Importance of lumbar instability in the study of associations between muscle morphology, pain, and disability in chronic low back pain.

OBJECTIVE: The purpose of this study was to (1) evaluate the relationship between lumbar extensor muscle morphology, with pain and disability in patients with chronic low back pain (CLBP) and (2) compare these relationships in subgroup of CLBP with and without lumbar structural segmental instability. DESIGN AND METHODS: This cross-sectional study included 183 patients with CLBP. Standing lateral lumbar flexion/extension radiographs were used to assess lumbar structural segmental instability. Lumbar multifidus (MF), erector spinae (ES), and psoas major (PM) morphology were determined from axial magnetic resonance imaging. Associations between lumbar muscle morphologies and patient pain and disability were evaluated in two groups with and without lumbar instability. RESULTS: Patients' disability was negatively associated with PM total cross-sectional area (beta = -22.82, 95%CI = -37.05 to -8.59) and functional cross-sectional area (beta = -23.45, 95%CI = -37.81 to -9.09). MF morphology was negatively associated with disability in the lumbar instability group. Pain intensity was only associated to PM total cross-sectional area (Beta = -3.33, 95%CI = -6.43 to -2.24) and functional cross-sectional area (Beta = -3.22, 95%CI = -6.40 to -0.05) only in the lumbar instability group. CONCLUSION: PM atrophy was associated with greater disability and pain in CLBP, but MF atrophy was associated with greater disability in CLBP patients with lumbar structural segmental instability.

Exploring the impacts of risk factors on mortality patterns of global Alzheimer's disease and related dementias from 1990 to 2021.

Alzheimer's Disease and Related Dementias (ADRD) affect millions of people worldwide, with mortality rates influenced by several risk factors and exhibiting significant heterogeneity across geographical regions. This study aimed to investigate the impact of risk factors on global ADRD mortality patterns from 1990 to 2021, utilizing clustering and modeling techniques. Data on ADRD mortality rates, cardiovascular disease, and diabetes prevalence were obtained for 204 countries from the GBD platform. Additional variables such as HDI, life expectancy, alcohol consumption, and tobacco use prevalence were sourced from the UNDP and WHO. All the data were extracted for men, women, and the overall population. Longitudinal k-means clustering and generalized estimating equations were applied for data analysis. The findings revealed that cardiovascular disease had significant positive effects of 1.84, 3.94, and 4.70 on men, women, and the overall ADRD mortality rates, respectively. Tobacco showed positive effects of 0.92, 0.13, and 0.39, while alcohol consumption had negative effects of - 0.59, - 9.92, and - 2.32, on men, women, and the overall ADRD mortality rates, respectively. The countries were classified into five distinct subgroups. Overall, cardiovascular disease and tobacco use were associated with increased ADRD mortality rates, while moderate alcohol consumption exhibited a protective effect. Notably, tobacco use showed a protective effect in cluster A, as did alcohol consumption in cluster B. The effects of risk factors on ADRD mortality rates varied among the clusters, highlighting the need for further investigation into the underlying causal factors.

Contributors to fatigue among nurses working in critical care units: A qualitative study.

BACKGROUND: Fatigue is a growing concern among nurses who provide care to unstable and critically ill patients in critical care wards. It has various negative consequences for both nurses and patients. AIM: To explore and describe contributors to fatigue among nurses working in critical care units. STUDY DESIGN: A qualitative content analysis. RESULTS: Participants were 21 nurses chosen using purposeful sampling. They were working in different critical care units at different hospitals in nine urban areas of Iran. Semi-structured interviews were used to collect data, and conventional content analysis was used to develop categories and subcategories. The analysis of data on the nurses' perspectives and experiences led to developing nine categories as contributors to fatigue: 'compassion fatigue', 'extensive network of interactions', 'sound and alarm fatigue', 'psychological tensions', 'managerial and organizational tensions', 'lack of motivation and incentives', 'individual characteristics of nurses', 'physical and mental pressure', and requirements of special care and situational complexity'. CONCLUSIONS: Understanding the factors that influence the experience of fatigue among nurses working in critical care units is essential for maintaining a reliable and high-quality health care environment within health care facilities. RELEVANCE TO CLINICAL PRACTICE: The experience of fatigue by critical care nurses can increase the possibility of practice errors, reduce patient safety and quality of care, and enhance staff burnout and turnover. Proactive policies should be formulated to assess nurses' fatigue levels and implement strategies for effective fatigue management. This approach aims to enhance both patient safety and job satisfaction in the workplace.

Development of a gastric cancer risk calculator for questionnaire-based surveillance of Iranian dyspeptic patients.

BACKGROUND: Gastric cancer (GC) is considered a silent killer, taking more than three quarters of a million lives annually. Therefore, prior to further costly and invasive diagnostic approaches, an initial GC risk screening is desperately in demand. METHODS: In order to develop a simple risk scoring system, the demographic and lifestyle indices from 858 GC and 1132 non-ulcer dyspeptic (NUD) patients were analysed. We applied a multivariate logistic regression approach to identify the association between our target predictors and GC versus NUD. The model performance in classification was assessed by receiver operating characteristic (ROC) analysis. Our questionnaire covering 64 predictors, included known risk factors, such as demographic features, dietary habits, self-reported medical status, narcotics use, and SES indicators. RESULTS: Our model segregated GC from NUD patients with the sensitivity, specificity, and accuracy rates of 85.89, 63.9, and 73.03%, respectively, which was confirmed in the development dataset (AUC equal to 86.37%, P < 0.0001). Predictors which contributed most to our GC risk calculator, based on risk scores (RS) and shared percentages (SP), included: 1) older age group [> 70 (RS:+ 241, SP:7.23), 60-70 (RS:+ 221, SP:6.60), 50-60 (RS:+ 134, SP:4.02), 2) history of gastrointestinal cancers (RS:+ 173, SP:5.19), 3) male gender (RS:+ 119, SP:3.55), 4) non-Fars ethnicity (RS:+ 89, SP:2.66), 5) illiteracy of both parents (RS:+ 78, SP:2.38), 6) rural residence (RS:+ 77, SP:2.3), and modifiable dietary behaviors (RS:+ 32 to + 53, SP:0.96 to 1.58). CONCLUSION: Our developed risk calculator provides a primary screening step, prior to the subsequent costly and invasive measures. Furthermore, public awareness regarding modifiable risk predictors may encourage and promote lifestyle adjustments and healthy behaviours.

Humoral immunogenicity assessment after receiving three types of SARS-CoV-2 vaccine.

Several vaccines have been developed against SARS-CoV-2 and subsequently approved by national/international regulators. Detecting specific antibodies after vaccination enables us to evaluate the vaccine's effectiveness. We conducted a prospective longitudinal study among members of Tarbiat Modares University of Tehran, Iran, from 4 September 2021 until 29 December 2021. We aimed to compare the humoral immunogenicity of 3 vaccine types. Participants consisted of 462 adults. Anti-SARS-CoV-2 receptor-binding domain [RBD] IgG titer was compared in 3 groups, each vaccinated by available vaccines in Iran at the time: Oxford/AstraZeneca, COVIran Barekat, and Sinopharm. The median IgG titer was: 91.2, 105.6, 224.0 BAU/ml for Sinopharm, COVIran Barekat and Oxford/AstraZeneca respectively after the first dose; 195.2, 192.0, 337.6 BAU/ml after the second one. We also analyzed the frequency of antibody presence in each vaccine group, in the same order the results were 59.0%, 62.6% and 89.4% after the first dose and 92.1%,89.5% and 98.9% after the second. The comparison of results demonstrated that AstraZeneca vaccine is a superior candidate vaccine for COVID-19 vaccination out of the three. Our data also demonstrated statistically significant higher antibody titer among recipients with an infection history.

Development and psychometric properties of Iranian Women's Quality of Life Instrument (IWQOLI): mixed exploratory study.

BACKGROUND: To determine the health needs and promote women's health, their quality of life should be investigated. For this purpose, a valid tool is needed, that has credible validity and reliability, and its concepts are clearly defined and culturally appropriate. This study aimed to develop and assess the psychometric properties of "Iranian Women's Quality of Life Instrument (IWQOLI)". METHODS: The items of "IWQOLI" were generated from themes extracted (150 items) from a content analysis approach with the participation of 40 women. Face validity of the questionnaire with the participation of 10 women and content validity by 10 experts was approved. To determine the domains of the questionnaire, exploratory factor analysis (principal component extraction method) was performed. Internal consistency and test-retest reliability methods with 14-day intervals (30 women) were used to assess the reliability of WQOLI. RESULTS: After performing the face and content validity, 32 items were deleted. S-CVI/Ave was obtained for the instrument (0.93). The factor structure of the inventory was identified by undertaking a principal component analysis in a sample of 590 women. Five factors were extracted with a total variance account of 56.24% and 28 items dropped at this point. The IWQOLI score was significantly correlated with the SF-36 (r = 0.717, p < 0.001). Reliability was demonstrated with Cronbach's alpha coefficient of 0.919 for the entire scale (90-item). Consistency of the instrument was established with test-retest reliability with an interval of 2 weeks (intra-cluster correlation = 0.889, P < 0.001). CONCLUSIONS: The Iranian women's Quality of life Instrument "IWQOLI", consisting of 90 items representing 5 domains (sense of peace in life, sense of security, health responsibility, pleasant communication, received comprehensive support), demonstrated excellent psychometric properties, so it may be used for measuring women's QOL in practical research.

Improving milk donation behavior through an educational intervention based on the theory of planned behavior: study protocol of a cluster randomized controlled trial.

BACKGROUND: Breastfeeding mothers' decisions to donate their milk is influenced by their knowledge, attitudes, and subjective norms such as their family's opinions on milk donation. In Iran, women have favorable knowledge and positive attitudes toward breastfeeding, but they lack sufficient information and education about milk banks. With respect to current childbearing policies, an increase in the number of infants who will be admitted to neonatal intensive care units is expected. Accordingly, improving milk donation behavior, which requires mothers' intention and ability to donate breast milk, is important for infants' survival and well-being. Therefore, this study aims to evaluate whether an educational program based on the theory of planned behavior affects breastfeeding mothers' decisions to donate their breast milk. METHODS: This cluster randomized controlled trial will be conducted in health centers affiliated to Tehran University of Medical Sciences and will enroll 66 breastfeeding mothers (intervention, n = 33; control, n = 33). After collecting baseline data, the intervention group will begin receiving a 60-minute weekly educational program based on Theory of Planned Behavior components for four weeks. The first follow-up assessment will be conducted immediately after the intervention, and the final one will be conducted 12 weeks later. The primary outcomes are the number of mothers who have donated their breast milk and changes in breastfeeding mothers' knowledge, attitude, subjective norms, and perceived behavioral control about donor human milk and intention to donate milk. DISCUSSION: This trial will evaluate if a well-designed educational program can improve breastfeeding mothers' knowledge and promote their behavioral factors regarding milk donation and lead to a significant increase in the number of potential milk donors. TRIAL REGISTRATION: irct.ir (IRCT20230124057203N1) registered February 14, 2023.

Bayesian clustering of 109 worldwide countries according to the trend of prostate cancer mortality rates from 1990 to 2019.

Neglecting possible growth heterogeneity and focusing only on the overall pattern of prostate cancer mortality rates can result in misunderstandings and incorrect conclusions about the growth process of the outcome. The main goal of this study was to capture the heterogeneity of prostate cancer mortality rates among countries from 1990 to 2019. To accomplish this aim, we performed the Bayesian latent Growth Mixture Model (GMM). In this longitudinal study, Prostate cancer mortality rates data from 1990 to 2019, as well as the Human Development Index (HDI), the Gross National Income (GNI), and the Life Expectancy at Birth (LEB), were obtained from WHO and UNDP platforms. The Bayesian GMM was used to discover homogeneous subgroups and estimate the pattern of prostate cancer mortality rates in each subgroup. The HDI, GNI and life expectancy effects were estimated using a Bayesian conditional Latent Growth Model (LGM). Globally, the intercept and the slope of the Bayesian LGM were equal to 8.77 and 0.19, respectively. The Bayesian GMM classified the 109 countries into four groups, which had significant positive growth patterns with different slopes except for the first class. The effect of HDI was not significant on the overall prostate cancer death rates, but GNI and LEB had a significantly positive effect on the model's intercepts and a significantly negative effect on the slope. Although the prostate cancer mortality rate increased globally, it has four distinct latent subgroups with various patterns. Additionally, the effects of HDI, GNI, and LEB on prostate cancer mortality rates varied significantly among the four subgroups, indicating a need for further investigation to identify causal factors.

Regularized Machine Learning Models for Prediction of Metabolic Syndrome Using GCKR, APOA5, and BUD13 Gene Variants: Tehran Cardiometabolic Genetic Study.

OBJECTIVE: Metabolic syndrome (MetS) is a complex multifactorial disorder that considerably burdens healthcare systems. We aim to classify MetS using regularized machine learning models in the presence of the risk variants of GCKR, BUD13 and APOA5, and environmental risk factors. MATERIALS AND METHODS: A cohort study was conducted on 2,346 cases and 2,203 controls from eligible Tehran Cardiometabolic Genetic Study (TCGS) participants whose data were collected from 1999 to 2017. We used different regularization approaches [least absolute shrinkage and selection operator (LASSO), ridge regression (RR), elasticnet (ENET), adaptive LASSO (aLASSO), and adaptive ENET (aENET)] and a classical logistic regression (LR) model to classify MetS and select influential variables that predict MetS. Demographics, clinical features, and common polymorphisms in the GCKR, BUD13 and APOA5 genes of eligible participants were assessed to classify TCGS participant status in MetS development. The models' performance was evaluated by 10-repeated 10-fold crossvalidation. Various assessment measures of sensitivity, specificity, classification accuracy, and area under the receiver operating characteristic curve (AUC-ROC) and AUC-precision-recall (AUC-PR) curves were used to compare the models. RESULTS: During the follow-up period, 50.38% of participants developed MetS. The groups were not similar in terms of baseline characteristics and risk variants. MetS was significantly associated with age, gender, schooling years, body mass index (BMI), and alternate alleles in all the risk variants, as indicated by LR. A comparison of accuracy, AUCROC, and AUC-PR metrics indicated that the regularization models outperformed LR. Regularized machine learning models provided comparable classification performances, whereas the aLASSO model was more parsimonious and selected fewer predictors. CONCLUSION: Regularized machine learning models provided more accurate and parsimonious MetS classifying models. These high-performing diagnostic models can lay the foundation for clinical decision support tools that use genetic and demographical variables to locate individuals at high risk for MetS.

A Bayesian latent class extension of naive Bayesian classifier and its application to the classification of gastric cancer patients.

BACKGROUND: The Naive Bayes (NB) classifier is a powerful supervised algorithm widely used in Machine Learning (ML). However, its effectiveness relies on a strict assumption of conditional independence, which is often violated in real-world scenarios. To address this limitation, various studies have explored extensions of NB that tackle the issue of non-conditional independence in the data. These approaches can be broadly categorized into two main categories: feature selection and structure expansion. In this particular study, we propose a novel approach to enhancing NB by introducing a latent variable as the parent of the attributes. We define this latent variable using a flexible technique called Bayesian Latent Class Analysis (BLCA). As a result, our final model combines the strengths of NB and BLCA, giving rise to what we refer to as NB-BLCA. By incorporating the latent variable, we aim to capture complex dependencies among the attributes and improve the overall performance of the classifier. METHODS: Both Expectation-Maximization (EM) algorithm and the Gibbs sampling approach were offered for parameter learning. A simulation study was conducted to evaluate the classification of the model in comparison with the ordinary NB model. In addition, real-world data related to 976 Gastric Cancer (GC) and 1189 Non-ulcer dyspepsia (NUD) patients was used to show the model's performance in an actual application. The validity of models was evaluated using the 10-fold cross-validation. RESULTS: The presented model was superior to ordinary NB in all the simulation scenarios according to higher classification sensitivity and specificity in test data. The NB-BLCA model using Gibbs sampling accuracy was 87.77 (95% CI: 84.87-90.29). This index was estimated at 77.22 (95% CI: 73.64-80.53) and 74.71 (95% CI: 71.02-78.15) for the NB-BLCA model using the EM algorithm and ordinary NB classifier, respectively. CONCLUSIONS: When considering the modification of the NB classifier, incorporating a latent component into the model offers numerous advantages, particularly within medical and health-related contexts. By doing so, the researchers can bypass the extensive search algorithm and structure learning required in the local learning and structure extension approach. The inclusion of latent class variables allows for the integration of all attributes during model construction. Consequently, the NB-BLCA model serves as a suitable alternative to conventional NB classifiers when the assumption of independence is violated, especially in domains pertaining to health and medicine.

Maternal mental health concerns during the COVID-19 pandemic in Iran: a content analysis study.

BACKGROUND: As crises occur, attention to physical health usually becomes more than mental health, neglecting mental health, especially in some vulnerable groups such as pregnant women and new mothers, can have adverse consequences. Therefore, it is imperative to recognize and comprehend their mental health needs, particularly during critical situations such as the recent COVID-19 pandemic. The aim of this study was to explain the understanding and experience of mental health concerns faced by pregnant and postpartum women during this pandemic. METHODS: This qualitative study was conducted from March 2021 to November 2021 in Iran. Data were collected using semi-structured in-depth interviews to understand mental health concerns in pregnancy and the postpartum period during the COVID-19 pandemic. Twenty-five purposefully retrieved and participated in the study. Due to the prevalence of coronavirus, most of the participants preferred tele interviews. When data saturation was achieved, the data were codified manually and analyzed using Graneheim and Lundman's approach 2004. RESULTS: Based on the content analysis of the interviews, 2 main themes, 8 categories 23 subcategories were identified. The identified themes were as follows: (1) Maternal mental health threats and (2) Inadequate access to the required information. CONCLUSION: The results of this study showed that the main concern and fear of pregnant and postpartum women in the COVID-19 pandemic was the fear of the possibility of death for themselves and/or their fetus/infant. The knowledge that was obtained from the understanding of pregnant women and new mothers about the mental health concerns during the COVID-19 pandemic can help managers in planning to improve and promote women's mental health, especially in critical situations.

Clinical and immunological characteristics of 69 leukocyte adhesion deficiency-I patients.

BACKGROUND: In order to support the comprehensive classification of Leukocyte Adhesion Deficiency-I (LAD-I) severity by simultaneous screening of CD11a/CD18, this study assessed clinical, laboratory, and genetic findings along with outcomes of 69 LAD-I patients during the last 15 years. METHODS: Sixty-nine patients (40 females and 29 males) with a clinical phenotype suspected of LAD-I were referred to Immunology, Asthma, and Allergy research institute, Tehran, Iran between 2007 and 2022 for further advanced immunological screening and genetic evaluations as well as treatment, were enrolled in this study. RESULTS: The diagnosis median age of the patients was 6 months. Delayed umbilical cord separation was found in 25 patients (36.2%). The median diagnostic delay time was 4 months (min-max: 0-82 months). Forty-six patients (66.7%) were categorized as severe (CD18 and/or CD11a: below 2%); while 23 children (33.3%) were in moderate category (CD18 and/or CD11a: 2%-30%). During the follow-ups, 55.1% of children were alive with a mortality rate of 44.9%. Skin ulcers (75.4%), omphalitis (65.2%), and gingivitis (37.7%) were the most frequent complaints. Genetic analysis of the patients revealed 14 previously reported and three novel pathogenic mutations in the ITGB2 gene. The overall survival of patients with and without hematopoietic stem cell transplantation was 79.3% and 55.6%, respectively. CONCLUSION: Physicians' awareness of LAD-I considering delayed separation of umbilical cord marked neutrophilic leukocytosis, and variability in CD11 and CD18 expression levels, and genetic analysis leads to early diagnosis and defining disease severity. Moreover, the prenatal diagnosis would benefit families with a history of LAD-I.

Therapy-based expert system on function and postural stability after anterior cruciate ligament reconstruction: a pilot study.

PURPOSE: Wii Fit exergames have been less commonly used for the rehabilitation of athletes after Anterior Cruciate Ligament Reconstruction (ACLR). This study aims to investigate the effects of an expert system using Wii Fit exergames compared to conventional rehabilitation following ACLR. A forward-chaining rule-based expert system was developed which proposed a rehabilitation program that included the number and type of exercise in terms of difficulty and ease and the duration of each exercise in a progressive manner according to the patient's physical condition. MATERIALS AND METHODS: Twenty eligible athletes aged 20-30 who underwent ACLR were enrolled in this study and randomly assigned to two groups; and received 12 sessions of either Wii Fit exergames as Wii group (n = 10) or conventional rehabilitation as CL group (n = 10). RESULTS: The main outcomes consisted of pain (Visual Analogue Scale (VAS)), knee effusion, knee flexion range (KFR), thigh girth (TG), single-leg hop for distance (SLHD), and for time (SLHT), static and dynamic balance tests. Both groups had considerable improvement in all outcomes, also there were significantly differences between Wii and CL groups as follows; VAS (P < 0.001), knee effusion (P < 0.001), TG (P = 0.001), KFR (P = 0.012), static balance in stable position (P < 0.001) and in unstable position (P = 0.001), dynamic balance in the anterior (P < 0.001), posteromedial (P < 0.001), posterolateral (P = 0.004) directions, symmetry index of SLHD (P < 0.001) and symmetry index of SLHT (P = 0.013). CONCLUSIONS: The findings showed that using Wii Fit exergames in post-ACLR patients reduced pain and effusion while also improving function and balance significantly. Iranian Registry of Clinical Trials registration number is IRCT20191013045090N1, and the registration date is 03-03-2020.

A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.

BACKGROUND: Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data. METHOD: Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC). RESULTS: The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches. CONCLUSION: Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure.

Non-invasive Brain Stimulation and Prism Adaptation in Art Constructive Errors in Painting.

Introduction: This study aimed to investigate the influence of neglect and the effect of prism adaptation (PA) combined with continuous Theta-burst transcranial magnetic stimulation (cTBS) on the art constructive errors in painting rehabilitation of stroke patients with neglect. Methods: Fourteen patients with neglect and art constructive errors in painting secondary to stroke were randomly assigned to the rehabilitation group and received PA combined with the inhibitory protocol of cTBS over the intact parietal cortex; the control group received PA combined with sham cTBS for two weeks in ten daily sessions. Patients were assessed for art constructive errors in painting in figure copying test (FCT), and coloring test (CT) before and after the intervention. Art constructive errors in painting were classified into omission, deformation, size, neglect of warm colors, and perseveration of errors. Neglect was evaluated using the line bisection task (LBT), figure copying test (FCT), and coloring test (CT). Results: All patients showed a significant improvement in art constructive errors in painting (measured using the pattern of painting' errors in FCT and CT), and neglect (measured using LBT, FCT, and CT) (P<0.05). Omission, neglect of warm colors, and deformation were the most frequent errors. Conclusion: Neglect and rehabilitation influence the painting system in stroke patients. Both approaches improved art constructive errors in painting and neglect symptoms.

The Intention of Waterpipe Tobacco Smoking by Women in the COVID-19 Pandemic and its Contributing Factors: a Nonparametric Path Analysis.

Background: People with waterpipe tobacco smoking (WTS) seem to be more at risk for the serious complications of coronavirus disease 2019 (COVID-19). This study aimed at assessing the behavioral intention (BI) of WTS by women in the COVID-19 pandemic and its contributing factors. Methods: This cross-sectional descriptive-correlational study was conducted in 2020 (ie, during the COVID-19 pandemic). Participants were 300 women randomly selected through multistage sampling from comprehensive healthcare centers in Khorramabad, Iran. Data collection instrument was a 42-item questionnaire with 4 main subscales, namely knowledge, attitude, differential association, and BI. Data were collected through both online and phone-based methods and were analyzed using non-parametirc path analysis. Results: The prevalence of WTS among women was 13% (95% CI, 11.06-14.94) and the mean scores of attitude, differential association, and behavioral intention among participants with WTS were significantly higher than participants without WTS (P < 0.001). Moreover, 46.12% (95% CI, 38.12-54.08) of participants with WTS reported intention to quit WTS due to the COVID-19 pandemic and 43.6% (95% CI, 35.66-51.54) of women with WTS and 16.5% (95% CI, 14.20-18.80) of women without WTS believed in the protective effects of WTS against COVID-19. The path analysis model showed that the BI of WTS had a significant inverse relationship with knowledge and a significant direct relationship with attitude and differential association. Conclusion: This study suggests the need for quality educational and counseling interventions for the general public to correct popular misconceptions about the protective effects of WTS against COVID-19.

Chronic Obstructive Pulmonary Disease: Novel Genes Detection with Penalized Logistic Regression.

OBJECTIVE: This study aimed to introduce novel techniques for identifying the genes associated with developing chronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using regression methods. MATERIALS AND METHODS: This is a secondary analysis of the data from an experimental study. We used penalized logistic regressions with three different types of penalties included least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP), and smoothly clipped absolute deviation (SCAD). The models were trained using genome-wide expression profiling to define gene networks relevant to the COPD stages. A 10-fold cross-validation scheme was used to evaluate the performance of the methods. In addition, we validate our results by the external validity approach. We reported the sensitivity, specificity, and area under curve (AUC) of the models. RESULTS: There were 21, 22, and 18 significantly associated genes for LASSO, SCAD, and MCP models, respectively. The most statistically conservative method (detecting less significant features) was MCP detected 18 genes that were all detected by the other two approaches. The most appropriate approach was a SCAD penalized logistic regression (AUC= 96.26, sensitivity= 94.2, specificity= 86.96). In this study, we have a common panel of 18 genes in all three models that show a significant positive and negative correlation with COPD, in which RNF130, STX6, PLCB1, CACNA1G, LARP4B, LOC100507634, SLC38A2, and STIM2 showed the odds ratio (OR) more than 1. However, there was a slight difference between penalized methods. CONCLUSION: Regularization solves the serious dimensionality problem in using this kind of regression. More exploration of how these genes affect the outcome and mechanism is possible more quickly in this manner. The regression-based approaches we present could apply to overcoming this issue.

Relationship between postpartum depression and plasma vasopressin level at 6-8 weeks postpartum: a cross-sectional study.

Postpartum depression (PPD) is the most important postpartum mood disorder due to its significant effect on both the infant and family health. Arginine vasopressin (AVP) has been suggested as a hormonal agent involved in the development of depression. The purpose of this study was to investigate the relationship between the plasma concentrations of AVP and the score of Edinburgh Postnatal Depression Scale (EPDS). This cross-sectional study was conducted in 2016-2017 in Darehshahr Township, Ilam Province, Iran. In the first phase, 303 pregnant women, who were at 38 weeks, met the inclusion criteria, and were not depressed (according to their EPDS scores) were included in the study. In the 6-8 week postpartum follow-up, using the EPDS, 31 depressed individuals were diagnosed and referred to a psychiatrist for confirmation. The maternal venous blood samples of 24 depressed individuals still meeting the inclusion criteria and 66 randomly selected non-depressed subjects were obtained to measure their AVP plasma concentrations with ELISA assay. There was a significant positive relationship between plasma AVP levels and the EPDS score (P = 0.000, r = 0.658). Also the mean plasma concentration of AVP was significantly higher in the depressed group (41.35 ± 13.75 ng/ml) than in the non-depressed group (26.01 ± 7.83 ng/ml) (P < 0.001). In a multiple logistic regression model for various parameters, increased vasopressin levels were associated with increased odds of PPD (OR = 1.15, 95% CI = 1.07-1.24, P = 0.000). Furthermore, multiparity (OR = 5.45, 95% CI = 1.21-24.43, P = 0.027) and non-exclusive breastfeeding (OR = 13.06, 95% CI = 1.36-125, P = 0.026) were associated with increased odds of PPD. Maternal gender preference (having a baby of desired and desired sex) decreased the odds of PPD (OR = 0.13, 95% CI = 0.02-0.79, P = 0.027 and OR = 0.08, 95% CI = 0.01-0.5, P = 0.007). AVP seems to be a contributor to clinical PPD by affecting the hypothalamic-pituitary-adrenal (HPA) axis activity. Furthermore, primiparous women had significantly lower EPDS scores.

Design and psychometric properties of the family support for older people questionnaire.

Background and objectives: The population of older people is increasing across the world. Older people need care and support from their families to be able to live independently. This study aimed to design and evaluate the psychometric properties of the family support for older people (FSOP) questionnaire. Methods: In this instrument development study using a mixed-methods design, the psychometric properties of the FSOP questionnaire in terms of validity and reliability were evaluated. Results: The FSOP questionnaire consisted of 50 items in six domains. It was shown to have appropriate qualitative and quantitative validities (score > 1.5). The indicators of content validity (CVR > 0.62, ICVI ≥ 0.80, and SCVI > 0.94) and confirmatory factor analysis (indexes of χ2/df = 2.50, CFI = 0.96, GFI = 0.97, AGFI = 0.96, NNFI = 0.96, PNFI = 0.89, TLI = 0.96, and RMSEA = 0.06) were satisfactory. Cronbach's alpha coefficient for reliability was 0.94, indicating an optimal score. Conclusions: Healthcare providers and family caregivers are suggested to use the FSOP questionnaire for improving the quality of life of older people at home.

The spousal role of middle-aged Iranian women: A qualitative content-analysis study.

This study aimed to explain the spousal role in the lives of Iranian middle-aged women. This qualitative study was conducted in Iran from July 2018 to November 2019. The participants included 25 middle-aged women selected through purposive sampling. The data were collected using semi-structured interviews and analyzed through conventional content analysis. The theme of reviving the spousal role was explained by three main categories of paying more attention to the spouse's needs, enhancing feminine charms, and maintaining married life. A deeper understanding of the middle-aged women's spousal role may help health-care personnel to develop indigenous marriage-enrichment programs for middle-aged individuals.