Nursing Students' Attitudes Toward Technology: Multicenter Cross-Sectional Study.

BACKGROUND: The growing presence of digital technologies in health care requires the health workforce to have proficiency in subjects such as informatics. This has implications in the education of nursing students, as their preparedness to use these technologies in clinical situations is something that course administrators need to consider. Thus, students' attitudes toward technology could be investigated to assess their needs regarding this proficiency. OBJECTIVE: This study aims to investigate attitudes (enthusiasm and anxiety) toward technology among nursing students and to identify factors associated with those attitudes. METHODS: Nursing students at 2 universities in Sweden and 1 university in Poland were invited to answer a questionnaire. Data about attitudes (anxiety and enthusiasm) toward technology, eHealth literacy, electronic device skills, and frequency of using electronic devices and sociodemographic data were collected. Descriptive statistics were used to characterize the data. The Spearman rank correlation coefficient and Mann-Whitney U test were used for statistical inferences. RESULTS: In total, 646 students answered the questionnaire-342 (52.9%) from the Swedish sites and 304 (47.1%) from the Polish site. It was observed that the students' technology enthusiasm (techEnthusiasm) was on the higher end of the Technophilia instrument (score range 1-5): 3.83 (SD 0.90), 3.62 (SD 0.94), and 4.04 (SD 0.78) for the whole sample, Swedish students, and Polish students, respectively. Technology anxiety (techAnxiety) was on the midrange of the Technophilia instrument: 2.48 (SD 0.96), 2.37 (SD 1), and 2.60 (SD 0.89) for the whole sample, Swedish students, and Polish students, respectively. Regarding techEnthusiasm among the nursing students, a negative correlation with age was found for the Swedish sample (P<.001; ρSwedish=-0.201) who were generally older than the Polish sample, and positive correlations with the eHealth Literacy Scale score (P<.001; ρall=0.265; ρSwedish=0.190; ρPolish=0.352) and with the perceived skill in using computer devices (P<.001; ρall=0.360; ρSwedish=0.341; ρPolish=0.309) were found for the Swedish, Polish, and total samples. Regarding techAnxiety among the nursing students, a positive correlation with age was found in the Swedish sample (P<.001; ρSwedish=0.184), and negative correlations with eHealth Literacy Scale score (P<.001; ρall=-0.196; ρSwedish=-0.262; ρPolish=-0.133) and with the perceived skill in using computer devices (P<.001; ρall=-0.209; ρSwedish=-0.347; ρPolish=-0.134) were found for the Swedish, Polish, and total samples and with the semester only for the Swedish sample (P<.001; ρSwedish=-0.124). Gender differences were found regarding techAnxiety in the Swedish sample, with women exhibiting a higher mean score than men (2.451, SD 1.014 and 1.987, SD 0.854, respectively). CONCLUSIONS: This study highlights nursing students' techEnthusiasm and techAnxiety, emphasizing correlations with various factors. With health care's increasing reliance on technology, integrating health technology-related topics into education is crucial for future professionals to address health care challenges effectively. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14643.

Five-factor model, technology enthusiasm and technology anxiety.

Older adults need to participate in the digital society, as societal and personal changes and what they do with the remaining time that they have in their older years has an undeniable effect on motivation, cognition and emotion. Changes in personality traits were investigated in older adults over the period 2019-2021. Technology enthusiasm and technology anxiety are attitudes that affect the relationship to the technology used. The changes in the score of technology enthusiasm and technology anxiety were the dependent variables. They were investigated with personality traits, age, gender, education, whether someone lives alone, cognitive function, digital social participation (DSP) and health literacy as predictors of the outcome. The Edwards-Nunnally index and logistic regression were used. The results indicated that DSP, lower age, lower neuroticism and higher education were indicative of less technology anxiety. High DSP and high extraversion are indicative of technology enthusiasm. DSP and attitude towards technology seem to be key in getting older adults to stay active online.

Masking ability of resin composites: Effect of the layering strategy and substrate color.

OBJECTIVE: To evaluate the effect of layering strategy and substrate color on the masking ability of resin composites. MATERIALS AND METHODS: A1-shaded specimens from Charisma Diamond and Filtek Z350XT were produced using different layering strategies. Color measurements were made by a reflectance spectrophotometer over A2, C2, A3.5, C3, C4 substrates. Color differences were calculated and interpreted by the 50%:50% perceptibility and acceptability visual thresholds. Data was analyzed by Kruskal-Wallis and Dunn post hoc test. Chi-square test was used to determine the association between masking ability, and independent variables. RESULTS: Color differences were significantly lower on A2 and C2 in comparison with C4 for the majority of the layering strategies. Acceptable matches were observed on most of the combinations over A2. Moderately unacceptable mismatches were observed in most of the combinations over C2 and A3.5. Clearly unacceptable mismatches were observed on the C3 and C4. The ΔE00 color shifts were predominantly influenced by ΔL00 for all layering strategies and substrate colors. CONCLUSION: Masking ability was affected by the layering strategy and substrate color. Acceptable masking was associated with A2 and C2, and with layering strategy composed of 0.5 mm enamel opacity and 1.0 mm dentin opacity thicknesses, using the Filtek Z350XT. CLINICAL SIGNIFICANCE: Resin composites-shade A1-applied by different layering strategies with a final thickness of 1.5 mm were able to mask mild and moderately discolored substrates. Severely discolored substrates were not masked effectively.

Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack.

This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high probability of detection and low false alarm rate. The predictions are based on image stacks, which are composed of images from the same scene acquired at different instants with the same flight geometry. The considered methods for obtaining the ground scene prediction include (i) autoregressive models; (ii) trimmed mean; (iii) median; (iv) intensity mean; and (v) mean. It is expected that the predicted image presents the true ground scene without change and preserves the ground backscattering pattern. The study indicates that the the median method provided the most accurate representation of the true ground. To show the applicability of the GSP, a change detection algorithm was considered using the median ground scene as a reference image. As a result, the median method displayed the probability of detection of 97 % and a false alarm rate of 0 . 11 / km 2 , when considering military vehicles concealed in a forest.