İbrahim Hakkı Tezci

Purpose: This study examined the associations among presenteeism, psychological resilience, and perioperative competence in operating room nurses and whether psychological resilience statistically accounted for part of the association between presenteeism and perioperative competence. Methods: This descriptive, cross-sectional, correlational study included 251 operating room nurses working in public and university hospitals in Türkiye. Data were collected using the Descriptive Information Form, the Perceived Perioperative Competence Scale-Revised, the four-item Turkish short form of the Stanford Presenteeism Scale, and the Brief Resilience Scale. Pearson correlation and mediation analyses were con-ducted using Hayes’ PROCESS macro, adjusting for age, gender, hospital type, professional experience, and shift type. An errors-in-variables sensitivity analysis was also performed. Results: Presenteeism was negatively associated with psychological resilience and perioperative competence, whereas psychological resilience was positively associated with perioperative competence (all p < 0.01). The indirect effect through psychological resilience was significant (ab = −0.410, 95% BC CI [−0.828, −0.123]) and accounted for 31.1% of the total effect. The direct effect did not reach statistical significance (c′ = −0.908, p = 0.066). The sensitivity analysis showed a similar pattern. Conclusions: Psychological resilience accounted for a modest but significant portion of the association between presenteeism and perioperative competence. Longitudinal studies are needed to clarify the temporal ordering of these relationships.

BACKGROUND The rapid adoption of artificial intelligence (AI) in healthcare emphasizes the importance of assessing healthcare professionals' attitudes towards this technology. OBJECTIVE The aim of this study was to develop and validate a reliable and comprehensive Artificial Intelligence Attitude Scale (AIAS) with a number of subscales for physicians. METHODS This qualitative study was conducted cross-sectionally between January and March 2024. For this investigation, three stages were identified. The first stage involves the development of an item pool pertaining to artificial intelligence and informatics. The next stage entails administering the generated items to a primary sample of physicians using a 5-point Likert questionnaire, followed by conducting explanatory and confirmatory factor analyses on the acquired data. The last stage consists of distributing the newly established scale to a secondary sample of physicians, assessing the scores across the scale's subcategories, and investigating their variations concerning certain independent variables. RESULTS A questionnaire comprising 47 items was distributed to clinicians following an expert evaluation. The initial sample consisted of 239 participants who completed the questionnaire. After the outliers were eliminated, the results of 198 participants were analyzed. Exploratory factor analysis (EFA) identified a three-factor structure (Belief, Knowledge, Practice) with robust factor loadings (0.64 and above) and an overall explained variance of 62.64%. The data set was considered appropriate for EFA according to the Kaiser-Mayer-Olkin (KMO) (0.91) and Bartlett's test (χ2=712.63, P<.001), and the principal axis factoring method with varimax rotation was utilized due to the lack of multivariate normality. After confirmatory factor analysis (CFA), the scale's (AIAS) final version comprised 26 items and three subscales emerged: belief (11 items), knowledge (7 items) and practice (8 items). All t values of the loadings of these subscales were significant (P<.001). The AIAS showed strong internal consistency (Cronbach's alpha >0.88 and composite reliability >0.70 for all subscales) and acceptable model fit indices in CFA. The AIAS was administered to a second new sample of 509 physicians in the concluding stage of the study, and 441 responses from this sample were considered to be valid. Findings revealed that physicians generally held positive beliefs about AI (mean belief score: 37.58 ± 9.22), but knowledge (18.71 ± 5.81) and practice (11.31 ± 3.7) scores remained lower. Male physicians (P<.001), those in academic roles (P<.001) and those working in private hospitals (P<.05) generally reported higher scores on some subscales, while higher workload was associated with lower practice scores (P<.05). CONCLUSIONS The AIAS provides a robust tool to assess attitudes towards AI in healthcare. While physicians recognize the potential benefits of AI, practical adoption requires targeted training, improved infrastructure and addressing ethical challenges.

The purpose of this research was to examine the perspectives of academicians on distance education activities during the pandemic from various aspects. The research study was carried out using a case study design, which is one of the qualitative research methods. The perspectives of 24 academicians working at a state university were explored, and the data collected through an online platform using a structured interview form were analyzed by utilizing the content analysis method. The findings were reported in the form of themes, sub-themes, and codes, supported by participant expressions. Results indicated that academicians faced infrastructure-related problems during the pandemic process, which arose from various aspects. They expressed that distance education applications would be appropriate to use, especially in social sciences, theoretical courses, and crowded classrooms in the post-pandemic period. However, using distance education in math, sciences, and engineering may be inconvenient and create an inequality of opportunity. Academicians also stated that they experienced technical issues during the distance education process, open-to-abuse exams, low participation in classes, and problems in accessing education for students. They emphasized that encountering cases of cheating and plagiarism regarding the measurement and evaluation processes is an important deficiency. Furthermore, academicians made suggestions regarding distance education applications such as maintaining the hybrid teaching model, examining the practices of leading universities, introducing a new model, integrating virtual classroom applications into the process, or introducing existing interactive systems into the system.

2023 Eğitim Vizyonu doğrultusunda Antalya İl Millî Eğitim Müdürlüğü tarafından 2018-2019 eğitim-öğretim yılı bahar döneminde “Okul 2023” projesi uygulamaya konulmuştur. Bu araştırmanın amacı Okul 2023 projesini okul müdürlerinin görüşleri doğrultusunda incelemektir. Araştırma, nitel araştırma yöntemlerinden durum çalışması modeliyle yürütülmüştür. Araştırmanın çalışma grubunu Okul 2023 projesine dâhil olan 14 okulda görev yapan okul müdürleri oluşturmaktadır. Üç okulda ilk ve ortaokul müdürü aynı olduğu için araştırma kapsamında 11 okul müdürü ile görüşmeler gerçekleştirilmiştir. Araştırma kapsamında veri toplama aracı olarak araştırmacılar tarafından hazırlanan yarı yapılandırılmış görüşme formu kullanılmıştır. Her biri yaklaşık 25 dakika süren görüşmeler, ses kayıt cihazıyla kayıt altına alınmıştır. Toplanan veriler yazıya aktarıldıktan sonra içerik analizi tekniği ile çözümlenmiştir. Analizden elde edilen bulgular tema, alt tema ve kod şeklinde gruplandırılmıştır. Araştırma kapsamında elde edilen bulgular incelendiğinde projenin, uygulandığı okullara ve paydaşlarına etkilerinin olduğu ve okulun atmosferini değiştirdiği görülmüştür. Projeyle ilgili okul müdürlerinin görüşlerinin incelenmesi sonucunda projenin genel olarak başarılı olduğu ve uygulanmasının projenin paydaşlarına katkı sağlayacağı düşünülmektedir. Özellikle bireylerin kendilerini tanımalarına ve geliştirmelerine imkân tanıması ve okulu sevilen bir mekân haline getirmesi nedeniyle proje önemli görülmektedir.