The impact of early parenting bonding on young adults' internet addiction, through the mediation effects of negative relating to others and sadness

The aim of the present study is the investigation of the potential role of negative relating to others, perceived loneliness, sadness, and anxiety, as mediators of the association between early parental bonding and adult Internet Addiction (IA). The factorial structure of the Internet Addiction Test (IAT) and the prevalence rates of it in a Greek sample will also be investigated. A total of 774 participants were recruited from a Technological Education Institute (mean age=20.2, SD=2.8) and from high school technical schools (mean age=19.9, SD=7.4). The IAT was used to measure the degree of problematic Internet use behaviors; the Parental Bonding Instrument was used to assess one's recalled parenting experiences during the first 16years of life; the shortened Person's Relating to Others Questionnaire was used to assess one's negative (i.e. maladaptive) relating to others (NRO). Both exploratory and confirmatory factor analyses confirmed the three-factor structure of the IAT. Only 1.0% of the sample was severely addicted to the Internet. The mediated effects of only the NRO and sadness were confirmed. Negative relating to others was found to fully mediate the effect of both the father's optimal parenting and affectionless control on IA, whereas sadness was found to fully mediate the effect of the mother's optimal parenting on IA. Overall, the results suggest that parenting style has an indirect impact on IA, through the mediating role of negative relating to others or sadness in later life. Both family-based and individual-based prevention and intervention efforts may reduce the incidence of IA.

Current methods and limitations for longitudinal fMRI analysis across development

The human brain is remarkably plastic. The brain changes dramatically across development, with ongoing functional development continuing well into the third decade of life and substantial changes occurring again in older age. Dynamic changes in brain function are thought to underlie the innumerable changes in cognition, emotion, and behavior that occur across development. The brain also changes in response to experience, which raises important questions about how the environment influences the developing brain. Longitudinal functional magnetic resonance imaging (fMRI) studies are an essential means of understanding these developmental changes and their cognitive, emotional, and behavioral correlates. This paper provides an overview of common statistical models of longitudinal change applicable to developmental cognitive neuroscience, and a review of the functionality provided by major software packages for longitudinal fMRI analysis. We demonstrate that there are important developmental questions that cannot be answered using available software. We propose alternative approaches for addressing problems that are commonly faced in modeling developmental change with fMRI data.

Disentangling causal webs in the brain using functional magnetic resonance imaging: A review of current approaches

In the past two decades, functional Magnetic Resonance Imaging (fMRI) has been used to relate neuronal network activity to cognitive processing and behavior. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this paper, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, Linear Non-Gaussian Acyclic Models, Patel's Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area.

Organizational and physician factors associated with patient enrollment in cancer clinical trials

BACKGROUND

Our purpose was to identify physicians' individual characteristics, attitudes, and organizational contextual factors associated with higher enrollment of patients in cancer clinical trials among physician participants in the National Cancer Institute's Community Clinical Oncology Program (CCOP). We hypothesized that physicians' individual characteristics, such as age, medical specialty, tenure, CCOP organizational factors (i.e. policies and procedures to encourage enrollment), and attitudes toward participating in CCOP would directly determine enrollment. We also hypothesized that physicians' characteristics and CCOP organizational factors would influence physicians' attitudes toward participating in CCOP, which in turn would predict enrollment.

METHODS

We evaluated enrollment in National Cancer Institute-sponsored cancer clinical trials in 2011 among 481 physician participants using Structural Equation Modeling. The data sources include CCOP Annual Progress Reports, two surveys of CCOP administrators and physician participants, and the American Medical Association Masterfile.

RESULTS

Physicians with more positive attitudes toward participating in CCOP enrolled more patients than physicians with less positive attitudes. In addition, physicians who practiced in CCOPs that had more supportive policies and practices in place to encourage enrollment (i.e. offered trainings, provided support to screen and enroll patients, gave incentives to enroll patients, instituted minimum accrual expectations) also significantly enrolled more patients. Physician status as CCOP Principal Investigator had a positive direct effect on enrollment, while physician age and non-oncology medical specialty had negative direct effects on enrollment. Neither physicians' characteristics nor CCOP organizational factors indirectly influenced enrollment through an effect on physician attitudes.

CONCLUSION

We examined whether individual physicians' characteristics and attitudes, as well as CCOP organizational factors, influenced patient enrollment in cancer clinical trials among CCOP physicians. Physician attitudes and CCOP organizational factors had positive direct effects, but not indirect effects, on physician enrollment of patients. Our results could be used to develop physician-directed strategies aimed at increasing involvement in clinical research. For example, administrators may want to ensure physicians have access to support staff to help screen and enroll patients or institute minimum accrual expectations. Our results also highlight the importance of recruiting physicians for volunteer clinical research programs whose attitudes and values align with programmatic goals. Given that physician involvement is a key determinant of patient enrollment in clinical trials, these interventions could expand the overall number of patients involved in cancer research. These strategies will be increasingly important as the CCOP network continues to evolve.

Attitudes Toward Addiction, Methadone Treatment, and Recovery Among HIV-Infected Ukrainian Prisoners Who Inject Drugs: Incarceration Effects and Exploration of Mediators

In this study, we use data from a survey conducted in Ukraine among 196 HIV-infected people who inject drugs, to explore attitudes toward drug addiction and methadone maintenance therapy (MMT), and intentions to change drug use during incarceration and after release from prison. Two groups were recruited: Group 1 (n = 99) was currently incarcerated and Group 2 (n = 97) had been recently released from prison. This paper's key finding is that MMT treatment and addiction recovery were predominantly viewed as mutually exclusive processes. Group comparisons showed that participants in Group 1 (pre-release) exhibited higher optimism about changing their drug use, were less likely to endorse methadone, and reported higher intention to recover from their addiction. Group 2 participants (post-release), however, reported higher rates of HIV stigma. Structural equation modeling revealed that in both groups, optimism about recovery and awareness of addiction mediated the effect of drug addiction severity on intentions to recover from their addiction.

The Benefits of Indirect Exposure to Trauma: The Relationships among Vicarious Posttraumatic Growth, Social Support, and Resilience in Ambulance Personnel in China

OBJECTIVE

Ambulance personnel who witness trauma experienced by patients have been reported to experience positive changes, known as vicarious posttraumatic growth (VPTG). We examined VPTG and its relationship with social support and resilience among ambulance personnel.

METHODS

The sample (n=227) was recruited from six emergency centers in China. The measures included the Posttraumatic Growth Inventory (PTGI), the Social Support Rating Scale (SSRS), and the 10-item Connor-Davidson Resilience Scale (CD-RISC-10). Structure Equation Modeling (SEM) and the bootstrapping procedure were used to examine indirect effects.

RESULTS

The participants' mean score for VPTG was 68.96 (SD=15.51). Social support had significant direct effects on resilience (β=0.51, p<0.001) and VPTG (β=0.25, p=0.001), and resilience (β=0.58, p<0.001) had a significant direct effect on VPTG. Furthermore, social support had a significant indirect effect (0.51×0.58=0.30, p<0.001) on VPTG through resilience.

CONCLUSION

Although the nature of the work of ambulance personnel is not expected to change, the negative effects of the trauma they encounter can be reduced by providing them with more support resources and interventions to foster their resilience, which in turn, promote VPTG.

Acquiring Science and Social Studies Knowledge in Kindergarten Through Fourth Grade: Conceptualization, Design, Implementation, and Efficacy Testing of Content-Area Literacy Instruction (CALI)

With national focus on reading and math achievement, science and social studies have received less instructional time. Yet, accumulating evidence suggests that content knowledge is an important predictor of proficient reading. Starting with a design study, we developed Content Area Literacy Instruction (CALI), as an individualized (or personalized) instructional program for kindergarteners through fourth graders to build science and social studies knowledge. We developed CALI to be implemented in general education classrooms, over multiple iterations (n=230 students), using principles of design-based implementation research. The aims were to develop CALI as a usable and feasible instructional program that would, potentially, improve science and social studies knowledge, and could be implemented during the literacy block without negatively affecting students' reading gains (i.e., no opportunity cost). We then evaluated the efficacy of CALI in a randomized controlled field trial with 418 students in kindergarten through fourth grade. Results reveal that CALI demonstrates promise as a useable and feasible instructional individualized general education program, and is efficacious in improving social studies (d=2.2) and science (d=2.1) knowledge, with some evidence of improving oral and reading comprehension skills (d=.125).

The Effect of Engagement in Everyday Occupations, Role Overload and Social Support on Health and Life Satisfaction among Mothers

One of the founding assumptions underlying the health professions is the belief that there is a strong relationship between engagement in occupations, health, and wellbeing. The ability to perform everyday occupations (occupational performance) has a positive effect on health and wellbeing. However, there is also conflicting evidence indicating that participation in multiple roles or in certain occupations may lead to poorer health. Therefore, there is a need to better understand this relationship. The purpose of the present study was to examine three possible theoretical models to explain mothers' health and life satisfaction from the perspective of their occupational performance, their role load, and their social support. 150 married mothers, ages of 25-45, who had at least one child between the ages of one to ten years, participated in the study. Data were collected by using seven self-report questionnaires. The models were analyzed using Structural Equation Modeling. The results show that social support has a direct effect on mothers' physical health and life satisfaction and an indirect effect, mediated through the occupational performance variables, on mothers' mental health and life satisfaction. Role overload does not affect mothers' health and life satisfaction. These results suggest that mothers could benefit from health programs that help them manage their occupational routines. Such programs should focus on improving the mother's occupational performance and adapting her social environment to fit her occupational needs.

Traffic accident severity analysis with rain-related factors using structural equation modeling - A case study of Seoul City

Weather conditions are strongly correlated with traffic accident severity. In particular, rain-related factors are an important cause of traffic accidents due to the poor visibility and reduced friction resulting from slippery road conditions. This paper presents a systematic approach to analyze the extent to which the rainfall intensity and level of water depth are responsible for traffic accidents using Seoul City, Korea, as a case study. The rainfall and traffic accident data over a nine-year period (from 2007 to 2015) for Seoul were analyzed through Structural Equation Modeling to identify the relationships among variables by handling endogenous and exogenous variables simultaneously. In the model, four latent variables, namely those representing the road; traffic, environmental, and human factors; and rain and water depth factors, were defined and the coefficients of the latent, endogenous, and exogenous variables were estimated to obtain the level of accident severity. Furthermore, a statistical goodness of fit index was suggested for model fitting. In conclusion, traffic, environmental, and human factors; rain and water depth factors; and road factors are mutually correlated with the level of accident severity. Compact cars, young drivers, female drivers, heavy rain, deep water, and roads with a long drainage length are more likely to be associated with an increase in the level of accident severity, as are features like a tangent, down slope, right-hand curve, and shorter curve length.

Nonlinear Structured Growth Mixture Models in Mplus and OpenMx

Growth mixture models (GMMs; Muthén & Muthén, 2000; Muthén & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models because of their common use, flexibility in modeling many types of change patterns, the availability of statistical programs to fit such models, and the ease of programming. In this paper, we present additional ways of modeling nonlinear change patterns with GMMs. Specifically, we show how LCMs that follow specific nonlinear functions can be extended to examine the presence of multiple latent classes using the Mplus and OpenMx computer programs. These models are fit to longitudinal reading data from the Early Childhood Longitudinal Study-Kindergarten Cohort to illustrate their use.

The pain, depression, disability pathway in those with low back pain: a moderation analysis of health locus of control

Low back pain (LBP) is common, impacts on the individual and society, and is a major health concern. Psychological consequences of LBP, such as depression, are significant barriers to recovery, but mechanisms for the development of depression are less well understood. One potential mechanism is the individual’s health locus of control (HLoC), that is, perception of the level of control an individual has over their health. The objective of this study is to investigate the moderation effect of HLoC on the pain–depression–disability pathway in those with LBP. The design is a nested cross-sectional analysis of two existing cohorts of patients (n=637) who had previously consulted their primary care physician about LBP. Measures were taken of HLoC, pain intensity and interference, depression, disability, and bothersomeness. Structural Equation Modeling analysis was applied to two path models that examined the pain to depression to disability pathway moderated by the HLoC constructs of Internality and Externality, respectively. Critical ratio (CR) difference tests were applied to the coefficients using pairwise comparisons. The results show that both models had an acceptable model fit and pathways were significant. CR tests indicated a significant moderation effect, with stronger pathway coefficients for depression for those who report low Internality (β 0.48), compared to those with high Internality (β 0.28). No moderation effects were found within the Externality model. HLoC Internality significantly moderates the pain–depression pathway in those with LBP, meaning that those who have a low perception of control report greater levels of depression. HLoC may signify depression among people with LBP, and could potentially be a target for intervention.

Dysfunctional role of parietal lobe during self-face recognition in schizophrenia

BACKGROUND

Anomalous sense of self is central to schizophrenia yet difficult to demonstrate empirically. The present study examined the effective neural network connectivity underlying self-face recognition in patients with schizophrenia (SZ) using [15O]H2O Positron Emission Tomography (PET) and Structural Equation Modeling.

METHODS

Eight SZ and eight age-matched healthy controls (CO) underwent six consecutive [15O]H2O PET scans during self-face (SF) and famous face (FF) recognition blocks, each of which was repeated three times.

RESULTS

There were no behavioral performance differences between the SF and FF blocks in SZ. Moreover, voxel-based analyses of data from SZ revealed no significant differences in the regional cerebral blood flow (rCBF) levels between the SF and FF recognition conditions. Further effective connectivity analyses for SZ also showed a similar pattern of effective connectivity network across the SF and FF recognition. On the other hand, comparison of SF recognition effective connectivity network between SZ and CO demonstrated significantly attenuated effective connectivity strength not only between the right supramarginal gyrus and left inferior temporal gyrus, but also between the cuneus and right medial prefrontal cortex in SZ.

CONCLUSION

These findings support a conceptual model that posits a causal relationship between disrupted self-other discrimination and attenuated effective connectivity among the right supramarginal gyrus, cuneus, and prefronto-temporal brain areas involved in the SF recognition network of SZ.

A Structural Equation Modeling approach to water quality perceptions

Researches on water quality perceptions have used various techniques and models to explain relationships between specific variables. Surprisingly, Structural Equation Modeling (SEM) has received little attention in water quality perceptions studies, and reporting has been inconsistent among existing studies. One objective of this article is to provide readers with a methodological example for conducting and reporting SEM. Another objective is to build a model that explains the different relationships among the diverse factors highlighted by previous studies on water quality perceptions. Our study focuses on the factors influencing people's perceptions of water quality in the Appalachian region. As such, researchers have conducted a survey in a mid-sized city in northcentral West Virginia to assess residents' perceptions of water quality for drinking and recreational purposes. Specifically, we aimed to understand the relationships between perceived water quality, health risk perceptions, organoleptic perceptions, environmental concern, area satisfaction and perceptions of surface water quality. Our model provided a good fit that explained about 50% of the variance in health risk perceptions and 43% of the variance in organoleptic perceptions. Environmental concern, area satisfaction and perceived surface water quality are important factors in explaining these variances. Perceived water quality was dismissed in our analysis due to multicollinearity. Our study demonstrates that risk communication needs to be better addressed by local decision-makers and water managers.

Do therapist effects really impact estimates of within-patient mechanisms of change? A Monte Carlo simulation study

Objective: Existing evidence highlights the importance of modeling differential therapist effectiveness when studying psychotherapy outcome. However, no study to date examined whether this assertion applies to the study of within-patient effects in mechanisms of change. The study investigated whether therapist effects should be modeled when studying mechanisms of change on a within-patient level. Methods: We conducted a Monte Carlo simulation study, varying patient- and therapist level sample sizes, degree of therapist-level nesting (intra-class correlation), balanced vs. unbalanced assignment of patients to therapists, and fixed vs random within-patient coefficients. We estimated all models using longitudinal multilevel and structural equation models that ignored (2-level model) or modeled therapist effects (3-level model). Results: Across all conditions, 2-level models performed equally or were superior to 3-level models. Within-patient coefficients were unbiased in both 2- and 3-level models. In 3-level models, standard errors were biased when number of therapists was small, and this bias increased in unbalanced designs. Ignoring random slopes led to biased standard errors when slope variance was large; but 2-level models still outperformed 3-level models. Conclusions: In contrast to treatment outcome research, when studying mechanisms of change on a within-patient level, modeling therapist effects may even reduce model performance and increase bias.

Structural equation modeling for decomposing rank-dependent indicators of socioeconomic inequality of health: an empirical study

We present a flexible structural equation modeling (SEM) framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with simple ordinary least squares (OLS) regression. The SEM framework forms the basis for a proper use of the most prominent one- and two-dimensional decompositions and provides an argument for using the bivariate multiple regression model for two-dimensional decomposition. Within the SEM framework, the two-dimensional decomposition integrates the feedback mechanism between health and socioeconomic status and allows for different sets of determinants of these variables. We illustrate the SEM approach and its outperformance of OLS using data from the 2011 Ethiopian Demographic and Health Survey.

How did COVID-19 impact driving behaviors and crash Severity? A multigroup structural equation modeling

Risky driving behaviors such as speeding and failing to signal have been witnessed more frequently during the COVID-19 pandemic, resulting in higher rates of severe crashes. This study aims to investigate how the COVID-19 pandemic impacts the likelihood of severe crashes via changing driving behaviors. Multigroup structural equation modeling (SEM) is used to capture the complex interrelationships between crash injury severity, the context of COVID-19, driving behaviors, and other risk factors for two different groups, i.e., highways and non-highways. The SEM constructs two latent variables, namely aggressiveness and inattentiveness, which are indicated by risk driving behaviors such as speeding, drunk driving, and distraction. One great advantage of SEM is that the measurement of latent variables and interrelationship modeling can be achieved simultaneously in one statistical estimation procedure. Group differences between highways and non-highways are tested using different equality constraints and multigroup SEM with equal regressions can deliver the augmented performance. The smaller severity threshold for the highway group indicates that it is more likely that a crash could involve severe injuries on highways as compared to those on non-highways. Results suggest that aggressiveness and inattentiveness of drivers increased significantly after the outbreak of COVID-19, leading to a higher likelihood of severe crashes. Failing to account for the indirect effect of COVID-19 via changing driving behaviors, the conventional probit model suggests an insignificant impact of COVID-19 on crash severity. Findings of this study provide insights into the effect of changing driving behaviors on safety during disruptive events like COVID-19.

Relief of depression and pain improves daily functioning and quality of life in patients with major depressive disorder

OBJECTIVE

The objective of this study was to investigate the effects of depression relief and pain relief on the improvement in daily functioning and quality of life (QOL) for depressed patients receiving a 6-week treatment of fluoxetine.

METHOD

A total of 131 acutely ill inpatients with major depressive disorder (MDD) were enrolled to receive 20mg of fluoxetine daily for 6 weeks. Depression severity, pain severity, daily functioning, and health-related QOL were assessed at baseline and again at week 6. Depression severity, pain severity, and daily functioning were assessed using the 17-item Hamilton Depression Rating Scale, the Short-Form 36 (SF-36) Body Pain Index, and the Work and Social Adjustment Scale. Health-related QOL was assessed by three primary domains of the SF-36, including social functioning, vitality, and general health perceptions. Pearson's correlation and structural equation modeling were used to examine relationships among the study variables. Five models were proposed. In model 1, depression relief alone improved daily functioning and QOL. In model 2, pain relief alone improved daily functioning and QOL. In model 3, depression relief, mediated by pain relief, improved daily functioning and QOL. In model 4, pain relief, mediated by depression relief, improved daily functioning and QOL. In model 5, both depression relief and pain relief improved daily functioning and QOL.

RESULTS

One hundred and six patients completed all the measures at baseline and at week 6. Model 5 was the most fitted structural equation model (χ(2) = 8.62, df = 8, p = 0.376, GFI = 0.975, AGFI = 0.935, TLI = 0.992, CFI = 0.996, RMSEA = 0.027).

CONCLUSION

Interventions which relieve depression and pain improve daily functioning and QOL among patients with MDD. The proposed model can provide quantitative estimates of improvement in treating patients with MDD.

Parental bonding and adolescents' depressive and anxious symptoms in Pakistan

INTRODUCTION

A quantitative cross sectional study was carried out to investigate the role of parental bonding in relation to depressive and anxious symptoms among secondary school adolescents in Pakistan. The study also aimed to investigate the construct validity of the parental bonding inventory in the cultural context of Pakistan.

METHODS

The sample consisted of 1124 adolescents recruited from eight secondary schools in Rawalpindi, Pakistan. Urdu translated versions of Parental Bonding Instrument (Qadir et al., 2005) and Hospital Anxiety and Depression Scales (Mumford et al., 1991) were administered in classroom settings. Confirmatory factor analysis (CFA) and Structural Equation Modeling (SEM) were used to analyze the data.

RESULTS

Results from the CFA of the Urdu version of the Parental Bonding Instrument supported a modified version of the three factor model proposed by Kendler (1996) consisting of warmth, protectiveness and authoritarianism. Based on SEM, we found a significant relationship between low parental warmth and depression symptoms among adolescents, whereas maternal protectiveness was a significant predictor for anxiety. Parental authoritarianism was not a significant predictor for depression or anxiety.

DISCUSSION

Findings of this study indicate that parental bonding is a central construct within a developmental framework in the cultural context of Pakistan, and is important when considering long-term psychosocial functioning of individuals. It should be explored further in clinical populations of Pakistani adolescents to ascertain significance of these constructs for interventions.

Test of a clinical model of poor physical health and suicide: The role of depression, psychosocial stress, interpersonal conflict, and panic

BACKGROUND

This study employed a structural equation model to examine the relationships between poor physical health, suicide, depression, psychosocial stress, interpersonal conflict, and panic.

METHODS

The sample consisted of a large, archived set of mental health treatment-seeking adults who completed a behavioral outcome questionnaire prior to beginning treatment.

RESULTS

Results supported the extant literature indicating that poor physical health, depression, psychosocial stress, interpersonal conflict, and panic impose increased risk for suicidal ideation, with depression demonstrating the highest risk for increased suicidal ideation. The results also supported the hypotheses that depression, psychosocial stress, interpersonal conflict, and panic would mediate the association between poor physical health and suicidal ideation. Although no a priori hypotheses were made regarding relationships among the 15 physical illnesses examined, results indicated that HIV/AIDS had the strongest correlation with depression and the weakest correlation with interpersonal conflict.

LIMITATIONS

Firstly, the study sample was primarily Caucasian, limiting its generalizability. Secondly, causal inferences should be interpreted with caution, due to the quasi-experimental design. Thirdly, these data were self-reported, which create response biases since suicidal ideation is stigmatized.

CONCLUSIONS

These findings highlight the importance of considering interpersonal factors as potential mediators in the relationship between poor physical health, mental illness, and suicide. Clinically, the impact of an active major depressive episode on an individual who is struggling with a serious physical illness may be strongly predictive of suicidal ideation.

Network inference of pal-1 lineage-specific regulation in the C. elegans embryo by structural equation modeling

The elucidation of spatial and temporal control during developmental stages is one of the central tasks for systems biology, and a variety of intracellular factors are known as regulators for specific gene expression. The activity information of those various factors is not directly reflected in their gene expression profiles. Hence, a method based on Structural Equation Modeling (SEM) is described. SEM can include the latent variables within the constructed model and infer the relationships among latent and observed variables, as a network model. An improved SEM approach for the construction of an optimal model is applied to infer the regulatory network for the determination of C lineage fate in C. elegans development. The inferred network model shows that the 13 analysed transcription factor genes were regulated by several other factors in addition to pal-1 expression. The other regulatory factors are those involved in protein accumulation and localization as important regulatory factors for normal development. Those regulatory factors were regulated sequentially in the network model. The regulation of the known pal-1 regulated genes was dependent on this sequential control of the regulatory factors. The interpretation of the network model shows insights to the complex regulation occurring during the C lineage determination by pal-1.

FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of "Generation X" in Hungary to use mobile payment

Organizations, such as the World Health Organization, encouraged consumers to use contactless payment methods instead of payment methods such as cash, which can be carriers of the SARS-2 virus. This study aims to evaluate factors that influence Hungarian Generation X's behavioral intentions to use mobile payment services during the pandemic. We conducted an electronic questionnaire-based survey among 1120 Generation X individuals. Using structural equation modeling to analyze the study's conceptual model, our results confirm that perceived COVID-19 risk, perceived usefulness, and subjective norms significantly influence Hungarian Generation X's behavioral intentions to use mobile payment services. Moreover, perceived usefulness mediates the relationship between perceived ease of use and behavioral intention to use mobile payment systems. Overall, our results show that the model of perceived COVID-19 risk, perceived usefulness, subjective norms, and perceived ease of use explains 62.9% of the variance in intention to use mobile payment systems. Our study contributes to the technology acceptance model and highlights its effectiveness in explaining the behavioral intention to adopt mobile payments during the COVID-19 pandemic.

Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries

Background

Individual and organizational factors are the factors influencing traumatic occupational injuries.

Objectives

The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors.

Materials and Methods

The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively.

Results

The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries’ severity (P < 0.05).

Conclusions

Path analysis of occupational injuries based on the SEM reveals that individual and organizational factors and their indicator variables are very influential on the severity of traumatic occupational injuries. So, these should be considered to reduce occupational accidents’ severity in large construction industries.

Psychiatric Symptom Clusters as Risk Factors for Alcohol Use Disorders in Adolescence: A National Study

BACKGROUND

Few epidemiologic studies have examined a full range of adolescent psychiatric disorders in the general population. The association between psychiatric symptom clusters (PSCs) and DSM-IV alcohol use disorders (AUDs) among adolescents is not well understood.

METHODS

This study draws upon the public-use data from the 2000 National Household Survey on Drug Abuse, including a study sample of 19,430 respondents aged 12 to 17. Logistic regression and exploratory structural equation modeling assess the associations between PSCs and DSM-IV AUDs by gender. The PSCs are based on brief screening scales devised from the Diagnostic Interview Schedule for Children Predictive Scales.

RESULTS

Several PSCs were found to be significantly associated with DSM-IV AUDs, including separation anxiety, generalized anxiety, depression, oppositional defiant disorder, and conduct disorder among both genders, and panic disorder and obsessive/ compulsive disorder among females. Consistent with the literature, the analysis of PSCs yields 3 factors identical for both genders-2 internalizing factors (fear and anxiety-misery) and 1 externalizing factor. Adolescents who scored higher on the externalizing factor tended to have higher levels of the AUD factor. Female adolescents who scored higher on the internalizing misery factor and lower on the internalizing fear factor also tended to have higher levels of the AUD factor.

CONCLUSIONS

The associations that we found between PSCs and AUDs among adolescents in this study are consistent with those found among adults in other studies, although gender may moderate associations between internalizing PSCs and AUDs. Our findings lend support to previous findings on the developmentally stable associations between disruptive behaviors and AUDs among adolescents as well as adults in the general population.

Mobile apps for SME business sustainability during COVID-19 and onwards

Small and Medium-Sized Enterprises (SMEs) are struggling to cope with the business uncertainty caused by the COVID-19 pandemic. This study examines how SMEs in developing economies have used mobile apps to improve their business efficiency during the pandemic. We aim to recognize effective measures and actions taken by SMEs that have turned to mobile-app-based business to improve their sustainability during the crisis. The study bridges a literature gap by extending the Theory of Consumption Values and the Theory of Planned Behavior to SMEs that incorporate mobile-app-based business. Data was collected from 343 SMEs from three Industrial Development Corporations (IDCs) in India. Using the covariance-based structural equation modeling method, we investigated the efficiency of a conceptual model of mobile-app-based business for SMEs. The results revealed that consumer choice behavior, perceived behavior control, subjective behavior control and attitude towards the mobile app all influence SMEs' decision-making and business strategy. As such, SMEs need a powerful mobile-app-based business network to succeed in the entrepreneurial business process. Using instrumental variable analysis, we discovered that increased mobile app usage significantly improves SMEs' long-term efficiency. The analysis provides several theoretical and managerial ramifications.