This study examines the impact of artificial intelligence (AI) on loss in decision-making, laziness, and privacy concerns among university students in Pakistan and China. Like other sectors, education also adopts AI technologies to address modern-day challenges. AI investment will grow to USD 253.82 million from 2021 to 2025. However, worryingly, researchers and institutions across the globe are praising the positive role of AI but ignoring its concerns. This study is based on qualitative methodology using PLS-Smart for the data analysis. Primary data was collected from 285 students from different universities in Pakistan and China. The purposive Sampling technique was used to draw the sample from the population. The data analysis findings show that AI significantly impacts the loss of human decision-making and makes humans lazy. It also impacts security and privacy. The findings show that 68.9% of laziness in humans, 68.6% in personal privacy and security issues, and 27.7% in the loss of decision-making are due to the impact of artificial intelligence in Pakistani and Chinese society. From this, it was observed that human laziness is the most affected area due to AI. However, this study argues that significant preventive measures are necessary before implementing AI technology in education. Accepting AI without addressing the major human concerns would be like summoning the devils. Concentrating on justified designing and deploying and using AI for education is recommended to address the issue.
The psychological intensity of orgasm in women constitutes one of the most significant domains related to sexual health. The objective of this study was to examine the role of psychological intensity of orgasm on sexual functioning in the context of sexual relationships in a sample of healthy women. The sample consisted of 518 healthy women from the general Spanish population, with ages ranging from 18 to 62 (M = 25.56, SD = 7.29). The participants completed an online background questionnaire, the Female Sexual Function Inventory, and the Orgasm Rating Scale. Results showed significant differences between women with and without a steady partner in the mean scores of affectivity, intimacy and rewards dimensions of orgasm and in global sexual functioning. Most of the observed correlations between the dimensions of psychological intensity of orgasm and sexual functioning were positive and significant. A significant multiple linear regression model was identified (F (5,517) = 15.526; p < .001) in which female sexual function was predicted by the affectivity dimension of orgasm and the presence of a stable partner. However, a second model indicated that the impact of the orgasm dimensions on sexual functioning was not contingent on the presence of a steady partner. In conclusion, psychological intensity of orgasm in the context of sexual relationships is a predictor of female sexual function. The findings have relevance for future research with a positive approach to healthy women, putting female sexuality as a priority.
Greenhouse gases in the atmosphere pose a risk to human life and ecosystems. The planet’s temperature is gradually increasing, causing changes in weather patterns, rising sea levels, and extreme weather events. In 2015, countries agreed on the 2030 Agenda for Sustainable Development, which includes 17 goals, one of which is climate action. As an EU member, Italy has committed to reducing GHG emissions by 55
Although sexting has become increasingly normalized among youth, less is known about how distinct patterns of sexting involvement relate to mental health and quality of life across developmental stages, and how gendered sexual norms shape these associations. This study analyzed a nationally representative sample of 3,534 Spanish adolescents and emerging adults aged 14–25 (M = 19.8, SD = 3.1; 49
A recent challenge is how to mix qualitative interpretation with computational techniques to analyze big qualitative data. To this end, we propose “multi-resolution design” for mixed method analysis of the same data: qualitative analysis zooms-in to provide in-depth contextual insight and quantitative analysis zooms-out to provide measures, associations, and statistical models. The raw qualitative data is transformed between excerpts, counts, and measures; with each having unique gains and losses. Multi-resolution designs entail transforming the data back-and-forth between these data types, recursively quantitizing and qualitizing the data. Two empirical studies illustrate how multi-resolution design can support abductive inference and increase validity. This contributes to mixed methods literature a conceptualization of how mixed analysis of the same big qualitative dataset can create tightly integrated synergies.
