Previous studies on reinforcement learning have identified three prominent phenomena: (1) individuals with anxiety or depression exhibit a reduced learning rate compared to healthy subjects; (2) learning rates may increase or decrease in environments with rapidly changing (i.e. volatile) or stable feedback conditions, a phenomenon termed learning rate adaptation; and (3) reduced learning rate adaptation is associated with several psychiatric disorders. In other words, multiple learning rate parameters are needed to account for behavioral differences across participant populations and volatility contexts in this flexible learning rate (FLR) model. Here, we propose an alternative explanation, suggesting that behavioral variation across participant populations and volatile contexts arises from the use of mixed decision strategies. To test this hypothesis, we constructed a mixture-of-strategies (MOS) model and used it to analyze the behaviors of 54 healthy controls and 32 patients with anxiety and depression in volatile reversal learning tasks. Compared to the FLR model, the MOS model can reproduce the three classic phenomena by using a single set of strategy preference parameters without introducing any learning rate differences. In addition, the MOS model can successfully account for several novel behavioral patterns that cannot be explained by the FLR model. Preferences for different strategies also predict individual variations in symptom severity. These findings underscore the importance of considering mixed strategy use in human learning and decision-making and suggest atypical strategy preference as a potential mechanism for learning deficits in psychiatric disorders.

BACKGROUND: Urge urinary incontinence (UUI) commonly occurs in elderly female patients. The application research of the Information-Motivation-Behavioural Skills (IMB) model has been applied in various therapeutic contexts, but research on its application in UUI management is limited.
METHODS: Elderly female patients diagnosed with UUI were selected as the research subjects, and they were divided into two groups. All patients were given pelvic floor muscle training. The control group received routine health education management, whereas the observation group received health education management on the basis of the IMB model in addition to routine education. Before and after treatment, the severity of urinary incontinence was evaluated using a 1 h urine pad test. The anxiety and depression statuses were evaluated using Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS). Incontinence Quality-of-Life (I-QOL) was used to evaluate the quality of life of patients.
RESULTS: After treatment, the leakage volume, SAS and SDS scores of both groups significantly decreased (p < 0.001), with the observation group having significantly lower leakage volume, SAS, and SDS scores than the control group (p < 0.001). The I-QOL scores of both groups increased (p < 0.001), and the observation group had significantly higher scores than the control group (p < 0.001).
CONCLUSIONS: Health education interventions based on the IMB model can improve urinary leakage in elderly women with UUI, improve their negative emotions and enable them to have an enhanced quality of life.

Augmented Reality (AR) offers a rich business format, convenient applications, great industrial potential, and strong commercial benefits. The integration of AR technology with online shopping has brought tremendous changes to e-commerce. The Technology Acceptance Model (TAM) is a mature model for assessing consumer acceptance of new technologies, and applying it to evaluate the impact of AR online shopping experiences on consumer purchase intention is an urgently needed area of research. Firstly, the typical applications of AR in online shopping were reviewed, and the connotations and experiences of AR online shopping were summarized. Secondly, using the five types of AR online shopping experiences as antecedent variables, and perceived ease of use and perceived usefulness as intermediate variables, a theoretical model was constructed to explore the impact of AR online shopping experiences on customer purchase intentions, followed by an empirical study. Finally, suggestions were proposed for optimizing the online shopping experience to enhance purchase intentions. The article expands the application scenarios of the Technology Acceptance Model and enriches the theory of consumer behavior in Metaverse e-commerce.

OBJECTIVE: Cervical cancer patients with post-operative chemotherapy experience anxiety, depression, and cancer-related fatigue, leading to a decline in their quality of life and posing challenges to the rehabilitation of patients. Therefore, it is necessary to explore effective nursing methods. This study aimed to investigate the effects of a web-based positive psychological nursing model on negative emotions, cancer-related fatigue, self-management efficacy, treatment compliance, and quality of life among cervical cancer patients with post-operative chemotherapy.
METHODS: This retrospective study included 101 cervical cancer patients who underwent surgical intervention at our hospital between January 2019 and December 2023. Patients who received the usual mode of care were included in the control group (n = 48), while those who received the web-based positive psychological care mode were included in the study group (n = 53). For all study subjects, various assessment indices were evaluated, including baseline characteristics, treatment adherence, and the Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Revised Piper Fatigue Scale (RPFS), the Chinese version of the Strategies Used by Patients to Promote Health (C-SUPPH), and European Organization for Research and Treatment of Cancer Quality of Life questionnaire -Core 30 (EORTC QLQ-C30). Additionally, anxiety/depression, cancer-related fatigue, self-management efficacy, treatment compliance, and quality of life were compared between the two groups.
RESULTS: After the intervention, the HAMA score, HAMD score, and RPFS score were significantly decreased for both groups compared to before intervention (p < 0.05). However, the C-SUPPH score was significantly increased than before intervention (p < 0.05). We observed that HAMA, HAMD, and RPFS scores were substantially lower in the study group than those in the control group after intervention (p < 0.05). In contrast, C-SUPPH scores were significantly higher (p < 0.05). After the intervention, treatment compliance was significantly better in the study group compared to the control group. Furthermore, the EORTC QLQ-C30 score was substantially higher than that of the control group (p < 0.05).
CONCLUSIONS: The network-based positive psychological nursing model can effectively alleviate negative emotions and cancer-related fatigue in cervical cancer patients who have undergone post-operative chemotherapy, thereby improving their quality of life. Additionally, this model improves patients\' self-management effectiveness and treatment compliance. These findings provide novel insights into the nursing of cervical cancer patients with post-operative chemotherapy, underscoring its clinical significance.

The binding problem is a crucial issue in the study of working memory (WM) and remains a central topic of debate among various WM models. Over the past decade, we have explored feature binding within WM, guided by the Hierarchical Binding Model (HBM). This model suggests that WM binding occurs in two stages: an initial implicit binding involving rapid, coarse feature processing, followed by explicit binding where focused attention refines these features via a reentry process. We found that implicit binding is closely related to the attentional processing of features during the perceptual stage. Basic features that can be rapidly and coarsely processed in parallel through spread attention are involuntarily extracted into WM along with the target features, forming a rough bound representation. For explicit binding, we examined the role of attention in retaining explicit binding in WM, emphasizing the unique role of reentry in the HBM. Our findings indicate that WM binding requires additional object attention through the reentry process. These results demonstrate that both implicit and explicit bindings are integral to WM and that the HBM is effective in elucidating the binding mechanisms within WM.

BACKGROUND: The burgeoning field of research on the dual-factor model of mental health (DFM) has highlighted its significance, yet the applicability of the DFM in military personnel and its longitudinal relationships with different dimensions of meaning in life remains unclear. This study aimed to clarify the applicability of the DFM for military personnel and to investigate longitudinal relationships between the dual factors of mental health (negative factor, positive factor) and the two dimensions of meaning in life (presence of meaning, search for meaning) in military personnel.
METHODS: In this study, data were collected in two waves (April and August 2023) from 227 Chinese military personnel. We constructed a dual-factor model with depression as the negative factor and subjective well-being as the positive factor, and we compared it with a single-factor model to determine if DFM could be applied to military personnel. We also constructed a cross-lagged model to investigate longitudinal relationships between depression, subjective well-being, presence of meaning, and search for meaning.
RESULTS: According to the findings, military personnel fit better with the DFM than with the single-factor model. Cross-lagged analysis results revealed that both the presence of meaning and the search for meaning negatively predicted depression and positively predicted subjective well-being.
CONCLUSIONS: The DFM had good applicability among military personnel. Both the presence of meaning and the search for meaning could improve military mental health, suggesting that both dimensions of meaning in life may be potential targets for improving military mental health.

AI Generated Content Law was extensively promoted in 2023; hence, it is crucial to uncover factors influencing people\'s behavioral intentions to comply with the AI Generated Content Law. This study extends the theory of planned behavior to explore the factors influencing people to follow AI Generated Content Law in China. In addition to the factors in TPB model, such as one\'s attitudinal factors, normative factors, and perceived behavioral control, we add another factor-moral obligation to extend the theory of planned behavior model. We used convenient sampling and there were 712 effective samples. Using the statistical software Amos17.0, the result shows that attitude, subjective norms, perceived behavioral control and moral obligation all have positive effects on intentions to follow AI Generated Content Law.

Since the social cognitive model of well-being in academic\\work settings was proposed, more and more studies have supported its validity. Nevertheless, most studies failed to test the temporal precedence of its core variables related to individual career development. Thus, we aimed to test this model among 1512 Chinese college students with a longitudinal perspective. They completed the Career-related Parental Support Inventory, Career Exploration and Decision Self-Efficacy-Brief Decision Scale, Career Commitment Making Scale, and Multiple Happiness Questionnaire three times being a four-month interval. The result indicated that there were more positive predicting associations between career-related parental support, career decision self-efficacy (CDSE), career commitment making, and well-being. Moreover, the longitudinal mediation analyses indicated that T1 career-related parental support was linked to T3 well-being via T2 career commitment making, and that T1 CDSE was linked to T3 well-being via T2 career commitment making. The implications of these findings for further research, practices, and policy-making were discussed.

UNASSIGNED: The mental health of unverisity students is influenced by diverse factorsis multifaceted, requiring further investigation to evaluate its current status and determinants. The present study aims to address this gap by targeting Chinese university students and employing the Psychological Resilience Dynamic System model. Through a questionnaire survey, this research endeavors to explore the mental health status and influencing factors. Ultimately, the findings of this study aim to provide a theoretical basis and tailored practical guidance for the development of mental health intervention strategies for university students.
UNASSIGNED: Based on the Psychological Resilience Dynamic System Model, the mental health status of 3,390 Chinese university students from 15 universities was empirically investigated with the principle of stratified sampling and the geographical distribution and disciplinary diversity of universities. The questionnaires used included Kessler psychological distress scale, psychological resilience scale,positive psychological capital scale, family hardiness index and social support scale. Among the participants, 47.85% were male and 52.15% were female. Regarding the origin, 42.89% of the students were from rural areas, while 57.11% were from urban areas.
UNASSIGNED: Key findings unveil: (1) A prevalence of 24.54% in students has suboptimal mental health, with 18.70 and 5.84%, respectively, representing those with poor and relatively poor mental health conditions; (2) A noteworthy negative correlation (p < 0.01) between mental health scores of university students and nine pivotal factors, including psychological resilience, self-efficacy, optimism, hope, resilience, family resilience, objective support, subjective support, and support utilization; (3) Eight factors, including grade, family economic status, psychological resilience, self-efficacy, optimism, family resilience, objective support, and support utilization, emerge as significant predictors of university students\' mental health (p <0.001), collectively elucidating 57.9% of the total variance in mental health.
UNASSIGNED: The aforementioned research results, indicate that the influencing factors on the mental health of university students encompass four main aspects. These include individual demographic factors such as grade and family economic status, positive psychological capital factors such as psychological resilience, self-efficacy, optimism, hope, and resilience, family resilience factors including responsibility, control, and challenge, and societal support factors including objective support, subjective support, and support utilization. Based on this, this paper focuses on four recommendations: giving full play to the leading role of universities in mental health education and stress intervention, strengthening the educational power of positive family ideals and role modeling, building a support system for positive social atmosphere and psychological counseling, and improving the self-shaping ability of university students\' psychological resilience and positive psychological capital. These recommendations aspire to better promote the mental health of university students and provide a strength reserve for psychological problem intervention.

OBJECTIVE: With the increase in the prevalence rate and improvements in the survival of breast cancer patients, there is a growing interest in understanding the level of psychosocial adjustment in these patients. The study aimed to describe the illness perception and psychosocial adjustment levels of both breast cancer patients and their spouses, to use the Actor-Partner Interdependence Model (APIM) to clarify the actor-partner relationships between spouses, and to explore the impact of illness perception on psychosocial adjustment to the disease within the joint actions of both spouses.
METHODS: A total of 216 female patients with breast cancer and their spouses participated in the study. They were selected from two tertiary hospitals in Guangdong Province, China from October 2022 to May 2023 using a convenience sampling method. The participants were assessed using the Brief Illness Perception Questionnaire and the Psychosocial Adjustment to Illness Scale to examine the relationship between illness perception and psychosocial adjustment. AMOS24.0 was used to test and analyze the actor-partner interdependence model.
RESULTS: The illness perception score (57.75 ± 10.91) was slightly higher than that of the spouse (57.10 ± 11.00), and the psychosocial adjustment score (64.67 ± 6.33) was slightly lower than that of the spouse (64.76 ± 7.49). The results of the actor-partner interdependence model indicated that there was a couple partner between breast cancer patients and their spouses: the spouse\'s illness perception significantly affected the patient\'s psychosocial adjustment (β = 0.095, p = 0.015); the patient\'s illness perception also significantly affected the spouse\'s psychosocial adjustment (β = 0.106, p = 0.033). Among them, the patient\'s psychosocial adjustment was found to be related to the patient\'s illness comprehensibility or coherence of illness (β = 0.433, p = 0.009), the spouse\'s emotional illness representation (β = 0.218, p = 0.037), and the spouse\'s illness comprehensibility or coherence of illness (β = 0.416, p = 0.007), while the spouse\'s psychosocial adjustment was only related to the spouse\'s illness comprehensibility or coherence of illness (β = 0.528, p = 0.007).
CONCLUSIONS: The psychosocial adjustment of breast cancer patients is affected by both their own and spouse\'s illness perception. Therefore, in the future, the healthcare staff can implement early psychological interventions for patients diagnosed with breast cancer and their spouses as a unit to promote the psychosocial adjustment of them.