Corrigendum: Using Machine Learning to Predict Cognitive Impairment Among Middle-Aged and Older Chinese: A Longitudinal Study.

[This corrects the article DOI: 10.3389/ijph.2023.1605322.].

Corrigendum to "Effects of acceptance and commitment therapy on cognitive function: A systematic review" [Heliyon 9(3) (March 2023) e14057].

[This corrects the article DOI: 10.1016/j.heliyon.2023.e14057.].

Effects of acceptance and commitment therapy on cognitive function: A systematic review.

Cognitive function is essential for daily activities. Acceptance and commitment therapy (ACT) may improve cognitive function by enhancing psychological flexibility, but the underlying mechanism is unknown. This systematic review evaluated the effectiveness of ACT on cognitive function. Seven research databases (PubMed, ProQuest Dissertations and Theses, Web of Science, EBSCOhost, CNKI, Scopus, Wanfang) were searched to collect articles with trials published in English and Chinese. After applying inclusion and exclusion criteria, we identified 12 studies published between 1994 and 2022 that included a combined total of 904 participants. Among the included studies were within-group (N = 3) and randomized controlled trial (RCT, N = 9) study designs. Outcome measures included cognitive scales and behavioral measurements. Of the 12 articles, 10 studies showed improvements in certain domains of cognitive function due indirectly to ACT intervention. We found that the ability of ACT intervention to promote psychological flexibility is due to its transdiagnostic nature. Also, the effects of the ACT intervention were observed in multiple cognitive domains: attention, subjective cognitive function, executive function, and memory. In conclusion, cognitive trainers could consider practicing ACT as part of their strategy to enhance an individual's psychological flexibility and cognitive function.

Using Machine Learning to Predict Cognitive Impairment Among Middle-Aged and Older Chinese: A Longitudinal Study.

Objective: To explore the predictive value of machine learning in cognitive impairment, and identify important factors for cognitive impairment. Methods: A total of 2,326 middle-aged and elderly people completed questionnaire, and physical examination evaluation at baseline, Year 2, and Year 4 follow-ups. A random forest machine learning (ML) model was used to predict the cognitive impairment at Year 2 and Year 4 longitudinally. Based on Year 4 cross-sectional data, the same method was applied to establish a prediction model and verify its longitudinal prediction accuracy for cognitive impairment. Meanwhile, the ability of random forest and traditional logistic regression model to longitudinally predict 2-year and 4-year cognitive impairment was compared. Results: Random forest models showed high accuracy for all outcomes at Year 2, Year 4, and cross-sectional Year 4 [AUC = 0.81, 0.79, 0.80] compared with logistic regression [AUC = 0.61, 0.62, 0.70]. Baseline physical examination (e.g., BMI, Blood pressure), biomarkers (e.g., cholesterol), functioning (e.g., functional limitations), demography (e.g., age), and emotional status (e.g., depression) characteristics were identified as the top ten important predictors of cognitive impairment. Conclusion: ML algorithms could enhance the prediction of cognitive impairment among the middle-aged and older Chinese for 4 years and identify essential risk markers.

Trajectory of suicidal ideation among medical students during the COVID-19 pandemic: the role of childhood trauma.

BACKGROUND: The aim of this study was to understand the longitudinal trajectory of suicidal ideation (SI) among Chinese medical students and the role of childhood trauma (CT). METHODS: Using a whole-group sampling method, we assessed SI in 2192 (male = 834, female = 1358) medical students on three occasions over a period of one year. The Suicidal Ideation Self-Assessment Scale (SISAS) and the Childhood Trauma Questionnaire-Short Form (CTQ-SF) were used to assess SI and CT. The growth mixture modeling (GMM) was used to classify the developmental trajectory of SI. RESULTS: A greater number of medical students were experiencing suicidal ideation during the COVID-19 pandemic. The trajectory of SI among medical students was divided into two groups: a low risk, slowly rising group and a high risk, continuous group. The low risk, slowly rising group had a significant time effect (B = 1.57, p < 0.001) and showed a slowly increasing trend. Emotional neglect (EN), physical neglect (PN), emotional abuse (EA) and physical abuse (PA) all had significant positive predictive effects for the high risk, continuous group (B = 0.18-0.65, P < 0.01). CONCLUSION: The trajectory of SI among medical students can be divided into a low risk, slowly rising group and a high risk, continuous group; the more EN, PN, EA and PA experienced during childhood, the more likely medical students are to develop a high risk, continuous state of SI.

Underlying Familial Factors for Aggressive Behavior in Romantic Relationships: A Systematic Review.

Aggressive behavior in romantic relationship has serious effects, including both intra- and inter-personal issues. Aggressive behaviors in romantic relationships have been linked to underlying familial problems. While there have been previous reviews that studied on many interpersonal and dyadic implications of aggressive behavior in romantic relationships, there is nonetheless a lack of studies on the various components of familial factors for aggressive behavior in romantic relationships. The databases Scopus, MEDLINE, Google Scholar, and SAGE Journals were used to search for terms that are related to familial factors (family factor, family support, family relationship) as well as terms related to aggressive behavior in romantic relationships (aggression in romantic relationship, violence in intimate relationship). The articles considered for this review were original studies, samples, or subsamples of males or females who reported any underlying familial factors in childhood or adulthood that contributed to aggressive behavior in romantic relationship, and the studies must be written in English. This review has 27 papers that met the inclusion criteria. The findings from this review revealed the presence of inconsistent conclusions between familial factors and aggressive behavior in romantic relationships, with some studies failing to establish such links. These findings are reviewed with regards to the existing gaps in the literature as well as potential research options.