Objective  To identify latent classes of medication adherence change trajectories in middle-aged and young patients with hypertension based on the Latent Growth Mixture Modeling (LGMM) and analyze its influencing factors.

Methods  A convenience sampling method was used to select 258 middle-aged and young patients with hypertension as study subjects. A cross-sectional survey was conducted on their general information, medication beliefs, self-management behaviors, and Family Care Index. Medication adherence was assessed one day before discharge (T₀), one month after discharge (T₁), three months after discharge (T₂), and six months after discharge (T₃). LGMM was used to identify latent classes of change trajectories, and univariate analysis and multivariate Logistic regression analysis were conducted to explore the influencing factors.

Results  After excluding 30 invalid data, 228 patients were ultimately included in this study. LGMM fitting results showed that medication adherence change trajectories comprised three latent classes: low adherence-fluctuating group (31.58%), medium adherence-continuously increasing group (32.46%), and high adherence-gradually declining group (35.96%). Multivariate Logistic regression analysis results indicated that age, medication types, medication belief scores, self-management behavior scores, and Family Care Index scores were all independent influencing factors for latent classes of medication adherence change trajectories in middle-aged and young patients with hypertension (P < 0.05).

Conclusion  There is significant population heterogeneity in medication adherence among middle-aged and young patients with hypertension, with varying change trajectories observed. Healthcare professionals should identify target populations early and formulate targeted intervention programs based on the influencing factors of different latent classes to effectively improve patients′ medication adherence.