Identifying the Underlying Factors Associated With Patients’ Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews

Abstract

BackgroundNonadherence to antidepressants is a major obstacle to deriving antidepressants’ therapeutic benefits, resulting in significant burdens on the individuals and the health care system. Several studies have shown that nonadherence is weakly associated with personal and clinical variables but strongly associated with patients’ beliefs and attitudes toward medications. Patients’ drug review posts in online health care communities might provide a significant insight into patients’ attitude toward antidepressants and could be used to address the challenges of self-report methods such as patients’ recruitment.ObjectiveThe aim of this study was to use patient-generated data to identify factors affecting the patient’s attitude toward 4 antidepressants drugs (sertraline [Zoloft], escitalopram [Lexapro], duloxetine [Cymbalta], and venlafaxine [Effexor XR]), which in turn, is a strong determinant of treatment nonadherence. We hypothesized that clinical variables (drug effectiveness; adverse drug reactions, ADRs; perceived distress from ADRs, ADR-PD; and duration of treatment) and personal variables (age, gender, and patients’ knowledge about medications) are associated with patients’ attitude toward antidepressants, and experience of ADRs and drug ineffectiveness are strongly associated with negative attitude.MethodsWe used both qualitative and quantitative methods to analyze the dataset. Patients’ drug reviews were randomly selected from a health care forum called askapatient. The Framework method was used to build the analytical framework containing the themes for developing structured data from the qualitative drug reviews. Then, 4 annotators coded the drug reviews at the sentence level using the analytical framework. After managing missing values, we used chi-square and ordinal logistic regression to test and model the association between variables and attitude.ResultsA total of 892 reviews posted between February 2001 and September 2016 were analyzed. Most of the patients were females (680/892, 76.2%) and aged less than 40 years (540/892, 60.5%). Patient attitude was significantly (P<.001) associated with experience of ADRs, ADR-PD, drug effectiveness, perceived lack of knowledge, experience of withdrawal, and duration of usage, whereas oth age (F4,874=0.72, P=.58) and gender (χ24=2.7, P=.21) were not found to be associated with patient attitudes. Moreover, modeling the relationship between variables and attitudes showed that drug effectiveness and perceived distress from adverse drug reactions were the 2 most significant factors affecting patients’ attitude toward antidepressants.ConclusionsPatients’ self-report experiences of medications in online health care communities can provide a direct insight into the underlying factors associated with patients’ perceptions and attitudes toward antidepressants. However, it cannot be used as a replacement for self-report methods because of the lack of information for some of the variables, colloquial language, and the unstructured format of the reports.

A Systematic Framework for Analyzing Patient-Generated Narrative Data: Protocol for a Content Analysis

“…Building on our previous experiences and lessons learned from the content analysis of patients’ narratives, we propose a systematic framework to address the subjective nature of patients’ narratives [11,18-20]. This framework integrates text mining methods, the framework method, and deductive-inductive approach for content analysis and is composed of 4 main phases: (1) data collection, (2) data preparation, (3) content analysis, and (4) interpretation of the results.…”

“…In the following sections, we demonstrate the implementation of each step of this systematic framework using 2 studies: (1) a case study that identified factors affecting patients attitudes toward antidepressants; we use the short title attitude to antidepressants to refer to this case study [11] and (2) a case study that analyzed the strategies and solutions of patients with diabetes facing financial difficulties to access medications and supplies; we use the short title access to diabetes medications to refer to this case study.…”

“…In fact, it can be used for describing patterns or regularities, generating and testing hypotheses, describing a phenomenon and the associated factors, identifying problematic areas in the health care systems, or even developing predictive models to predict a specific patient’s behavior, such as medication nonadherence behavior. For example, for the project attitude to antidepressants , we tested the association between themes (variables) and patient attitudes toward antidepressants using statistical methods (analysis of variance and chi-square test) [11].…”

“…In this study, we first provide a brief introduction to the framework method [10] and content analysis and theme generation approaches with examples from research conducted using patient-generated narratives. Next, we describe the proposed framework and demonstrate its applicability for analysis of patient narratives using 2 case studies: one on determining factors affecting patients’ attitudes toward antidepressants using data from askapatient.com [11] and another on identifying the disease management strategies in patients with diabetes facing financial difficulties using data from 4 diabetes-focused forums.…”

“…Finally, the deductive-inductive approach is used when researchers wish to test the existing knowledge in a new context and leave space to discover new aspects of the data that were not covered by existing knowledge. For example, Zolnoori et al used the deductive-inductive approach to test hypotheses concerning patients’ attitudes toward antidepressants using patients’ drug reviews in askapatient.com [11].…”