in their numerous questions about it, especially their worries about its long‐term effectiveness ( 24 ). The cross‐sectional study presented here asked only about immediate symptoms or symptoms at the time a decision was made rather than longer‐term symptoms, but it was notable that prevention of long‐term consequences/damage was more important to bDMARD participants, compared with participants not on bDMARDs, than were current symptoms (ie, “how good or bad the disease is making me feel at the time of a treatment decision”).…”

Section: Discussionmentioning

confidence: 99%

“…Participants in the study are part of an online registry and patient community and may be more likely to take part regularly in research studies and thus may have had greater interest in managing their disease, giving rise to the potential for selection bias. In the social media study reporting axSpA patient attitudes about TNFi treatment, patients had expressed a lack of trust in physicians and a need for psychological and social support, namely, an understanding from others in their social circle of what it is like to live in a body affected by the disease ( 24 ). In our study, participants largely expressed trust in their physician and considered the physician's guidance to be important in their treatment change decision.…”

Section: Discussionmentioning

confidence: 99%

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Treatment Satisfaction and Decision‐making from the Patient Perspective in Axial Spondyloarthritis: Real‐World Data from a Descriptive Cross‐sectional Survey Study from the ArthritisPower Registry

Nowell

Gavigan

Hunter

et al. 2021

ACR Open Rheumatology

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Objective. Aims were to 1) to characterize patient decision-making with treatment for axial spondyloarthritis (axSpA) and 2) to explore relationships among decision-making, treatment satisfaction, and biologic disease modifying antirheumatic drugs (bDMARDs).Methods. ArthritisPower participants with physician-diagnosed axSpA were invited to complete an online survey about their treatment and their most recent physician visit. Analysis compared treatment decision by satisfaction and bDMARD status.Results. Among the 274 participants, 87.2% were female, and the mean age was 50 years. Of participants, 79.5% had researched treatment before their most recent physician visit, and 56.9% discussed treatment change at their most recent physician visit. Of treatment-change discussions, 69.2% of them were related to escalation, compared with deescalation (27.6%) and/or switching (39.1%). Among those participants who discussed a change, 73.7% agreed to it because they felt that their disease was not being controlled (54.9%) or felt that it could be better controlled on new treatment (20.3%). Top symptoms prompting change were back/buttock pain (63.3%), other joint pain (55.1%), and fatigue (54.1%). Among bDMARD-treated participants (n = 128), important factors for treatment decisions were prevention of long-term axSpA consequences (92.9%) and doctor's advice (87.5%). Among 43.4% of participants reporting treatment dissatisfaction, 37% did not discuss treatment change. Current bDMARD use was more common in satisfied (61.9%) than dissatisfied participants (26.9%).Conclusion. In this cross-sectional study of a predominantly female axSpA population, patients frequently researched treatment options and discussed escalation with their providers. Under two-thirds of participants who were dissatisfied with treatment discussed changes at their most recent visit. Current bDMARD use was associated with higher satisfaction, and bDMARD users considered prevention of long-term consequences and doctor's advice to be very important for decision-making.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Treatment Satisfaction and Decision‐making from the Patient Perspective in Axial Spondyloarthritis: Real‐World Data from a Descriptive Cross‐sectional Survey Study from the ArthritisPower Registry

Nowell

Gavigan

Hunter

et al. 2021

ACR Open Rheumatology

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“…To supplement the manual inductive coding process, we applied a second, more novel technique, LDA, that allowed for the review of the entire data set. LDA is an unsupervised probabilistic topic model process that relies on the contextual co-occurrence of words to identify patterns of words that, when found together, have a semantic meaning [11,12]. For example, the word "bank" can have different meanings when paired with "money" versus "water."…”

Section: Lda: a Quantitative And Qualitative Approachmentioning

confidence: 99%

Using Large-scale Social Media Analytics to Understand Patient Perspectives About Urinary Tract Infections: Thematic Analysis

Gonzalez¹,

Vaculik²,

Khalil³

et al. 2022

J Med Internet Res

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Background Current qualitative literature about the experiences of women dealing with urinary tract infections (UTIs) is limited to patients recruited from tertiary centers and medical clinics. However, traditional focus groups and interviews may limit what patients share. Using digital ethnography, we analyzed free-range conversations of an online community. Objective This study aimed to investigate and characterize the patient perspectives of women dealing with UTIs using digital ethnography. Methods A data-mining service was used to identify online posts. A thematic analysis was conducted on a subset of the identified posts. Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. Each identified topic was generated as a discrete distribution over the words in the collection, which can be thought of as a word cloud. We also performed a thematic analysis of the word cloud topic model results. Results A total of 83,589 posts by 53,460 users from 859 websites were identified. Our hand-coding inductive analysis yielded the following 7 themes: quality-of-life impact, knowledge acquisition, support of the online community, health care utilization, risk factors and prevention, antibiotic treatment, and alternative therapies. Using the LDA topic model method, 105 themes were identified and consolidated into 9 categories. Of the LDA-derived themes, 25.7% (27/105) were related to online community support, and 22% (23/105) focused on UTI risk factors and prevention strategies. Conclusions Our large-scale social media analysis supports the importance and reproducibility of using online data to comprehend women’s UTI experience. This inductive thematic analysis highlights patient behavior, self-empowerment, and online media utilization by women to address their health concerns in a safe, anonymous way.

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“…14 One particular unsupervised topic modelling method, latent Dirichlet allocation (LDA), 15 has proven particularly popular and successful. LDA has been used for topic mining in studies of health data across an array of data sources, including discussions from condition-specific online support groups [16][17][18][19][20] and more general online discussion platforms, [21][22][23][24][25][26][27][28][29] data about adverse medical events, 30 interview transcripts of patients, 31 32 media articles 33 and survey data. 34 35 Other studies have used LDA to analyse topics in patient-reported concerns as well, in situations where no existing topic information is available.…”

Section: What Does This Paper Add?mentioning

confidence: 99%

Categorising patient concerns using natural language processing techniques

Fairie

Zhang

D’Souza

et al. 2021

BMJ Health Care Inform

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ObjectivesPatient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis. This study reports the results of using a semiautomated, computational topic-modelling approach to analyse a corpus of patient feedback.MethodsPatient concerns were received by Alberta Health Services between 2011 and 2018 (n=76 163), regarding 806 care facilities in 163 municipalities, including hospitals, clinics, community care centres and retirement homes, in a province of 4.4 million. Their existing framework requires manual labelling of pre-defined categories. We applied an automated latent Dirichlet allocation (LDA)-based topic modelling algorithm to identify the topics present in these concerns, and thereby produce a framework-free categorisation.ResultsThe LDA model produced 40 topics which, following manual interpretation by researchers, were reduced to 28 coherent topics. The most frequent topics identified were communication issues causing delays (frequency: 10.58%), community care for elderly patients (8.82%), interactions with nurses (8.80%) and emergency department care (7.52%). Many patient concerns were categorised into multiple topics. Some were more specific versions of categories from the existing framework (eg, communication issues causing delays), while others were novel (eg, smoking in inappropriate settings).DiscussionLDA-generated topics were more nuanced than the manually labelled categories. For example, LDA found that concerns with community care were related to concerns about nursing for seniors, providing opportunities for insight and action.ConclusionOur findings outline the range of concerns patients share in a large health system and demonstrate the usefulness of using LDA to identify categories of patient concerns.

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Patient Concerns and Perceptions Regarding Biologic Therapies in Ankylosing Spondylitis: Insights From a Large‐Scale Survey of Social Media Platforms

Cited by 32 publications

References 25 publications

Treatment Satisfaction and Decision‐making from the Patient Perspective in Axial Spondyloarthritis: Real‐World Data from a Descriptive Cross‐sectional Survey Study from the ArthritisPower Registry

Treatment Satisfaction and Decision‐making from the Patient Perspective in Axial Spondyloarthritis: Real‐World Data from a Descriptive Cross‐sectional Survey Study from the ArthritisPower Registry

Using Large-scale Social Media Analytics to Understand Patient Perspectives About Urinary Tract Infections: Thematic Analysis

Categorising patient concerns using natural language processing techniques

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