Yuling Hu, Hailun Huang, Li Jiang, Zhaoqian Gong, Liyu Yang, Shuyu Huang, Jianpeng Liang, Yisheng Lan, Wenshan Ouyang, Wenqu Zhao, Shaoxi Cai, Haijin Zhao
BackgroundMedication adherence is critical for asthma management but often suboptimal. Illness perceptions (IP), patients' cognitive and emotional representations of illness, are key determinants of adherence.ObjectiveThis study aimed to identify IP clusters at diagnosis and determine their predictive value for medication adherence over the 6-month follow-up period and clinical outcomes.MethodsIn this prospective cohort study, 212 newly diagnosed asthma patients were enrolled. We applied consensus clustering analysis to the Brief Illness Perception Questionnaire (B-IPQ) to identify robust IP clusters. Multivariable logistic regression was used to assess whether cluster membership independently predicted medication adherence over the 6-month follow-up period.ResultsFour distinct IP clusters were identified: Pessimistic-Helpless, Underestimating-Low Control, Hypersensitive-Anxious, and Adaptive-Vigilant. Over the 6-month follow-up period, the Hypersensitive-Anxious cluster, despite reporting the highest level of concern, demonstrated the poorest medication adherence and suboptimal asthma control, suggesting an "anxiety-adherence paradox". Moreover, baseline cluster membership independently predicted good medication adherence over follow-up.ConclusionsIllness perceptions are heterogeneous early in asthma. Baseline IP clusters may aid risk stratification and personalized management.