Three latent profiles of kinesiophobia were identified in stroke patients with type 2 diabetes mellitus, with 30.7% in a high-kinesiophobia group, and comorbidities, history of falls, duration of diabetes, exercise self-efficacy, social support, pain, and fatigue were significantly associated with subtype membership.
Key Findings
Results
Three distinct latent profiles of kinesiophobia were identified among stroke patients with type 2 diabetes mellitus.
The three profiles were classified as low-kinesiophobia, medium-kinesiophobia, and high-kinesiophobia groups.
The low-kinesiophobia group comprised 124 patients (41.3% of the sample).
The medium-kinesiophobia group comprised 84 patients (28.0% of the sample).
The high-kinesiophobia group comprised 92 patients (30.7% of the sample).
Latent profile analysis (LPA) was used to identify these distinct subtypes using the Tampa Scale for Kinesiophobia as the primary assessment tool.
Results
Comorbidities, history of falls, and duration of diabetes were significantly associated with kinesiophobia subtype membership.
Multinomial logistic regression demonstrated these associations were statistically significant (all p < 0.05).
These variables were identified among a set of sociodemographic and clinical characteristics examined.
The study sample consisted of 300 stroke patients with T2DM hospitalized in the Department of Neurology at a Grade 3 Class A hospital in Lianyungang City between August and December 2025.
Univariate analysis preceded multinomial logistic regression to screen for associated factors.
Results
Psychosocial factors including Exercise Self-Efficacy, social support, pain, and fatigue were significantly associated with kinesiophobia subtype membership.
All associations were statistically significant (all p < 0.05) in multinomial logistic regression analysis.
Exercise Self-Efficacy (SEE) was among the psychosocial variables significantly differentiating kinesiophobia subtypes.
Social support, pain, and fatigue were also identified as significant predictors of subtype membership.
The latent profiles exhibited differences in both sociodemographic and clinical characteristics.
Results
The prevalence of kinesiophobia was substantial in this population, with nearly 59% of stroke patients with T2DM classified in the medium or high kinesiophobia groups.
28.0% of patients were in the medium-kinesiophobia group (n = 84) and 30.7% were in the high-kinesiophobia group (n = 92).
Combined, 176 of 300 patients (58.7%) were classified as having medium or high kinesiophobia.
The study population included stroke patients with T2DM, who face additional challenges including motor impairments, vascular lesions, and diabetic peripheral neuropathy.
The cross-sectional study was conducted in a single Grade 3 Class A hospital in Lianyungang City.
Conclusions
The authors concluded that developing targeted interventions based on subtype-specific features of kinesiophobia may help alleviate patients' symptoms and promote active participation in rehabilitation training.
Stroke patients with T2DM were described as facing 'additional challenges, including motor impairments, vascular lesions, and diabetic peripheral neuropathy, which may increase their susceptibility to kinesiophobia.'
Exercise rehabilitation was noted to play 'a critical role in promoting functional recovery after stroke.'
The identification of three distinct subtypes supports differentiated rather than uniform intervention approaches.
Prior studies using LPA to characterize kinesiophobia in this specific patient population were noted to be limited.
What This Means
This research suggests that fear of movement (kinesiophobia) is common among stroke patients who also have type 2 diabetes, with nearly 59% of the 300 patients studied falling into medium or high kinesiophobia categories. Using a statistical technique called latent profile analysis, researchers identified three distinct groups of patients based on their level of movement-related fear: low (41.3%), medium (28%), and high (30.7%). This grouping approach allowed researchers to go beyond simply measuring fear of movement and instead identify meaningfully different patient profiles.
The study found that several factors were linked to which kinesiophobia group a patient belonged to, including having multiple health conditions, a history of falling, how long they had lived with diabetes, their confidence in exercising (self-efficacy), their social support network, and whether they experienced pain or fatigue. These findings suggest that kinesiophobia in this population is not one-size-fits-all but is shaped by a combination of medical, personal, and social factors.
This research suggests that rehabilitation programs for stroke patients with type 2 diabetes could benefit from tailoring interventions to specific patient profiles rather than applying generic approaches. For example, patients in the high-kinesiophobia group might need more focused attention to pain management, fatigue, and building exercise confidence, while social support interventions might be particularly helpful for others. Because this was a cross-sectional study conducted at a single hospital in China, the findings may not generalize to all populations, and future longitudinal research would help clarify cause-and-effect relationships.
Ban N, Guo M, Zhu S, Miao X, Tan D, Ma L. (2026). Kinesiophobia in stroke patients with type 2 diabetes mellitus: a cross-sectional study based on latent profile analysis.. Frontiers in neurology. https://doi.org/10.3389/fneur.2026.1846279