871 resultados para Five Factor Model


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Background: Spirituality is fundamental to all human beings, existing within a person, and developing until death. This research sought to operationalise spirituality in a sample of individuals with chronic illness. A review of the conceptual literature identified three dimensions of spirituality: connectedness, transcendence, and meaning in life. A review of the empirical literature identified one instrument that measures the three dimensions together. Yet, recent appraisals of this instrument highlighted issues with item formulation and limited evidence of reliability and validity. Aim: The aim of this research was to develop a theoretically-grounded instrument to measure spirituality – the Spirituality Instrument-27 (SpI-27). A secondary aim was to psychometrically evaluate this instrument in a sample of individuals with chronic illness (n=249). Methods: A two-phase design was adopted. Phase one consisted of the development of the SpI-27 based on item generation from a concept analysis, a literature review, and an instrument appraisal. The second phase established the psychometric properties of the instrument and included: a qualitative descriptive design to establish content validity; a pilot study to evaluate the mode of administration; and a descriptive correlational design to assess the instrument’s reliability and validity. Data were analysed using SPSS (Version 18). Results: Results of exploratory factor analysis concluded a final five-factor solution with 27 items. These five factors were labelled: Connectedness with Others, Self-Transcendence, Self-Cognisance, Conservationism, and Connectedness with a Higher Power. Cronbach’s alpha coefficients ranged from 0.823 to 0.911 for the five factors, and 0.904 for the overall scale, indicating high internal consistency. Paired-sample t-tests, intra-class correlations, and weighted kappa values supported the temporal stability of the instrument over 2 weeks. A significant positive correlation was found between the SpI-27 and the Spirituality Index of Well-Being, providing evidence for convergent validity. Conclusion: This research addresses a call for a theoretically-grounded instrument to measure spirituality.

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This study investigates whether higher input use per stay in the hospital (treatment intensity) and longer length of stay improve outcomes of care. We allow for endogeneity of intensity and length of stay by estimating a quasi-maximum-likelihood discrete factor model, where the distribution of the unmeasured variable is modeled using a discrete distribution. Data on elderly persons come from several waves of the National Long-Term Care Survey merged with Medicare claims data for 1984-1995 and the National Death Index. We find that higher intensity improves patient survival and some dimensions of functional status among those who survive.

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Externalizing behavior problems of 124 adolescents were assessed across Grades 7-11. In Grade 9, participants were also assessed across social-cognitive domains after imagining themselves as the object of provocations portrayed in six videotaped vignettes. Participants responded to vignette-based questions representing multiple processes of the response decision step of social information processing. Phase 1 of our investigation supported a two-factor model of the response evaluation process of response decision (response valuation and outcome expectancy). Phase 2 showed significant relations between the set of these response decision processes, as well as response selection, measured in Grade 9 and (a) externalizing behavior in Grade 9 and (b) externalizing behavior in Grades 10-11, even after controlling externalizing behavior in Grades 7-8. These findings suggest that on-line behavioral judgments about aggression play a crucial role in the maintenance and growth of aggressive response tendencies in adolescence.

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Background— Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study.
Methods and Results— Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008).
Conclusions— The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.

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Stochastic modeling of mortality rates focuses on fitting linear models to logarithmically adjusted mortality data from the middle or late ages. Whilst this modeling enables insurers to project mortality rates and hence price mortality products it does not provide good fit for younger aged mortality. Mortality rates below the early 20's are important to model as they give an insight into estimates of the cohort effect for more recent years of birth. It is also important given the cumulative nature of life expectancy to be able to forecast mortality improvements at all ages. When we attempt to fit existing models to a wider age range, 5-89, rather than 20-89 or 50-89, their weaknesses are revealed as the results are not satisfactory. The linear innovations in existing models are not flexible enough to capture the non-linear profile of mortality rates that we see at the lower ages. In this paper we modify an existing 4 factor model of mortality to enable better fitting to a wider age range, and using data from seven developed countries our empirical results show that the proposed model has a better fit to the actual data, is robust, and has good forecasting ability.

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A functional polymorphism (Val-158-Met) at the Catechol-O-methyltransferase (COMT) locus has been identified as a potential etiological factor in schizophrenia. Yet the association has not been convincingly replicated across independent samples. We hypothesized that phenotypic heterogeneity might be diluting the COMT effect. To clarify the putative association, we performed an exploratory analysis to test for association between COMT and five psychosis symptom scales. These were derived through factor analysis of the Operational Criteria Checklist for Psychiatric Illness. Our sample was the Irish Study of High Density Schizophrenia Families, a large collection consisting of 268 multiplex families. This sample has previously shown a small but significant effect of the COMT Val allele in conferring risk for schizophrenia. We tested for preferential transmission of COMT alleles from parent to affected offspring (n = 749) for each of the five factor-derived scales (negative symptoms, delusions, hallucinations, mania, and depression). Significant overtransmission of the Val allele was found for mania (P <0.05) and depression (P = 0.01) scales. Examination of odds ratios (ORs) revealed a heterogeneous effect of COMT, whereby it had no effect on Negative Symptoms, but largest impact on Depression (OR = 1.4). These results suggest a modest affective vulnerability conferred by this allele in psychosis, but will require replication.

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Objective: The aim of this study was to investigate the effect of pre-treatment verification imaging with megavoltage (MV) X-rays on cancer and normal cell survival in vitro and to compare the findings with theoretically modelled data. Since the dose received from pre-treatment imaging can be significant, incorporation of this dose at the planning stage of treatment has been suggested.

Methods: The impact of imaging dose incorporation on cell survival was investigated by clonogenic assay, irradiating DU-145 prostate cancer, H460 non-small cell lung cancer and AGO-1522b normal tissue fibroblast cells. Clinically relevant imaging-to-treatment times of 7.5 minutes and 15 minutes were chosen for this study. The theoretical magnitude of the loss of radiobiological efficacy due to sublethal damage repair was investigated using the Lea-Catcheside dose protraction factor model.

Results: For the cell lines investigated, the experimental data showed that imaging dose incorporation had no significant impact upon cell survival. These findings were in close agreement with the theoretical results.

Conclusions: For the conditions investigated, the results suggest that allowance for the imaging dose at the planning stage of treatment should not adversely affect treatment efficacy.

Advances in Knowledge: There is a paucity of data in the literature on imaging effects in radiotherapy. This paper presents a systematic study of imaging dose effects on cancer and normal cell survival, providing both theoretical and experimental evidence for clinically relevant imaging doses and imaging-to-treatment times. The data provide a firm foundation for further study into this highly relevant area of research.

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Objective: To simultaneously evaluate 14 biomarkers from distinct biological pathways for risk prediction of ischemic stroke, including biomarkers of hemostasis, inflammation, and endothelial activation as well as chemokines and adipocytokines.
Methods and Results: The Prospective Epidemiological Study on Myocardial Infarction (PRIME) is a cohort of 9771 healthy men 50 to 59 years of age who were followed up over 10 years. In a nested case–control study, 95 ischemic stroke cases were matched with 190 controls. After multivariable adjustment for traditional risk factors, fibrinogen (odds ratio [OR], 1.53; 95% confidence interval [CI], 1.03–2.28), E-selectin (OR, 1.76; 95% CI, 1.06–2.93), interferon-γ-inducible-protein-10 (OR, 1.72; 95% CI, 1.06–2.78), resistin (OR, 2.86; 95% CI, 1.30–6.27), and total adiponectin (OR, 1.82; 95% CI, 1.04–3.19) were significantly associated with ischemic stroke. Adding E-selectin and resistin to a traditional risk factor model significantly increased the area under the receiver-operating characteristic curve from 0.679 (95% CI, 0.612–0.745) to 0.785 and 0.788, respectively, and yielded a categorical net reclassification improvement of 29.9% (P=0.001) and 28.4% (P=0.002), respectively. Their simultaneous inclusion in the traditional risk factor model increased the area under the receiver-operating characteristic curve to 0.824 (95% CI, 0.770–0.877) and resulted in an net reclassification improvement of 41.4% (P<0.001). Results were confirmed when using continuous net reclassification improvement.
Conclusion: Among multiple biomarkers from distinct biological pathways, E-selectin and resistin provided incremental and additive value to traditional risk factors in predicting ischemic stroke.

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A reliable and valid instrument is needed to screen for depression in palliative patients. The interRAI Depression Rating Scale (DRS) is based on seven items in the interRAI Palliative Care instrument. This study is the first to explore the dimensionality, reliability and validity of the DRS in a palliative population. Palliative home care patients (n = 5,175) residing in Ontario (Canada) were assessed with the interRAI Palliative Care instrument. Exploratory factor analysis and Mokken scale analysis were used to identify candidate conceptual models and evaluate scale homogeneity/performance. Confirmatory factor analysis compared models using standard goodness-of-fit indices. Convergent and divergent validity were investigated by examining polychoric correlations between the DRS and other items. The “known groups” test determined if the DRS meaningfully distinguished among client subgroups. The non-hierarchical two factor model showed acceptable fit with the data, and ordinal alpha coefficients of 0.83 and 0.82 were observed for the two DRS subscales. Omega hierarchical (ωh) was 0.78 for the bifactor model, with the general factor explaining three quarters of the common variance. Despite the multidimensionality evident in the factor analyses, bifactor modelling and the Mokken homogeneity coefficient (0.34) suggest that the DRS is a coherent scale that captures important information on sub-constructs of depression (e.g., somatic symptoms). Higher correlations were seen between the DRS and mood and psychosocial well-being items, and lower correlations with functional status and demographic variables. The DRS distinguished in the expected manner for known risk factors (e.g., social support, pain). The results suggest that the DRS is primarily unidimensional and reliable for use in screening for depression in palliative care patients.

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The purpose of this paper is to conceptualise and operationalise the concept of supply chain management sustainability practices. Based on a multi-stage procedure involving a literature review, expert Q-sort and pre-test process, pilot test and survey of 156 supply chain directors and managers in Ireland, we develop a multidimensional conceptualisation and measure of social and environmental supply chain management sustainability practices. The research findings show theoretically sound constructs based on four underlying sustainable supply chain management practices: monitoring, implementing systems, new product and process development and strategy redefinition. A two-factor model is then identified as the most reliable: comprising process-based and market-based practices.

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Permafrost peatlands contain globally important amounts of soil organic carbon, owing to cold conditions which suppress anaerobic decomposition. However, climate warming and permafrost thaw threaten the stability of this carbon store. The ultimate fate of permafrost peatlands and their carbon stores is unclear because of complex feedbacks between peat accumulation, hydrology and vegetation. Field monitoring campaigns only span the last few decades and therefore provide an incomplete picture of permafrost peatland response to recent rapid warming. Here we use a high-resolution palaeoecological approach to understand the longer-term response of peatlands in contrasting states of permafrost degradation to recent rapid warming. At all sites we identify a drying trend until the late-twentieth century; however, two sites subsequently experienced a rapid shift to wetter conditions as permafrost thawed in response to climatic warming, culminating in collapse of the peat domes. Commonalities between study sites lead us to propose a five-phase model for permafrost peatland response to climatic warming. This model suggests a shared ecohydrological trajectory towards a common end point: inundated Arctic fen. Although carbon accumulation is rapid in such sites, saturated soil conditions are likely to cause elevated methane emissions that have implications for climate-feedback mechanisms.

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There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.

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The contemporary literature investigating the construct broadly known as time perspective is replete with methodological and conceptual concerns. These concerns focus on the reliability and factorial validity of measurement tools, and the sample-specific modification of scales. These issues continue to hamper the development of this potentially useful psychological construct. An emerging body of evidence has supported the six-factor structure of scores on the Adolescent Time Inventory-Time Attitudes Scale, as well as their reliability. The present study utilized data from the first wave of a longitudinal study in the United Kingdom to examine the reliability, validity, and cross-cultural invariance of the scale. Results showed that the hypothesized six-factor model provided the best fit for the data; all alpha and omega estimates were >. .70; scores on ATI-TA factors related meaningfully to self-efficacy scores; and the factor structure was invariant across both research sites. Results are discussed in the context of the extant temporal literature.

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O mercado imobiliário tem um papel importante nas economias modernas, tanto a nível macro como a nível micro. Ao nível macro, a construção de habitação representa um sector importante e influente na economia, com efeitos multiplicadores significativos sobre a produção e o emprego. Ao nível micro, uma residência representa o activo mais valioso da maioria dos indivíduos e uma parcela muito relevante da riqueza das famílias. Para estas, o custo e a qualidade das suas habitações influencia directa e indirectamente a sua qualidade de vida. A habitação é por isso mesmo um tema, que avaliado nas suas múltiplas dimensões, se caracteriza por ser bastante complexo, mas também ao mesmo tempo desafiante. De modo a delimitar o objecto de análise do trabalho de investigação, esta tese realça os aspectos de localização e distribuição espacial das habitações urbanas. Será desenvolvido um quadro conceptual e respectiva metodologia para a compreender a estrutura espacial da habitação urbana realçando os três aspectos fundamentais da análise espacial: heterogenidade espacial, dependência espacial e escala espacial. A metodologia, aplicada à área urbana de Aveiro e Ílhavo é baseada numa análise hedónica factorial de preços e na noção não geométrica do espaço. Primeiro, é fixada uma escala territorial e são definidos submercados habitacional. Posteriormente, quer a heterogeneidade quer a dependência espaciais são estudados utilizando métodos econométricos, sem considerar qualquer padrão fixo e conhecido de interações espaciais. Em vez disso, são desenvolvidos novos métodos,tendo como base o modelo hedónico factorial, para inferir sobre os potenciais drivers de difusão espacial no valor de uma habitação. Este modelo, foi aplicado a duas diferentes escalas espaciais, para compreender as preferências dos indivíduos em Aveiro ao escolher os seus locais de residencia, e como estas afectam os preços da habitação. O trabalho empírico, utilizando duas bases de dados de habitação distintas, aplicadas ao mercado de habitação de Aveiro mostram: i) em linha com a literatura, a dificuldade de definir submercados e compreender as inter-relações entre esses mercados; ii) a utilidade de uma abordagem híbrida, combinando análise factorial com regressão; iii) a importância fundamental que o efeito escala espacial desempenha no estudo da heterogeneidade e dos spillovers e, finalmente, iv) uma metodologia inovadora para analisar spillovers sem assumir aprioristicamente uma estrutura espacial específica de difusão espacial. Esta metodologia considera a matriz de pesos espaciais (W) desconhecida e estimatima as interações espaciais dentro e entre submercados habitação.