Impulsivity Factors Research Articles

The role of impulsivity and emotional dysregulation in smartphone overdependence explored through network analysis

Smartphone overdependence is a maladaptive behavior characterized by excessive and uncontrollable smartphone use despite negative consequences. Impulsivity and emotional dysregulation, which are multidimensional constructs with each factor exerting a different effect, have been found to influence the development and persistence of smartphone overdependence. This study utilized network analysis to investigate the intricate relationships between the factors of impulsivity, emotional dysregulation, and smartphone overdependence. A sample of 687 adults in their twenties completed an online survey. Central nodes of the network were “Impulse-control difficulties,” “Positive Urgency,” “Salience” and “Relapse,” and bridge nodes included a “Lack of emotional awareness and understanding,” “Negative Urgency,” “Lack of Perseverance,” and “Impulse-control difficulties.” These findings suggest that emotion-related impulsivity plays a pivotal role in smartphone overdependence and emotional dysregulation, with impulsivity acting as a critical mediator between emotional dysregulation and smartphone overdependence.

Digital financial literacy and financial well-being – evidence from India

PurposeThis study aims to examine the influence of digital financial literacy (DFL) on the financial well-being (FWB) of students in Andhra Pradesh, specifically exploring the factors of impulsivity and self-control. Both DFL and FWB are treated as multi-dimensional constructs in the study. The research delves into the impact of DFL dimensions, viz. digital financial knowledge, digital financial experience and digital financial skills, on both impulsivity and self-control. Subsequently, the study assesses the effects of impulsivity and self-control on financial well-being.Design/methodology/approachTo gather data, a questionnaire-based survey method was employed, reaching 475 university students through purposive sampling. The study utilizes confirmatory factor analysis for scale validation and structural equation modeling for hypothesis testing.FindingsThe results reveal a significantly negative influence of digital financial knowledge (DFK), digital financial experience (DFE) and digital financial skills (DFS) on impulsivity, while demonstrating a significantly positive impact on self-control. Additionally, the study finds that impulsivity negatively affects financial well-being, whereas self-control has a positive impact. Focusing on higher education institutions in Andhra Pradesh, the research highlights students’ limited concern for long-term financial planning.Originality/valueThis study underscores the relevance of understanding the crucial role of digital financial literacy in enhancing their financial well-being. The implications of these research findings are substantial and can be utilized to shape educational programs for students in higher education institutions. Such programs can guide institutions in imparting knowledge and skills related to personal finance management, particularly in the context of the increasing digitalization of financial transactions.

Structural projections to the nucleus accumbens link to impulsive components of human risk preference

Abstract Functional responses in the Nucleus Accumbens (NAcc) to risk- and reward-related cues can predict real-life risk-taking behavior. Since NAcc activity depends on neurotransmission from connected brain regions, projections to the NAcc may also predict risk preference. To quantify risk preference, we employed latent variables previously derived in a comprehensive, independent study examining the psychometric structure of risk preference, which yielded a general risk preference factor as well as several specific factors, including a factor capturing impulsivity. Informed by previous work, we preregistered a set of hypotheses concerning the association between different risk preference factors and fractional anisotropy (or FA, which is sensitive to fiber coherence) for projections to the NAcc from Medial PreFrontal Cortex (MPFC), Anterior Insula, Amygdala, and an inferior tract from the Ventral Tegmental Area (iVTA). We tested our hypotheses in a community sample of 125 healthy human adults. As predicted, bilateral iVTA-NAcc tract FA showed a negative correlation with a psychometric factor that captured impulsivity, generalizing findings from prior research. Also as predicted, FA of the bilateral Amygdala-NAcc tract was positively associated with the impulsivity factor. Contrary to predictions, however, we observed no robust associations between the general risk preference factor and FA for projections from bilateral MPFC, right Anterior Insula, or bilateral Amygdala to the NAcc. Notably, exploratory unilateral analyses revealed an association between the general risk preference factor and left MPFC-NAcc tract FA. Taken together, these findings suggest that impulse control as a facet of risk preference maps onto specific neurobiological targets, while more general facets of risk preference may be supported by structural properties of lateral fronto-striatal projections. Although the exact associated functional mechanisms remain to be fully clarified, conNAcctomic approaches like the one presented here could pave the way for further research into the physiological foundations of risk preference and related constructs.

Originalarbeiten / Original Articles. Sexuelle Risiken bei jungen Patient:innen in der stationären kinder- und jugendpsychiatrischen und -psychotherapeutischen Suchtbehandlung / Sexual Risks in Young Patients in Inpatient Child and Adolescent Psychiatric and Psychotherapeutic Addiction Treatment

Sexual Risks in Young Patients in Inpatient Child and Adolescent Psychiatric and Psychotherapeutic Addiction Treatment Engaging in fulfilling and low-risk sexual relationships is a developmental task in adolescence and young adulthood. At the same time, sexual contact is associated with risks, including early and/or unwanted pregnancies, sexually transmitted infections (STIs) and negative sexual experiences. In the present study, n = 84 inpatients in child and adolescent psychiatric and psychotherapeutic addiction treatment aged between 13 and 19 years were examined. The aim was to determine how many participants had experienced sexual risks due to (1) sexual contact under the influence of alcohol and/or drugs, (2) sexual contact without a condom outside of a committed relationship and (3) regretted sexual contact. It was also checked whether there was a state of intoxication during the situation in the three risk situations. 69.7 % of adolescent SUD patients stated that they had had sexual contact under the influence of alcohol and/or drugs. 46.1 % of SUD patients reported unprotected sexual intercourse in the last 12 months. A total of 53.6 % of female and 12.5 % of male adolescent SUD patients reported regretting sexual contact. 90 % of cases occurred while intoxicated, regardless of gender. No connection to comorbid disorders was found, but there was a clear connection to the impulsivity factor urgency. The figures indicate that young SUD patients are at considerable risk of having unwanted sexual experiences. Preventive measures should take into account aspects of managing urgency.

COMPUTER DIAGNOSTICS OF THE CONDITION OF SHIP ROLLING BEARINGS DURING THEIR OPERATION

The results of statistical processing of vibration signals obtained during diagnostics of ship power plants during the operation process are offered. A distinctive feature of monitoring the technical condition of elements of ship power plants is the uncertainty in the fixation and duration of extreme loads. The peculiarity of computer vibration diagnostics of rotary mechanisms is determined, which is that, in particular, physical measurements of vibration signals require their use in mathematical models of the physical state of the bearing. Calculations of statistical characteristics of vibration signals in the time domain, such as standard deviation (Std), asymmetry (Skewness), kurtosis (Kurtosis), full range of oscillations (Peak2Peak), root mean square value (RMS), cross factor (CrestFactor), form- factor (ShapeFactor), impulse factor (ImpulseFactor), marginal factor (MarginFactor), energy (Energy). The variety of diagnostic signals leads to the need to merge indicators of different dimensions without losing available information into a single generalizing indicator, for which the method of principal components is used in the work. The methodology of statistical processing and practical implementation of diagnostics of vibration signals during the analysis of damage evolution of rolling bearings of turbochargers of marine power plants are described. A new computer information parameter of vibration diagnostics based on the analysis of the first principal component in the time domain and spectral excess in the frequency domain has been identified and experimentally confirmed. The use of new diagnostic parameters makes it possible not only to judge the degree of damage to the rolling bearing, but also to observe the dynamics of the development of the defect and make a relative forecast of the working life of the rolling bearing. A real practical situation is considered - computer diagnostics of vibration signals of ship rolling bearings of a point defect of an external defect of a rolling bearing ring. Determining the applicability of the principal component method to other types of defects showed their potential for vibrodiagnosis of defects located on the inner ring of the bearing and when the ball falls out of the holder.

Exponential Stability of Impulsive Stochastic Neutral Neural Networks with Lévy Noise Under Non-Lipschitz Conditions

In this paper, the exponential stability issue of stochastic impulsive neutral neural networks driven by Lévy noise is explored. By resorting to the Lyapunov-Krasovskii function that involves neutral time-delay components, the properties of the Lévy process, as well as various inequality approaches, some sufficient exponential stability criteria in non-Lipschitz cases are obtained. Besides, the achieved results depend on the time-delay, noise intensity, and impulse factor. At the end of the paper, two numerical examples with simulations are presented to demonstrate the effectiveness and feasibility of the addressed results

Viability for impulsive stochastic differential inclusions driven by fractional Brownian motion

In this paper, we prove necessary and sufficient conditions for the viability for an impulsive stochastic functional differential inclusion driven by a fractional Brownian motion. The viable property is of interest since it reflects the stability of the model under consideration. The fractional Brownian motion provides a memory effect to the model. Whereas, the appearance of the impulsive factor introduces jumps to the solutions and is new to the analysis of this type. Hence our results are new even in the special case of stochastic differential equation setting.

On the design of Optimal Health Indicators for early fault detection and their statistical thresholds

This research presents a method for developing optimal health indicators for early fault detection in machine condition monitoring. The devised health indicators are optimal in the Neyman–Pearson sense, as they maximize the probability of detection while maintaining a constant false alarm rate. They are generated through a generalized likelihood ratio test that involves the probability density functions representing the healthy and faulty states. The essence of the approach lies in establishing a framework that defines optimal health indicators as functions of the partial derivatives of the healthy probability density function and a modulation function, representing the distortion of the probability density function in the faulty state. Specific modulation functions lead to the recovery of several traditional health indicators, including kurtosis, skewness, the crest factor, the clearance factor, the smoothness factor, the shape factor, the impulse factor, ℓp/ℓq-norms, the negentropy, among others. New health indicators are also derived. As the proposed optimal health indicators asymptotically follow a chi-squared distribution, they come with a statistical threshold. The study comprehensively outlines the methodology, with its performance assessed through simulated and experimental signals. The results reveal that the early transition from healthy to faulty can be well detected via the established optimal health indicators and their thresholds.

Impulsivity and reward and punishment sensitivity among patients admitted to a specialized inpatient eating disorder treatment program.

Eating disorders (EDs) are conceptualized as disorders of under- and over-control, with impulsivity reflecting under-control. Extant research indicates that impulsivity and related factors such as reward sensitivity and punishment sensitivity may serve as trait-level transdiagnostic risk and/or maintenance factors in EDs. Findings on impulsivity and reward and punishment sensitivity by diagnosis are mixed and research on the relationship between these factors and ED symptoms, hospital course, and treatment outcomes is limited. Participants (N = 228) were patients admitted to a specialized inpatient behavioral treatment program for EDs who agreed to participate in a longitudinal study and completed self-report measures of impulsivity, reward sensitivity, and punishment sensitivity at admission. Weight and ED symptomatology were measured at admission and discharge. Hospital course variables included length of stay and premature treatment dropout. Impulsivity was lower in individuals with anorexia nervosa (AN) restricting type compared to those with AN binge/purge type or bulimia nervosa; no other group differences were observed. Higher impulsivity was associated with greater bulimic symptoms on the Eating Disorder Inventory 2 (EDI-2) at admission. Impulsivity was not related to ED symptoms, weight outcomes, length of hospital stay, or treatment dropout at program discharge. Impulsivity may help distinguish restrictive versus binge/purge EDs, but does not necessarily relate to discharge outcomes in an intensive inpatient ED program. Findings from this study provide novel contributions to the literature on personality traits in EDs and have important clinical implications. Results suggest that patients with higher levels of impulsivity or reward and punishment sensitivity can be expected to respond to inpatient treatment. Suggestions for future research are discussed.

Development and validation of the IS-C psychometric tool for evaluating children's impulsivity

This research aims to develop an instrument for the evaluation of impulsivity traits in children and to examine the psychometric features of the developed scale. The process of developing the scale involved three main phases: namely, item generation, evaluation of content validity, and analysis of psychometric properties. The study sample comprised 319 children (68 females, 201 males) aged 5-18, all diagnosed with attention deficit hyperactivity disorder (ADHD), including 50 who underwent pilot testing. Both exploratory and confirmatory factor analyses were employed to assess the factor structure of the scale, resulting in an 18-item scale encompassing motor impulsivity, non-planning impulsivity, and attention-related impulsivity factors. The Confirmatory Factor Analysis (CFA) indicated a satisfactory model-data fit. The overall scale demonstrated high reliability, with Cronbach's Alpha coefficients reaching 0.863. The analyses indicated that the scale is both valid and reliable.

Attention-deficit/hyperactivity disorder combined subtype exacerbates opioid use disorder consequences: Mediation by impulsive phenotypes

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is highly prevalent and associated with opioid use disorder (OUD). Yet, little is known about the mechanisms by which ADHD (which is a heterogeneous construct/diagnosis) might alter the trajectory of OUD outcomes in persons who use heroin. AimWe examined whether ADHD subtypes are related to heroin-use consequences and the extent to which the effects of ADHD on lifetime heroin-use consequences are mediated by two impulsivity factors that may be partly independent of ADHD: foreshortened time perspective and drug-use impulsivity. MethodsIndividuals who reported regular heroin use (N=250) were screened using the Assessment of Hyperactivity and Attention (AHA), Impulsive Relapse Questionnaire (IRQ), Stanford Time Perception Inventory (STPI), and a comprehensive assessment of lifetime and current substance use and substance-related consequences. This secondary analysis examined whether ADHD or intermediate phenotypes predicted heroin-use consequences. ResultsRelative to participants whose AHA scores indicated lifetime absence of ADHD (n=88), those with scores indicating persistent ADHD (childhood and adult, n=62) endorsed significantly more total lifetime heroin-use consequences despite comparable heroin-use severity. Likewise, there was a significant indirect effect of the combined ADHD subtype in childhood on lifetime heroin-use consequences. This effect was mediated by STPI scores indicating less future (and more hedonism in the present) temporal orientation and by IRQ scores indicating less capacity for delaying drug use. ConclusionThe combined ADHD subtype is significantly associated with lifetime heroin-use consequences, and this effect is mediated through higher drug-use impulsivity (less capacity for delay) and lower future temporal orientation.

Cognitive Impulsivity in Anorexia Nervosa in Correlation with Eating and Obsessive Symptoms: A Comparison with Healthy Controls.

Impulsivity in eating disorders (ED) has been historically focused on bingeing-purging symptoms, evidencing lower levels in restricting subtypes. In the recent literature, obsessive-compulsive disorder (OCD) has been described as characterized by high cognitive impulsivity. This specific impulsivity factor has been rarely studied in anorexia nervosa (AN). In this study, 53 inpatients with anorexia nervosa and 59 healthy controls completed the following questionnaires: the Barratt Impulsiveness Scale (BIS-11), the Obsessive-Compulsive Inventory (OCI), the Eating Disorders Inventory-2 (EDI-2), the State-Trait Anxiety Inventory (STAI), and the Beck Depression Inventory (BDI). AN individuals showed significantly increased levels of cognitive instability but no difference in global score and other subscales of impulsivity compared to the healthy controls. Among AN individuals, cognitive instability emerged as being associated with the global score and obsession subscale of the OCI. It was also significantly associated with interoceptive awareness and impulse regulation. Cognitive instability was the main predictor of obsessive thoughts and behaviors in AN. Our study supports the hypothesis of AN as being characterized by high cognitive instability and adds the result that the cognitive domain of impulsivity may be associated with the presence of obsessive symptoms, specifically obsessive thoughts.

Aggression among Preschool Children within the Framework of Temperament, Attachment and Parental Attitudes

Aggression is a common problem in preschool children. The relationship between aggressive behaviors in early ages and psychopathologies in later years has been shown in previous studies. Therefore, it is imperative to understand both the causes of childhood aggression and identify the sustaining factors. This review discusses aggression in the context of temperament, parental attitudes, and attachment factors. The concept of temperament was explained with the terminology of difficult and easy temperament, emotionality, activity, sociability, and impulsivity factors, especially from the perspectives of Thomas and Chess, Goldsmith and Plomin, and Cloninger, and associated with aggression in the preschool period. In addition, possible causes of aggression in children were assessed with attachment theory. Finally, the relationship between parents, their attitudes towards aggression, socioeconomic determinants in the family, and the possible relationship between aggression in children were discussed. This study examines the determinants of preschool children's aggression to solve aggression problems, focusing on family and temperamental characteristics. A more holistic assessment of aggression with child and parent characteristics is intended.

Interactions between anxiety and impulsive dimensions are differentially associated with experiential avoidance

Anxiety and impulsivity often co-occur, but due to broad conceptualizations of impulsive behavior, it remains unclear whether anxiety could be positively associated with global impulsivity or specific facets of impulsivity. Negative urgency, or rash behavior that specifically occurs during negative emotional states, may provide common ground to examine the overlap between high anxiety and high impulsivity. Limited work has examined relationships between negative urgency and behavioral processes that are often associated with both anxiety and global impulsivity, such as experiential avoidance. In this study, we examined self-report data collected from a non-clinical sample of adult participants (n = 589) to test relationships between anxiety and experiential avoidance through both negative urgency and global impulsivity. Contrary to hypotheses, we found that negative urgency alone did not alter the relationship between anxiety and experiential avoidance. However, follow-up analyses including data-driven factors of impulsivity revealed that in combination, anxiety and both emotion-based impulsivity (i.e. negative and positive urgency) and hyperactivity were linked to greater experiential avoidance. By contrast, anxiety and non-planning were associated with lower experiential avoidance. These results provide targets for future studies to examine individual differences in profiles of co-occurring anxiety and impulsivity.

Impact of Social Media Addiction and Internet Gaming Disorder on Sleep Quality: Serial Mediation Analyses.

Poor sleep quality is a concerning and prevalent consequence of social media addiction (SMA) and internet gaming disorder (IGD). Due to the lack of research examining how SMA and IGD lead to poor sleep quality, the current study aimed to understand the relationship between SMA and sleep quality, as well as that between IGD and sleep quality, through impulse control and bedtime procrastination. The study tested the hypotheses that higher levels of SMA and IGD would predict lower levels of impulse control, which would then predict higher levels of bedtime procrastination, leading to poorer sleep quality. A serial mediation analysis was performed with a sample of 221 participants (63.3% females, 34.4% males, and 2.3% prefer not to say) aged 18 to 53years (M = 23.64, SD = 5.72). Participants completed questionnaires that assessed for social media addiction, internet gaming disorder, impulse control factor, bedtime procrastination, and sleep quality. There was a full serial mediation of impulse control and bedtime procrastination in the relationship between SMA and sleep quality, as well as that between IGD and sleep quality, providing support for the hypotheses. The findings provide the knowledge needed to develop and implement strategies that target impulse control issues and reduce bedtime procrastination to improve sleep quality.

A competition model with impulsive interventions and environmental perturbations in moving environments

In order to understand how impulsive interventions and environmental perturbations affect dynamics of competitors, we focus on a diffusive competition model with free boundaries and periodic pulses in a temporally heterogeneous environment with upward or downward advection. The dependence of the principal eigenvalue of corresponding periodic impulsive eigenvalue problem on advection rates, habitat sizes and pulses is investigated, which gives precise conditions that classify the dynamics into four types of competition outcomes including coexistence, co-extinction, two different competition exclusions for small or negative advection rates. Some sufficient conditions on pulses or initial habitats for species spreading or vanishing, and spreading speeds are then established. Our results not only extend the existing ones to the case with pulses, but also reveal the effects of human and natural factors, that is, impulsive interventions factors including positive or negative impulsive effect, pulse intensity and timing can significantly affect and alter the competition outcomes. The different performances of the superior and inferior affected by environmental perturbations are also reflected in the simulations.

A novel identification method of microseismic events based on empirical mode decomposition and artificial neural network features

Microseismic technology has been widely used in geological hazard monitoring. However, the effective identification and classification of microseismic events in mines have always been a challenge in hazard monitoring. In this paper, a new method combining the empirical mode decomposition (EMD) algorithm and artificial neural network is proposed for the classification and identification of microseismic waveforms. This is the first study to explore such a model in the microseismic monitoring of coal mines. The data for this study were collected from a coal mine in northern China. A total of 2768 microseismic events and 2435 non-microseismic events were manually selected from a large amount of data. Firstly, the microseismic waveform reconstruction was performed using the 4th to 8th Intrinsic Mode Function (IMF) obtained by the EMD algorithm. Secondly, the peak factor, clearance factor, impulse factor, kurtosis, skewness, and waveform factor of each reconstructed microseismic waveform were used as features. Subsequently, the convolutional neural network (CNN) was used to classify microseismic events. Among them, data from 3600 microseismic events were used as the training set, and data from 1603 microseismic events were used as the test set. Finally, the original waveform data were used as input and compared with the classification results processed with the EMD algorithm. The classification methods of the BP neural network and Radial Basis Function (RBF) neural network were used for verification. The results of the processed features showed a significant increase in accuracy. The classification accuracy of CNN, BP neural network, and RBF neural network are 97.37%, 91.99%, and 94.23%, respectively. The results show that the utilization of the feature processing technique and CNN algorithm in this study demonstrates superior efficacy in microseismic event classification, which can be used in practice.

Individual, Familial and Environmental Risk Factors for Treatment Relapse Among Patients with Substance Use Disorders in Kerala: A Mixed Method Study

ABSTRACT A statewide mixed-methods study was conducted at government-funded deaddiction centers in Kerala, India, to examine the psycho-socioeconomic risk factors of addiction relapse. 435 randomly selected participants from 36 Government-funded centers were included in the quantitative assessment. Among them, 50 were purposively selected for qualitative assessment. The quantitative assessment examined self-esteem, personality dimensions, and various risk factors associated with relapse. On the other hand, the qualitative assessment explored individual, psychological, familial, societal, and economic challenges. Among the beneficiaries, 271 were current and 166 ex-beneficiaries, and among the latter, 73 had addiction relapse. Relapsed patients were younger, had relatively stable jobs, used multiple substances more frequently, and had a family history of addiction. Additionally, individual risk factors of impulsivity and environmental risk factors of association with deviant peers were prevalent. Qualitative analysis identified risk and protective factors under three major domains – individual, environmental and familial. In relapsed patients, the individual and psychological vulnerabilities were activated by social and familial triggers. Though the family was protective, the patient’s expectations from the family were dissimilar and vague, which would be clarified during the treatment process. Therefore, the research suggests developing a patient-centric and process-driven personal care plan to prevent the risk of addiction relapse.

A step-by-step parameter-adaptive FMD method and its application in fault diagnosis

A newly proposed method, feature mode decomposition (FMD), can effectively enhance signal features while decomposing the signal. This feature is beneficial for analyzing weak vibration signals. However, the input parameters (the segment number K, the filter length L, and the mode number n,) significantly influence the decomposition performance and efficiency. Based on the analysis of filter properties and decomposition performance of the FMD method, a step-by-step parameter-adaptive FMD method is proposed. First, parameters K and L are optimized; second, the parameter n is determined. In addition, a comprehensive evaluation indicator, the ratio of sample entropy and ensemble kurtosis, is constructed considering both the periodic impact characteristics of fault signals and the noise intensity to create objective functions for each step. Compared with the methods of variational mode decomposition spectral kurtosis method and the wavelet packet decomposition, the proposed method exhibits better decomposition performance: the amplitude has increased by nearly ten times for the simulation data and six times for the actual engineering data, and three evaluation factors (the crest factor, the impulse factor, and the kurtosis) have higher value. Therefore, it can be concluded that the proposed method has better superiority in identifying weak periodic fault features.

Adaptive exponential synchronization of impulsive coupled neutral stochastic neural networks with Lévy noise and probabilistic delays under non-Lipschitz conditions

<p>In this paper, we investigated the adaptive exponential synchronization problem of impulsive coupled neutral stochastic neural networks with Lévy noise and probabilistic delays under non-Lipschitz conditions. A stochastic variable with a Bernoulli distribution was utilized to transform the information regarding probabilistic delays into a model featuring deterministic time delays and stochastic parameters. In the context of adaptive controllers, exponential synchronization conditions depending on the delay, noise intensity, and impulse factor were derived using Lyapunov-Krasovskii functions, the nature of Lévy noise, and some inequality methods. To provide further support for the proposed approach, two numerical illustrations were presented.</p>