Predictors Of Behavior Research Articles

Understanding the Relationship Between Empathy, Theory of Mind (ToM), and Parenting Styles Among Children With Disruptive Behaviour.

Disruptive behaviour has been recognized as one of the most common and persistent forms of childhood maladjustment, and predictive of a range of negative adolescent and adult outcomes including continuing aggression, failure in school and work settings, substance abuse, and late-onset psychopathology. As a child grows many factors influence the child's development like genetic factors, parenting styles, attachment patterns, environmental factors etc. These factors help in the development of empathy, theory of mind (ToM), emotional and behaviour regulation. We need to understand the relation between these factors among children with disruptive behaviours, inorder to develop targeted interventions and support strategies tailored to the unique needs of this population. A sample of 70 children and their mothers completed validated psychometric scales. Pearson correlation & regression analysis were conducted to determine the relation between variables. Results indicated that a significant negative correlation was observed between the permissive parenting style of the father and ToM among children with disruptive behaviour. Empathy was considered a significant inverse predictor of disruptive behaviour among children with disruptive behaviour. Another finding suggests that there is no significant difference in disruptive behaviour between boys and girls and no evident association between parenting styles and disruptive behaviours in children. While this could imply that inherent factors (nature) may have a more notable influence on disruptive behaviour in this sample, it is important to consider that this does not rule out the potential impact of environmental factors (nurture). The results should be viewed as part of a complex interplay between nature and nurture, and further investigation, particularly through longitudinal studies, is needed to clarify their respective contributions. This study builds upon existing research in providing a better understanding of contributors to disruptive behaviour among children, which may assist in the development of interventions to promote positive socio-emotional development and enhance the overall well-being of children.

How eHealth use and cancer information-seeking influence older adults' acceptance of genetic testing: Mediating roles of PIGI and cancer worry.

This study aims to investigate how eHealth use and information-seeking behavior affect older adults' acceptance of genetic testing, focusing on their participation in genetic tests and their willingness to adopt lifestyle changes based on test results. The research highlights the mediating roles of the perceived importance of genetic information (PIGI) and cancer worry. This cross-sectional study used secondary data from the Health Information National Trends Survey (HINTS 5, Cycle 4), conducted in 2020. The analysis included 1852 adults aged 60 and above. Two mediation models were tested using SPSS 25. Model 1 examined the relationship between eHealth use, perceived importance of genetic information (PIGI), and genetic test behavior. Model 2 analyzed how cancer information-seeking influences willingness to change lifestyle behavior (WCLB) based on genetic test results, with cancer worry as a mediator. Both models showed statistically significant mediation effects (p < 0.05). Model 1 found that eHealth use positively influences genetic test behavior through PIGI. Model 2 revealed that cancer information-seeking indirectly impacts willingness to change lifestyle behavior (WCLB) based on the genetic test results via cancer worry, confirming a full mediation effect. Additionally, among demographic variables, educational level was the strongest predictor of genetic test behavior, while gender significantly predicted WCLB, with older female adults showing higher intentions to change their lifestyle based on genetic test results than males. The study highlights the pivotal roles of PIGI and cancer worry in shaping older adults' acceptance of genetic testing, encompassing both performing genetic test behaviors and adopting lifestyle changes based on test results. These findings offer actionable insights for designing targeted health communication strategies and interventions to enhance genetic testing uptake and foster proactive health management among older populations.

Illness behavior and its predictors in young and middle-aged colorectal cancer patients: A latent profile analysis.

To describe the characteristics of sick role adaptation and understand the differences in young and middle-aged colorectal cancer (CRC) patients. 225 colorectal cancer patients aged 18-59 admitting to a specialized oncology hospital in Guangzhou, China were involved from January to April 2022. Socio-demographic characteristics, disease-related characteristics, scores of Illness Behavior Questionnaire, Hospital Anxiety and Depression Scale, the Brief Illness Perception Questionnaire, Mishel Uncertainty in Illness Scale and Medical Coping Modes Questionnaire were applied to collect quantitative data. Latent profile analysis (LPA) of illness behavior, analysis of variance (ANOVA) and multiple logistic regression were performed. Three latent classes of illness behavior were identified: low maladaptive illness behavior group, moderate maladaptive illness behavior group, and high maladaptive illness behavior group. Univariate analysis revealed statistically significant differences among the three latent classes with respect to education level, anxiety and depression, illness perception, uncertainty in illness and coping modes. Multiple logistic regression analysis revealed that marital status, family history of cancer, education level, family monthly income, anxiety and depression, illness perception, uncertainty in illness and coping modes were predictors of maladaptive illness behaviors among young and middle-aged CRC patients. The results of the study raise a concern of maladaptive illness behaviors in young and middle-aged colorectal cancer patients, highlighting the need for age-appropriate psychosocial care approaches to promote adjustment of the illness behaviors followed by the diagnosis and treatment of CRC.

Factors Influencing Help-seeking Behavior for Mental Health Among Distressed Young Adults: A Path Analysis Model.

There seems to be a relationship between barriers of distress-perception and stigma to consult a mental health professional (MHP), help-seeking inclination from MHP, help negation, and encouragement from significant others (SO) to consult MHP in bringing about a change in help-seeking behavior. However, these have not been studied in tandem. This study aimed to explore the relationship between factors influencing help-seeking behavior among distressed, non-treatment-seeking young adults (D-NTS) for common mental health concerns following the ReachOut intervention. A total of 109 D-NTS aged 20-35 engaged with ReachOut were recruited online using purposive and snowball sampling. ReachOut was aimed at enhancing professional help-seeking. Participants were assessed at baseline and one month post-intervention for help-seeking barriers, inclination, and encouragement from SO. Help-seeking behavior from MHP was evaluated at a two-month follow-up. Inferential statistics in the form of Spearman's rho correlation, logistic regression, and path analysis were computed. Regression analysis revealed a significant model (χ2 = 34.53, P < .001) with an R2 value of 0.52. Help-seeking inclination from MHP (B = 0.711, P = .037), help negation (B = -0.452, P = .039), and encouragement from SO to consult MHP (B = 1.942, P = .008) at post-assessment were significant predictors of help-seeking behavior, assessed at follow-up. The SEM hypothesized for path analysis with help-seeking behavior as the outcome was a good fit. Help-seeking decisions are complex processes influenced by an intricate interplay of internal and external factors. A comprehensive examination of these elements simultaneously provides valuable insights for tailoring interventions and strategies aimed at enhancing help-seeking behavior in D-NTS young adults. The intervention trial was registered in the ISRCTN registry (ISRCTN14504454).

Utilizing Noseband Sensor Technology to Evaluate Rumination Time as a Predictor of Feeding and Locomotion Behaviors in Dairy Cows

The objective of the study was to examine the relationship between rumination time and various parameters related to eating and locomotion, including other chews, eating chews, eating time, drinking gulps, bolus counts, chews per minute, activity, and activity change, utilizing RumiWatch technology. The RumiWatch noseband sensor (RWS; ITIN + HOCH GmbH, Feeding Technology, Liestal, Switzerland) was utilized to record time and frequency related to rumination, eating, and movement behaviors. The RumiWatch system (RWS) was put into operation from 1 June 2023 to 30 June 2023. The first two weeks, from 1 June to 14 June 2023 at 7 a.m., served as a period for the cows to acclimate to the RWS, acting as an adjustment phase. Monitoring activities with the RWS commenced on 7. a.m. and lasted until the end of the month, 30 June 2023, with data being recorded daily on an hourly basis. Our findings indicate a significant negative correlation between rumination time and other activity time (r = −0.50), which represents the duration cows allocate to behaviors outside of eating, chewing cud, or distinct movement activities. Additionally, a significant negative correlation was observed between rumination time and eating time (r = −0.54). Furthermore, we observed strong positive correlations with rumination chews (r = 0.84) and bolus (r = 0.75). A weaker positive correlation was found with chews per minute (r = 0.29), while no significant correlation was detected with drinking gulps (r = 0.10). Based on our findings, we recommend the implementation of the RumiWatch System for monitoring rumination and feeding behaviors in lactating dairy cattle. This technology provides valuable insights into cow health and welfare, enabling early detection of potential health issues and improving herd management practices.

Hyperparameter Tuning of Random Forest using Social Group Optimization Algorithm for Credit Card Fraud Detection in Banking Data

As the adoption of credit cards continues to expand alongside advancements in e-commerce, the frequency and complexity of fraudulent activities have also grown, posing significant challenges for the financial sector. Detecting fraudulent transactions within highly imbalanced datasets remains a critical issue in ensuring secure banking operations. This study explores a robust approach RF_SGO to credit card fraud detection by combining pre-processing techniques such as Synthetic Minority Oversampling Technique (SMOTE) and class weight adjustment with Random Forest (RF) models optimized using the Social Group Optimization (SGO) algorithm. Additionally, the study utilizes Random Forest's feature importance mechanism to identify the most influential features contributing to fraud detection, enhancing interpretability and decision-making. Our methodology evaluates RF_SGO across three datasets: the original European cardholders' imbalanced dataset, a class-weight-adjusted dataset, and a SMOTE-enhanced dataset. Model performance is measured using key metrics, including Accuracy, Precision, Recall, F1-Score, and ROC-AUC. The RF_SGO model demonstrated superior performance, with the SMOTE-enhanced variant achieving the highest ROC-AUC (0.98) and Recall (0.88), effectively balancing sensitivity and specificity. The class-weighted RF_SGO achieved the highest Precision (0.96), making it ideal for minimizing false positives. Furthermore, the feature importance analysis identified key predictors of fraudulent behavior, providing actionable insights for financial institutions. Comparisons with traditional machine learning algorithms (e.g., Logistic Regression, Decision Trees, and SVM) and advanced models (e.g., XGBoost, CatBoost, and deep learning) highlight RF_SGO's ability to outperform in precision-recall trade-offs and overall classification effectiveness. This study underscores the significance of incorporating hyperparameter tuning, feature importance analysis, and data balancing strategies to improve fraud detection. The proposed RF_SGO framework offers a scalable and efficient solution for financial institutions to mitigate fraud, ensuring more reliable and secure transaction systems.

Personal, environmental and behavioral predictors associated with online fraud victimization among adults.

Online malicious attempts such as scamming continue to proliferate across the globe, aided by the ubiquitous nature of technology that makes it increasingly easy to dupe individuals. This study aimed to identify the predictors for online fraud victimization focusing on Personal, Environment and Behavior (PEB). Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework. Specifically, three factors were identified-Self-awareness (Personal), Attitude (Personal and Environment) and Safe Practice (Behavior) as the potential predictors for online fraud victimization. A self-reporting questionnaire was developed based on the PEB framework and used to collect data targeting Malaysian adults. The study reports result from two separate datasets collected across two separate timelines. Study I involved data collection in January 2023 (n = 820) whereas Study II was conducted with a modified questionnaire from November 2023 -January 2024 (n = 629). Study I identified the online fraud victimization predictors through an Exploratory Factor Analysis (EFA) and a hierarchical binary logistic regression. The dataset from Study II was used to validate the online fraud victimization model derived from Study I by executing another round of hierarchical binary logistic regression. Results from both the samples show that most of the respondents are aware of digital privacy. EFA from Study I yielded a five-factor solution with a total variance of 60.6%, namely, Self-awareness, Safe Practice, Bank Trust, Overconfidence and Social Influence. Hierarchical binary logistic regression results from both the studies were found to be consistent. Specifically, Overconfidence (β = 0.374; OR = 1.453; 95% CI [1.119, 1.887]; p = 0.005) and Social Influence (β = 0.332; OR = 1.225; 95% CI [1.077, 1.512]; p = 0.006) were found to significantly predict online fraud victimization as well as gender (β = 0.364; OR = 1.440; 95% CI [1.008, 2.016]; p = 0.045) with females exhibiting higher risks to victimization. The emergence of Overconfidence and Social Influence as significant predictors can guide the development of targeted online fraud awareness campaigns and/or tools emphasizing critical thinking and skepticism. Policymakers can leverage this knowledge to implement regulations that reduce deceptive practices online, promote digital literacy programs, and mandate clearer consumer protections to mitigate the impact of social manipulation and overconfidence on fraud victimization. This study identifies online fraud victimization predictors, hence improving our understanding of the factors behind this phenomenon-allowing for the development of effective preventive measures and policies to safeguard individuals and improve digital security. For instance, gender- specific educational campaigns can be developed to enhance awareness and equip women with strategies to detect and avoid scams. Additionally, addressing systemic factors like social norms and digital literacy gaps is crucial for creating equitable and effective solutions to reduce online fraud victimization.

Resilience as a predictor of internet addictive behaviours: a study among Ghanaian and Saudi samples using structural equation modelling approach

This study aimed to examine the relationship between resilience and internet addictive behaviours, focusing on cross-cultural contexts involving tertiary education students in Ghana and Saudi Arabia. Using a cross-sectional survey design, data were collected from 738 students across selected universities in both countries. Structural equation modeling (SEM) techniques were employed to analyse the data. The findings indicated that most respondents exhibited low resilience levels alongside a high prevalence of internet addictive behaviours. A significant positive relationship was identified between resilience levels and various dimensions of internet addiction, as well as the overall composite of internet addictive behaviours. Interestingly, while low resilience levels were found to increase the risk of internet addiction, higher resilience levels also appeared to heighten susceptibility to addictive behaviours. These results suggest the need for targeted interventions to address internet addiction. Programs should focus on enhancing resilience through resilience-building initiatives, promoting digital well-being, and integrating mental health support services. These approaches can help mitigate the risks associated with internet addiction while fostering healthier coping mechanisms in students across diverse cultural settings.

Delay discounting predicts COVID-19 vaccine booster willingness

Developing ways to predict and encourage vaccine booster uptake are necessary for durable immunity responses. In a multi-nation sample, recruited in June–August 2021, we assessed delay discounting (one’s tendency to choose smaller immediate rewards over larger future rewards), COVID-19 vaccination status, demographics, and distress level. Participants who reported being vaccinated were invited back one year later (n = 2547) to report their willingness to receive a booster dose, along with reasons for their decision. After controlling for demographic variables and distress level, a greater tendency to discount future rewards was associated with reduced willingness to receive a booster dose. Thematic coding revealed that the most common reason for booster willingness was protection against COVID-19, and for unwillingness was non-necessity. The results identify delay discounting as a behavioral predictor of booster willingness that may be used to inform tailored approaches to increase booster uptake (e.g., trust in science vs. vaccine mandates).

Attention speed and anterior cingulate cortex volume in female and male veterans with suicide ideation and attempts

IntroductionAn average of 17.5 Veterans died by suicide each day in 2021, highlighting the importance of research and prevention efforts aimed at suicide risk. Attentional processes have emerged as a possible predictor of suicide behaviors (SB), yet associated neural correlates remain understudied, particularly in the Veteran population.MethodsThe current study examines sustained and selective attention performance as indexed by the Ruff 2 &amp;amp; 7 Selective Attention Test and anterior cingulate cortex (ACC) volume as they relate to SB in Veterans. A subset of Veterans also completed a structural magnetic resonance imaging protocol. Participants were grouped on history of suicidal ideation (SI), suicide attempt (SA), and no SB (HC).ResultsAnalyses from the Ruff 2 &amp;amp; 7 test showed that Veterans with a history of SA performed more slowly on Automatic Detection Speed (ADS) and Controlled Search Speed (CSS) compared to Veterans with SI and no SB. SI and SA group differences on ADS and CSS remained after Bonferroni correction, and CSS differences remained after controlling for depressive and anxious symptoms. There were no between-group differences on Ruff 2 &amp;amp; 7 Accuracy measures. When analyses were divided by sex, males with a history of SA performed more slowly than SI and HC on ADS and more slowly on CSS and Total Speed than males with a history of SI. Results remained significant after controlling for depressive and anxious symptoms. When Bonferroni corrections were applied, males with a history of SA performed more slowly on ADS, CSS, and Total Speed compared to males with a history of SI. Female Veterans with a history of SA performed more slowly than female HC on CSS only; however, these findings were no longer significant after controlling for depressive and anxious symptoms. No significant differences were found between female groups on ADS or Total Speed. Measures of left rostral ACC gray matter (GM) volume for the combined female and male Veteran sample were positively correlated with ADS and CSS scores in HC but not SA. Conversely, right rostral ACC GM volume negatively correlated with ADS and CSS scores in the SA group but not HC. Right rostral ACC white matter volume correlated positively with ADS and CSS in HC.DiscussionThese findings highlight associations between attention speed, ACC volume, and SB even after controlling for acute mood symptoms, in addition to emphasizing the importance of including sex in analyses.

Analysis of predictors of smoking and alcohol abuse among healthcare workers considering specialty and gender differences

Results of foreign studies indicate a relatively high prevalence of smoking and alcohol consumption among healthcare workers, which can be explained by various socio-demographic and psycho-emotional characteristics, as well as stressinducing and psychological trauma factors related to their professional duties.Aim. Analyse predictors of smoking and alcohol abuse among health care workers.Materials and methods. The ASSIST screening test was used to assess the severity of clinically significant symptoms of substance abuse. The IES-R and K-10 questionnaires were used to evaluate psycho-emotional states.Results. It was found that among men working in the “obstetrics and gynecology” specialty, a significant predictor of smoking was a high level of distress (p ≤ 0.05), and alcohol abuse was associated with the absence of a marital relationship (p ≤ 0.01). For women, alcohol abuse was related to increasing age (p ≤ 0.001), high income (p ≤ 0.01), living in a large urban area (p ≤ 0.05), and being married (p ≤ 0.01). Among men working in the “psychiatry and addiction medicine” specialty, alcohol abuse was associated with high income (p ≤ 0.01) and education levels (p ≤ 0.05). For women, there were associations between alcohol abuse and young age (p ≤ 0.01), high income (p ≤ 0.001) and education levels (p ≤ 0.01), distress (p ≤ 0.001), and post-traumatic stress disorder symptoms (p ≤ 0.05). For women, regardless of specialty, smoking and alcohol consumption were positively correlated (p ≤ 0.001).Conclusion. The identified predictors of addictive behavior could become targets for targeted psychological and medical interventions.

Effect of Perceived Neighborhood Environment on Cannabis Use during Pregnancy among African American Women.

Environmental context is an important predictor of health behavior. Understanding its effect on cannabis use among pregnant women is yet to be understood. The aim of the study is to assess the impact of perceived neighborhood environment on prenatal cannabis use and explore the mediating role of stress. Data are from the Life-Course Influences on Fetal Environments Study (LIFE), a retrospective cohort of postpartum African American women in Metropolitan Detroit, Michigan (2009-2011). Prenatal cannabis use was defined as self-reported ever use during pregnancy. Three perceived neighborhood scales were considered: social cohesion and trust, social disorder, and danger and safety. Out of 1,369 women, 151 (11.0%) self-reported using cannabis during pregnancy. After adjusting for age, marital status, income, years of education, and general social support scale, the odds of cannabis use significantly increased among the lowest quartiles of all the neighborhood scales suggesting higher cannabis use among women who perceived their neighborhoods to have the worst conditions. Compared to the highest quartile, the odds ratio (OR) for the lowest quartiles for social cohesion and trust, social disorder, and danger and safety were 1.77 (95% confidence interval (CI): 1.04-3.03), 1.83 (95% CI: 1.15-2.91), and 1.93 (95% CI: 1.12-3.31) respectively. Evidence of mediation by perceived stress was only present between the association of perceived levels of safety and danger with cannabis use during pregnancy. Future prospective studies are warranted to understand the causal associations between individual correlates and social and physical environmental factors of prenatal cannabis use.

Promising Predictors of Adolescent Sexual Behavior Outcomes: ASystematic Review of Longitudinal Research.

This review examined research to identify longitudinal predictors of adolescent sexual behavior outcomes. These predictors hold promise as potential outcomes for teen pregnancy prevention program evaluations when measuring sexual behavior outcomes is infeasible or theoretically, methodologically, or developmentally inappropriate. We conducted a systematic review using a prespecified search strategy and processes consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We examined 32 research studies published between 2008 and 2024. Four categories of predictors of sexual behavior during adolescence emerged across the reviewed studies. Variables within the caregiver control, self-regulation, sexting, and substance use categories each predict future sexual behavior outcomes, with findings consistent across 3 or more studies for each category. This systematic review documents the current evidence base for precursors of sexual behavior outcomes among adolescents and specifies which predictors have promising, potentially promising, mixed, and limited evidence. This review is the first step in gathering information that will eventually inform an avenue for teen pregnancy prevention program developers and researchers to highlight the promise of programs when evaluating impacts on sexual behavior outcomes is infeasible or inappropriate.

Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction

Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. We provide a dataset on human decision-making during evacuations from virtual buildings, captured using experimental methods that controlled specific building layout parameters. An online experiment assigned participants a random subset of tasks featuring T-intersections. Data from 208 respondents, aged 17 to 71, were analyzed, considering education levels and excluding those with significant technical issues. Quantitative data on user interaction and evacuation route choices included decision time, mouse rotation, and the selected corridor, recorded through mouse clicks on invisible areas of interest. Respondents also self-reported their choice confidence on a Likert scale. Additionally, responses to final retrospective evaluation questionnaires were recorded. This dataset offers diverse research opportunities, particularly in emergency evacuation planning, where understanding evacuation choices in simulations can inform real-world strategies. It supports the development of models to predict human behavior in emergencies using machine learning and predictive modeling and is accessible for both academic and commercial use.

Self-regulation skills and prosocial behaviours in preschool children with and without autism

Objectives The purpose of this study was to examine the self-regulation skills and prosocial behaviours of children on the autism spectrum (AS) and their non-autistic (NA) peers of the same chronological age. For this purpose, self-regulation skills and prosocial behaviours of children on the AS and NA children were compared, and the relationships between self-regulation skills and prosocial behaviours in both groups were examined. Methods To measure self-regulation skills, Self-Regulation Skills Scale for 4–6-Year-Old Children was used. To measure prosocial behaviours, prosocial sub-domain of Strengths and Difficulties Questionnaire was used. All measures were based on mother reports. Results Findings showed that (a) there were significant differences between groups in both self-regulation skills and prosocial behaviours, (b) there were moderately positive relationships between self-regulation skills and prosocial behaviours in both groups, and (c) self-regulation was a significant predictor of prosocial behaviours in both children on the AS and their NA peers. Conclusions This study shows that children on the AS and their NA peers differ in both self-regulation skills and prosocial behaviours in preschool years. Self-regulation is positively correlated with, and an important predictor of prosocial behaviours. Supporting self-regulation skills can be an important facilitator for preschoolers on the AS to develop prosocial skills which are important for both academic achievements and social skills. Further research examining other variables which may be effective on prosocial behaviours, such as language, educational experience, and symptom severity are needed.

Do gritty salespersons mitigate relationship damage in unethical sales subcultures?

ABSTRACT Previous research has shown that salesperson grit is not a consistent predictor of ethical sales behaviors. Our study relies on the integrated theory of ethical decision-making to evaluate the influence of the sales ethics subculture and the interaction of salesperson grit across two distinct types of unethical behavior. Unethical sales behaviors are motivated by self-interest, but pro-social rule breaking is more selfless in nature. Empirical data from 197 salespeople were analyzed via structural equation modeling. We find that higher levels of salesperson grit result in lower levels of selfish, unethical sales behaviors, but grit does not change the amount of selfless pro-social rule breaking. Moreover, unethical sales behaviors damage the relationship between salespersons and their clients, but contrary to our beliefs, pro-social rule breaking neither damages nor improves these relationships. Our findings support the notion that salespersons operate according to dual processes when facing ethical dilemmas.

Research Review: Sex differences in the clinical correlates of nonsuicidal self-injury in adolescents - a systematic review.

Nonsuicidal self-injury (NSSI), or 'the deliberate, self-inflicted destruction of body tissue…without suicidal intent and for purposes not culturally sanctioned', is a robust predictor of future suicide-related behavior and therefore a modifiable target for suicide prevention. The prevalence of NSSI is rising in adolescents, particularly among females; however, it is unknown whether sex differences also exist in the clinical and psychosocial factors associated with NSSI. Understanding how the correlates of NSSI differ by sex is important for developing tailored treatments. This study systematically reviews sex differences in the clinical and psychosocial correlates of NSSI among adolescents. MEDLINE and PsycINFO were searched using the keywords 'adolescents', 'self-injury', and 'sex factors' and synonyms for English-language articles published between January 1, 2000 and May 10, 2022. We included studies that presented original data on NSSI, included adolescents ages 10-19, reported sex differences, and explicitly defined self-injury as that done without suicidal intent. Fifty-seven studies containing 54 unique samples were included. Data were summarized by sex and recorded by: (a) characteristics of NSSI, (b) clinical and psychosocial correlates of NSSI, and (c) associations with suicide. We used data on NSSI from 54 unique samples of adolescents worldwide. Males more commonly used violent methods of NSSI, such as burning, and were more likely to be physically aggressive and experience substance abuse. Females more commonly self-injured by cutting, and their NSSI was more likely to be repetitive and associated with emotional distress. In both sexes, NSSI was associated with adverse childhood experiences (ACEs) such as sexual abuse/violence and bullying. NSSI was predictive of suicide in females but not males. Data from 22 countries and 352,516 participants suggest important sex differences in the clinical and psychosocial factors associated with NSSI among adolescents that future assessment and treatment strategies ought to consider.

Research on Consumer Buying Behavior When Watching Livestreams on Digital Technology Platforms in Vietnam

This study provides a comprehensive analysis of consumer purchasing behavior during livestream sales on digital technology platforms, focusing on psychological and technological factors influencing buying decisions. Using Structural Equation Modeling (SEM), the research identifies key relationships between consumer attitudes, trust, perceived behavioral control, subjective norms, and purchase intentions. The findings reveal that consumer attitudes towards livestream sales positively impact purchase intentions, with perceived usefulness, ease of use, and perceived behavioral control contributing significantly to positive attitudes. Conversely, perceived risk does not significantly affect attitudes, indicating its limited role in livestream contexts. Consumer trust also positively affects purchase intentions, influenced by perceived risk, livestreamer reputation, and subjective norms. Purchase intention is a critical predictor of actual buying behavior. The study highlights practical implications for businesses and livestreamers, including improving livestream quality, enhancing user experience, and building consumer trust. Recommendations are provided for both businesses and consumers to optimize livestream sales strategies. The study also outlines limitations, such as the sample size and geographic focus, and suggests future research directions to broaden the understanding of livestream purchasing behavior.

Prime and punishment: Effect of religious priming and group membership on prosocial behavior

This research investigates the influence of religious priming and group membership on prosocial behavior, measured by the willingness to donate to fictitious charities in a hypothetical scenario. A sample of 258 Hindu participants, averaging 21.3 years of age, were engaged in an online study designed on PsyToolkit. The study employed a 3*2 factorial design, wherein participants were subliminally primed with concepts of “reward” and “punishment” within religious contexts through a lexical decision task. Post-priming, individuals were presented with a decision to allocate a portion of a potential lucky draw prize to selected charities, which represented either their religious ingroup or an outgroup. The findings demonstrated that religious priming did not significantly enhance prosocial behavior toward either group. Bayesian analysis supported the absence of an effect for priming and group conditions. Moreover, other variables such as religiosity, sex, and political orientation showed no substantial effect on the likelihood of charitable giving. However, consistent with previous research, past charity behavior emerged as the most salient predictor of prosocial behavior, underscoring the importance of experiential factors in shaping altruistic tendencies. The study reflects on the influence of India’s secular and culturally rich backdrop, which may modulate the propensity to engage in charitable acts, especially when the donations come from unexpected gains rather than one’s own money. It reveals that prosocial behavior is shaped by a mix of situational and personal factors, not just religious beliefs. The research contributes to the understanding of prosocial behavior in diverse religious contexts and the role of personal experience in predicting charitable actions, advocating for further investigation into these dynamics.

Suicidal Thoughts and Behaviors Among Health Care Trainees, Staff and Faculty at an Academic Medical Center.

Background/Objectives: Health care workers are at greater risk for death by suicide compared to the general population and are less likely to seek assistance. More information about correlates of suicidality and treatment-seeking behavior are needed to reduce risk. Methods: The American Foundation for Suicide Prevention developed an Interactive Screening Program to identify and engage at-risk staff and trainees in health care settings. The study reports on the prevalence and demographic and clinical predictors of current suicidal thoughts, behaviors and mental health treatment at a single site (n = 5898) from 2009 to 2024. Results: The study found that 18.2% of respondents reported current suicidal thoughts and behaviors. These were more common among respondents who were younger, male, and who identified as a race/ethnicity other than non-Hispanic White. Suicidal thoughts and behaviors were more likely among those with higher PHQ-8 scores (OR = 1.23, p < 0.01) and those who endorsed maladaptive coping behaviors, hopelessness, loneliness, stress and nervousness (ORs 1.36-3.04, ps < 0.01). Current mental health treatment was more likely among women, non-Hispanic White respondents compared with Asian or Pacific Islander respondents, and nurses relative to physicians. Mental health treatment was also associated with higher PHQ-8 scores, lifetime suicide attempts, difficulty controlling eating and alcohol consumption, and recent feelings of anxiety, stress and nervousness. Conclusions: Findings suggest a continued need to identify and engage health care trainees and staff who are at risk for suicide and to establish new approaches to linking these individuals to resources or interventions aimed at reducing risk. The study identified male and/or Asian/Pacific Islander-identifying health care workers who reported intense loneliness and/or hopelessness, use of non-prescription drugs and recent suicidal thoughts and/or behaviors as high-risk individuals who may require enhanced methods of outreach, identification, acceptance and accessibility of treatment.