English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background  Patients with chronic conditions are required to take long-term treatments for their disease itself or to prevent any potential health risks. Measuring patient acceptance of their medication should help to better understand and predict patients’ behavior toward treatment. This study aimed to describe the level of patient acceptance toward various long-term treatments in real life using an online patient community.    Methods  This was an observational, cross-sectional study conducted through the French Carenity platform. All Carenity patient members were invited to complete an online questionnaire including the 25-item ACCEptance by the Patients of their Treatment (ACCEPT©) questionnaire. ACCEPT© measures patient acceptance toward their medication and includes one general acceptance dimension (Acceptance/General) and six treatment-attribute specific dimensions (scores 0–100; lowest to highest acceptance): Acceptance/Medication Inconvenience, Acceptance/Long-term Treatment, Acceptance/Regimen Constraints, Acceptance/Side effects, Acceptance/Effectiveness, and Acceptance/Numerous Medications. Patients included in the analysis were treated adults experiencing any chronic diseases and who responded to at least one ACCEPT© item.    Results  Among the 4193 patients included in the analysis, more than 270 chronic diseases were represented, amidst which 19 included more than 30 patients. Mean ACCEPT© Acceptance/General score for those 19 diseases were 61.2 (SD = 31.9) for type 1 diabetes, 59.8 (SD = 32.3) for asthma, 56.3 (SD = 34.3) for hypertension, 52.0 (SD = 32.2) for chronic obstructive pulmonary disease, 51.7 (SD = 27.0) for epilepsy, 50.1 (SD = 33.1) for bipolar disorder, 49.9 (SD = 33.1) for type 2 diabetes, 48.6 (SD = 31.6) for multiple sclerosis, 46.1 (SD = 34.5) for Crohn’s disease/ulcerative colitis, 44.3 (SD = 31.5) for depression, 42.8 (SD = 31.5) for lupus, 42.3 (SD = 33.0) for arthrosis, 41.8 (SD = 32.6) for Parkinson’s disease, 40.5 (SD = 32.2) for rheumatoid arthritis, 38.6 (SD = 31.7) for breast cancer, 36.4 (SD = 36.4) for myocardial infarction, 35.8 (SD = 32.0) for ankylosing spondylitis, 34.1 (SD = 32.3) for psoriasis, and 33.7 (SD = 31.7) for fibromyalgia.    Conclusions  This first of its kind study enabled ACCEPT© data to be collected in real life for a variety of chronic diseases. These data may help in evaluating and interpreting levels of acceptance in future studies and provide valuable insights about patient priorities and current unmet needs.

Assessing patients’ acceptance of their medication to reveal unmet needs: results from a large multi-diseases study using a patient online community