Currently accepted at: JMIR Mental Health
Date Submitted: Apr 7, 2018
Open Peer Review Period: Apr 9, 2018 - Jul 19, 2018
Date Accepted: Aug 25, 2018
(closed for review but you can still tweet)
Identifying the Underlying Factors Associated With Patientsâ€™ Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews
Nonadherence to antidepressants is a major obstacle to deriving antidepressantsâ€™ 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 patientsâ€™ beliefs and attitudes toward medications. Patientsâ€™ drug review posts in online health care communities might provide a significant insight into patientsâ€™ attitude toward antidepressants and could be used to address the challenges of self-report methods such as patientsâ€™ recruitment.
The aim of this study was to use patient-generated data to identify factors affecting the patientâ€™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 patientsâ€™ knowledge about medications) are associated with patientsâ€™ attitude toward antidepressants, and experience of ADRs and drug ineffectiveness are strongly associated with negative attitude.
We used both qualitative and quantitative methods to analyze the dataset. Patientsâ€™ 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.
A 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 (Ï‡24=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 patientsâ€™ attitude toward antidepressants.
Patientsâ€™ self-report experiences of medications in online health care communities can provide a direct insight into the underlying factors associated with patientsâ€™ 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.
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