An Evaluation of Antibacterial Effects of Human Amniotic Fluid on Pathogenic and Probiotic Bacteria In Vitro.

Background: Amniotic fluid in the uterus is beneficial for the fetus growth and protection due to its nutritional elements as well as its antibacterial and anti-inflammatory properties. Today, body membranes are increasingly being used in multiple fields. The purpose of the current study was evaluation of the antibacterial effects of amniotic fluid and comparison of its effects on pathogenic and probiotic bacteria. Methods: This experimental study was conducted on amniotic fluid obtained from 43 healthy mothers who gave birth by selective cesarean section. Then, antibacterial effects of amniotic fluids were investigated on 8 standard bacterial strains, including Bacillus cereus, Escherichia coli, Staphylococcus aureus, Shigella flexneri, Pseudomonas aeruginosa, Klebsiella pneumoniae, Bacillus cereus, and Lactobacillus plantarum by agar well-diffusion method. Data analysis was performed by SPSS software, vs. 22 (IBM, US). Results: Amniotic fluid revealed an inhibitory effect on the growth of bacterial strains. Staphylococcus aureus and Streptococcus pyogenes strains showed growth inhibition in 39% and 17% of samples, respectively. In other bacterial strains, there was growth inhibition in less than 5% of the samples. Also, the zone of growth inhibition for Staphylococcus aureus and Streptococcus pyogenes was significantly higher than the other strains. Amniotic fluid samples had an antibacterial effect on all pathogen strains in general, but not on the Lactobacillus plantarum probiotic strain. Conclusion: Our findings suggest that the antibacterial effect of amniotic fluid on pathogenic bacteria is significantly higher than the Lactobacillus plantarum as a probiotic one. Overall, the findings support the use of natural substances as alternative therapeutic agents to combat antibiotic resistance.

Evaluation of psychometric properties of the Dental Anxiety Inventory (DAI-36) questionnaire using iterative hybrid ordinal logistic: Differential item functioning (DIF).

OBJECTIVES: Dental Anxiety Inventory (DAI-36) questionnaire is an instrument for assessing dental anxiety. The different perceptions of the questionnaire items in the individual at the same level of underlying dental anxiety may lead to different reported dental anxieties. This study aims to determine the differential item functioning (DIF) of the DAI-36 measure items. METHODS: The DAI-36 was completed by 950 participants. An iterative hybrid ordinal logistic regression model was used to detect DIF across gender, education, and age groups. DIF analysis was done by lordif package in R3.1.3 software. RESULTS: The chi-square statistics declared 7, 7, and 4 nonuniform DIF items, and 2, 5, and 4 uniform DIF items across gender, education, and age groups, respectively. ΔR2 was always lower than 0.07 in all uniform and nonuniform DIF items. However, Δß1 revealed significant uniform DIF in items 1 and 8 across gender (Δß1(item 1) = 0.0137, Δß1(item 8) = 0.0124) and items 22 and 27 across age categories (Δß1(item 22) = 0.0110, Δß1(item 27) = 0.0136). CONCLUSIONS: DIF items had no large magnitude or cancel out each other, so statements phrased in the DAI-36 questionnaire have equivalent meaning across participants, regardless of their gender, education, and age groups.

COVID-19 screening: use of an artificial neural network.

OBJECTIVES: COVID-19 is the biggest pandemic of the 21st century. The disease can be influenced by various sociodemographic factors and can manifest as clinical, pulmonary and gastrointestinal symptoms. This study used an artificial neural network (ANN) model with important sociodemographic factors as well as clinical, pulmonary and gastrointestinal symptoms to screen patients for COVID-19. Patients themselves can screen for these symptoms at home. METHODS: Data on all registered patients were extracted in autumn. The best ANN model was selected from different combinations of connections, some hidden layers and some neurons in each hidden layer. In this study, 70% of the data were used in the network training process and the remaining 30% were used to evaluate the function of the multilayer, feed-forward, back-propagation algorithm. RESULTS: The sensitivity and specificity of the ANN model in diagnosing patients with COVID-19 were 94.5% and 17.4%. In order of priority, clinical symptoms, sociodemographic factors, pulmonary symptoms and gastrointestinal symptoms were important predictive factors for COVID-19 using the ANN model. Screening patients for COVID-19 using clinical symptoms and sociodemographic factors (80% importance) remains essential. CONCLUSIONS: Home monitoring of oxygen saturation and body temperature as well as old age and drug addiction can be helpful in self-screening symptoms of COVID-19 at home, thereby preventing unnecessary visits to medical centres and reducing burden on medical services.

Applying artificial neural-network model to predict psychiatric symptoms.

Introduction: Mental disorders result in mental disabilities and discomfort in the affected person as they affect both thinking and behavior. Therefore, more vulnerable people must first be identified to improve the psychological level of society. Aim: This study aims to determine the importance of gender, employment, education, place of residence, and age in predicting mental disorders using artificial neural network modeling. Methods: The pattern held between variables in this study will be identified using multilayer feed-forward back-propagation neural networks with five inputs and 10 outputs. To determine the neural network with the least sum of square errors, we evaluated the performance of all neural networks with varying algorithms and different numbers of neurons in the hidden layer. Data were analyzed for 380 people aged 10-82 years using the SPSS software. Results: The optimal neural network model was effective in predicting mental disorders. In this model, the variables of the place of residence, education, age, gender, and employment were important in fitting the optimal model with 34.08, 20.11, 18.93, 14.55, and 12.33%, respectively. The accuracy rate for the neural network model was 99.2%. Conclusion: To achieve further results in improving mental health problems, it is better to focus more on employed, rural, and younger people with a non-tertiary education level.

Artificial neural networks (ANNs) for modeling efficient factors in predicting pap smear screening behavior change stage.

Background and objectives: Cervical cancer is ranked as the third most prevalent cancer that affects women all over the world and Pap smear seems to be the single most critical intervention to prevent cervical cancer. In the present study, the effects of demographic factors (age, education level, job, income level, marriage age, pregnancy, child number, breastfeeding, and menopause), insurance type, disease history and screening (sono and mammography, breast problem) and cancer information on Pap smear screening and behavior stage of change were investigated and modeled using an artificial neural network model (ANN). Materials and methods: Data were collected from a descriptive-analytical cross-sectional study. This research was conducted on 1898 female employees of governmental agencies of Birjand, a city located in the east of Iran. The questionnaire consisted of four parts (socioeconomic, reproductive characteristics, information about cervical cancer screening, and stage of change for cervical cancer screening). Multilayer feed-forward back-propagation neural networks were used to detect the patterns between variables using a neural network with 14 inputs and one output. To find out the neural network with the minimum sum of squared errors, we evaluated the performance of all neural networks using varying algorithms and numbers of neurons in the hidden layer. For this purpose, the data collected from 1898 women were analyzed using SPSS-22 software. Results: In the optimal ANN model, the variables of marriage age, age, breastfeeding, and the number of children were identified as the most significant factors with 18.3, 16.3, 7.3, and 7.3 percent, respectively, whereas the history of cancer, job, pregnancy, and menopause had importance of lower than 5 percent. Conclusion: Our findings showed that among many associated variables, the marriage age, age, breastfeeding, and the number of children were the most important predictors for the behavioral stage of change. Thus, it seems, focusing on these factors may lead to the adoption of effective programs and policies to improve cervical cancer screening practices in women.

The Comparison of Inflammatory Cytokines between Spinal and General Anesthesia following Changes in Ischemic Reperfusion due to Tourniquet during Lower Limb Surgery.

METHODS: In this randomized controlled clinical trial, 34 patients with lower limb surgery admitted at the orthopedic ward of Imam Reza Hospital, Birjand, Iran, were selected by the available sampling method. They were randomly divided into two groups as follows: general anesthesia (n = 17) and spinal anesthesia (n = 17). Venous blood samples were taken from the patients of both groups at baseline (before the use of tourniquet) and 12 and 24 hours after reperfusion. Interleukin-6 (IL-6), tumor necrotizing factor-α (TNF-α), high-sensitivity C-reactive protein (hs-CRP), and ferritin were measured and recorded. The data were analyzed using independent t-test, chi-square, and repeated measure at the significant level of 0.05. RESULTS: The results showed that hs-CRP and IL-6 significantly increased during the study (p < 0.001); however, the mean changes of TNF-α and ferritin were not significant during the study. Moreover, none of the inflammatory cytokines indicated significant differences between these two study groups (p < 0.05). CONCLUSION: According to the results, the use of tourniquet can lead to inflammation, and the inflammation is similar in both groups.

Dry Eye and Meibomian Glands in Vitiligo

Objectives: To evaluate aqueous and lipid tear film parameters and the meibomian glands (MGs) with non-contact meibography in patients with vitiligo. Materials and Methods: This case-control study was conducted in the right (OD) and left (OS) eyes of 43 patients with vitiligo and 43 controls in Birjand, Iran. In addition to demographic information and skin disease characteristics, the Ocular Surface Disease Index (OSDI) questionnaire was completed for each patient, followed by eye examinations including slit lamp examination, Schirmer test, strip meniscometry (SMTube), and tear break-up time (TBUT) measurement. The MGs were also imaged using a non-contact meibography system (SBM System, Italy). The data were analyzed using SPSS version 22.0 with a significant level of less than 0.05. Results: Patients had higher OSDI score than controls but it was not significant (10.90±13.03 vs. 5.57±6.85; p=0.07). There were significant differences between the groups in mean Schirmer test values for both eyes (OD: 8.07±5.47 vs. 17.37±6.52; OS: 7.60±5.00 vs. 17.30±6.44, p<0.001) and mean SMTube results (OD: 4.49±2.40 vs. 9.74±3.67; OS: 4.30±2.81 vs. 9.65±4.52; p<0.001). However, mean TBUT did not differ between the groups (OD: 9.14±3.17 vs. 10.12±2.08, p=0.27; OS: 9.16±3.30 vs. 10.05±2.10, p=0.25). Meibography also showed no significant difference in MG dropout between the groups (OD: 20.86±9.79 vs. 21.05±12.07; p=0.74; OS: 18.16±8.83 vs. 19.53±10.30; p=0.51). Conclusion: Vitiligo is associated with a reduction in the production of aqueous tear film, but does not affect the structure and function of the MGs.

Association between Cardiometabolic risk factor and responsiveness to vitamin D supplementation: a new approach using artificial neural network analysis.

BACKGROUND: There are increasing data highlighting the effectiveness of vitamin D supplementation in the treatment of vitamin D deficiency. But individuals vary in their responsiveness to vitamin D supplementation. In this study, the association between several cardiometabolic risk factors and the magnitude of response to vitamin D supplementation (change in vitamin D level) was investigated using a novel artificial neural networks (ANNs) approach. METHODS: Six hundred eight participants aged between 12 to 19 years old were recruited to this prospective interventional study. Nine vitamin D capsules containing 50,000 IU vitamin D/weekly were given to all participants over the 9 week period. The change in serum 25(OH) D level was calculated as the difference between post-supplementation and basal levels. Suitable ANNs model were selected between different algorithms in the hidden and output layers and different numbers of neurons in the hidden layer. The major determinants for predicting the response to vitamin D supplementation were identified. RESULTS: The sigmoid in both the hidden and output layers with 4 hidden neurons had acceptable sensitivity, specificity and accuracy, assessed as the area under the ROC curve, was determined in our study. Baseline serum vitamin D (30.4%), waist to hip ratio (10.5%), BMI (10.5%), systolic blood pressure (8%), heart rate (6.4%), and waist circumference (6.1%) were the most important factors in predicting the response to serum vitamin D levels. CONCLUSION: We provide the first attempt to relate anthropometric specific recommendations to attain serum vitamin D targets. With the exception of cardiometabolic risk factors, the relative importance of other factors and the mechanisms by which these factors may affect the response requires further analysis in future studies (Trial registration: IRCT201509047117N7; 2015-11-25; Retrospectively registered).

The study of dry eye and meibomian glands in psoriasis.

BACKGROUND: To investigate aqueous and lipid layers of the tear film as well as meibomian gland structure by meibography in psoriatic patients in the Iranian population. METHODS: This case-control study was conducted on 31 psoriasis patients and 31 controls in Birjand University of Medical Sciences in 2018. The sampling method was available from the date of approval of the proposal in the Ethics Committee until it reached the sample size. After entering the study, patients were examined individually with a slit lamp. Then, Ocular Surface Disease Index (OSDI) score assessment, Schirmer test 1, lacrimal measurement with SM tube, tear break-up time (TBUT), and meibomian glands imaging by SBM Sistemi were done. Finally, the obtained data were entered into SPSS 15 software and analyzed at a significant level of less than 0.05. RESULTS: The two groups were matched according to age and gender (p = 0.39 and p = 0.80; respectively). With the exception of the SM Tube score, the mean of all tear film and meibomian glands functional and structural parameters including Schirmer test 1, TBUT, and meibography were significantly different between patients and control groups. Moreover, the proportion of abnormal OSDI (OSDI ⩾ 13) and the dry eye was significantly higher in psoriasis patients. CONCLUSIONS: Psoriasis is associated with dry eye as well as meibomian glands atrophy and dysfunction.

Predicting mental health of prisoners by artificial neural network.

INTRODUCTION: Maintaining and improving prisoners' health and their rehabilitation can be effective steps towards eliminating health inequalities and approaching the UN's Sustainable Development Goals. Accordingly, identifying protective factors and health barriers of this vulnerable group and changing the prison into an environment that can deliver health interventions tailored to the needs of inmates can provide the basis for attaining justice in health. PURPOSE: This study builds on an artificial neural network model to determine the effect of demographic, psychological, criminological, and physical activity factors on prisoners' general health. METHODS: The study detected the patterns between variables using a neural network with nine inputs and one output. To determine the neural network with the minimum sum of squared errors, we evaluated the performance of all neural networks using varying algorithms and numbers of neurons in the hidden layer. For this purpose, the analysis of the data of 149 prisoners aged between 16 and 61 years was performed using SPSS-22 software. RESULTS: The optimal neural network model was useful in predicting prisoners' general health. In this model, the variables of occupation, life expectancy, age, and hope of acceptance were identified as the first most significant factors with 19.25, 17.45, 15.98, and 15.16 percentages, respectively, whereas the cause of incarceration, education level, type of drug misuse, and physical activity were the second most important factors with 8.82, 8.38, 7.91, and 7.04 percentages, respectively. CONCLUSION: Experiencing psychosocial pressures related to incarceration is more severe for the marginalized and disadvantaged individuals, persons in very young or old age ranges, and those with no history of incarceration, which can increase the likelihood of impaired health for these inmates. Consideration of the prisoners' needs in proportion to their characteristics and provision of emotional and spiritual support of the inmates, especially in the early stages of incarceration, can help shape an effective adjustment process and select appropriate and efficient strategies.

Differential item functioning analysis on the Geriatric Depression Scale-15: An iterative hybrid ordinal logistic regression.

The elderly population has extensively increased globally, so depression like a common problem in late life may convert to one of the economic, social, and health challenges of the 21st century. Due to the high cost of clinical diagnosis of depression, it is necessary to provide effective questionnaires like the 15-item Geriatric Depression Scale (GDS-15) for screening. But, the measurement invariance of GDS-15 is still unknown in the general population. In our study, 1473 participants of all Iran's ethnic groups were asked to answer GDS-15 and demographic factors such as human settlements, employment, disease, marital status, age, gender, homebound, financial status, and ethnicity. Then, the lordif package in R 3.1.3 was used to assess differential item functioning (DIF) items that behave unevenly across demographic factors. Our findings reveal that women, homebound patients, poorer, and non-Persian mother tongue score classic psychological symptoms higher than peoples of the same depression score in other groups. Since, psychologists have to remove or replace these items before using this questionnaire for screening geriatric depression.

Differential item functioning analysis of the Bar-On Emotional Quotient Inventory (EQ-i) across gender and age groups: an iterative hybrid ordinal logistic regression / Funcionamiento diferencial de los ítems del Inventario de Cociente Emocional de Bar-On (EQ-i): una regresión logística ordinal híbrida iterativa

Abstract There has been a heated debate on emotional intelligence (EI) and, more particularly, on the Bar-On Emotional Quotient Inventory (EQ-i) measuring all dimensions of emotional intelligence. To ensure measurement equivalence of EQ-i, the present article evaluated whether statements phrased in EQ-i questionnaire have equivalent meaning across respondents, regardless of their sex and age group membership. For 2,078 participants, three EI subscale (item 50 in reality testing, items 4 and 19 in stress tolerance, and items 7, 52, and 82 in interpersonal) for age groups had clinically significant Differential item functioning (DIF). So previous observed associations between EI and age might be misleading and deserve further study after removing or replacing DIF items.

Resumen En medio del acalorado debate sobre la Inteligencia Emocional, este estudio retoma el Inventario de Cociente Emocional Bar-On (EQ-i), que mide todas las dimensiones de este constructo psicológico. Con el fin de comprobar la equivalencia de medición de EQ-i, se comprueba si las declaraciones formuladas en el cuestionario EQ-i tienen un significado equivalente entre los encuestados, independientemente de su sexo y grupo de edad. Se aplicó a los 2078 participantes las tres subescalas de IE. Se halló un funcionamiento diferencial de los ítems (DIF) clínicamente significativo. Por lo tanto, las asociaciones observadas anteriormente entre la IE y la edad pueden ser espurias y merecen un estudio adicional después de eliminar o reemplazar los elementos DIF.

The relationship between neuropsychological function and responsiveness to vitamin D supplementation using artificial neural networks.

BACKGROUND: Vitamin D has recently attracted interest for its pleiotropic effects. Vitamin D supplements are a potentially important public health intervention, but the response to supplementation varies between individuals. AIM: We aimed to assess the association between several neuropsychological parameters and the magnitude of response to vitamin D supplementation using an artificial neural network method. METHODS: Neuropsychological function was assessed in 619 participants using standard questionnaires. The study participants received vitamin D capsules containing 50,000 IU vitamin D per week over 9 weeks. To assess the relationship between responsiveness to vitamin D supplements and the impact on these neuropsychological parameters, the best-performing artificial neural network algorithms were selected from a combination of different transfer functions in hidden and output layers and variable numbers of hidden layers (between two and 50). The performance of the artificial neural network algorithm was assessed by receiver operating characteristic analysis and variables of importance were identified. RESULTS: The artificial neural network algorithm with sigmoid transfer function in both hidden and output layers could predict responsiveness to vitamin D supplementation effectively. The sensitivity and specificity were between 0.60 and 0.70 and 0.66 and 0.70, respectively. Cognitive abilities (42.5%), basal vitamin D (21.3%), body mass index (9.5%), and daytime sleepiness (8%) are the most widely used variables to predict changes in serum vitamin D levels. CONCLUSIONS: Cognitive abilities status and baseline 25-hydroxyvitamin D are important novel modifiers of the enhancement in circulating 25-hydroxyvitamin D after vitamin D supplementation.

Application of artificial neural network in predicting EI.

Emotional intelligence (EI) constitutes a whole set of non-cognitive capabilities, competencies, and skills that affect one's ability to deal successfully with environmental demands and pressures. Different factors such as gender, age, education, place of residence, etc. can influence this variable. Nevertheless, the influence of a multitude of factors involved in behavioral phenomena cannot often be controlled. PURPOSE: Therefore, some difficulty may often raise in finding associations between these variables using regression models as regression models are built on restrictive assumptions. METHODS: In these cases, models such as artificial neural networks are excellent alternatives to regression models. In this study, the neural network model was used in SPSS software to predict the pattern held among the variables of age, gender, occupation, marital status, and education for predicting the EI of 901 individuals aged from 17 to 73 years. RESULTS: The appropriate neural network model for EI prediction is a hyperbolic tangent transfer function with two neurons in the hidden layer and a sigmoid transfer function in the output layer. This network was able to predict EI in most of its dimensions with significant correlations and could demonstrate the neural network's advantage over regression models in predicting EI using sociological variables. CONCLUSION: This model is able to estimate the EI level in different occupational, educational, gender, and age groups, and provide the ground for planning to address potential deficiencies in each group.

The Effect of High-Dose Vitamin C on Biochemical Markers of Myocardial Injury in Coronary Artery Bypass Surgery.

OBJECTIVE: To evaluate the effect of high-dose vitamin C on cardiac reperfusion injury and plasma levels of creatine kinase-muscle/brain (CK-MB), troponin I, and lactate dehydrogenase (LDH) in patients undergoing coronary artery bypass grafting (CABG). METHODS: This is a double-blind randomized clinical trial study. Fifty patients (50-80 years old) who had CABG surgery were selected. The intervention group received 5 g of intravenous vitamin C before anesthesia induction and 5 g of vitamin C in cardioplegic solution. The control group received the same amount of placebo (normal saline). Arterial blood samples were taken to determine the serum levels of CK-MB, troponin I, and LDH enzymes. Left ventricular ejection fraction was measured and hemodynamic parameters were recorded at intervals. RESULTS: High doses of vitamin C in the treatment group led to improvement of ventricular function (ejection fraction [EF]) and low Intensive Care Unit (ICU) stay. The cardiac enzymes level in the vitamin C group was lower than in the control group. These changes were not significant between the groups in different time intervals (anesthesia induction, end of bypass, 6 h after surgery, and 24 h after surgery) for CK-MB, LDH, and troponin I. Hemodynamic parameters, hematocrit, potassium, urinary output, blood transfusion, arrhythmia, and inotropic support showed no significant difference between the groups. CONCLUSION: Vitamin C has significantly improved the patients' ventricular function (EF) 72 h after surgery and reduced the length of ICU stay. No significant changes in cardiac biomarkers, including CK-MB, troponin I, and LDH, were seen over time in each group. IRCT CODE: IRCT2016053019470N33.

The effect of high-dose vitamin c on biochemical markers of myocardial injury in coronary artery bypass surgery

Abstract Objective: To evaluate the effect of high-dose vitamin C on cardiac reperfusion injury and plasma levels of creatine kinase-muscle/brain (CK-MB), troponin I, and lactate dehydrogenase (LDH) in patients undergoing coronary artery bypass grafting (CABG). Methods: This is a double-blind randomized clinical trial study. Fifty patients (50-80 years old) who had CABG surgery were selected. The intervention group received 5 g of intravenous vitamin C before anesthesia induction and 5 g of vitamin C in cardioplegic solution. The control group received the same amount of placebo (normal saline). Arterial blood samples were taken to determine the serum levels of CK-MB, troponin I, and LDH enzymes. Left ventricular ejection fraction was measured and hemodynamic parameters were recorded at intervals. Results: High doses of vitamin C in the treatment group led to improvement of ventricular function (ejection fraction [EF]) and low Intensive Care Unit (ICU) stay. The cardiac enzymes level in the vitamin C group was lower than in the control group. These changes were not significant between the groups in different time intervals (anesthesia induction, end of bypass, 6 h after surgery, and 24 h after surgery) for CK-MB, LDH, and troponin I. Hemodynamic parameters, hematocrit, potassium, urinary output, blood transfusion, arrhythmia, and inotropic support showed no significant difference between the groups. Conclusion: Vitamin C has significantly improved the patients' ventricular function (EF) 72 h after surgery and reduced the length of ICU stay. No significant changes in cardiac biomarkers, including CK-MB, troponin I, and LDH, were seen over time in each group. IRCT code: IRCT2016053019470N33

Comparison of Infusion of Propofol and Ketamine-Propofol Mixture (Ketofol) as Anesthetic Maintenance Agents on Blood Pressure of Patients Undergoing Orthopedic Leg Surgeries.

BACKGROUND: Some studies have reported the effects of anesthesia induction using a single propofol dose and low ketamine doses in short-term outpatient operations. OBJECTIVES: In this study, we aimed to evaluate the intra and post-operative hemodynamic effects of ketamine-propofol mixture (Ketofol) infusion in comparison with propofol infusion. METHODS: This study was performed on 54 class I and II of the American Society of Anesthesia patients aged 15 to 45 years who were candidates for leg fracture surgery. The patients were randomly assigned to propofol and ketofol groups. In the propofol and ketofol groups, propofol infusion (100 µg/kg/min) and propofol-ketamine infusion (50 µg/kg/min propofol + 25 µg/kg/min ketamine) were used for the maintenance of anesthesia, respectively. Heart rate and systolic, diastolic and mean blood pressure before, immediately after the induction of anesthesia and at 10-minute intervals were measured and recorded. Pain, nausea, and vomiting were recorded immediately after surgery and each 2 hours until 6 hours. RESULTS: Systolic, diastolic and mean blood pressure were significantly higher in the ketofol group than in the propofol group at 10 - 60 min intervals (P < 0.05). There was no significant difference, however, between the two groups in terms of the severity of nausea and pain and vomiting frequency. CONCLUSIONS: Infusion of hypnotic doses of ketofol leads to increase in diastolic and systolic blood pressure and improves blood pressure stability in addition to inducing more as compared with propofol infusion, but it leads to higher risk of nausea and vomiting.

A Simulation Study to Assess the Effect of the Number of Response Categories on the Power of Ordinal Logistic Regression for Differential Item Functioning Analysis in Rating Scales.

Objective. The present study uses simulated data to find what the optimal number of response categories is to achieve adequate power in ordinal logistic regression (OLR) model for differential item functioning (DIF) analysis in psychometric research. Methods. A hypothetical ten-item quality of life scale with three, four, and five response categories was simulated. The power and type I error rates of OLR model for detecting uniform DIF were investigated under different combinations of ability distribution (θ), sample size, sample size ratio, and the magnitude of uniform DIF across reference and focal groups. Results. When θ was distributed identically in the reference and focal groups, increasing the number of response categories from 3 to 5 resulted in an increase of approximately 8% in power of OLR model for detecting uniform DIF. The power of OLR was less than 0.36 when ability distribution in the reference and focal groups was highly skewed to the left and right, respectively. Conclusions. The clearest conclusion from this research is that the minimum number of response categories for DIF analysis using OLR is five. However, the impact of the number of response categories in detecting DIF was lower than might be expected.

Item-level informant discrepancies across obese-overweight children and their parents on the PedsQL™ 4.0 instrument: an iterative hybrid ordinal logistic regression.

PURPOSE: Child obesity has become a major health concern worldwide. In order to provide successful intervention strategies, it is necessary to understand how obese-overweight children and their parents perceive obesity and its consequences on child's health-related quality of life (HRQoL). This study aimed to assess measurement equivalence of the PedsQL™ 4.0 across obese-overweight children and their parents. METHODS: The items in the PedsQL™ 4.0 were analysed for differential item functioning (DIF) across obese-overweight children and their parents using an iterative hybrid ordinal logistic regression/item response theory approach. The sample included 647 overweight-obese children and their parents, who completed child and parent reports of the PedsQL™ 4.0, respectively. RESULTS: Overall, 17 out of 23 (74%) items were flagged with DIF across two groups: eight items exhibited uniform DIF and nine items non-uniform DIF. In addition, parents of obese children rated the child's HRQoL significantly lower than their children in all domains of the PedsQL™ 4.0, and this finding did not change whether or not items with uniform DIF were included. CONCLUSIONS: Although obese-overweight children and their parents interpret items of the PedsQL™ 4.0 in a conceptually different manner, removing or retaining DIF items in the subscales had no significant effects on group differences. Accordingly, it appears that observed differences in HRQoL scores across child and parent reports are a true difference and not a reflection of measurement artefact.

Testing measurement equivalence of the SF-36 questionnaire across patients on hemodialysis and healthy people.

BACKGROUND: Differential item functioning (DIF) occurs when members from different groups respond differently to particular items in a health-related quality of life (HRQoL) questionnaire after controlling for underlying HRQoL construct. This study aimed to assess DIF in the SF-36 questionnaire and its effect on comparing HRQoL scores across patients on HD and healthy people. METHODS: One hundred fifty patients on maintenance hemodialysis (HD) and 642 healthy individuals filled out the Persian version of the SF-36 questionnaire. Multiple-group multiple-indicator multiple-causes (MG-MIMIC) model was used to assess DIF across patients on HD and healthy population. RESULTS: Sixteen out of 36 (44.4 %) items were flagged with DIF. Six out of 16 items (37.5 %) were flagged with uniform DIF, nine items (56.2 %) with non-uniform DIF, and one item (6.2 %) with both uniform DIF and non-uniform DIF. DIF items were associated with all subscales with the exception of the limitation due to physical problems and bodily pain subscales. The significant lower HRQoL scores of patients on HD in comparison with healthy people in the physical functioning and vitality subscales did not change after removing the items with uniform DIF. CONCLUSIONS: Our findings revealed that patients on HD and healthy people perceived the meaning of the items in SF-36 questionnaire differently. Although the impact of DIF is minimal, the cross-group comparison across patients on HD and healthy people should be performed with caution.