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    Item type:Publicación,
    Influence of Attitude toward Artificial Intelligence (AI) on Job Performance with AI in Nurses
    (2025-01-13) ; ;
    Flores-Paredes, Alcides
    ;
    ;
    Gutierrez-Caballero, Fernando N.
    AI has revolutionized the workplace, significantly impacting the nursing profession. Attitudes toward AI, defined as workers’ perceptions and beliefs about its utility and effectiveness, are critical for its adoption and efficient use in clinical settings. Factors such as age, marital status, and education level may influence this relationship, affecting job performance. This study examines the influence of attitude toward AI on job performance with AI among Peruvian nurses, while also assessing how sociodemographic characteristics moderate this relationship. A descriptive cross-sectional design was used with a sample of 249 Peruvian nurses aged 24 to 53 years (M = 35.58, SD = 8.3). Data were collected using two validated scales: the Brief Artificial Intelligence Job Performance Scale (BAIJPS) and the Attitude toward Artificial Intelligence Scale (AIAS-4). Descriptive statistics, Pearson correlations, and multiple linear regression were applied. A significant positive correlation was found between attitude toward AI and job performance with AI (r = 0.43, p < 0.01). Age (β = -0.177, p < 0.05), divorced marital status (β = -8.144, p < 0.01), and having a bachelor’s degree (β = -3.016, p < 0.05) were negatively associated with job performance, while being from the Selva region had a positive effect (β = 4.182, p < 0.05). A favorable attitude toward AI positively influences nurses’ job performance, highlighting the need for interventions that enhance AI perception. Age, marital status, and education moderate this relationship, suggesting AI adoption strategies should be tailored to different demographic groups.
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    Adaptation and Validation of a Self-Assessment Work Performance Scale for Nursing Staff
    Introduction: work performance in nursing is crucial for the effectiveness of health services and the quality of patient care. Factors affecting this performance include work motivation, organizational culture, institutional support, and working conditions. The need for accurate tools to measure work performance in specific contexts, such as nursing in Peru, is imperative, especially given the increased demands and pressures brought about by the COVID-19 pandemic. Objective: this study aims to adapt and validate a Short Version of the Self-Assessment Work Performance Scale for Peruvian nursing staff, ensuring its relevance and psychometric accuracy in this specific context. Method: an instrumental design was used with convenience sampling, selecting 409 Peruvian nurses (M=20,22, SD=2,6). The scale, composed of 10 items, was adapted to Spanish and evaluated through confirmatory factor analysis. Reliability measures such as Cronbach's alpha and McDonald's omega were employed, along with invariance analysis to ensure the scale's consistency across sexes. Results: the factor structure confirmed the construct validity of the scale with a good fit in the unifactorial models (χ² = 139,820, df = 35, p < ,001, CFI = 0,94, TLI = 0,93, RMSEA = 0,07, SRMR = 0,03). Reliability was high, with Cronbach's alpha and McDonald's omega of 0,92 for the general model. The scale demonstrated full measurement invariance across sexes, reinforcing its applicability in gender-divided populations. Conclusions: the scale is a valid and reliable tool for assessing work performance in nursing staff in Peru. Its ability to adequately reflect the specific conditions and challenges of this professional group ensures its utility in the continuous improvement of health service quality and effective management of nursing staff in diverse and demanding contexts
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    Item type:Publicación,
    Post-covid in patients with obesity: a narrative review
    (2025-02-18)
    Vásquez-Granda, Janeth
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    Tarrillo-Olivos, Jessy C.
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    Pereyra-Urbina, Naomy R.
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    Santacruz, Jose F.
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    Cabanillas-Carrero, Yajahira M.
    Objective: This study aims to conduct a brief literature review on post-COVID-19 complications in obese patients.Design: A literature review based on a narrative synthesis.Data Sources: The databases consulted include Science Direct, Scopus, Scielo, Google Scholar, and PubMed.Study Selection: Multiple articles were selected, applying inclusion criteria focused on post-COVID-19 complications in obese patients, with publications ranging from 2020 to 2024. Irrelevant studies were excluded. The final selection included articles from 10 different countries.Data Extraction: From each study, key data were extracted, including research design, population characteristics, and main reported complications. The information was organized narratively to facilitate comparison of findings across studies.Results: Out of 261,357 articles, 15 relevant articles were selected for the review. These articles were published in 10 countries, as follows: Spain (3 middle-income and 1 lower-middle income), Italy (1 lower-middle income, 1 high-income, and 1 mixed-income), India (2 middle and lower income), Russia (1 middle income), Japan (1 high, middle, and low income), Germany (1 middle income), United States (1 middle income), Mexico (1 middle income), Brazil (1 middle income), and China (1 high and middle income). The findings indicate that socioeconomic inequalities tend to increase the risk of COVID-19-related mortality.Conclusion: COVID-19 is associated with type 2 diabetes, an increased risk of coronary problems, hypertension, and nerve damage such as polyneuropathy, affecting muscle strength and increasing the mortality rate in respiratory diseases such as COPD, leading to lung damage and fibrosis. Treatment should be comprehensive, including vaccines, respiratory exercises, and physiotherapy, where the drug Veklury (remdesivir) has shown efficacy in accelerating recovery and strengthening the immune system. Additionally, post-COVID conditions such as anxiety, depression, and persistent respiratory issues should be addressed.
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    Psychometric properties and invariance of an English self-efficacy scale for university students in Peru
    (2023-06-15)
    Mendoza-Torres, Mariela Estela
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    ; ;
    Morales-García, Sandra B.
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    Rivera‐Lozada, Oriana
    Background English is a global language used to communicate with members of the international community. Self-efficacy in learning English is an important factor that is influenced by perceived importance, interest, and beliefs about the ability to successfully perform tasks in English. Objective The aim is to develop and validate a measurement instrument to assess English self-efficacy. Methods A total of 453 students from different Peruvian universities participated, with ages ranging from 18 to 60 years (M = 23; SD = 6.18). Statistical techniques for latent variables were used and recommendations for educational and psychological tests were followed in its construction. The sample was divided into two groups to perform exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results The English Self-Efficacy Scale (ESS-P) is representative and relevant in terms of its item content (Aiken’s V > 0.70). Its internal structure is organized into three first order factors and a second order factor that are consistent with the theoretical proposal and was confirmed through CFA with excellent goodness-of-fit indices (χ 2 = 1184.9, gl = 626, CFI = 0.92, TLI = 0.92, RMSEA = 0.06 y SRMR = 0.04). It also has adequate internal consistency in its three factors (Reading α/ω = 0.96), Oral Communication (α/ω = 0.95), and Writing (α/ω = 0.97) and the whole scale (α/ω = 0.98), is invariant with respect to sex, and has a conceptual relationship with variables such as academic self-efficacy and exam anxiety. Conclusion The ESS-P is a measurement instrument with evidence of validity, factorial invariance, and good reliability of its scores. Therefore, it can be used in future studies in the academic context.
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    Item type:Publicación,
    Psychometric Properties of a Short Academic Motivation Scale (SAMS) in Medical Students
    Background: Medical education represents a complex field of study, influenced by various psychological, demographic, and contextual factors. Academic motivation, essential for educational success, has been linked to critical decisions in medical careers and can be modulated by contextual elements such as socioeconomic and geographical environments. The theory of self-determination has provided a solid framework for understanding the multidimensional nature of motivation. Objective: To evaluate the psychometric properties of a Spanish version of the Short Scale of Academic Motivation among Peruvian medical students. Methods: Using an instrumental design, the factorial structure, reliability, and gender invariance of the SAMS-S were assessed. A confirmatory factor analysis (CFA) was conducted to validate the scale’s structure based on seven dimensions. Additionally, reliability was assessed through Cronbach’s alpha coefficient and omega coefficient, and gender invariance was determined through multi-group confirmatory factor analysis. Results: The Peruvian version of the SAMS-S showed a good fit in the CFA with satisfactory goodness-of-fit indices. However, challenges in discriminant validity among certain dimensions were detected, suggesting the presence of a second-order factor. The proposed second-order model yielded an adequate fit (χ2 = 198.26, df = 70, CFI = 0.92, TLI = 0.90, RMSEA = 0.08 [90% CI: 0.07–0.1], SRMR = 0.07), validating the factorial structure of the SAMS-S. The scale’s reliability and its subscales were within acceptable ranges. Furthermore, the gender invariance of the SAMS-S was confirmed at all levels, from configural to strict. Conclusions: The second-order model of the SAMS-S presents as a valid and reliable tool for measuring academic motivation among medical students in Peru. Its robustness and adaptability make it relevant for future research in similar educational contexts and can serve as a basis for interventions aimed at improving academic motivation in this specific group.
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    Healthy Habits Factors and Stress Associated with Health-Related Quality of Life in a Peruvian Adult Population: A Cross-Sectional Study
    Background Healthy habits contribute to the prevention of diseases and, therefore, improve the health-related quality of life of people. However, stress is one of the main risk factors associated with serious health problems in the individual. Therefore, the literature suggests a relationship between healthy habits, stress, and health-related quality of life. Objective To assess the factors of healthy habits and stress associated with health-related quality of life in a Peruvian adult population. Methods A cross-sectional study was conducted with a sample of 540 Peruvian citizens aged between 18 and 60 years. A questionnaire was applied on the Google Forms platform to be completed online, using the "Healthy Lifestyle Questionnaire" and the PSS-4 to assess healthy habits and stress, respectively. Health-related quality of life was evaluated using the EuroQol-5D. Results In the multivariate analysis, stress was the most associated factor with quality of life. Physical activity, drug consumption, tobacco consumption, rest habits, and a balanced diet were healthy habits associated with quality of life. Conclusion Physical activity, rest habits, and a balanced diet improve health-related quality of life, while drug or tobacco consumption and stress are associated with a lower health-related quality of life.
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    Validation of a Job Satisfaction Scale among Health Workers
    Background: job satisfaction is a key focus in organizational behavior studies, particularly relevant in the healthcare sector and nursing. It influences patient care quality and staff retention and is shaped by the work environment, working conditions, managerial support, and interactions among colleagues. However, there is limited research specifically addressing the job satisfaction of nurses in Peru, a critical area in health administration. Objective: this study aimed to evaluate the metric properties of the S20/23 job satisfaction scale among Peruvian nurses. Methods: an instrumental research design was employed using a non-probabilistic sample of 325 nurses from two hospitals in Lima, Peru. The Chilean version of the S20/23 scale was used, comprising four dimensions of job satisfaction (relationship with supervision, physical work space, professional fulfillment, and training and decision-making opportunities). Data analysis included descriptive statistics, confirmatory factor analysis (CFA), and reliability tests using Cronbach's Alpha and McDonald's Omega. Results: the CFA revealed a satisfactory fit for the four-dimensional structure with 18 items (χ2 = 387,290, df = 124, p < ,001, CFI = 0,92, TLI = 0,90, RMSEA = 0,08, SRMR = 0,05). The scale also demonstrated high reliability for each dimension: relationship with supervision (α = 0,90, ꞷ = 0,87), physical work space (α, ꞷ = 0,92), professional fulfillment (α, ꞷ = 0,88), and training and decision-making opportunities (α = 0,88, ꞷ = 0,84), with acceptable factor loadings (>0,70). Conclusions: the adapted 18-item S20/23 scale is a valid and reliable tool for assessing job satisfaction among Peruvian nurses. The study highlights the importance of specific job satisfaction dimensions, such as relationships with supervisors and professional development opportunities, in the Peruvian nursing context
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    Development and validation of a scale for dependence on artificial intelligence in university students
    Background Artificial Intelligence (AI) has permeated various aspects of daily life, including education, specifically within higher education settings. These AI technologies have transformed pedagogy and learning, enabling a more personalized approach. However, ethical and practical concerns have also emerged, including the potential decline in cognitive skills and student motivation due to excessive reliance on AI. Objective To develop and validate a Scale for Dependence on Artificial Intelligence (DIA). Methods An Exploratory Factor Analysis (EFA) was used to identify the underlying structure of the DIA scale, followed by a Confirmatory Factor Analysis (CFA) to assess and confirm this structure. In addition, the scale’s invariance based on participants’ gender was evaluated. Results A total of 528 university students aged between 18 and 37 years ( M = 20.31, SD = 3.8) participated. The EFA revealed a unifactorial structure for the scale, which was subsequently confirmed by the CFA. Invariance analyses showed that the scale is applicable and consistent for both men and women. Conclusion The DAI scale emerges as a robust and reliable tool for measuring university students’ dependence on AI. Its gender invariance makes it applicable in diverse population studies. In the age of digitalization, it is essential to understand the dynamics between humans and AI to navigate wisely and ensure a beneficial coexistence.
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    Influence of Self-Efficacy in the Use of Artificial Intelligence (AI) and Anxiety Toward AI Use on AI Dependence Among Peruvian University Students
    Background: The advancement of artificial intelligence (AI) in education has transformed the way students interact with technological tools, creating new challenges related to self-efficacy, anxiety, and AI dependence. Self-efficacy refers to one's confidence in their ability to use AI, while AI-related anxiety pertains to the fear or concern when interacting with these systems. These variables can influence technological dependence, affecting academic performance and emotional well-being. Objective: This study aims to examine the influence of self-efficacy in AI use and anxiety toward AI on AI dependence among Peruvian university students. Methods: A descriptive cross-sectional study was conducted with 528 Peruvian university students aged 18 to 37 years (M = 19.00, SD = 3.84). Scales were used to measure AI self-efficacy, anxiety toward AI, and AI dependence. Correlation and multiple regression analyses were applied to identify predictors of technological dependence. Results: The results showed that AI self-efficacy was positively correlated with AI anxiety (r = 0.43, p < .01) and AI dependence (r = 0.61, p < .01). Anxiety also significantly correlated with AI dependence (r = 0.71, p < .01). Multiple regression analysis revealed that both AI anxiety (β = 1.131, p < .001) and AI self-efficacy (β = 0.610, p < .001) predicted AI dependence. Additionally, business administration students exhibited greater dependence compared to students from other fields (β = 1.025, p < .05). Conclusions: Students with higher self-efficacy in AI use tend to utilize AI more frequently but also experience greater anxiety and dependence on AI. Educational interventions should focus on reducing AI-related anxiety to prevent excessive dependence, especially among students.
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    Sociodemographic Factors, Mental Health, and Emotional Eating Associated With Concern for COVID-19 Contagion in Nurses: A Cross-Sectional Study
    OBJECTIVE: To determine the association between sociodemographic factors, stress, depression and anxiety, emotional eating, and concern about COVID-19 contagion in first and second-line Peruvian nurses. METHODOLOGY: The study was cross-sectional and conducted with 500 Peruvian nurses of both sexes, over 18 years of age. Validated questionnaires were used to measure sociodemographic aspects, concern about COVID-19, generalized anxiety, depression, self-perceived stress, and emotional eating. Multiple linear regression analysis was performed to analyze the factors affecting concern about COVID-19 contagion. RESULTS: The multiple linear regression analysis showed that stress, being between the ages of 18 and 29 years, being male, being from the coastal region or the jungle region, having a bachelor's degree, severe anxiety, and severe depression were associated with higher concern about COVID-19. On the other hand, having more than 5 to 10 years of experience and more than 10 years of experience, low emotional eating, and non-emotional eating were negatively associated with concern. This model explained 44.05% of the variability among the participating nurses. CONCLUSION: These findings provide resources for future research on the comprehensive well-being of nursing staff by exploring various sociodemographic aspects and mental conditions associated with greater concern about COVID-19. Meanwhile, years of experience and emotional eating behavior were associated with lower concern about COVID-19. Future studies could incorporate this information to preserve the mental and physical health of nurses in the face of potential occupational threats.
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