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Exploring Demographic Factors, Ambivalent Sexism and Psychological Well-being in an Irish Context
No full textThis study investigated how demographic variables (age, gender, education levels and perceived socioeconomic status (SES)) predicted benevolent and hostile sexism and how each sexism influenced various aspects of psychological well-being (autonomy, environmental mastery, personal growth, positive relations with others, purpose in life and self-acceptance) in a contemporary Irish context. This quantitative, cross-sectional study used convenience sampling and recruited 101 participants through social media platforms (female: n = 72, male: n = 27), aged 18–63 (M = 33.5, SD = 14.86). Education levels ranged from secondary school to postgraduate degree and perceived SES ranged from 1 to 9 (M = 6.11, SD = 1.43), on a 1-10 scale. Participants completed a questionnaire, including demographic questions, Ryff’s Psychological Well-Being Scale and the Ambivalent Sexism Inventory. Regression analyses were conducted to investigate these relationships and the results showed that age, gender and perceived SES were statistically significant predictors of benevolent sexism, while only gender was for hostile sexism. Neither form of sexism significantly predicted any aspect of psychological well-being. These findings could contribute to the development of targeted interventions to reduce sexism in at-risk groups. Further research is needed to explore cultural and external influences on these relationships
The Role of Romantic Relationships in Body Image
No full textBody image dissatisfaction is an increasing problem in society, with many people of all ages experiencing some level of body dissatisfaction. Body image dissatisfaction can lead to negative psychological outcome for many, highlighting the need to understand the factors that both positively and negatively influence body image. Romantic Relationships have been identified as a potential factor offsetting the negative outcomes that result from poor body image perceptions and in promoting body positivity. Romantic relationships have been directly linked in an increase in body satisfaction and many factors that are related to romantic relationships, such as length and satisfaction have been directly linked to an increase in both body satisfaction and dissatisfaction. The aim of the current study was to address these contradictions relating to the influence that romantic relationships have on body image in existing literature, while also attempting to identify gender differences in body image satisfaction regardless of relationships status. Data was collected from participants (N = 90) via an online Google Forms survey where they were asked for demographic information and to complete two surveys: the Body Image Concern Inventory and the Relationship Assessment Scale. The results indicated that while there are significant gender differences in body image satisfaction, factors such as relationship status, length and satisfaction do not appear to have the same influence on body image. Further research should prioritise longitudinal studies, aiming to gather a more diverse sample of participants
The Power of Language: Study of How Language Influences Moral Decisions
No full textAims: Previous findings suggest that language influences moral decisions, with native language providing stronger utilitarian decisions, while foreign language provides stronger deontological ones. The current study sought to provide a greater understanding of the Foreign Language Effect and investigate how moral decisions are affected by this phenomenon. This study also examined the difference between gender and types of environments in the prevalence of making utilitarian decisions.
Method: The Moral Dilemmas Questionnaire was administered to two groups of participants (total n=160) through a random allocation link that assigned participants to either Serbian/Croatian/Bosnian or English language groups. Both groups received the same questionnaire but in two different languages. Independent sample t-test and one-way between groups ANOVA were administrated using SPSS version 28.0.1.1.
Results: The results showed no significant effect between language, gender, environment, and moral judgements. However, age was found to be a significant factor, with middle-aged adults making stronger deontological moral decisions.
Conclusion: Findings suggest that language on its own might not be the greatest predictor of making different moral decisions in different languages. Other factors such as age, culture, heuristics, personality differences, family history, etc., might influence the prior findings. Further research using different research methods, such as longitudinal studies and qualitative analysis, might have a better understanding of the Foreign Language Effect
Priming and its Effect on Attitudes
No full textAims: This study examines the impact of priming on self-reported prosocial attitudes, focusing on whether exposure to prosocial or antisocial primes influences attitudes toward helping behaviour.
Method: Using a randomized, between-subjects design, 97 participants completed a Scrambled Sentence Task (SST) featuring prosocial, antisocial, or neutral primes, followed by the Helping Attitudes Scale (HAS) both pre- and post-priming.
Results: A repeated-measures ANOVA revealed no significant interaction between priming conditions and changes in HAS scores, suggesting that priming did not significantly alter self-reported helping attitudes. Visual inspection of the data further indicated that a weak positive correlation between age and HAS scores was driven by outliers, limiting its interpretability.
Conclusion: The findings challenge prior research indicating strong behavioural effects of priming, suggesting that while priming may influence unconscious behaviours, its impact on explicit self-reported attitudes may be limited. Methodological factors, such as the online study format and potential distractions, may have contributed to these results. This study highlights the need for further research into the boundary conditions of priming. Future studies should integrate implicit behavioural measures alongside self-reports to capture a more nuanced understanding of priming effects
Emotional intelligence as a moderator between perfectionism and depression levels
No full textBackground: Perfectionism is a multidimensional concept which demands unattainable standards in almost every part of one’s life. Perfectionism has often been linked with depression in previous literature. While emotional intelligence has been shown to act as a protective factor for both depression and perfectionism. Hence, the current study aimed to add to the literature that perfectionism and depression have a relationship. The study also explored if scores of overall perfectionism were correlated with emotional intelligence. Lastly, the study investigated if emotional intelligence is a moderator between perfectionism and depression levels.
Method: Convenience sampling was used to collect data from an online questionnaire of 131 participants. Questionnaire obtained demographics and measured for emotional intelligence, perfectionism, and depression levels.
Results: Findings from a Pearson’s correlation identified a strong correlation between perfectionism and depression. Another Pearson’s correlation found no correlation for emotional intelligence and perfectionism. Moderation analysis revealed that emotional intelligence successfully moderated the relationship between perfectionism and depression. The present study is the first study to investigate emotional intelligence as a moderator for perfectionism and depression and gives good foundational basis for future research. Findings provide a greater insight into this relationship as emotional intelligence weakened the link between perfectionism and depression
The Effects of Social Media on Implicit Peer Pressure and Risk-Taking
No full textBackground: Peer pressure is defined as the influence exerted by a peer group on individuals to conform to the norms of the group. Peer pressure can be explicit (direct) or implicit (indirect). Peer pressure is linked to an increase in risk-taking behaviours with males, adolescents and young adults reporting the highest levels of susceptibility. The aim of this study is to assess to what extent does social media influence implicit peer pressure and risk-taking as well as assessing age and gender differences within an Irish context.
Method: The study consisted of 113 participants (Males: n = 34, Females: n = 77) between the ages of 18 and 72 (M = 31.24, SD = 12.94) and a correlational, cross-sectional study design. The Social Media Intensity Scale was used to assess social media intensity, the Online Peer Pressure Scale was used to assess online implicit peer pressure and risk-taking and a demographic questionnaire was used to measure age, gender and average social media hours.
Results: The results indicate there is a small correlation between social media intensity and implicit peer pressure and risk-taking. Age is a statistically significant predictor for implicit peer pressure and risk-taking (β = -.37, p <.001).
Conclusions: The results of this study suggest that implicit peer pressure is facilitated by social media on some level. The findings have practical implications for preventing offline risk-taking
Deep Learning-Based Detection of Shoplifting Behavior: using 3DCNN and LRCN
No full textThis research explores the effectiveness of deep learning models in detecting pre-crime behavior in surveillance footage, specifically targeting shoplifting scenarios. Using 94 videos (50 shoplifting and 44 normal) from the UCF-Crime dataset, the study employs the Pre-Crime Behavior (PCB) methodology to segment video clips into four distinct behavior classes: Normal, Suspicious, Theft and Post-Theft. Two architectures, Long-Term Recurrent Convolutional Network (LRCN) and 3D Convolutional Neural Network (3DCNN) were trained on input sequences of 120 grayscale frames (64×64 resolution). Three experiments were conducted: multi-class classification, binary classification, and data augmented binary classification to address class imbalance. In the best performing setup, LRCN achieved 90.15% accuracy and an F1-score of 0.90, outperforming 3DCNN which reached 83.33% accuracy and an F1- score of 0.84. The results underscore the benefits of combining temporal modeling with balanced training data for early and accurate detection of suspicious activity. These findings support the development of intelligent surveillance systems capable of identifying abnormal behavior before crimes occur
Optimizing Real-Time Data Analytics in Healthcare: A Predictive Model for Cardiovascular Disease Management
No full textCardiovascular disease continues to be a global leading cause of death, but conventional prediction techniques often lack the ability for real-time and customized intervention. The paper proposes solving the problem of predictive accuracy by using machine learning algorithms for the prediction of cardiovascular disease based on lifestyle and clinical information. The research made use of the Kaggle Cardiovascular Disease dataset containing 70,000 patients. The initial preprocessing involved the removal of outliers and scaling of features. Feature selection using SHAP values and RFECV followed. Three supervised learning classifiers—Decision Tree, Random Forest, and Support Vector Machine (SVM)—were created and tested. The SVM model returned the best accuracy of 72%. It was also found through statistical analysis that cardiovascular disease had strong correlation with lifestyle habits like smoking and inactivity. The study illustrates how machine learning could be used for early detection and customized healthcare planning and explains its importance for preventive interventions in the future
A real world case study of Infrastructure vs serverless computing
No full textHR industry was one of the first to use the cloud technology. However, as user engagement becomes more dynamic and real-time interactions grow in demand, traditional server-based infrastructures often face challenges related to scalability, latency, and operational cost. A possible solution is to move to a serverless architecture. This study presents the design and implementation of JobSpace, a full-stack job hiring portal built using a hybrid serverless architecture. The system leverages serverless computing technologies such as AWS Lambda, Google Cloud Functions, and API Gateway, combined with a Node.js and Express backend, and MongoDB for persistent data storage. It was implemented on ec2 instances and also implemented in aws using serverless architecture. Results showed a notable improvement in responsiveness, with average response times below 150ms, and a significant reduction in infrastructure costs during periods of low traffic. The study concludes that a hybrid serverless approach is effective for building scalable, secure, and cost-efficient recruitment platforms and sets the foundation for future as compared IAS
The Complexities of Acculturation and Discrimination of Immigrants in Ireland
No full textIntroduction: The increasing number of multi-cultured immigrants reaching the Republic of Ireland, suggests notable psychological adaptations for the Irish-arrived immigrants, in relation to their ability to acculturate and assimilate in Irish society. This research study explores the relationship between perceived discriminatory experiences and the processes of assimilation and acculturation among Irish immigrants, considering demographic variables (age, gender, ethnicity).
Method: This study employs a quantitative, cross-sectional, within-subjects design. A number of 82 participants, have been administered three measured scales, 1) the Acculturation Attitude Scale (AAS), (2) Vancouver Index of Acculturation (VIA), and lastly, (3) Day-to-Day and Major Events Discrimination Scale (EDS) & (MEDS); alongside recording the demographical factors of each individual (age, gender, and ethnicity).
Results: The results administered non-significant results regarding all hypotheses identified; two correlational analyses, simple linear regression analyses for each variable, and lastly, two multiple regression analyses.
Conclusion: The findings of this study determined non-significant relationship between perceived discrimination and assimilation/acculturation in Irish immigrants. Therefore, suggesting that other factors beyond discrimination influence assimilative and acculturative attitudes among Irish immigrants. Further research is recommended to explore these potential influencing factors in greater depth