2026-10-11T03:56:45Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33962374 2026-09-22T05:41:03Z category_427 portal_316 item_type_3 month_year_09_2026

Table 1_Exercise self-management behavioral phenotypes in type 2 diabetes: a multicenter cross-sectional study.docx Xi Chen (35903) Liya Zhang (551488) Huili Jiang (12790667) Yuhao Chen (1406335) Fangping Xie (25088050) Xiaowen Zhai (10322603) Yifan Liu (219681) Chunyan Zhao (141856) Fei He (145896) Qian Zhou (125859) Di Zhang (197959) Bin Xue (388921) Fanglei Xu (24254535) Suwen Feng (13221273) Public Health and Health Services not elsewhere classified complications exercise management knowledge-attitude-practice (KAP) latent profile analysis type 2 diabetes Background<p>Exercise management is important in type 2 diabetes mellitus (T2DM). However, individual variability in exercise-related knowledge, attitudes, and practices (KAP) is significantly associated with behavioral adherence yet is often overlooked in average-based analyses. This study applied Latent profile analysis (LPA) to characterize this heterogeneity and explored associations between the resulting behavioral profiles and clinical indicators.</p>Methods<p>We conducted a multicenter cross-sectional study of 516 adults with T2DM in China. LPA was performed using standardized exercise-related KAP indicators. Candidate solutions were evaluated using fit indices, classification diagnostics, interpretability, and bootstrap reproducibility. Clinical associations were examined using adjusted regression and posterior-probability pseudo-class analyses.</p>Results<p>Four exploratory profiles were identified: Favorable Engagement (7.0%), Average Engagement (59.7%), Knowledge-Constrained (21.7%), and Attitude–Practice Constrained (11.6%). After covariate adjustment, BMI differed across profiles; only the Average Engagement contrast remained significant after accounting for classification uncertainty. Glycemic indicators and diabetes-related complications did not differ robustly. The adjusted association with other chronic disease was sensitive to classification uncertainty.</p>Conclusion<p>Exercise self-management heterogeneity included distinct knowledge-related and attitude–practice constraints. These exploratory patterns may inform tailored support, but profile instability and cross-sectional data require independent prospective validation.</p> 2026-09-22T05:41:03Z Dataset Dataset 10.3389/fpubh.2026.1892333.s001 https://figshare.com/articles/dataset/Table_1_Exercise_self-management_behavioral_phenotypes_in_type_2_diabetes_a_multicenter_cross-sectional_study_docx/33962374 CC BY 4.0