Hormone receptor status is determined primarily to identify breast cancer patients who may benefit from hormonal therapy. The current clinical practice for the testing using either Allred score or H-score is still based on laborious manual counting and estimation of the amount and intensity of positively stained cancer cells in immunohistochemistry (IHC)-stained slides. This work integrates cell detection and classification workflow for breast carcinoma estrogen receptor (ER)-IHC-stained images and presents an automated evaluation system. The system first detects all cells within the specific regions and classifies them into negatively, weakly, moderately, and strongly stained, followed by Allred scoring for ER status evaluation. The generated Allred score relies heavily on accurate cell detection and classification and is compared against pathologists' manual estimation. Experiments on 40 whole-slide images show 82.5% agreement on hormonal treatment recommendation, which we believe could be further improved with an advanced learning model and enhancement to address the cases with 0% ER status. This promising system can automate the exhaustive exercise to provide fast and reliable assistance to pathologists and medical personnel. The system has the potential to improve the overall standards of prognostic reporting for cancer patients, benefiting pathologists, patients, and also the public at large.
Artificial intelligence (AI), a rousing advancement disrupting a wide spectrum of applications with remarkable betterment, has continued to gain momentum over the past decades. Within breast imaging, AI, especially machine learning and deep learning, honed with unlimited cross-data/case referencing, has found great utility encompassing four facets: screening and detection, diagnosis, disease monitoring, and data management as a whole. Over the years, breast cancer has been the apex of the cancer cumulative risk ranking for women across the six continents, existing in variegated forms and offering a complicated context in medical decisions. Realizing the ever-increasing demand for quality healthcare, contemporary AI has been envisioned to make great strides in clinical data management and perception, with the capability to detect indeterminate significance, predict prognostication, and correlate available data into a meaningful clinical endpoint. Here, the authors captured the review works over the past decades, focusing on AI in breast imaging, and systematized the included works into one usable document, which is termed an umbrella review. The present study aims to provide a panoramic view of how AI is poised to enhance breast imaging procedures. Evidence-based scientometric analysis was performed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline, resulting in 71 included review works. This study aims to synthesize, collate, and correlate the included review works, thereby identifying the patterns, trends, quality, and types of the included works, captured by the structured search strategy. The present study is intended to serve as a "one-stop center" synthesis and provide a holistic bird's eye view to readers, ranging from newcomers to existing researchers and relevant stakeholders, on the topic of interest.
Cervical cancer is the most common cancer and ranked as 4th in morbidity and mortality among Malaysian women. Currently, Magnetic Resonance Imaging (MRI) is considered as the gold standard imaging modality for tumours with a stage higher than IB2, due to its superiority in diagnostic assessment of tumour infiltration with excellent soft-tissue contrast. In this research, the robustness of semi-automatic segmentation has been evaluated using a flood-fill algorithm for quantitative feature extraction, using 30 diffusion weighted MRI images (DWI-MRI) of cervical cancer patients. The relevant features were extracted from DWI-MRI segmented images of cervical cancer. First order statistics, shape features, and textural features were extracted and analysed. The intra-class relation coefficient (ICC) was used to compare 662 radiomic features extracted from manual and semi-automatic segmentations. Notably, the features extracted from the semi-automatic segmentation and flood filling algorithm (average ICC = 0.952 0.009, p > 0.05) were significantly higher than the manual extracted features (average ICC = 0.897 0.011, p > 0.05). Henceforth, we demonstrate that the semi-automatic segmentation is slightly expanded to manual segmentation as it produces more robust and reproducible radiomic features.
A corneal ulcers are one of the most common eye diseases. They come from various infections, such as bacteria, viruses, or parasites. They may lead to ocular morbidity and visual disability. Therefore, early detection can reduce the probability of reaching the visually impaired. One of the most common techniques exploited for corneal ulcer screening is slit-lamp images. This paper proposes two highly accurate automated systems to localize the corneal ulcer region. The designed approaches are image processing techniques with Hough transform and deep learning approaches. The two methods are validated and tested on the publicly available SUSTech-SYSU database. The accuracy is evaluated and compared between both systems. Both systems achieve an accuracy of more than 90%. However, the deep learning approach is more accurate than the traditional image processing techniques. It reaches 98.9% accuracy and Dice similarity 99.3%. However, the first method does not require parameters to optimize an explicit training model. The two approaches can perform well in the medical field. Moreover, the first model has more leverage than the deep learning model because the last one needs a large training dataset to build reliable software in clinics. Both proposed methods help physicians in corneal ulcer level assessment and improve treatment efficiency.
Oral health is a likely source of health inequalities in children with special health care needs (CSHCN), according to multiple studies. This systematic review aimed to explore the evidence of family influence—as well as family features, such as societal variables and parents’ perspectives—on these children’s dental caries status. Embase, Ebsco, Scopus, PubMed, and Web of Science databases were all searched. All cross-sectional research published on the variables of family impact ranging from 2010 to 2021 were considered. The DMFT and dmft index was utilised for the report data of dental caries, whereas the National Heart, Lung, and Blood Institute (NHLBI) was used for the purposes of assessing quality. Of the 3861 records identified, 14 were eligible. Further, most of the studies had a caries prevalence of over 50%, (p-value < 0.005). Family influences imparted a significant relationship and association towards the dental caries status of the demographic being studied. The influences on the children included tooth brushing behaviour, parents’ education level, parents’ occupation level, diet pattern, dental visit, snacking frequency, parents’ psychological status, family size, and parents’ knowledge towards oral health. Future research should further explore the family functioning domains, specifically among the CSHCN population. This study was registered on PROSPERO, number CRD42021274923.
The resin infiltration (RI) technique was introduced as one of the minimal intervention dentistry strategies in addressing dental caries among the paediatric population. This technique used the low-viscosity resin monomer to infiltrate the non-cavitated carious lesion and other developmental enamel porosities, thus allowing the conservation of the tooth structure. This narrative review aims to explore the value of RI in Paediatric Dentistry. Through our search of the literature, the development of the material, their clinical applications and shortcomings, as well as the innovation that has been carried out to improve the current RI, were discussed. There are number of high-level evidence supporting the use of RI in arresting non-cavitated proximal caries lesions in primary and permanent teeth, but its efficacy in managing anterior white spot lesions is still unclear. Limited penetration depth, not radiopaque and questionable long-term colour and material stability were among the limitation of the material. Various laboratory-based studies have been conducted to improve the current properties of RI. Nevertheless, RI has emerged as one of the important micro-invasive techniques in addressing non-cavitated and anterior white-spot enamel lesions in children and adolescents with great success.
Apart from the major drawback of black staining once lesion is arrested, few studies have indicated that dental personnel's perception and attitude towards silver diamine fluoride (SDF) influences its usage. This report aims to provide a systematic review presenting dental personnel's knowledge, attitudes, and perceptions, (KAPs) regarding SDF. A search of multiple electronic literature databases and a manual search were performed. The review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. A comprehensive search yielded 719 publications and 14 cross-sectional studies matching the inclusion criteria. Awareness of SDF among respondents ranged from 29.6% to 87.8%, whereas awareness of its use in dentistry ranged from 14.4% to 94.5%. Regarding attitude towards SDF, the mean score ranged from 3.39 to 14.35. An increase in knowledge of and attitude towards SDF is significantly associated with the usage of SDF and may increase the usage of SDF. This review provides vital information on dental personnel's KAPs regarding SDF. It is anticipated that the adaptation of SDF usage will be more widespread in the future, especially among children. Findings from the review may assist intervention programs to change misperceptions and to enhance awareness regarding SDF among dental personnel.
Background: Chemoresistance is a significant barrier to combating head and neck cancer, and decoding this resistance can widen the therapeutic application of such chemotherapeutic drugs. This systematic review and meta-analysis explores the influence of microRNA (miRNA) expressions on chemoresistance in head and neck cancers (HNC). The objective is to evaluate the theragnostic effects of microRNA expressions on chemoresistance in HNC patients and investigate the utility of miRNAs as biomarkers and avenues for new therapeutic targets. Methods: We performed a comprehensive bibliographic search that included the SCOPUS, PubMed, and Science Direct bibliographic databases. These searches conformed to a predefined set of search strategies. Following the PRISMA guidelines, inclusion and exclusion criteria were framed upon completing the literature search. The data items extracted were tabulated and collated in MS Excel. This spreadsheet was used to determine the effect size estimation for the theragnostic effects of miRNA expressions on chemoresistance in HNC, the hazard ratio (HR), and 95% confidence intervals (95% CI). The comprehensive meta-analysis was performed using the random effects model. Heterogeneity among the data collected was assessed using the Q test, Tau2, I2, and Z measures. Publication bias of the included studies was checked using the Egger's bias indicator test, Orwin and classic fail-safe N test, Begg and Mazumdar rank collection test, and Duval and Tweedie's trim and fill methods. Results: After collating the data from 23 studies, dysregulation of 34 miRNAs was observed in 2189 people. These data were gathered from 23 studies. Out of the 34 miRNAs considered, 22 were up-regulated, while 12 were down-regulated. The TaqMan transcription kits were the most used miRNA profiling platform, and miR-200c was seen to have a mixed dysregulation. We measured the overall pooled effect estimate of HR to be 1.516 for the various analyzed miRNA at a 95% confidence interval of 1.303-1.765, with a significant p-value. The null hypothesis test's Z value was 5.377, and the p-value was correspondingly noted to be less than 0.0001. This outcome indicates that the risk of death is determined to be higher in up-regulated groups than in down-regulated groups. Among the 34 miRNAs that were investigated, seven miRNAs were associated with an improved prognosis, especially with the overexpression of these seven miRNAs (miR15b-5p, miR-548b, miR-519d, miR-1278, miR-145, miR-200c, Hsa- miR139-3p). Discussion: The findings reveal that intricate relationships between miRNAs' expression and chemotherapeutic resistance in HNC are more likely to exist and can be potential therapeutic targets. This review suggests the involvement of specific miRNAs as predictors of chemoresistance and sensitivity in HNC. The examination of the current study results illustrates the significance of miRNA expression as a theragnostic biomarker in medical oncology.
Meat spoilage caused by temperature abuse is a major problem for producers, retailers, and consumers that can generate large economic losses to industries. Microbial growth of Pseudomonas spp. is the main source of spoilage during storage. Cinnamon has antimicrobial properties that may potentially be used to reduce the spoilage caused by Pseudomonas. The objectives of this study were to determine the inhibitory effect of cinnamon extract (CE) against Pseudomonas aeruginosa (ATCC 27853) and evaluate the treatment of CE on meat quality during different storage temperatures (5 °C, 10 °C, 15 °C, and 25 °C). The anti-Pseudomonas result showed that 100% (w/v) CE concentration produced a 13.50 mm zone of inhibition in a disc diffusion assay. The minimum inhibitor concentration (MIC) of CE was noted at 25% (v/v), whereas the minimum bactericidal concentration (MBC) value was observed at 50% (v/v) concentration of CE. The time-kill showed the growth of P. aeruginosa decreased from 7.64 to 5.39 log CFU/mL at MIC concentration. Total phenolic content and IC50 value of the cinnamon extract was expressed as 6.72 ± 0.87 mg GAE/g extract and 0.15 mg/mL, respectively. When the meat was marinated with 50% (v/v) CE and stored at various temperatures, the total viable count (TVC) and growth of Pseudomonas spp. were lowered as compared to the control sample. However, the reduction in microbial count in all samples was influenced by the storage temperature, where the lowered microbial count was noted in the sample treated with CE and stored at 5 and 10 °C for 48 h. The pH of meat treated with or without CE ranged from pH 5.74 to 6.48. The sensory attributes of colour, texture, and overall acceptability have a significant difference, except for odour, between marinated meat and control. The results indicate that the use of cinnamon extract as the marination agent for meat could reduce the growth of Pseudomonas spp. and therefore assist in extending the shelf life of meat at 5 and 10 °C storage temperatures.
The heads and bones of hybrid groupers are potential precursors for angiotensin-converting enzyme (ACE)-inhibitory and antioxidant peptides. The aim of this study was to isolate the dual-action peptides from the Alcalase-treated head and bone hydrolysate of hybrid groupers followed by identification of the novel peptides. The stability of these peptides against stimulated in vitro gastrointestinal digestion (SGID) was also determined. Fraction HB-IV (less than 1 kDa) obtained from ultrafiltration showed the strongest ACE-inhibition ability (IC50: 0.28 mg/mL), which was comparable to the potency of the commercial supplement, PeptACE (IC50: 0.22 mg/mL). This fraction also demonstrated the highest hydroxyl radical scavenging and metal-chelating activities. However, further fractionation of HB-IV by a series of chromatography resulted in peptide fractions of reduced ACE-inhibitory and antioxidant activities. The hydroxyl radical scavenging and reduction potential of HB-IV were enhanced, whereas ACE-inhibitory and metal-chelating activities were reduced following SGID. A total of 145 peptide sequences were identified from HB-IV, of which 137 peptides were novel to the BIOPEP database. The results suggested that the bioactive peptides isolated from the heads and bones of hybrid groupers could be used as functional foods/ingredients with potential ACE-inhibitory and antioxidant effects.
Asia accounts for over 70% of total global aquatic food consumption, but aquatic food consumption behaviours and attitudes among Asian consumers are poorly documented and understood. This paper synthesises literature on factors influencing aquatic food consumption behaviour in Asia and the potential to support transitions toward more sustainable food consumption patterns. We identified 113 studies for inclusion in a scoping review, and identified five clusters of publications: (1) product attributes, availability, and accessibility (24% of publications); (2) willingness to pay for aquatic foods (25%); (3) psychosocial factors (e.g., attitudes and subjective norms) (17%); (4) sociodemographic and lifestyle factors (21%); and (5) miscellaneous factors, including food safety and social status (13%). This study indicates that multiple interacting factors influence aquatic food consumption behaviours among Asian consumers, among which price is central. Knowledge of, and attitudes toward, the perceived quality and safety of aquatic foods were identified as important but were mediated by household characteristics. Sustainable production practices, country of origin, and ecolabels were found to be less influential on consumption behaviour. We found that improving consumers' knowledge and attitudes about the quality and safety of aquatic foods might positively influence aquatic food consumption behaviour. Future multidisciplinary research is required to better understand interactions among the multiple factors that influence Asian consumers' aquatic food consumption behaviour.
With the prevalence of edible diacylglycerol (DAG) oil, which is beneficial to human, the generation of 3-monochloropropanediol esters (3-MCPDE) and glycidyl esters (GE) as well as the stability of physical properties during heat-induced processing still need to be explored. In this study, the experiment used olive-based edible oil with different contents of DAG (40, 60, and 80%) to make crackers and fry chicken. They were heated at 160 and 180 °C to determine the changes in 3-MCPDE and GE, the crackers’ hardness and gumminess, and the physical properties of the oil. During baking and frying, 3-MCPDE decreased, while the content of GE slightly increased with the prolonged heating duration. Finally, 3-MCPDE and GE were lower than 1.25 mg/kg and 1.00 mg/kg, respectively. The AV increased proportionally as duration increased and POV was below 0.30 g/100 g. In general, the changes in 3-MCPDE and GE were related to the heating temperature and duration, and not significantly (p > 0.05) related to the content of DAG.
This study aimed to investigate the prevalence of upper limb musculoskeletal disorders (MSDs) and their association with smartphone addiction and smartphone usage among university students in the Kingdom of Saudi Arabia during the COVID-19 pandemic. A total of 313 university students aged 18 years and older who owned a smartphone and used it during the preceding 12 months participated in this cross-sectional study. The prevalence of upper limb MSDs, smartphone addiction/overuse, and levels of physical activity were recorded using the standardized Nordic musculoskeletal questionnaire, the smartphone addiction scale (short version), and the international physical activity questionnaire (short form), respectively. Data collection was performed on campus between March and May 2021. Binary logistic regression was used to determine the association between the prevalence of upper limb MSDs and smartphone addiction/overuse and levels of physical activity. The 12-month prevalence of MSDs of the shoulder, elbow, and wrist/hand regions due to smartphone use among participants was found to be 20.13%, 5.11%, and 13.42%, respectively. Shoulder (odds ratio (OR) = 11.39, 95% confidence interval (CI) = 4.64−27.94, p < 0.001), elbow (OR = 15.38, 95% CI = 1.92−123.26, p = 0.01), and wrist/hand MSDs (OR = 7.65, 95% CI = 2.75−21.22, p < 0.001) were more prevalent among participants who were categorized as having smartphone addiction/overuse measures. Promoting awareness about the healthy use of smartphones, including postural education and decreasing screen time, is necessary to reduce smartphone-related MSDs.
Due to the increasing importance of caregivers in the treatment outcomes of patients with mental illness, this study aimed to systematically review studies investigating the former's caregiver burden and determine its prevalence. An open search, without filters, was conducted. Articles were selected from Medline, Scopus, and PubMed from inception to 30 April 2022 using the PRISMA protocol. Subgroup analyses examined the between-group differences by study setting, measurements used, and disorder type. A total of 5034 caregivers from 23 countries were included in this review. Thirty-nine studies were included in the systematic review, and, among them, twenty-six were deemed eligible for meta-analysis. The overall pooled prevalence of caregiver burden among caregivers of individuals with mental illness was 31.67% (95% CI = 26.22-37.12). Pooled prevalence was the highest among care recipients receiving treatment in a hospital setting (36.06%; 95% CI = 22.50-49.63), followed by the community and clinic settings. Caregiver prevalence values were higher for burden measured using the Zarit Burden Interview (38.05%; 95% CI = 27.68-48.43). compared with other instruments, and for carers of care recipients with psychosis (35.88%; 95% CI = 27.03-44.72) compared with those without. Thus, targeted interventions should focus on caregivers of patients in hospital settings and with psychotic symptoms.
Dyslipidaemia is a major cause of morbidity and mortality. The aims of this study are to determine the prevalence of dyslipidaemia subtypes, the proportions of lipid-lowering therapy (LLT) use, and the achievement of low-density lipoprotein cholesterol (LDL-C) treatment targets for high-risk (HR) and very high-risk (VHR) Malaysians. This cross-sectional study involves 5279 participants across 11 states in Malaysia. The data were obtained through a standardised questionnaire, anthropometric measurements, venous glucose and lipid profile. The participants with existing cardiovascular disease (CVD) or diabetes with at least one of the other major risk factors (smoking, hypertension or dyslipidaemia) were grouped into the VHR category. Other participants were risk-categorised using the Framingham General CVD Risk Score (FRS-CVD). The prevalence of elevated LDL-C, LLT use and LDL-C target were set according to respective risk categories. Pearson's chi-squared test was used to test the difference in the proportions. The mean ± standard deviation (SD) age was 41.1 ± 14.8 years, and 62.2% (3283/5279) of the group were females. Within the participant group, 51.5% were found to have elevated total cholesterol, 28.8% had low HDL-C, and 33.8% had high triglyceride. As for elevated LDL-C, 9.8% were in VHR, 8.6% in HR, 5.8% in MR and 34.9% in LR categories. Among the VHR group, 75.8% were not on LLT, and only 15.9% achieved the LDL-C target. As for the HR category, 87.7% were not on LLT, and only 16.1% achieved the LDL-C target. Dyslipidaemia is highly prevalent among Malaysians. The majority of VHR and HR participants were not on LLT and did not achieve LDL-C treatment targets. Proactive programs are warranted to combat dyslipidaemia-associated CVD events in these groups.
This work provides consensus guidance regarding clinical diagnosis and early medical management of endometriosis within Asia. Clinicians with expertise in endometriosis critically evaluated available evidence on clinical diagnosis and early medical management and their applicability to current clinical practices. Clinical diagnosis should focus on symptom recognition, which can be presumed to be endometriosis without laparoscopic confirmation. Transvaginal sonography can be appropriate for diagnosing pelvic endometriosis in select patients. For early empiric treatment, management of women with clinical presentation suggestive of endometriosis should be individualized and consider presentation and therapeutic need. Medical treatment is recommended to reduce endometriosis-associated pelvic pain for patients with no immediate pregnancy desires. Hormonal treatment can be considered for pelvic pain with a clinical endometriosis diagnosis; progestins are a first-line management option for early medical treatment, with oral progestin-based therapies generally a better option compared with combined oral contraceptives because of their safety profile. Dienogest can be used long-term if needed and a larger evidence base supports dienogest use compared with gonadotropin-releasing hormone agonists (GnRHa) as first-line medical therapy. GnRHa may be considered for first-line therapy in some specific situations or as short-term therapy before dienogest and non-steroidal anti-inflammatory drugs as add-on therapy for endometriosis-associated pelvic pain.
This paper addresses a design optimization of a gas turbine (GT) for marine applications. A gain-scheduling method incorporating a meta-heuristic optimization is proposed to optimize a thermodynamics-based model of a small GT engine. A comprehensive control system consisting of a proportional integral (PI) controller with additional proportional gains, gain scheduling, and a min-max controller is developed. The modeling of gains as a function of plant variables is presented. Meta-heuristic optimizations, namely a genetic algorithm (GA) and a whale optimization algorithm (WOA), are applied to optimize the designed control system. The results show that the WOA has better performance than that of the GA, where the WOA exhibits the minimum fitness value. Compared to the unoptimized gain, the time to reach the target of the power lever angle is significantly reduced. Optimal gain scheduling shows a stable response compared with a fixed gain, which can have oscillation effects as a controller responds. An effect of using bioethanol as a fuel has been observed. It shows that for the same input parameters of the GT dynamics model, the fuel flow increases significantly, as compared with diesel fuel, because of its low bioethanol heating value. Thus, a significant increase occurs only at the gain that depends on the fuel flow.
Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m3/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam.
MeSH terms: Malaysia; Probability; Reproducibility of Results; Floods*; Climate Change*
During the initial phase of the coronavirus disease 2019 (COVID-19) pandemic, there was a critical need to create a valid and reliable screening and surveillance for university staff and students. Consequently, 11 medical experts participated in this cross-sectional study to judge three risk categories of either low, medium, or high, for all 1536 possible combinations of 11 key COVID-19 predictors. The independent experts' judgement on each combination was recorded via a novel dashboard-based rating method which presented combinations of these predictors in a dynamic display within Microsoft Excel. The validated instrument also incorporated an innovative algorithm-derived deduction for efficient rating tasks. The results of the study revealed an ordinal-weighted agreement coefficient of 0.81 (0.79 to 0.82, p-value < 0.001) that reached a substantial class of inferential benchmarking. Meanwhile, on average, the novel algorithm eliminated 76.0% of rating tasks by deducing risk categories based on experts' ratings for prior combinations. As a result, this study reported a valid, complete, practical, and efficient method for COVID-19 health screening via a reliable combinatorial-based experts' judgement. The new method to risk assessment may also prove applicable for wider fields of practice whenever a high-stakes decision-making relies on experts' agreement on combinations of important criteria.
MeSH terms: Cross-Sectional Studies; Humans; Public Health*; Records as Topic; Risk Assessment
(1) Background: The present study investigated the relationships between social identity, core self-evaluation, school adaptation, and mental health problems in migrant children, and the mechanism underlying these relationships; (2) Methods: The participants were migrant middle school students in China. Data analysis was conducted using SPSS version 26. A survey comprising the social identity scale, core self-evaluation scale, school adaptation scale, and mental health scale MMHI-60 was deployed; (3) Results: Findings indicated a significant and negative association between social identity and mental health problems, and such an association was sequentially mediated by core self-evaluation and school adaptation. Furthermore, core self-evaluation and school adaptation played a chain mediation role between social identity and migrant children's mental health problems; (4) Conclusions: It is crucial to improve social identity, core self-evaluation, and school adaptation to reduce mental health problems among this population. Therefore, the research results provide a new direction for promoting the development of mental health education for migrant workers and their children in China.
MeSH terms: Child; China/epidemiology; Humans; Mental Health*; Schools; Social Identification; Transients and Migrants*; Diagnostic Self Evaluation