Psychometric Properties of Mobile Phone Abuse (MPA): Exploratory and Confirmatory Factor Analysis in Student Mobile Users.

Objective: Smartphone is an important technology device in our lifestyle. It has an important part of our daily lives, but it also has a negative effect, such as cell phone dependency. This research aimed to evaluate the psychometric properties of mobile phone abuse (MPA) in the Iranian population. Method: In this study, data were chosen from 1100 participants who were studying in Tehran universities. The principal version of the scale was translated into Persian using the back translation method. All attendees completed Demographic Questionnaire, MPA Questionnaire, and Mobile Phone Problematic Use Scale (MPPUS). Eventually, a clinical interview (based on the fifth version of DSM) was done for all the participants. For data analysis, internal and external consistency, factor analysis, construct validity and confirmatory factor analysis (CFA) were used. Statistically, less than 0.05 were considered to be significant. Results: According to expert judgments, content validity index was satisfactory. Furthermore, the reliability of the questionnaire was confirmed with Cronbach's α of 0.90 and test-retest reliability of 0.56 after 3 weeks. The best cutoff point for this questionnaire (MPA) was 46. Also, 4 factors were extracted by principal components method and varimax rotation: "excessive use of cell phone," "addictive use of social networks," "mood modification," and "preoccupation" for both male and female students. Conclusion: MPA could be used in studies on the evaluation of mobile phone addiction. This can be a stepping stone towards the identification of problems and improvement of students' mobile phone abuse.

The effects of cognitive-behavioral group therapy for reducing symptoms of internet addiction disorder and promoting quality of life and mental health.

INTRODUCTION: Internet addiction disorder has reportedly become an important cause of health and social problems. The aim of this study was to investigate the effectiveness of cognitive-behavioral group therapy for internet addiction symptoms, quality of life, and mental health of students with internet addiction. METHODS: This was a quasi-experimental study with pretest-posttest measures and a control group. The statistical population of the study consisted of all students at Tehran universities in the academic year of 2018-19. The target group was selected through an internet addiction test and a clinical interview using a targeted sampling method and was divided into experimental and control groups by randomization. The experimental group participated in fifteen 90-minute cognitive-behavioral group therapy sessions. Before, immediately after, and 3 months after the treatment, the internet addiction symptoms of both groups were evaluated to assess mental health with the IAT, quality of life (QOL), and SCL-90-R questionnaires. Data were analyzed with ANCOVA analysis using SPSS Statistics 20 software. RESULTS: After treatment, cognitive-behavioral therapy groups showed reductions in internet addiction scores (p < 0.05). Results showed that the cognitive-behavioral group therapy was effective for improving quality of life (p < 0.05) and mental illnesses (p < 0.05) in students with internet addiction. CONCLUSIONS: Cognitive-behavioral group therapy can enhance awareness and mental health of students with internet addiction. Therefore, this intervention can be used as a beneficial treatment to reduce internet addiction symptoms and improve the condition of people with behavioral addictions such as internet dependency.

The effects of cognitive-behavioral group therapy for reducing symptoms of internet addiction disorder and promoting quality of life and mental health

Abstract Introduction Internet addiction disorder has reportedly become an important cause of health and social problems. The aim of this study was to investigate the effectiveness of cognitive-behavioral group therapy for internet addiction symptoms, quality of life, and mental health of students with internet addiction. Methods This was a quasi-experimental study with pretest-posttest measures and a control group. The statistical population of the study consisted of all students at Tehran universities in the academic year of 2018-19. The target group was selected through an internet addiction test and a clinical interview using a targeted sampling method and was divided into experimental and control groups by randomization. The experimental group participated in fifteen 90-minute cognitive-behavioral group therapy sessions. Before, immediately after, and 3 months after the treatment, the internet addiction symptoms of both groups were evaluated to assess mental health with the IAT, quality of life (QOL), and SCL-90-R questionnaires. Data were analyzed with ANCOVA analysis using SPSS Statistics 20 software. Results After treatment, cognitive-behavioral therapy groups showed reductions in internet addiction scores (p < 0.05). Results showed that the cognitive-behavioral group therapy was effective for improving quality of life (p < 0.05) and mental illnesses (p < 0.05) in students with internet addiction. Conclusions Cognitive-behavioral group therapy can enhance awareness and mental health of students with internet addiction. Therefore, this intervention can be used as a beneficial treatment to reduce internet addiction symptoms and improve the condition of people with behavioral addictions such as internet dependency.

Addictive Use of Smartphones and Mental Disorders in University Students.

Objective: Despite the awareness of smartphone addiction, low findings and lack of validated standards have led to insufficient information in this area. This study aimed to examine the relationship between mobile phone dependency and mental disorders in students in Iran, while controlling for the impact of gender, age, educational levels, and marital status. Method : In this cross-sectional study, a sample of 1400 university students (445 males and 955 females) aged 18-35 years were selected from 3 cities of Tehran, Isfahan and Karaj. The participants filled out a set of questionnaires: Cell Phone Dependency Questionnaire (CPDQ), Millon Multiaxial Clinical Inventory, and participated in interviews. Data were analyzed using multiple logistic regression method via SPSS-22 software. Results: In terms of controlling the demographic variables, the results revealed that bipolar disorder, depression, anxiety, somatization, dependent personality disorder, and compulsive personality disorder could increase the possibility of mobile phone addiction by 4.2, 4.2, 1.2, 2.8, 3.1, and 3.2 folds, respectively (P < 0.05). However, other disorders and demographic characteristics did not have any significant effects on the equation. Conclusion: The results can help better understand the relationship between psychological syndromes and smartphone addiction and can also facilitate further studies in this field. In addition, those students with smartphone addiction should be provided with different preventative strategies. Moreover, a growing range of stimulating applications may trigger the risk of addiction.

Psychological Factors Including Demographic Features, Mental Illnesses, and Personality Disorders as Predictors in Internet Addiction Disorder.

Objective: Problematic internet use is an important social problem among adolescents and has become a global health issue. This study identified predictors and patterns of problematic internet use among adult students. Method: In this study, 401 students were recruited using stratified sampling technique. Participants were selected among students from 4 universities in Tehran and Karaj, Iran, during 2016 and 2017. Internet Addiction Test (IAT), Millon Clinical Multiaxial Inventory - Third Edition (MCMI-III), Structured Clinical Interview for DSM (SCID-I), and semi-structured interview were used to diagnose internet addiction. Then, the association between main psychiatric disorders and internet addiction was surveyed. Data were analyzed using SPSS18 software by performing descriptive statistics and multiple logistic regression analysis methods. P- Values less than 0.05 were considered statistically significant. Results: After controlling the demographic variables, it was found that narcissistic personality disorder, obsessive- compulsive personality disorder, anxiety, bipolar disorders, depression, and phobia could increase the odds ratio (OR) of internet addiction by 2.1, 1.1, 2.6, 1.1, 2.2 and 2.5-folds, respectively (p-value<0.05), however, other psychiatric or personality disorders did not have a significant effect on the equation. Conclusion: The findings of this study revealed that some mental disorders affect internet addiction. Considering the sensitivity and importance of the cyberspace, it is necessary to evaluate mental disorders that correlate with internet addiction.

Mixed hemi-micelle solid-phase extraction based on modified magnetic nanoparticles for extraction of cadmium and lead from food and water samples.

A simple and rapid method for the separation and preconcentration of trace amounts of Cd(ll) and Pb(ll) in milk powder and water samples by magnetic SPE has been developed. The application of silica- coated magnetite nanoparticles (SCMNPs), modified with an anionic surfactant as an effective sorbent material for the microextractioh and determination of trace amounts of Cd(ll)and Pb(ll) from food samples was investigated. The synthesized SCMNPs modified with sodium dodecyl sulfate have the ability to adsolubilize the metal ions after complexation with 1-(2-pyridylazo)-2-naphthol. These magnetic nanoparticles which are carrying the target metals can be easily separated from the aqueous solution by applying an external magnetic field, and the complexed metals can be desorbed using a proper eluent. The effect of pH, concentration of complexing agent, eluent, extraction time, capacity, and desorp tion conditions were investigated. Under the optimized conditions, preconcentration of a 50.0 mL sample solution permitted the LODs of 0.147 and 2.02 µg/L; and the RSDs (n = 7) for 0.05 µg/mL of Cd(ll) and 0.2 µg/mL of Pb(ll) were 2.96 and 1.3%, respectively. The maximum sorption capacity was 8.8 and 9.5 mglg for Cd(ll) and Pb(ll), respectively.

Ferrofluid based dispersive-solid phase extraction for spectrophotometric determination of dyes.

For the first time, ferrofluid based dispersive-solid phase extraction (D-SPE) has been applied for determination of trace levels of dyes in aqueous and fish samples. The contaminant used as a model compound was crystal violet (CV), a cationic dye, and was preconcentrated without any derivatization or ion-pair formation. The method is based on rapid injection of ferrofluid into the aqueous sample by a syringe. The sample preparation time is decreased by the fact that the sorbent dispersed in the bulk solution and extraction can be achieved very fast. In this way, the separation of sorbent from the aqueous bulk was achieved by a magnet, and no centrifugation is required. These significant features which obtained with this method are of key interest for routine trace laboratory analysis. The influence of different variables on D-SPE was investigated. Under optimum conditions, the calibration graph was linear over the range of 3.3-90 µg L(-1), and the enrichment factor (EF) 267 was obtained. Detection limit was 1.51 µg L(-1) (n=7), and the relative standard deviation of 5.6% at 50 ng mL(-1) was obtained (n=7). The proposed method was successfully applied for the determination of crystal violet in various samples.

Ferrofluid-based dispersive solid phase extraction of palladium.

A new mode of dispersive solid phase extraction based on ferrofluid has been developed. In this method, an appropriate amount of ferrofluid is injected rapidly into the aqueous sample by a syringe. Since the sorbent is highly dispersed in the aqueous phase, extraction can be achieved within a few seconds. The ferrofluid can be attracted by a magnet and no centrifugation step is needed for phase separation. Palladium was used as a model compound in the development and evaluation of the extraction procedure in combination with flame atomic absorption spectrometry. The experimental parameters (pH, DDTC concentration, type and concentration of eluent, the amount of adsorbent, extraction time, and the effect of interfering ions) were investigated in detail. Under the optimized conditions, the calibration graph was linear over the range of 1-100 µg L(-1) and relative standard deviation of 3.3% at 0.1 µg mL(-1) was obtained (n=7). The limit of detection and enrichment factor (EF) was obtained to be 0.35 µg L(-1) and 267, respectively. The maximum adsorption capacity of the adsorbent at optimum conditions was found to be 24.6 mg g(-1) for Pd(II). The method was validated using certified reference material, and has been applied for the determination of trace Pd(II) in actual samples with satisfactory results.

Cold-induced aggregation microextraction based on ionic liquids and fiber optic-linear array detection spectrophotometry of cobalt in water samples.

A new simple and rapid cold-induced aggregation microextraction (CIAME) method was applied to preconcentrate cobalt(II) ions from water samples as a prior step to its determination by fiber optic-linear array detection spectrophotometry (FO-LADS). In this method, very small amounts of 1-hexyl-3-methylimidazolium hexafluorophosphate [Hmim][PF(6)] and 1-hexyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide [Hmim][Tf(2)N] as hydrophobic ionic liquids (ILs) and extractant solvents were dissolved in the sample solution containing Triton X-114 (anti-sticking agent). 1-(2-Pyridylazo)-2-naphthol (PAN) was chosen as the complexing agent. After dissolving, the solution was cooled in the ice bath and a cloudy solution was formed of IL fine droplets due to the decrease of IL solubility. After centrifuging, the fine droplets of extractant phase were settled to the bottom of the conical-bottom centrifuge tube. Analysis was carried out by a fiber optic-linear array detector spectrophotometer at 570 nm. In this method, which is robust against high content of salt and water-miscible organic solvents, various parameters were investigated and optimized. The applicability of the technique was evaluated by the determination of trace amounts of cobalt in several water samples. Under the optimum conditions, the limit of detection (LOD) of the method was 0.14 ng mL(-1) and the relative standard deviation (R.S.D.) for 30 ng mL(-1) cobalt was 2.32%.