The psychosocial challenges of mothers of children with thalassemia: A qualitative study.

BACKGROUND: Caring for the children suffering from thalassemia is a stressful experience with various aspects making the mothers face various challenges. Thus, the present study aimed to explain the psychosocial challenges of mothers with thalassemia children based on their lived experience. MATERIALS AND METHODS: In this qualitative study, which was conducted using the phenomenological method, 14 mothers with thalassemia children were selected from two thalassemia treatment centers in Hamadan and Babol (Iran) in 2020 using the purposive sampling method. Data were collected using in-depth and semi-structured interviews and were analyzed by van Manen's phenomenological methodology. RESULTS: In the first stage of data analysis, 534 initial codes were extracted, which were reduced to 290 by comparison and integration. The primary themes turned into 24 secondary themes after clustering. By comparing the secondary themes, three main themes (i.e., "psychological distress," "bodily burnout," and "mothers' need to empathy and support") with 7 secondary themes (i.e., "emotional exhaustion," "mental strain," "social stigma," "acute psychosomatic reactions," "long-term psychosomatic consequences," "expectation of family support," and support needs outside the family) were extracted. CONCLUSION: The results indicated that mothers with thalassemia children experience several challenges in various aspects. Therefore, they require care interventions and psychosocial support.

The concept of coping in male spouses of Iranian women with breast cancer: A qualitative study using a phenomenological approach.

INTRODUCTION: Breast cancer is a multidimensional crisis that affects not just the patient, but the spouse and other family members. Coping with this phenomenon, as one of the important challenges for the families and spouses, requires investigation. Understanding more about how spouses of women with breast cancer cope with this crisis could lead to better performance of spouses in front of their wives and raise their wives' quality of life. PURPOSE: The study was conducted to explore the concept of coping based on the lived experiences of spouses of women with breast cancer. METHODS: This qualitative study was conducted with a phenomenological approach in Hamedan and Rasht cities in Iran in 2019. Participants included 20 spouses of women with breast cancer selected by a purposive sampling method. Data were collected through unstructured face-to-face interviews and analyzed using van Manen's six-stage phenomenological method. RESULTS: The lived experiences of participants showed that the phenomenon of coping in spouses of women with breast cancer included five themes: Emotional pain, Shouldering the burden of care, Striving for family life cohesion, Future in ambiguity, and Sense of loss of self concept. Understanding the concept of coping in the spouses of women with breast cancer in health strategies can help wives achieve effective adaptation and also help professionals take effective measures in the field of medical care for patients and their spouses.

Concept d'adaptation chez les conjoints de femmes iraniennes atteintes du cancer du sein: étude qualitative basée sur une approche phénoménologique.

INTRODUCTION: Le cancer du sein provoque une crise multidimensionnelle qui ébranle non seulement la patiente, mais aussi le conjoint et les autres membres de sa famille. Il convient donc d'étudier l'adaptation à ce phénomène, qui constitue l'une des principales difficultés pour les proches. En comprenant mieux comment les conjoints de femmes atteintes d'un cancer du sein font face à cette crise, ces derniers pourraient mieux prendre soin de leurs épouses et améliorer leur qualité de vie. BUT DE L'ÉTUDE: L'étude visait à explorer le concept d'adaptation à partir d'expériences vécues par les conjoints de femmes souffrant d'un cancer du sein. MÉTHODOLOGIE: Cette étude qualitative a été réalisée en 2019 selon une approche phénoménologique dans les villes de Hamadan et Rasht, en Iran. Le groupe de participants comptait 20 conjoints de femmes atteintes du cancer du sein, recrutés grâce à une méthode d'échantillonnage par choix raisonné. Les données ont été recueillies au moyen d'entretiens non structurés en personne; elles ont été analysées à l'aide de la méthode phénoménologique en six étapes de van Manen. RÉSULTATS: Les expériences vécues par les participants ont montré que le phénomène d'adaptation des conjoints au cancer du sein de leur femme se décline en cinq thèmes: souffrance émotionnelle, fardeau des soins, maintien de la cohésion familial, incertitude de l'avenir et sentiment de perte du concept de soi. La compréhension du concept d'adaptation chez les conjoints de femmes atteintes du cancer du sein dans les stratégies de santé peut aider les femmes à bien s'adapter, tout en aidant les professionnels à adopter des mesures efficaces dans le domaine des soins médicaux, pour les patientes et leurs conjoints.

A Qualitative Study Exploring the Experiences of Mothers Caring for Their Children with Thalassemia in Iran.

Background: Mothers of children with thalassemia usually experience many sufferings and challenges in caring of their children. The present study aimed to explore the experiences of mothers caring for their children with thalassemia. Methods: In this qualitative study, 14 mothers caring for their children with thalassemia in Hamedan and Babol Cities, Iran were selected using purposeful sampling, from December 2019 to August 2020. Data were collected through semi-structured face-to-face interviews. Graneheim and Lundman's approach of conventional content analysis was used for data analysis. Results: After data analyzing, four themes, including physical distress, psychological suffering, hellish life, and self-negligence, as well as nine categories, including the mother's physical problems, physical weakness, confusion, painful emotions, restless life, involvement in a painful caring process, turmoil in the family, neglect of one's health, and disregard for the occurrence of psychosomatic illnesses, were extracted. Conclusion: Our findings provide a broad range of context-specific challenges that mothers of thalassemic child faced during caring of their children that can affect different aspects of their life and health. Thus, mothers of children with thalassemia need various types of support such as social, emotional, and informational support during caring process of their children.

The relationship between internet addiction and psychosomatic disorders in Iranian undergraduate nursing students: a cross-sectional study.

Internet addiction has an important impact on individuals, families, and communities. The effects of internet addiction are cumulative, significantly contributing to costly physical, mental, social, and public health problems. Thus, this study sought to examine relationships between internet addiction and psychosomatic disorders in Iranian undergraduate nursing students. This cross-sectional study was conducted on 300 undergraduate nursing students in the city of Hamadan in Iran, in 2018. Data collection tools included socio-demographic, the internet addiction test (IAT), and the psychosomatic complaints questionnaire. Data were analyzed by a Pearson's and independent t-tests using SPSS-18.0. The mean age of the students were 22.3 ± 3.02. The findings showed that 78.7% of nursing students reported mild, 20% moderate and 1.3% severe internet addiction, and there was a significant positive correlation between internet addiction and psychosomatic disorders (P < 0.05, r = 0.132). Internet addiction and psychosomatic disorders in nursing students can jeopardize their mental and physical health, and affect their future academic and professional activities. Therefore, providing educational and counseling interventions and reducing the negative effects of the internet can help to improve student health.

Coping Assessment Tools in the Family Caregivers of Patients with Breast Cancer: A Systematic Review.

BACKGROUND: Breast cancer is a problem that affects not only the individual's health and quality of life, but also the functionality of the family system. Caregivers experience stress when their patients cannot cope with the symptoms of their disease. The stress experienced by caregivers gives rise to psychological and physical symptoms in them. This study seeks to present a complete set of tools for assessing coping in the spouses or caregivers of women with breast cancer and evaluate the various instruments developed within these lines of inquiry. METHODS: A search was carried out in PubMed, Scopus, Web of Science, CINAHL, PsycINFO, Medline, ProQuest, Scopus and Google Scholar and also in the reference lists of the key articles retrieved for any coping assessment instrument targeting family caregivers' needs that had acceptable psychometric properties and was published until September 2019. The instruments used to assess coping in the spouses and caregivers of women with breast cancer were thus identified and their properties were described. RESULTS: Overall, 88 adaptation assessment tools related to family caregivers of patients with breast cancer were identified in 28 related articles. The tools examine different dimensions of adaptation such as satisfaction, stress, burden and needs of spouses and caregivers of patients with breast cancer. CONCLUSION: Assessing family caregivers' coping is essential for providing them with the appropriate sources of support. Although several instruments have been used to assess coping in the spouses and caregivers of women with breast cancer, the properties of these instruments have to be examined before they can be more widely implemented.

The Effect of Counseling on Stigma in Psychiatric Patients Receiving Electroconvulsive Therapy: A Clinical Trial Study.

PURPOSE: Despite its efficacy and safety, electroconvulsive therapy (ECT) is underutilized, in part, due to the stigma associated with the treatment. This study aimed to evaluate the effect of counseling on stigma in patients with psychiatric disorders receiving ECT. PATIENTS AND METHODS: A total of 114 patients with psychiatric disorders undergoing ECT were randomly divided into two groups. Both the groups received routine care and treatment, but the intervention group (n=57) received four counseling sessions. At the beginning and end of the study (6 weeks, post-treatment), patients completed the Internalized Stigma of Mental Illness scale. The data were analyzed using independent and paired sample t-tests. RESULTS: There was no significant difference in the mean stigma scores of participants in the control and intervention groups before counseling (P>0.08). However, post-intervention, there was a significant difference in the mean stigma scores between both the groups (P<0.001). CONCLUSION: The findings demonstrate that the counseling intervention is effective in decreasing stigma in patients undergoing ECT. Therefore, it is recommended to use this therapeutic method in such patients.

Application of data mining techniques and logistic regression to model drug use transition to injection: a case study in drug use treatment centers in Kermanshah Province, Iran.

BACKGROUND: Drug injection has been increasing over the past decades all over the world. Hepatitis B and C viruses (HBV and HCV) are two common infections among people who inject drugs (PWID) and more than 60% of new human immunodeficiency virus (HIV) cases are PWID. Thus, investigating risk factors associated with drug use transition to injection is essential and was the aim of this research. METHODS: We used a database from drug use treatment centers in Kermanshah Province (Iran) in 2013 that included 2098 records of people who use drugs (PWUD). The information of 29 potential risk factors that are commonly used in the literature on drug use was selected. We employed four classification methods (decision tree, neural network, support vector machine, and logistic regression) to determine factors affecting the decision of PWUD to transition to injection. RESULTS: The average specificity of all models was over 84%. Support vector machine produced the highest specificity (0.9). Also, this model showed the highest total accuracy (0.91), sensitivity (0.94), positive likelihood ratio [1] and Kappa (0.94) and the smallest negative likelihood ratio (0). Therefore, important factors according to the support vector machine model were used for further interpretation. CONCLUSIONS: Based on the support vector machine model, the use of heroin, cocaine, and hallucinogens were identified as the three most important factors associated with drug use transition injection. The results further indicated that PWUD with the history of prison or using drug due to curiosity and unemployment are at higher risks. Unemployment and unreliable sources of income were other suggested factors of transition in this research.

The Effect of Empowerment Program on Maternal Discharge Preparation and Neonatal Length of Hospital Stay: A Randomized Controlled Trial.

BACKGROUND: Despite the increased survival of premature infants, many infants are discharged from the hospital while they still require care and follow-up. The present study aimed to determine the effect of empowerment program on maternal discharge preparation and infants' length of hospital stay. MATERIALS AND METHODS: In this pretest-posttest clinical trial, 60 premature infants along with their mothers were selected from the neonatal intensive care unit (NICU) of a teaching hospital in Kermanshah in 2016 via convenience sampling and were allocated to experimental and control groups. Mothers in the control group performed routine care and those in experimental group, in addition to the routine care, performed an intervention program, training sessions including touching and massage, bathing, infection prevention, warning signs, and neonatal resuscitation. Data were collected by a maternal and neonatal demographic questionnaire and a discharge preparation checklist, performed twice (at admission and before discharge), by the researcher. The collected data were analyzed by independent and paired t-test. RESULTS: The mean (standard deviation) of the total score of maternal discharge preparation in intervention group 44.65 (3.90) was significantly higher than that of the control group 33.00 (8.28) (t = -6.58, p <0.001). The mean length of neonatal hospitalization in the intervention group (14.79 days) was significantly shorter than that of the control group (20.43 days) (p = 0.020). CONCLUSIONS: The increasing maternal discharge readiness and reducing the length of neonatal hospital stay would decrease the medical costs and supply more beds for admission of other infants.

High-dimensional additive hazards regression for oral squamous cell carcinoma using microarray data: a comparative study.

Microarray technology results in high-dimensional and low-sample size data sets. Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified. A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present. The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest. The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves. The selected genes by all methods were highly significant (P < 0.001). The Lasso showed maximum median of area under ROC curve over time (0.95) and smoothly clipped absolute deviation showed the lowest prediction error (0.105). It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features. So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.

Prediction the groundwater level of Hamadan-Bahar Plain, west of Iran using support vector machines.

BACKGROUND: Water is considered as the main source of life but water resources are limited and nonrenewable. Different factors have caused groundwater to decrease. Therefore, modeling and predicting groundwater level is of great importance. METHODS: Monthly groundwater level data of about 20 years (October 1991 to February 2012) from the Hamadan-Bahar Plain, west of Iran were used based on peizometric height related to hydrologic years. The support vector machine (SVM), a new nonlinear regression technique, was used to predict groundwater level. The performance of the SVM model was assessed by using criteria of R(2), root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE), correlation coefficient and efficiency coefficient (E) and was then compared with the classic time series model. RESULTS: The SVM model had greater R(2) (=0.933), E (=0.950) and Correlation (=0.965). Moreover, SVM had lower RMSE (=0.120), MAPE (=0.140) and MAE (=0.124). There was no significant difference between the estimated values using two models and the observed value. CONCLUSIONS: The SVM outperforms classic time series model in predicting groundwater level. Therefore using the SVM model is reasonable for modeling and predicting fluctuations of groundwater level in Hamadan-Bahar Plain.

Survival analysis of gastric cancer patients with incomplete data.

PURPOSE: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. MATERIALS AND METHODS: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. RESULTS: The mean patient survival time after diagnosis was 49.1±4.4 months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). CONCLUSIONS: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.

Real-data comparison of data mining methods in prediction of diabetes in iran.

OBJECTIVES: Diabetes is one of the most common non-communicable diseases in developing countries. Early screening and diagnosis play an important role in effective prevention strategies. This study compared two traditional classification methods (logistic regression and Fisher linear discriminant analysis) and four machine-learning classifiers (neural networks, support vector machines, fuzzy c-mean, and random forests) to classify persons with and without diabetes. METHODS: The data set used in this study included 6,500 subjects from the Iranian national non-communicable diseases risk factors surveillance obtained through a cross-sectional survey. The obtained sample was based on cluster sampling of the Iran population which was conducted in 2005-2009 to assess the prevalence of major non-communicable disease risk factors. Ten risk factors that are commonly associated with diabetes were selected to compare the performance of six classifiers in terms of sensitivity, specificity, total accuracy, and area under the receiver operating characteristic (ROC) curve criteria. RESULTS: Support vector machines showed the highest total accuracy (0.986) as well as area under the ROC (0.979). Also, this method showed high specificity (1.000) and sensitivity (0.820). All other methods produced total accuracy of more than 85%, but for all methods, the sensitivity values were very low (less than 0.350). CONCLUSIONS: The results of this study indicate that, in terms of sensitivity, specificity, and overall classification accuracy, the support vector machine model ranks first among all the classifiers tested in the prediction of diabetes. Therefore, this approach is a promising classifier for predicting diabetes, and it should be further investigated for the prediction of other diseases.