Ansiedad Futura en Adultos Jóvenes Españoles : Propiedades Psicométricas de la Dark Future Scale

Background/Objective:The Dark Future Scale (DFS) is a selfreport instrument which assesses the tendency to think about the future with anxiety, fear, and uncertainty. Although it has been applied in different populations, instrumental studies are scarce, and there is no validated Spanish version. The aim was therefore to develop a Spanish version of the scale (DFS-S) and to analyze its psychometric properties in a sample of young adults. Method:Participants were 1,019 individuals aged from 18 to 24 years. They completed the DFS-S and the IPIP-BFM-20. Validity evidence based on the internal structure, including measurement invariance across gender, as well as on relationships with personality traits was obtained. Reliability and gender differences in DFS-S scores were also examined. Results:Results supported a single-factor structure, χ2(5) = 10.79, CFI = .999, RMSEA = .034, SRMR = .016, that was invariant across gender. Reliability of test scores was satisfactory (ω= .92). In the correlation analysis, future anxiety showed a strong positive correlation with neuroticism (.42) and a moderate negative correlation with extraversion (-.25). Females scored higher than males on future anxiety. Conclusions:The DFS-S has sat-isfactory psychometric properties and it is an adequate tool for measuring future anxiety among young adults.Antecedentes/Objetivo: La Dark Future Scale (DFS) evalúa la tendencia a pensar en el futuro con ansiedad, miedo e incertidumbre. Aunque ha sido usada en diferentes poblaciones, los estudios instrumentales son es-casos y no hay una versión adaptada al español. El objetivo del estudio fue adaptarla al español (DFS-S) y analizar sus propiedades psicométricas en una muestra de adultos jóvenes. Método: Participaron 1.019 jóvenes entre 18 y 24 años. Completaron la DFS-S y el IPIP-BFM-20. Se analizan evidencias de validez basadas en la estructura interna, incluyendo la invarianza de medida según el género, y basadas en las relaciones con rasgos de personalidad, así como análisis de la fiabilidad y de las diferencias de género. Resultados: Los resultados apoyaron una estructura de un solo factor, χ2(5) = 10.79, CFI = .999, RMSEA = .034, SRMR = .016, con invarianza respecto al género, y con coeficiente de fiabilidad satisfactorio (ω= .92). Se encontró correlación positiva fuerte entre ansiedad futura y neuroticismo (.42) y una correlación negativa moderada con extraversión (-.25). Las puntuaciones en ansiedad futura fueron mayores en las mujeres. Conclusiones: Los resultados muestran propiedades psicométricas satisfactorias de la DFS-S, siendo un instrumento adecuado para medir la ansiedad futura en adultos jóvenes

Life satisfaction and the mediating role of character strengths and gains in informal caregivers

Introduction: Being an informal caregiver can have both negative and positive consequences for well-being. Within the framework of he stress process model, few studies have examined values and perceived gains of caregiving as mediating variables of life satisfaction. Aim: To explore the role of character strengths and perceived gains as mediators in the association between life satisfaction and primary and secondary stressors in informal caregivers of persons with dementia. Method: Participants were 112 informal caregivers. Hierarchical regression, correlation and mediation analyses were performed. Results: Lower life satisfaction was associated with being female, unmarried, caring for someone with greater cognitive impairment, a higher level of stress, having restricted leisure time and perceiving financial difficulties. Hope mediated the associations between perceived stress and both life satisfaction and perceived gains of caregiving. Discussion: Hope is a key strength and its lack is one pathway through which stress may cause low satisfaction and low perceived gains from caregiving. Implications for practice: Without hope, it is difficult for caregivers to generate goals and be motivated to achieve them. Nursing and care staff should aim to promote a sense of purpose and achievement among informal caregivers so as to foster a more positive caring experience

The Phubbing Scale (PS-8) in the Portuguese population: psychometric properties

Phubbing is defined as ignoring other individuals by using a mobile phone during a face-to-face conversation. The Phubbing Scale (PS) was developed to assess this practice. In this study, we analyze the psychometric properties of the 8-item version of the PS (PS-8) in the Portuguese population, providing validity evidence based on internal structure and on relationships with other variables, and examining item properties, reliability, and measurement invariance across gender. Participants were 391 Portuguese adults (132 men, 259 women) who completed a battery of questionnaires. Confirmatory factor analysis yielded satisfactory goodness-of-fit indices for the two-factor structure (communication disturbance and phone obsession), which was invariant across gender. Item homogeneity and reliability of factor scores (McDonald’s omega) were satisfactory. Validity evidence based on relationships with other variables was provided by positive associations with time spent on the Internet on weekdays and at the weekend, time spent on social networking sites, number of social networks used, Internet addiction, problematic mobile phone use, Facebook intrusion, fear of missing out, and depression. These associations show the addictive component of phubbing and its relationship with mental health. The PS-8 is a short and easy-to-administer scale with adequate psychometric properties for measuring phubbing in the Portuguese population.info:eu-repo/semantics/publishedVersio

Antibiotic Prophylactic Regimens for Infective Endocarditis in Patients Undergoing Dental Procedures

Up to date causal relationship has been demonstrated between dental manipulations and the onset of infective endocarditis (IE). However, since 1955, numerous expert committees have proposed antibiotic prophylaxis (AP) to prevent bacteraemia of oral origin. Controversy regarding the efficacy of AP prior to the dental procedures has intensified in recent years because of the lack of conclusive evidence on its efficacy for the prevention of IE and on its cost-effectiveness, as well as the possibility of allergic reactions and the emergence of antibiotic resistance. Accordingly, AP is now maintained exclusively for patients at highest risk and who require the manipulation of the gingival or periapical regions of the teeth or perforation of the oral mucosa. In the context of a restrictive policy, the National Institute for Health and Clinical Excellence (NICE) of the United Kingdom published a new guideline in 2008 stating that “AP against IE is not recommended for persons undergoing dental procedures”, regardless of risk status and of the nature of the procedure to be performed. The NICE guideline has generated further controversy, and expert committees in other countries continue to publish prophylactic regimens for the prevention of IE secondary to dental procedures. In this chapter, we discuss the principal guidelines currently applicable in Europe, the USA and Australia, and we draw particular attention to the need for randomised clinical trials

Current sensorless power factor correction based on digital current rebuilding

A new digital control technique for power factor correction is presented. The main novelty of the method is that there is no current sensor. Instead, the input current is digitally rebuilt, using the estimated input current for the current loop. Apart from that, the ADCs used for the acquisition of the input and output voltages have been designed ad-hoc. Taking advantage of the slow dynamic behavior of these voltages, almost completely digital ADCs have been designed, leaving only a comparator and an RC filter in the analog part. The final objective is obtaining a low cost digital controller which can be easily integrated in an ASIC along with the controller of paralleled and subsequent power section

Robustness of Generalized Linear Mixed Models for Split-Plot Designs with Binary Data.

This paper examined the robustness of the generalized linear mixed model (GLMM). The GLMM estimates fixed and random effects, and it is especially useful when the dependent variable is binary. It is also useful when the dependent variable involves repeated measures, since it can model correlation. The present study used Monte Carlo simulation to analyze the empirical Type I error rates of GLMMs in split-plot designs. The variables manipulated were sample size, group size, number of repeat-ed measures, and correlation between repeated measures. Extreme condi-tions were also considered, including small samples, unbalanced groups, and different correlation in each group (pairing between group size and correlation between repeated measures). For balanced groups, the results showed that the group effect was robust under all conditions, while for unbalanced groups the effect tended to be conservative with positive pair-ing and liberal with negative pairing. Regarding time and interaction ef-fects, the results showed, for both balanced and unbalanced groups, that: (a) The test was robust with low correlation (.2), but conservative for me-dium values of correlation (.4 and .6), and (b) the test tended to be con-servative for positive and negative pairing, especially the latter.Our work was funded by the grants PSI2016-78737-P and PID2020-113191GB-I00 (AEI/FEDER, UE) from the Spanish Ministry of Economy, Industry and Competitiveness, and the Spanish Ministry of Science and Innovation

Datos no Normales en el ANOVA de Medidas Repetidas: Impacto en el Error Tipo I y Potencia

Background: Repeated measures designs are commonly used in health and social sciences research. Although there are other, more advanced, statistical analyses, the F-statistic of repeated measures analysis of variance (RM-ANOVA) remains the most widely used procedure for analyzing differences in means. The impact of the violation of normality has been extensively studied for between-subjects ANOVA, but this is not the case for RM-ANOVA. Therefore, studies that extensively and systematically analyze the robustness of RM-ANOVA under the violation of normality are needed. This paper reports the results of two simulation studies aimed at analyzing the Type I error and power of RM-ANOVA when the normality assumption is violated but sphericity is fulfilled. Method: Study 1 considered 20 distributions, both known and unknown, and we manipulated the number of repeated measures (3, 4, 6, and 8) and sample size (from 10 to 300). Study 2 involved unequal distributions in each repeated measure. The distributions analyzed represent slight, moderate, and severe deviation from normality. Results: Overall, the results show that the Type I error and power of the F-statistic are not altered by the violation of normality. Conclusions: RM-ANOVA is generally robust to non-normality when the sphericity assumption is met

Robustez de los Modelos Lineales Mixtos Generalizados para Diseños Split-Plot con Datos Binarios

This paper examined the robustness of the generalized linear mixed model (GLMM). The GLMM estimates fixed and random effects, and it is especially useful when the dependent variable is binary. It is also useful when the dependent variable involves repeated measures, since it can model correlation. The present study used Monte Carlo simulation to analyze the empirical Type I error rates of GLMMs in split-plot designs. The variables manipulated were sample size, group size, number of repeated measures, and correlation between repeated measures. Extreme conditions were also considered, including small samples, unbalanced groups, and different correlation in each group (pairing between group size and correlation between repeated measures). For balanced groups, the results showed that the group effect was robust under all conditions, while for unbalanced groups the effect tended to be conservative with positive pairing and liberal with negative pairing. Regarding time and interaction effects, the results showed, for both balanced and unbalanced groups, that: (a) The test was robust with low correlation (.2), but conservative for medium values of correlation (.4 and .6), and (b) the test tended to be conservative for positive and negative pairing, especially the latter

Repeated Measures ANOVA and adjusted F-tests when sphericity is violated: Which procedure is best?

Introduction: One-way repeated measures ANOVA requires sphericity. Research indicates that violation of this assumption has an important impact on Type I error. Although more advanced alternative procedures exist, most classical texts recommend the use of adjusted F-tests, which are frequently employed because they are intuitive, easy to apply, and available in most statistical software. Adjusted F-tests differ in the procedure used to estimate the corrective factor ε, the most common being the Greenhouse-Geisser (F-GG) and Huynh-Feldt (F-HF) adjustments. Although numerous studies have analyzed the robustness of these procedures, the results are inconsistent, thus highlighting the need for further research. Methods: The aim of this simulation study was to analyze the performance of the Fstatistic, F-GG, and F-HF in terms of Type I error and power in one-way designs with normal data under a variety of conditions that may be encountered in real research practice. Values of ε were fixed according to the Greenhouse–Geisser procedure (ε). We manipulated the number of repeated measures (3, 4, and 6) and sample size (from 10 to 300), with ε values ranging from the lower to its upper limit. Results: Overall, the results showed that the F-statistic becomes more liberal as sphericity violation increases, whereas both F-HF and F-GG control Type I error; of the two, F-GG is more conservative, especially with large values of ε and small samples. Discussion: If different statistical conclusions follow from application of the two tests, we recommend using F-GG for ε values below 0.60, and F-HF for ε values equal to or above 0.60

Repeated measures ANOVA and adjusted F-tests when sphericity is violated: which procedure is best?

Introduction: One-way repeated measures ANOVA requires sphericity. Research indicates that violation of this assumption has an important impact on Type I error. Although more advanced alternative procedures exist, most classical texts recommend the use of adjusted F-tests, which are frequently employed because they are intuitive, easy to apply, and available in most statistical software. Adjusted F-tests differ in the procedure used to estimate the corrective factor ε, the most common being the Greenhouse-Geisser (F-GG) and Huynh-Feldt (F-HF) adjustments. Although numerous studies have analyzed the robustness of these procedures, the results are inconsistent, thus highlighting the need for further research. Methods: The aim of this simulation study was to analyze the performance of the F-statistic, F-GG, and F-HF in terms of Type I error and power in one-way designs with normal data under a variety of conditions that may be encountered in real research practice. Values of ε were fixed according to the Greenhouse–Geisser procedure (εˆ). We manipulated the number of repeated measures (3, 4, and 6) and sample size (from 10 to 300), with εˆ values ranging from the lower to its upper limit. Results: Overall, the results showed that the F-statistic becomes more liberal as sphericity violation increases, whereas both F-HF and F-GG control Type I error; of the two, F-GG is more conservative, especially with large values of εˆ and small samples. Discussion: If different statistical conclusions follow from application of the two tests, we recommend using F-GG for εˆ values below 0.60, and F-HF for εˆ values equal to or above 0.60.This research was supported by University of Malaga and grant PID2020-113191GB-I00 from the MCIN/AEI/10.13039/50110001103