Personality and motivation of physical activity in adolescent girls: effects of perceived parental support and social physical anxiety.

In the present study, we investigated the relationship between personality and motivation for physical activity while introducing perceived parental support and social physical anxiety in adolescent girls (N = 318, Mage: 16.19 ± 0.51 years). The present study was a retrospective correlational study that was conducted to analyze of a path model. Dark triad traits: Machiavellianism, narcissism, and psychopathy, student's motivation for physical activity, social physique anxiety, and participants' perceptions of parents' behaviors were measured. The findings indicated that psychopathy and Machiavellianism were directly and indirectly associated with motivation for physical activity, but Narcissism could only directly predict the motivation for physical activity. Also, need-thwarting (the most), need-supportive and social physical anxiety could predict motivation for physical activity. This model of the result suggests that among adolescent girls, dark triad personality could, directly and indirectly, predict motivation with need-supportive and need-thwarting and also social physical anxiety. It seems that the sense of importance and more attention to oneself in adolescent girls, which exists in the narcissistic personality, can directly lead to more motivation for physical activity. Also, the duplicitous ways of Machiavellian people in pursuing their motives were confirmed in this research.

Effect of extracorporeal photopheresis on survival in acute graft versus host disease.

BACKGROUND: Extracorporeal photopheresis (ECP) is the main non-pharmacological approach accompanying systemic medical treatments in steroid-resistant acute or chronic graft versus host disease. The study aimed to examine the effect of ECP on survival in acute graft versus host disease (aGVHD). METHODS: A total of 35 patients who were followed up in the adult hematology clinic of Inönü University Turgut Özal Medical Center for aGVHD were included in the study. Stem cell transplantation and ECP application parameters that may affect the survival of the patients were examined. RESULTS: In aGVHD using ECP, the degree of involvement affects survival. Involvements with a clinical and laboratory score (Glucksberg system) of 2 and above significantly reduced survival. The duration of ECP use is associated with survival. Especially, 45 days and longer use increases survival (hazard ratio, P-value <.05). The duration of steroid use was found to be effective in survival in aGVHD (P < .001). ECP administration day (P = .003), duration of steroid use (P < .001), duration of ECP use (P = .001), and grade of aGVHD (P < .001) affect survival. CONCLUSION: ECP use is effective in survival in patients with aGVHD score ≥2. In patients with aGVHD, especially the use of 45 days and longer has a positive effect on survival. The duration of steroid use is associated with survival in aGVHD.

Does body mass index distinguish motor proficiency, social and emotional maturity among adolescent girls?

BACKGROUND: The objective of this study was to investigate whether different body mass index (BMI) groups could serve as a distinguishing factor for assessing motor proficiency and social and emotional maturity in adolescent girls. METHODS: 140 girls ranging from 12 to 14.5 years old were selected from the schools of Tabriz city, Iran. After their height and weight were measured to calculate body mass index, they completed the following questionnaires: Bruininks-Oseretsky Test of motor proficiency, Second Edition,Vineland Social Maturity Scale, and Emotional Maturity scale. RESULTS: normal-weight girls had a meaningful advantage against overweight and underweight participants in the gross motor factor of motor proficiency (p = 0.004), but there wasn't a meaningful difference in the fine motor p = 0.196) and coordination factors (p = 0.417). Also, social maturity showed an advantage of normal and underweight adolescent girls in the self-help dressing factor (p = 0.018), while the locomotion skills (p = 0.010) factor revealed a better performance of normal weight and overweight groups over underweight adolescents. No significant differences were observed in the emotional maturity subscales (p = 0.63) between the groups. CONCLUSIONS: The present study demonstrates that BMI has a direct influence on adolescents' gross motor proficiency and social maturity.

Protective effect of dexpanthenol against methotrexate-induced liver oxidative toxicity in rats.

Methotrexate is a familiar chemotherapeutic preferred in a wide range of clinical fields such as leukemia, psoriasis, rheumatoid arthritis, neoplastic and autoimmune disorders. However, methotrexate therapy has limitations as it causes severe side effects from which liver damage is the most important one. Several antioxidant compounds have been studied against methotrexate related liver toxicity, but dexpanthenol has not been experienced. Vitamin B5-derived dexpanthenol is a usual therapeutic having a potent anti-inflammatory and antioxidant effect. In this study, we aimed to evaluate the ameliorating effect of dexpanthenol against methotrexate-induced hepatotoxicity. We performed our experiments on Wistar albino rats divided randomly into four groups involving control, dexphantenol, dexpanthenol + methotrexate and methotrexate applied animals. After this experimental work on rats, for the first time, we showed dexpanthenol improvement effect on ROS-caused hepatotoxicity initiated by methotrexate administration in terms of liver tissue antioxidant/oxidant enzymes, liver function tests, and histological changes. We suggest that dexpanthenol might be applied during methotrexate treatment in order to reduce the liver toxicity. However, further studies are needed to find out the optimal dose regimen and to understand the mechanism of action.

The effect of functional remission and cognitive insight on criminal behavior in patients with schizophrenia.

OBJECTiVE: This study was planned to determine the relationship of functional remission with a criminal history and determine its effect on criminal behavior in patients with schizophrenia. METHODS: This cross-sectional study was conducted with 132 patients with schizophrenia (66 with and 66 without a criminal history). Data were collected between November 2020 and April 2021 using a personal information form, the Functional Remission of General Schizophrenia (FROGS), the Taylor Crime Violence Rating Scale, the Beck Cognitive Insight Scale, and the Positive and Negative Syndrome Scale (PANSS) was used to collect data. RESULTS: In terms of all scale variables, there were significant differences between the groups with and without a criminal history (p < 0.05). These differences were mostly clearly observed in the FROGS-social functionality (effect size: 16.79), PANSS-positive (effect size: 2.62) and FROGS-health and treatment (effect size: 2) subscales. CONCLUSIONS: In this study, it was determined that as the symptoms of the illness increased in schizophrenia, the patients' functional remission and insight decreased, and their tendency to commit crimes increased. Psychiatric nurses can plan therapeutic interventions to increase the functionality and insight levels of patients with schizophrenia.

Developmental characteristics of Williams-Beuren syndrome and evaluation of adaptive behavioral skills.

Background/aim: Williams-Beuren syndrome (WBS) is a rare genetic disorder with delays in language and cognitive development, but, with increased awareness of clinical features and a reliable diagnostic test, WBS is becoming more widely recognized in childhood. Adaptive behavior skills and/or maladaptive behavior are important for the prognosis of individuals with WBS. The aim of this study was to investigate the clinical and developmental characteristics of patients with WBS and further increase awareness about it by evaluating the adaptive skills and maladaptive behaviors of the patients. Materials and methods: The data of WBS patients followed-up at the Developmental Behavioral Pediatrics Unit were reviewed. Patient data on perinatal and postnatal history, developmental stages, physical and neurological examination findings were collected. The International Guide for Monitoring Child Development (GMCD) was administered to each child. In addition, semistructured interviews were conducted with the parents using the Vineland Adaptive Behavior Scales, Second edition (Vineland-II). Results: A total of 12 patients diagnosed with WBS via detection of the 7q11.23 deletion, of whom 6 were girls, were retrospectively reviewed. The mean age at the time of review was 54.6 ± 32.5 months. The mean age at first presentation to the Developmental Behavioral Pediatrics Outpatient Clinic was 15 ± 11.5 months. In the first developmental evaluation using the GMCD, there was a delay in fine and gross motor domains in 6 patients, in the language domains in 4 patients, and in all of the domains in 2 patients. Findings with Vineland-II showed socialization and communication domains as strengths, but the daily living skills and motor skills domains were weaknesses. In terms of maladaptive behavior, the patients tended to frequently have behavioral problems, neurodevelopmental disease, anxiety disorders, eating problems, and sleeping problems. Conclusion: This retrospective review of 12 patients indicated a general delay in overall development, and confirmed impairment in both adaptive and maladaptive functioning in WBS.

Interpretable Estimation of Suicide Risk and Severity from Complete Blood Count Parameters with Explainable Artificial Intelligence Methods.

BACKGROUND: The peripheral inflammatory markers are important in the pathophysiology of suicidal behavior. However, methods for practical uses haven't been developed enough yet. This study developed predictive models based on explainable artificial intelligence (xAI) that use the relationship between complete blood count (CBC) values and suicide risk and severity of suicide attempt. SUBJECTS AND METHODS: 544 patients who attempted an incomplete suicide between 2010-2020 and 458 healthy individuals were selected. The data were obtained from the electronic registration systems. To develop prediction models using CBC values, the data were grouped in two different ways as suicidal/healthy and attempted/non-attempted violent suicide. The data sets were balanced for the reliability of the results of the machine learning (ML) models. Then, the data was divided into two; 80% of as the training set and 20% as the test set. For suicide prediction, models were created with Random Forest, Logistic Regression, Support vector machines and XGBoost algorithms. SHAP, was used to explain the optimal model. RESULTS: Of the four ML methods applied to CBC data, the best-performing model for predicting both suicide risk and suicide severity was the XGBoost model. This model predicted suicidal behavior with an accuracy of 0.83 (0.78-0.88) and the severity of suicide attempt with an accuracy of 0.943 (0.91-0.976). Lower levels of NEU, WBC, MO, NLR, MLR and, age higher levels of HCT, PLR, PLT, HGB, RBC, EO, MPV and, BA contributed positively to the predictive created model for suicide risk, while lower PLT, BA, PLR and RBC levels and higher MO, EO, HCT, LY, MLR, NEU, NLR, WBC, HGB and, age levels have a positive contribution to the predictive created model for violent suicide attempt. CONCLUSION: Our study suggests that the xAI model developed using CBC values may be useful in detecting the risk and severity of suicide in the clinic.

Energy expenditure, oxygen consumption, and heart rate while exercising on seven different indoor cardio machines at maximum and self-selected submaximal intensity.

Objective: One of the main objectives of practicing indoor cardiovascular exercise is to maximize caloric expenditure. This study aimed to compare energy expenditure (EE), oxygen consumption (VO2), and heart rate (HR) recorded in middle-aged adults while exercising on seven different indoor cardiovascular machines at self-selected maximal and submaximal intensity. Method: Thirty recreational-active adult males (Age: 41.69 ± 4.64) performed 12-min bouts at RPE (Rate of perceived exertion) 17 and maximum intensity (MAX INT) on the following indoor cardio machines: Recumbent bike (r_BIKE), upright bike (u-BIKE), spin bike (s-BIKE), rowing machine (ROW), elliptical trainer (ELLIP), stair climber (STAIR), and treadmill (TMILL). Heart rate (HR) and oxygen consumption (VO2) were measured during exercise, whereas EE (energy expenditure) was calculated indirectly. Results: Overall, TMILL induced the highest levels of EE, VO2, and HR, followed by STAIR, ELLIP, s_BIKE, u_BIKE, ROW, and r_BIKE. RPE was reliable across exercise modalities (r_BIKE, u-BIKE, s-BIKE, ROW, ELLIP, STAIR, and TMILL) and intensities (RPE 17 and MAX INT) for EE, HR, and VO2 measurements. Conclusion: To maximize EE while performing indoor cardiovascular exercise for recreational active middle-aged male participants, the TMILL is the best option, followed by the STAIR and the ELLIP. The least recommended options are, respectively, s_BIKE, u_BIKE, ROW, and r_BIKE. Beyond caloric expenditure considerations, promoting exercises that participants genuinely enjoy can enhance adherence, fostering sustained health benefits. Furthermore, RPE is a reliable tool for assessing EE, VO2, and HR across different exercise modalities and intensities.

Integrating proteomics and explainable artificial intelligence: a comprehensive analysis of protein biomarkers for endometrial cancer diagnosis and prognosis.

Endometrial cancer, which is the most common gynaecological cancer in women after breast, colorectal and lung cancer, can be diagnosed at an early stage. The first aim of this study is to classify age, tumor grade, myometrial invasion and tumor size, which play an important role in the diagnosis and prognosis of endometrial cancer, with machine learning methods combined with explainable artificial intelligence. 20 endometrial cancer patients proteomic data obtained from tumor biopsies taken from different regions of EC tissue were used. The data obtained were then classified according to age, tumor size, tumor grade and myometrial invasion. Then, by using three different machine learning methods, explainable artificial intelligence was applied to the model that best classifies these groups and possible protein biomarkers that can be used in endometrial prognosis were evaluated. The optimal model for age classification was XGBoost with AUC (98.8%), for tumor grade classification was XGBoost with AUC (98.6%), for myometrial invasion classification was LightGBM with AUC (95.1%), and finally for tumor size classification was XGBoost with AUC (94.8%). By combining the optimal models and the SHAP approach, possible protein biomarkers and their expressions were obtained for classification. Finally, EWRS1 protein was found to be common in three groups (age, myometrial invasion, tumor size). This article's findings indicate that models have been developed that can accurately classify factors including age, tumor grade, and myometrial invasion all of which are critical for determining the prognosis of endometrial cancer as well as potential protein biomarkers associated with these factors. Furthermore, we were able to provide an analysis of how the quantities of the proteins suggested as biomarkers varied throughout the classes by combining the SHAP values with these ideal models.

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery.

BACKGROUND: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques. METHODS: Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D. RESULTS: As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures. CONCLUSIONS: ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.

Effects of Swedish Massage at Different Times of the Day on Dynamic and Static Balance in Taekwondo Athletes.

The purpose of this study is to investigate the impact of different durations of Swedish massage on the static and dynamic balance at different times of the day in taekwondo athletes. Twelve taekwondo athletes who had been practicing on a regular basis for more than 5 years participated in this study. Taekwondo athletes completed static and dynamic balance tests either after a no-massage protocol (NMP), a five-minute massage protocol (5MMP), a ten-minute massage protocol (10MMP), or a fifteen-minute massage protocol (15MMP) two times a day in the morning (08:00-12:00) and in the evening (16:00-20:00), on non-consecutive days. The findings of this study suggest that the duration of the massage has a discernible impact on dynamic balance, particularly with regard to the right foot. Taekwondo athletes who received a 10MMP or 15MMP displayed significantly improved dynamic balance compared to those in the NMP. Importantly, these improvements were independent of the time of day when the massages were administered. It underscores the potential benefits of incorporating short-duration Swedish massages into taekwondo athletes' pre-competition routines to enhance dynamic balance. These findings highlight the potential benefits of incorporating short-duration Swedish massages into taekwondo athletes' pre-competition routines to enhance dynamic balance, a critical component of their performance, regardless of the time of day.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

Shared Reading of the Families With the Children With Chronic Disease.

The aim of the study is to evaluate shared reading of families of children with chronic diseases. The mothers of children aged 2 to 6 years with chronic health problems who applied to the pediatric outpatient clinic between January and May 2022 were the study group, and the mothers of children with an acute health problem were the control group. The sociodemographic information form and "Child-Parent Shared Reading Activities Scale" were applied. At the end of the interview, 3 questions about shared reading were asked. A total of 187 children were enrolled in the study: 92 and 95 in the chronic disease group and control group, respectively. 57.6% of mothers of chronically ill children reported that the parents almost never did shared reading with their child. It was found that all mothers knew the importance of reading, but they could not support especially in the risky chronic disease group.

Assessment of Sepsis Risk at Admission to the Emergency Department: Clinical Interpretable Prediction Model.

This study aims to develop an interpretable prediction model based on explainable artificial intelligence to predict bacterial sepsis and discover important biomarkers. A total of 1572 adult patients, 560 of whom were sepsis positive and 1012 of whom were negative, who were admitted to the emergency department with suspicion of sepsis, were examined. We investigated the performance characteristics of sepsis biomarkers alone and in combination for confirmed sepsis diagnosis using Sepsis-3 criteria. Three different tree-based algorithms-Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost)-were used for sepsis prediction, and after examining comprehensive performance metrics, descriptions of the optimal model were obtained with the SHAP method. The XGBoost model achieved accuracy of 0.898 (0.868-0.929) and area under the ROC curve (AUC) of 0.940 (0.898-0.980) with a 95% confidence interval. The five biomarkers for predicting sepsis were age, respiratory rate, oxygen saturation, procalcitonin, and positive blood culture. SHAP results revealed that older age, higher respiratory rate, procalcitonin, neutrophil-lymphocyte count ratio, C-reactive protein, plaque, leukocyte particle concentration, as well as lower oxygen saturation, systolic blood pressure, and hemoglobin levels increased the risk of sepsis. As a result, the Explainable Artificial Intelligence (XAI)-based prediction model can guide clinicians in the early diagnosis and treatment of sepsis, providing more effective sepsis management and potentially reducing mortality rates and medical costs.

Investigation of sports participation motivation in people with disabilities: a cross-sectional study of individuals with physical and hearing impairments.

While reading the literature, it is seen that there are not enough studies on the motivation of disabled individuals to participate in sports. This study aims to examine the sports participation motivations of hearing impaired and physically disabled athletes. This study was a cross-sectional study. The research group of the study consists of physically and hearing-impaired individuals between the ages of 18-47. The participants of this research group consisted of 253 volunteer disabled individuals, 150 of whom were men and 103 of whom were women. Sports participation motivation scale was used for disabled individuals. The scale consists of 3 dimensions and is a 5-point Likert type. The results of the study showed that hearing-impaired people have a higher high school rate and physically person with disability have a higher bachelor's degree rate, but the primary education rate did not change between hearing and physically person with disability. Physical activity participation differed between hearing and physically person with disability, and it was observed that hearing-impaired people participated in more physical activities. The level of well-being of the physically disabled was significantly better than the hearing impaired. As conclusion, it is observed that the people with the lowest motivation to participate in sports are primary school graduates and those with high welfare have a high motivation to participate in sports.

Analysis of hematological indicators via explainable artificial intelligence in the diagnosis of acute heart failure: a retrospective study.

Introduction: Acute heart failure (AHF) is a serious medical problem that necessitates hospitalization and often results in death. Patients hospitalized in the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Unfortunately, there is not yet a fast and accurate laboratory test for identifying AHF. The purpose of this research is to apply the principles of explainable artificial intelligence (XAI) to the analysis of hematological indicators for the diagnosis of AHF. Methods: In this retrospective analysis, 425 patients with AHF and 430 healthy individuals served as assessments. Patients' demographic and hematological information was analyzed to diagnose AHF. Important risk variables for AHF diagnosis were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) feature selection. To test the efficacy of the suggested prediction model, Extreme Gradient Boosting (XGBoost), a 10-fold cross-validation procedure was implemented. The area under the receiver operating characteristic curve (AUC), F1 score, Brier score, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) were all computed to evaluate the model's efficacy. Permutation-based analysis and SHAP were used to assess the importance and influence of the model's incorporated risk factors. Results: White blood cell (WBC), monocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), red cell distribution width-standard deviation (RDW-SD), RDW-coefficient of variation (RDW-CV), and platelet distribution width (PDW) values were significantly higher than the healthy group (p < 0.05). On the other hand, erythrocyte, hemoglobin, basophil, lymphocyte, mean platelet volume (MPV), platelet, hematocrit, mean erythrocyte hemoglobin (MCH), and procalcitonin (PCT) values were found to be significantly lower in AHF patients compared to healthy controls (p < 0.05). When XGBoost was used in conjunction with LASSO to diagnose AHF, the resulting model had an AUC of 87.9%, an F1 score of 87.4%, a Brier score of 0.036, and an F1 score of 87.4%. PDW, age, RDW-SD, and PLT were identified as the most crucial risk factors in differentiating AHF. Conclusion: The results of this study showed that XAI combined with ML could successfully diagnose AHF. SHAP descriptions show that advanced age, low platelet count, high RDW-SD, and PDW are the primary hematological parameters for the diagnosis of AHF.

Do Oncologists Recommend the "Pill" of Physical Activity in Their Practice? Answers from the Oncologist and Patients' Perspectives.

OBJECTIVES: The purposes of this current questionnaire-based study were to analyse whether oncologists prescribed PA to their patients in Spain, as well as the type of exercise recommended, the variables that influence whether or not to recommend it and to compare these recommendations with the values reported by their patients. METHODS: Two online questionnaires were designed for this study. The first one, filled in by the oncologists (n = 93), contained aspects such as the attitude or barriers to promoting PA. The second was designed for patients with cancer (n = 149), which assessed PA levels and counselling received from oncologists, among other facets. RESULTS: The majority of oncologists (97%) recommend PA during their consultations. Instead, only 62% of patients reported participating in exercise within the last 7 days. Walking was the most common form of exercise, reported by 50% of participants. Patients who received exercise recommendations from their oncologist walked for more days (p = 0.004; ES = 0.442) and more minutes per day (p = 0.022; ES = 0.410). The barriers most highlighted by patients were lack of time and not knowing how to perform PA. CONCLUSION: Oncologists and patients seem to be interested and able to participate in PA counselling and programmes. However, there was a discrepancy between what was reported by oncologists and expressed by patients in terms of recommendations for PA and the modality itself.

Corrigendum: Analysis of hematological indicators via explainable artificial intelligence in the diagnosis of acute heart failure: a retrospective study.

[This corrects the article DOI: 10.3389/fmed.2024.1285067.].

Emotional and Social Outcomes of the Teaching Personal and Social Responsibility Model in Physical Education: A Systematic Review and Meta-Analysis.

CONTEXT: In today's ever-changing world, fostering personal and social responsibility is essential for building strong and compassionate communities. This study aimed to provide a quantitative synthesis focusing on the emotional and social outcomes of Teaching Personal and Social Responsibility (TPSR) model-based Physical Education (PE) programs. METHODS: A comprehensive literature review covering the period from November 2022 to September 2023 identified 637 articles published between 2005 and 2023. Of these, 20 met the inclusion criteria. Data from these articles were coded, and a comprehensive meta-analysis was conducted, incorporating 28 effect sizes. Methodological quality was assessed using the Medical Education Research Study Quality Instrument. Hedge's g served as the effect size measure and emotional and social outcomes subgroups were consolidated. Heterogeneity was evaluated with Cochran's Q and I2. Meta-regression and ANOVA-like models addressed categorical moderators, whereas publication bias was assessed through funnel plot, failsafe number, and Egger's linear regression. RESULTS: A significant and positive effect of the TPSR model on product outcomes (Hedge's g = 0.337, 95% CI = 0.199 to 0.476) was found. Despite considerable heterogeneity (I2 = 83.830), a random effects model was justified. Assessment of publication bias indicated a low likelihood. Moderator analyses revealed that publication countries significantly influenced the effect, with stronger effects in Turkey. Publication type (article vs. thesis) also played roles in moderation. The meta-regression analyses did not reveal significant effects for the grade level, duration of intervention, publication year or sample size on the TPSR model's impact on product outcomes. The TPSR model positively impacts emotional and social outcomes in PE, enhancing children' skills and behaviour. However, variations across cultures highlight the need for further research, considering limitations like language constraints and potential biases in study selection and data extraction.

The impact of enriched environments on cerebral oxidative balance in rodents: a systematic review of environmental variability effects.

Introduction: The present review aimed to systematically summarize the impacts of environmental enrichment (EE) on cerebral oxidative balance in rodents exposed to normal and unfavorable environmental conditions. Methods: In this systematic review, four databases were used: PubMed (830 articles), Scopus (126 articles), Embase (127 articles), and Science Direct (794 articles). Eligibility criteria were applied based on the Population, Intervention, Comparison, Outcomes, and Study (PICOS) strategy to reduce the risk of bias. The searches were carried out by two independent researchers; in case of disagreement, a third participant was requested. After the selection and inclusion of articles, data related to sample characteristics and the EE protocol (time of exposure to EE, number of animals, and size of the environment) were extracted, as well as data related to brain tissues and biomarkers of oxidative balance, including carbonyls, malondialdehyde, nitrotyrosine, oxygen-reactive species, and glutathione (reduced/oxidized). Results: A total of 1,877 articles were found in the four databases, of which 16 studies were included in this systematic review. The results showed that different EE protocols were able to produce a global increase in antioxidant capacity, both enzymatic and non-enzymatic, which are the main factors for the neuroprotective effects in the central nervous system (CNS) subjected to unfavorable conditions. Furthermore, it was possible to notice a slowdown in neural dysfunction associated with oxidative damage, especially in the prefrontal structure in mice. Discussion: In conclusion, EE protocols were determined to be valid tools for improving oxidative balance in the CNS. The global decrease in oxidative stress biomarkers indicates refinement in reactive oxygen species detoxification, triggering an improvement in the antioxidant network.