Objective To investigate the development trajectories of kinesiophobia and their influencing factors in patients after total hip arthroplasty (THA). Methods Patients after THA from three tertiary hospitals in Wuhan from February to June 2023 were selected by convenience sampling method. The general situation questionnaire, Tampa Scale for Kinesiophobia, Self-Efficacy for Exercise Scale (SEE), Groningen Orthopaedic Social Support Scale, Generalized Anxiety Disorder, Patient Health Questionnaire, and Visual Analogue Scale (VAS) were distributed 1-2 d after surgery (T1), which were used again 1 week (T2), 1 month (T3), and 3 months (T4) after surgery, to evaluate the level of kinesiophobia and the physical and psychological conditions of the patients. The latent category growth model was used to classify the kinesiophobia trajectories of patients after THA, and the influencing factors of different categories of kinesiophobia trajectories were analyzed. Results A total of 263 patients after THA were included. The kinesiophobia trajectories of patients after THA were divided into four potential categories, including 29 cases in the C1 high kinesiophobia persistent group, 41 cases in the C2 medium kinesiophobia improvement group, 131 cases in the C3 low kinesiophobia improvement group, and 62 cases in the C4 no kinesiophobia group. Multicategorical logistic regression analysis showed that compared to the C4 no kinesiophobia group, the influencing factors for the kinesiophobia trajectory in THA patients to develop into the C1 high kinesiophobia persistent group were age [odds ratio (OR)=1.081, 95% confidence interval (CI) (1.025, 1.140)], chronic comorbidities [OR=6.471, 95%CI (1.831, 22.872)], the average SEE score at T1-T4 time points [OR=0.867, 95%CI (0.808, 0.931)], and the average VAS score at T1-T4 time points [OR=7.981, 95%CI (1.718, 37.074)], the influencing factors for the kinesiophobia trajectory to develop into the C2 medium kinesiophobia improvement group were age [OR=1.049, 95%CI (1.010, 1.089)], education level [OR=0.244, 95%CI (0.085, 0.703)], and the average VAS score at T1-T4 time points [OR=8.357, 95%CI (2.300, 30.368)], and the influencing factors for the kinesiophobia trajectory to develop into the C3 low kinesiophobia improvement group were the average SEE score [OR=0.871, 95%CI (0.825, 0.920)] and the average VAS score at T1-T4 time points [OR=4.167, 95%CI (1.544, 11.245)] . Conclusion Kinesiophobia in patients after THA presents different trajectories, and nurses should pay attention to the assessment and intervention of kinesiophobia in patients with advanced age, low education level, chronic diseases, low exercise self-efficacy, and high pain level.
Objective To systematically review the efficacy of six cognitive interventions on cognitive function of patients with mild cognitive impairment after stroke. Methods The PubMed, EMbase, Cochrane Library, SinoMed, WanFang Data and CNKI databases were electronically searched to collect randomized controlled trials on the effects of non-drug interventions on the cognitive function of patients with mild cognitive impairment after stroke from inception to March 2023. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Network meta-analysis was then performed using Openbugs 3.2.3 and Stata 16.0 software. Results A total of 72 studies involving 4 962 patients were included. The results of network meta-analysis showed that the following five cognitive interventions improved the cognitive function of stroke patients with mild cognitive impairment: cognitive control intervention (SMD=−1.28, 95%CI −1.686 to −0.90, P<0.05) had the most significant effect on the improvement of cognitive function, followed by computer cognitive training (SMD=−1.02, 95%CI −1.51 to −0.53, P<0.05), virtual reality cognitive training (SMD=−1.20, 95%CI −1.78 to −0.62, P<0.05), non-invasive neural regulation (SMD=−1.09, 95%CI −1.58 to −0.60, P<0.05), and cognitive stimulation (SMD=−0.94, 95%CI −1.82 to −0.07, P<0.05). Conclusion Five cognitive interventions are effective in improving cognitive function for stroke patients with mild cognitive impairment, among which cognitive control intervention is the most effective. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.