Lili Ji’s research while affiliated with Peking University and other places

Background Patients with cardiovascular disease (CVD) often experience anxiety and depression. However, the central and bridge symptoms of anxiety and depression among patients with CVD remain unclear. Network analysis is a statistical method that can reveal and visualise complex relationships between multiple variables. This study aimed to identify the central and bridge symptoms in the anxiety-depression network, which may provide potential targets for preventing and intervening in anxiety and depression. Methods A total of 1180 patients with CVD were selected from the Psychology and Behavior Investigation of Chinese Residents. The survey was conducted from July 10 to September 15, 2021. Face-to-face electronic questionnaires were distributed to respondents by the investigators. The Generalized Anxiety Disorder 7 (GAD-7) and Patient Health Questionnaire-9 were used to assess anxiety and depressive symptoms among patients with CVD. Network analysis was conducted using R4.02 to identify central and bridge symptoms in the anxiety-depression network. Results Among the 1180 patients with CVD included in this study, 673 (57%) were male and 507 (43%) were female. More than half (53.5%) of patients were under 60 years old. The mean GAD-7 score was 4.66 ± 4.38, and 169 (14.3%) patients had anxiety symptoms. The mean PHQ-9 score was 6.29 ± 5.29, and 235 (19.9%) had depressive symptoms. Furthermore, 144 (12.2%) patients people had both anxiety and depressive symptoms. In the network of anxiety and depressive symptoms, “unable to sit still because of anxiety”, “feeling afraid that something terrible is about to happen”, and “feeling bad or like a failure, or disappointing oneself or family” were the most influential and central symptoms. We also found that “feeling afraid that something terrible is about to happen” and “thoughts of dying or hurting oneself in some way” were pivotal bridge symptoms between anxiety and depression. Conclusions This study provides new insights into the network structure of anxiety and depression in patients with CVD. These identified central and bridge symptoms may be potentially effective targets for preventing anxiety and depression in patients with CVD, and may provide treatment strategies for patients with anxiety and depression.

Subjective support-focused cognitive behavioral therapy (SS-CBT) could increase subjective support among (pre)frail community-dwelling older adults, however, the underlying mechanisms remain unclear. We conducted a randomized controlled trial, in which the SS-CBT group (n = 50) received SS-CBT once a week for eight weeks and the wait-list control group (n = 50) received no intervention. The dependent variable was subjective support, and potential mediators included self-esteem, gratitude, cognitive distortions, interpersonal competence and rumination. Measurements took place before and after the intervention. We found that interpersonal competence mediated the effectiveness of SS-CBT on both perceived support availability (β = 2.030, 95%CI = 1.164, 3.081) and perceived support adequacy (β = 6.37, 95%CI = 3.52, 9.74), while self-esteem only mediated the effectiveness of SS-CBT on perceived support availability (β = 1.621, 95%CI = 0.502, 2.843). Gratitude, cognitive distortions, and rumination neither mediated the effectiveness of SS-CBT on perceived support availability nor on perceived support adequacy. These findings highlight self-esteem and interpersonal competence as the mechanisms through which SS-CBT increases subjective support, especially perceived support availability. This implicates that the SS-CBT should exclusively emphasize the apparent active ingredients (self-esteem and interpersonal competence) to promote its efficiency.

Objective: To appraise the methodological quality, clinical applicability, and reporting quality of clinical practice guidelines (CPGs) for frailty in primary care and identify research gaps using evidence mapping. Study design and setting: We conducted a systematic literature search in PubMed, Web of Science, Embase, CINAHL, guideline databases, and frailty or geriatric society websites. Appraisal of Guidelines Research and Evaluation II, AGREE-Recommendations Excellence, and Reporting Items for Practice Guidelines in Healthcare checklist were used to evaluate overall quality for frailty CPGs as "high", "medium" or "low" quality. We used bubble plots to show recommendations in CPGs. Results: Twelve CPGs were identified. According to the overall quality evaluation, five CPGs were considered as high quality, six as medium quality, and one as low quality. The recommendations in CPGs were generally consistent and mainly focused on frailty prevention, identification, multidisciplinary, non-pharmacological, and other treatments. However, evidence was lacking in some areas, such as effective prevention strategies and implementation of recommendations. Conclusion: The frailty CPGs vary in quality but have consistent recommendations that can guide clinical practice in primary care. This could point the way for future research to address existing gaps and facilitate the development of trustworthy CPGs for frailty.

Objective: To develop the wed-based system for predicting risk of (pre)frailty among community-dwelling older adults. Materials and methods: (Pre)frailty was determined by physical frailty phenotype scale. A total of 2802 robust older adults aged ≥60 years from the China Health and Retirement Longitudinal Study (CHARLS) 2013-2015 survey were randomly assigned to derivation or internal validation cohort at a ratio of 8:2. Logistic regression, Random Forest, Support Vector Machine and eXtreme Gradient Boosting (XGBoost) were used to construct (pre)frailty prediction models. The Grid search and 5-fold cross validation were combined to find the optimal parameters. All models were evaluated externally using the temporal validation method via the CHARLS 2011-2013 survey. The (pre)frailty predictive system was web-based and built upon representational state transfer application program interfaces. Results: The incidence of (pre)frailty was 34.2 % in derivation cohort, 34.8 % in internal validation cohort, and 32.4 % in external validation cohort. The XGBoost model achieved better prediction performance in derivation and internal validation cohorts, and all models had similar performance in external validation cohort. For internal validation cohort, XGBoost model showed acceptable discrimination (AUC: 0.701, 95 % CI: [0.655-0.746]), calibration (p-value of Hosmer-Lemeshow test > 0.05; good agreement on calibration plot), overall performance (Brier score: 0.200), and clinical usefulness (decision curve analysis: more net benefit than default strategies within the threshold of 0.15-0.80). The top 3 of 14 important predictors generally available in community were age, waist circumference and cognitive function. We embedded XGBoost model into the server and this (pre)frailty predictive system is accessible at http://www.frailtyprediction.com.cn. A nomogram was also conducted to enhance the practical use. Conclusions: A user-friendly web-based system was developed with good performance to assist healthcare providers to measure the probability of being (pre)frail among community-dwelling older adults in the next two years, facilitating the early identification of high-risk population of (pre)frailty. Further research is needed to validate this preliminary system across more controlled cohorts.

Background: The ecological model of health and ageing has proposed that functional ability (FA) is determined by the interaction between intrinsic capacity (IC) and environmental characteristics. This study empirically examined how social support, as an important social environmental resource, interacts with IC to affect FA trajectories among older adults. Methods: This was a prospective three-wave cohort study with a sample of 775 community-dwelling older adults. Social support, IC and FA were assessed using the Social Support Rating Scale, the revised Integrated Care for Older People screening tool and the Lawton Instrumental Activities of Daily Living Scale, respectively. Latent growth curve models (LGCM) were implemented to test their relationships. Results: FA significantly declined over 3 years, and the detrimental effect of impaired IC on the deterioration rate of FA was buffered by subjective support but was aggravated by support utilization and was not changed by objective support. FA decline among older adults with impaired IC was observed in those with low subjective support or with high support utilization but not in those with high subjective support or with low support utilization. Among older adults with intact IC, FA decline was observed in those with low support utilization but not in those with high support utilization or with low or high subjective support. Conclusions: Subjective support may prevent FA decline among older adults with impaired IC, while support utilization may benefit older adults with intact IC but may be detrimental for those with impaired IC. Social support interventions to optimize FA trajectories should improve older adults' perceptions of support and bridge the gap in support utilization among older adults with impaired IC.

The current study validated and compared three short Geriatric Depression Scales (GDS), including the GDS-5, D'Ath GDS-4, and van Marwijk GDS-4, among 917 Chinese community-dwelling older adults. The GDS-5, D'Ath GDS-4, and van Marwijk GDS-4 presented satisfactory accuracy against the GDS-15 (area under the curve [AUC] = 0.872 to 0.952), and the GDS-5 and D'Ath GDS-4 had better accuracy than the van Marwijk GDS-4. Satisfactory accuracy (AUC = 0.842 to 0.979) for the three scales was also observed across subgroups by age, sex, education, cognitive function, and multimorbidity. The GDS-5 but not D'Ath GDS-4 and van Marwijk GDS-4 retained a 2-point optimal cutoff for depressive symptoms across subgroups. The GDS-5 (average inter-item correlation coefficient [AIIC] = 0.233) and the D'Ath GDS-4 (AIIC = 0.171) but not van Marwijk GDS-4 (AIIC = 0.128) had acceptable internal consistency. Three scales had stable test-retest reliability within a 1- to 2-week interval (intraclass correlation coefficient = 0.670 to 0.885). The GDS-5 is an accurate and reliable depression screening tool with an invariable optimal cutoff among Chinese community-dwelling older adults. The variable optimal cutoffs for the D'Ath GDS-4 and van Marwijk GDS-4 across subgroups may limit their applicability in this population. [Research in Gerontological Nursing, xx(x), xx-xx.].