Women's holistic self-care behaviors during pregnancy and associations with psychological well-being: implications for maternal care facilities.

BACKGROUND: Self-care behaviors during pregnancy significantly impacts mother and children's health. This study aimed to explore the self-care behaviors and the associations of these behaviors with the psychological well-being of women during pregnancy, as well as the mediating effects of different social support with these associations. METHODS: A cross-sectional data of 562 pregnant women at Hanoi Obstetrics & Gynecology Hospital and Ca Mau Obstetrics & Pediatrics in Vietnam were analyzed. Questions about self-care behaviors, pregnancy characteristics, social support, and psychological well-being were asked. Multivariate regression models were performed. Structural Equation Modeling (SEM) was employed to test the mediating effects of different social support with the association between self-care behaviors and psychological well-being. FINDINGS: Only 13% of pregnant women often or always did physical exercise at least three times a week, and 40% consumed enough fiber and five servings of vegetables a day. Only 78.7% always avoided alcohol drinking, and 53.9% of pregnant women avoided being exposed to second-hand smoking and 71,7% avoided using traditional medicine without physicians' prescriptions. Around 66% of pregnant women always or often had prenatal care checkups as scheduled. Information sources, social support and childbirth expectation were major drivers for self-care practices. SEM model showed that social support mediated the relationship between maternal health behaviors and mental well-being. CONCLUSION: This study highlighted the remarkable gaps in self-care practices among our pregnant women, which were significantly associated with their mental well-being. Social support-oriented consultancy and interventions should be warranted for improving behaviors and the mental well-being of pregnant women in Vietnam.

Utility of portable functional near-infrared spectroscopy (fNIRS) in patients with bipolar and unipolar disorders: A comparison with healthy controls.

BACKGROUND: This study aimed to evaluate portable functional near-infrared spectroscopy (fNIRS) device as an adjunct diagnostic tool for bipolar and unipolar disorders while performing cognitive tasks. METHODS: 150 participants were divided into three groups including bipolar, unipolar disorder, and healthy controls (50:50:50), matched by age, gender, and family history of mood disorder. Hemodynamics in the frontal cortex were monitored by fNIRS during the Stroop Color-Word Test and Verbal Fluency Test. The GLM compared the differences in oxy-hemoglobin levels between the two groups. The Receiver Operating Characteristic (ROC) graph was generated for each neuroanatomical area. RESULTS: For people with BD group, the area under the ROC curve (AUC) for the left orbitofrontal cortex was maximal during the VFT [AUC = 0.727, 95%CI = 0.617-0.824]. The Youden's index reached a peak (0.40) at the optimal cut-point value (HbO2 cutoff <0.180 µmol/ml for BD) in which the sensitivity was 82 %; specificity was 58 %; PPV was 0.66; NPV was 0.76 and correct classification rate was 70 %. Regarding the UD group, during VFT, the highest value AUC [AUC = 0.822, 95%CI = 0.740-0.903] was recorded in the left dorsolateral prefrontal cortex with the optimal cut-off value (HbO2cutoff ≥0.163 µmol/ml for healthy controls; <0.163 for unipolar disorder), the sensitivity was 72 %; specificity was 82 %; PPV was 0.80; NPV was 0.75, correct classification rate was 77 %, and the Youden's index was 0.54. CONCLUSION: Assessing hemodynamics during VFT using portable fNIRS offers the potential as an adjunct diagnostic tool for mood disorders in low-resource environments.

Differentiating people with schizophrenia from healthy controls in a developing Country: An evaluation of portable functional near infrared spectroscopy (fNIRS) as an adjunct diagnostic tool.

Introduction: This study aimed to evaluate portable functional near-infrared spectroscopy (fNIRS) device as an adjunct diagnostic tool in Vietnam to assess hemodynamics when people with schizophrenia and healthy controls performed cognitive tasks. Methods: One hundred fifty-seven participants were divided into schizophrenia (n = 110) and healthy controls group (n = 47), which were recruited by match of age, and gender. Hemodynamic responses in the frontal cortex were monitored with a 48-channel portable device during the Stroop Color-Word Test (SCWT) and Verbal Fluency Test (VFT). General linear model compared the differences in oxyhemoglobin (HbO2) levels between the two groups. The Receiver Operating Characteristic (ROC) graph was generated for each neuroanatomical area. Results: People with schizophrenia did not show significant activation in the frontal lobe during the SCWT and VFT as compared to pre-task. During the VFT, the area under the ROC curve of the bilateral dorsolateral prefrontal cortex, bilateral orbitofrontal cortex, bilateral frontopolar prefrontal cortex, and bilateral ventrolateral prefrontal cortex were greater than 0.7 (p < 0.001). The area under the ROC curve (AUC) for the right orbitofrontal cortex was maximal during the VFT (AUC = 0.802, 95%CI = 0.731-0.872). The Youden's index reached a peak (0.57) at the optimal cut-point value (HbO2 cutoff <0.209 µmol/ml for schizophrenia) in which the sensitivity was 85%; specificity was 72%; positive predictive value (PPV) was 0.88; negative predictive value (NPV) was 0.68 and correct classification rate was 76%. Discussion: Assessing hemodynamics during VFT by portable fNIRS offers the potential as an adjunct diagnostic tool for schizophrenia in developing countries.

Determinants of Intention to Use Artificial Intelligence-Based Diagnosis Support System Among Prospective Physicians.

Background: This study aimed to develop a theoretical model to explore the behavioral intentions of medical students to adopt an AI-based Diagnosis Support System. Methods: This online cross-sectional survey used the unified theory of user acceptance of technology (UTAUT) to examine the intentions to use an AI-based Diagnosis Support System in 211 undergraduate medical students in Vietnam. Partial least squares (PLS) structural equational modeling was employed to assess the relationship between latent constructs. Results: Effort expectancy (ß = 0.201, p < 0.05) and social influence (ß = 0.574, p < 0.05) were positively associated with initial trust, while no association was found between performance expectancy and initial trust (p > 0.05). Only social influence (ß = 0.527, p < 0.05) was positively related to the behavioral intention. Conclusions: This study highlights positive behavioral intentions in using an AI-based diagnosis support system among prospective Vietnamese physicians, as well as the effect of social influence on this choice. The development of AI-based competent curricula should be considered when reforming medical education in Vietnam.