Frontiers in Psychology最新文献

Introduction: A promising approach to optimizing recovery in youth football has been the use of machine learning (ML) models to predict recovery states and prevent mental fatigue. This research investigates the application of ML models in classifying male young football players aged under (U)15, U17, and U19 according to their recovery state. Weekly training load data were systematically monitored across three age groups throughout the initial month of the 2019-2020 competitive season, covering 18 training sessions and 120 observation instances. Outfield players were tracked using portable 18-Hz global positioning system (GPS) devices, while heart rate (HR) was measured using 1 Hz telemetry HR bands. The rating of perceived exertion (RPE 6-20) and total quality recovery (TQR 6-20) scores were employed to evaluate perceived exertion, internal training load, and recovery state, respectively. Data preprocessing involved handling missing values, normalization, and feature selection using correlation coefficients and a random forest (RF) classifier. Five ML algorithms [K-nearest neighbors (KNN), extreme gradient boosting (XGBoost), support vector machine (SVM), RF, and decision tree (DT)] were assessed for classification performance. The K-fold method was employed to cross-validate the ML outputs.

Results: A high accuracy for this ML classification model (73-100%) was verified. The feature selection highlighted critical variables, and we implemented the ML algorithms considering a panel of 9 variables (U15, U19, body mass, accelerations, decelerations, training weeks, sprint distance, and RPE). These features were included according to their percentage of importance (3-18%). The results were cross-validated with good accuracy across 5-fold (79%).

Conclusion: The five ML models, in combination with weekly data, demonstrated the efficacy of wearable device-collected features as an efficient combination in predicting football players' recovery states.

This study investigated motivation of Chinese heritage language (CHL) learners with diverse Chinese language backgrounds at an American university. Using a mixed-methods design, it examined the factors that motivated CHL learners to enroll in Chinese courses and continue their studies. The Study explored interactions that enhanced the learning experience and self identity development. A survey was conducted, followed by individual interviews. The results identified five motivation factors significantly correlated to the ideal L2 self, which functions as an anchor. The ideal L2 self was the strongest predictor of intended effort via positive attitude. The classroom-related experience was another significant predictor of intended effort. Interview data highlighted the dynamic interplay between sociocultural contexts and learner-environment interactions which provokes motivation development and strengthens identity reconstruction and future self-guides. In the process, the learner continuously constructs and consolidates the identity as "Chinese" relating to family and culture. Lastly, the anti-ought-to L2 self, characterized by reactions to "others," emerged in dynamic interactions between learners and contexts. This motive inspired the learner to continuously develop the possible self and gain positive learning experiences.

Purpose: To test spatial ability in athletes with different axial rotation experience and analyze their behavioral data to explain the cognitive mechanisms of spatial ability in athletes.

Methods: Experiment 1: A total of 147 athletes were selected for the paper-and-pencil mental rotation test (MRT). The athletes were separated according to three sport types: open high-spatial (OH) sport, closed high-spatial (CH) sport, closed low-spatial (CL) sport. Spatial ability testing with a two-factor mixed experimental design of 3 (sport type) × 2 (stimulus type). Experiment 2: In this study, 47 players were selected for computerized mental rotation test, with a three-factor mixed experimental design of 3 (sport type) × 2 (angle: 45°, 90°) × 3 (rotational axis: left-right axis, up-down axis, and front-back axis). Repeated-measures ANOVA was performed to evaluate the data.

Results: (1) The CH group and OH group outperformed the CL group in the non-embodied task (all ps < 0.003) and the CH group was better than the other groups in the embodied and tasks (all ps < 0.008). (2) Under 45° rotational conditions, the reaction time (RT) for the left-right (LR) and up-down (UD) axes were shorter than that for the front-back (FB) axis (all ps < 0.026). However, under 90° conditions, the RT for FB < LR < UD, with superior accuracy and rotational speed for the FB axis than for the LR and UD axes (all ps < 0.034). (3) Male players from the CH and CL groups had shorter RTs than did those from the OH group at both angles (all ps < 0.047). For female players, the CH group presented a shorter RT than the OH and CL groups did at 90° (all ps < 0.006). (4) No sex difference was found for paper and pencil MRTs, but a male advantage existed only in the CL group for computerized MRTs (p = 0.005).

Conclusion: The motor skills associated with axial rotation could promote mental rotation performance and compensate for sex differences in mental rotation ability.

Introduction: Mental health is the cornerstone of public health, especially where middle-aged and older adults during the COVID-19 pandemic were concerned. The impact of Internet usage on mental health in the time of the crisis still presents a mixed picture.

Methods: This study employs the PSM-DID method according to longitudinal data (CFPS) to explore whether Internet usage reduced the impact of COVID-19 on the mental health of middle-aged and older adults.

Results: The results reveal that Internet use improves the mental health of middle-aged and older adults during the pandemic in China, but that the impact varies between urban and rural residents. Furthermore, the moderator effects model shows that people's perceptions of the Internet have an impact upon the length of time spent online and its consequent effect on mental health.

Discussion: These findings suggested that Internet use had a significant effect on alleviating the levels of depression in middle-aged and older adults. Greater marginal gains may be realized by enhancing the digital capacity of and narrowing the digital divide that exists among rural residents. The enhancement of digital capacity and proper guidance in digital education should be taken into consideration where the mental health of middle-aged and older adults is at issue.

The purpose of the study was to develop guidelines for the facilitation of self-leadership in nurse faculty. Of the 12 guidelines developed, this paper discusses the two related to resilience through self-leadership practices, namely: encouraging reliance on internal sources for self-preservation; and strengthening the positive self-image of nurse faculty through management and peer support. An exploratory, sequential mixed-methods design was used to guide the development of guidelines. Enhancing nurse faculty resilience can be achieved by promoting engagement in self-leadership activities. These activities contribute to faculty members' profound satisfaction, confidence in their knowledge, and overall competence. Resilience is enriched through practicing self-leadership in a supportive work environment and plays a crucial role in adapting to significant changes in the work environment. It has been identified as a key factor that facilitates the ability to persist against struggles and challenges in the workplace. The implementation of higher education reforms in South Africa has brought about increased workload, stress, and uncertainties to an already overwhelmed nurse faculty workforce, consisting of mainly female faculty. It is prudent that a supportive environment that empowers nurse faculty well-being and resilience be facilitated to ensure adaptation to a dynamic and competitive nursing education environment.

In recent years, the capabilities of Large Language Models (LLMs), such as ChatGPT, to imitate human behavioral patterns have been attracting growing interest from experimental psychology. Although ChatGPT can successfully generate accurate theoretical and inferential information in several fields, its ability to exhibit a Theory of Mind (ToM) is a topic of debate and interest in literature. Impairments in ToM are considered responsible for social difficulties in many clinical conditions, such as Autism Spectrum Disorder (ASD). Some studies showed that ChatGPT can successfully pass classical ToM tasks, however, the response style used by LLMs to solve advanced ToM tasks, comparing their abilities with those of typical development (TD) individuals and clinical populations, has not been explored. In this preliminary study, we administered the Advanced ToM Test and the Emotion Attribution Task to ChatGPT 3.5 and ChatGPT-4 and compared their responses with those of an ASD and TD group. Our results showed that the two LLMs had higher accuracy in understanding mental states, although ChatGPT-3.5 failed with more complex mental states. In understanding emotional states, ChatGPT-3.5 performed significantly worse than TDs but did not differ from ASDs, showing difficulty with negative emotions. ChatGPT-4 achieved higher accuracy, but difficulties with recognizing sadness and anger persisted. The style adopted by both LLMs appeared verbose, and repetitive, tending to violate Grice's maxims. This conversational style seems similar to that adopted by high-functioning ASDs. Clinical implications and potential applications are discussed.

This study investigates the role of gaze in initiating episodes of conflict by examining, using multimodal conversation analysis, a set of cases in which a recipient is prompted to speak by another's extended gaze. In these cases, this recipient response may be, e.g., "What," or a more elaborate demand for an account, such as "Why are you looking at me like that for?" Here we investigate the characteristics of the gaze that prompts such responses, and what actions such responses constitute. While "What" compositionally resembles other-initiated repair, its sequential position characterizes it as a so-called "go-ahead" action. In these cases, the sequential positioning of such gazes, constituting it structurally as a so-called "pre," alongside its durational characteristics and facial expression, are examined to identify the normative associations of gaze and subsequent conduct that make such gazes accountable.

The permanence of students in doctoral programs is a multi-causal phenomenon, which makes it difficult to address and leads to an isolated investigation of its causes, being necessary a joint understanding. The aim is to investigate, through a scoping review of quantitative studies published between 2015 and 2021, the influence of individual, academic, socioeconomic and institutional factors on retention, attrition and dropout. The 32 included studies evidenced a predominance of research focused on individual factors versus few that combined all possibly relevant factors. The present study provides evidence for the emergence of several subfactors: female students, self-efficacy and motivation (individual); the relationship with the supervisor (academic); support for psychological needs (institutional); and migratory status (socioeconomic). This article highlights the need for research that understands this problem with a multifactor approach and an impact on permanence.

Introduction: This study explores the intricate relationships among psychological capital, emotional intelligence, psychological safety, and knowledge sharing among e-commerce practitioners. Grounded in social exchange theory, the research aims to fill a gap in the literature by focusing on the psychological and emotional factors influencing knowledge sharing in a fast-paced and highly competitive industry.

Methods: This study used snowball and purposive sampling to collect 439 valid online questionnaires from e-commerce professionals in Guangdong, Zhejiang, and Jiangsu, China. The survey, conducted from October to November 2023, explored the relationships between psychological capital, emotional intelligence, psychological safety, and knowledge sharing. Data were analyzed using structural equation modeling (SEM) with AMOS 26.0.

Results: The structural path model revealed significant positive correlations between psychological capital and both emotional intelligence (β = 0.494, p < 0.001) and psychological safety (β = 0.297, p < 0.001). Emotional intelligence was significantly positively related to psychological safety (β = 0.513, p < 0.001) and knowledge sharing (β = 0.452, p < 0.001). Psychological safety was also positively correlated with knowledge sharing (β = 0.311, p < 0.001). Bootstrap analysis indicated that emotional intelligence and psychological safety significantly mediate the relationship between psychological capital and knowledge sharing (standardized indirect effect = 0.394, p < 0.01).

Discussion: Based on the significant findings of this study, a key recommendation is to implement targeted interventions aimed at enhancing psychological capital, emotional intelligence, and psychological safety among e-commerce practitioners. Specifically, developing training programs focused on building resilience, self-efficacy, hope, and optimism can improve employees' psychological capital. Additionally, workshops designed to enhance emotional intelligence and create a culture of psychological safety can encourage open communication and trust, thereby promoting knowledge sharing.

Introduction: Endometriosis is a chronic gynecological disease associated with chronic debilitating pain, poor mental health and quality of life. The objective of this paper is to evaluate the effectiveness of psychological interventions aimed at improving the pain, quality of life and mental health of women with endometriosis.

Methods: A systematic review (SR) of the literature with meta-analysis (MA) was carried out. MEDLINE, Embase, PsycINFO and CENTRAL were searched to locate Randomized Controlled Trials (RCTs). The risk of bias assessment of each study was conducted using the Cochrane Collaboration's RoB 2.0 tool.

Results: Seven RCTs were included (N = 757). The data obtained suggest that psychological interventions reduce dyspareunia [standardized mean difference (SMD): -0.54, 95% CI: -0.86, -0.22] and dyschezia [mean difference (MD): -2.90, 95% CI: -4.55, -1.26] and increase mental health levels (SMD: 0.70, 95% CI: 0. 42, 0.99); they also point to a large reduction in levels of trait anxiety (MD: -6.63, 95% CI: -8.27, -4.99) and depression (MD: -2.49, 95% CI: -3.20, -1.79), and a likely reduction in state anxiety (MD: -9.72, 95% CI: -13.11, -6.33) experienced by women with endometriosis. It was also identified that psychological interventions probably slightly reduce pelvic pain and may increase physical health. However, most of the included studies have a high overall risk of bias or have certain concerns, which limit conclusions about the certainty of the evidence.

Discussion: The available evidence indicates that psychological interventions are effective in improving the pain, quality of life and mental health variables of women with endometriosis.

Systematic review registration: https://www.crd.york.ac.uk/prospero/, CRD42024516100.