270 resultados para Validation par connaissance expert
Resumo:
The Flinders Decision Making Questionnaire (DMQ; Mann, 1982) was designed to measure decision making coping patterns identified by Janis and Mann (1977). The validity of four DMQ Scales (vigilance, defensive avoidance, hypervigilance, and decision self-esteem) were tested as predictors of students' course and career decision making. Students administered the DMQ scales were also measured on independence of choice, satisfaction, and planfulness relating to their university course and on planfulness and options relating to their future employment. Two samples were studied. In study 1, 40 students residing in a university college were the subjects. In Study 2, 42 second-year students who completed the DMQ one year earlier constituted the subjects. Modest but significant correlations were found in both samples between DMQ scores and measures of course and career decision making. The findings lend support to the validity of the DMQ as an instrument for measuring decision making behaviour.
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The generic IS-success constructs first identified by DeLone and McLean (1992) continue to be widely employed in research. Yet, recent work by Petter et al (2007) has cast doubt on the validity of many mainstream constructs employed in IS research over the past 3 decades; critiquing the almost universal conceptualization and validation of these constructs as reflective when in many studies the measures appear to have been implicitly operationalized as formative. Cited examples of proper specification of the Delone and McLean constructs are few, particularly in light of their extensive employment in IS research. This paper introduces a four-stage formative construct development framework: Conceive > Operationalize > Respond > Validate (CORV). Employing the CORV framework in an archival analysis of research published in top outlets 1985-2007, the paper explores the extent of possible problems with past IS research due to potential misspecification of the four application-related success dimensions: Individual-Impact, Organizational-Impact, System-Quality and Information-Quality. Results suggest major concerns where there is a mismatch of the Respond and Validate stages. A general dearth of attention to the Operationalize and Respond stages in methodological writings is also observed.
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Background: The reasons that a patient has to start treatment, their “Cues to Action”, are important for determining subsequent health behaviours. Cues to action are an explicit component of the Health Belief Model of CPAP acceptance adherence. At present there is no scale available to measure this construct for individuals with Obstructive Sleep Apnoea (OSA). This paper aims to develop, validate and describe responding patterns within an OSA patient sample to the Cues to CPAP Use Questionnaire (CCUQ).----- Method: Participants were 63 adult patients diagnosed with OSA who had never tried CPAP when initially recruited. The CCUQ was completed at one month after being prescribed CPAP.----- Results: Exploratory factor analysis (EFA) showed a three factor structure of the 9-item CCUQ, with “Health Cues”, “Partner Cues” and “Health Professional Cues” subscales accounting for 59.91% of the total variance. The CCUQ demonstrated modest internal consistency and split-half reliability. The questionnaire is brief and user-friendly, with readability at a 7th grade level. The most frequently endorsed cues for starting CPAP were Health Professional Cues (prompting by the sleep physician) and Health Cues such as tiredness and concern about health outcomes.----- Conclusions: This study validates a measure of an important motivational component of the Health Belief Model. Health Professional Cues and internal Health Cues were reported to be the most important prompts to commence CPAP by this patient sample.
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It is important to detect and treat malnutrition in hospital patients so as to improve clinical outcome and reduce hospital stay. The aim of this study was to develop and validate a nutrition screening tool with a simple and quick scoring system for acute hospital patients in Singapore. In this study, 818 newly admitted patients aged above 18 years old were screened using five parameters that contribute to the risk of malnutrition. A dietitian blinded to the nutrition screening score assessed the same patients using the reference standard, Subjective Global Assessment (SGA) within 48 hours. The sensitivity and specificity were established using the Receiver Operator Characteristics (ROC) curve and the best cutoff scores determined. The nutrition parameter with the largest Area Under the ROC Curve (AUC) was chosen as the final screening tool, which was named 3-Minute Nutrition Screening (3-MinNS). The combination of the parameters weight loss, intake and muscle wastage (3-MinNS), gave the largest AUC when compared with SGA. Using 3-MinNS, the best cutoff point to identify malnourished patients is three (sensitivity 86%, specificity 83%). The cutoff score to identify subjects at risk of severe malnutrition is five (sensitivity 93%, specificity 86%). 3-Minute Nutrition Screening is a valid, simple and rapid tool to identify patients at risk of malnutrition in Singapore acute hospital patients. It is able to differentiate patients at risk of moderate malnutrition and severe malnutrition for prioritization and management purposes.
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BACKGROUND: The Edinburgh Postnatal Depression Scale (EPDS) has been validated and used extensively in screening for depression in new mothers, both in English speaking and non-English speaking communities. While some studies have reported the use of the EPDS with fathers, none have validated it for this group, and thus the appropriate cut-off score for screening for depression or anxiety caseness for this population is not known. METHODS: Couples were recruited antenatally and interviewed at six weeks postpartum. EPDS scores and distress caseness (depression or anxiety disorders) for 208 fathers and 230 mothers were determined using the Diagnostic Interview Schedule. RESULTS: Analyses of the EPDS for fathers using distress caseness (depression or anxiety disorders) as the criterion shows that a cut-off of 5/6 has optimum receiver operating characteristics. Furthermore acceptable reliability (split-half and internal consistency) and validity (concurrent) coefficients were obtained. For mothers the optimum cut-off screening value to detect distress caseness was 7/8. Item analysis revealed that fathers endorsed seven of the ten items at lower rates to mothers, with the most significant being that referring to crying. CONCLUSIONS: The EPDS is a reliable and valid measure of mood in fathers. Screening for depression or anxiety disorders in fathers requires a two point lower cut-off than screening for depression or anxiety in mothers, and we recommend this cut-off to be 5/6
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Preterm infants have an increased risk of low bone mass and subsequent fracture due to limited bone mass accretion in utero and a greater need for bone nutrients. The diagnosis of ostepeonia of prematurity remains difficult as there is no sctreening test which is both sensitive and specific.
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1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.
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Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.
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A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set. The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone.
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The two outcome indices described in a companion paper (Sanson et al., Child Indicators Research, 2009) were developed using data from the Longitudinal Study of Australian Children (LSAC). These indices, one for infants and the other for 4 year to 5 year old children, were designed to fill the need for parsimonious measures of children’s developmental status to be used in analyses by a broad range of data users and to guide government policy and interventions to support young children’s optimal development. This paper presents evidence from Wave 1data from LSAC to support the validity of these indices and their three domain scores of Physical, Social/Emotional, and Learning. Relationships between the indices and child, maternal, family, and neighborhood factors which are known to relate concurrently to child outcomes were examined. Meaningful associations were found with the selected variables, thereby demonstrating the usefulness of the outcome indices as tools for understanding children’s development in their family and socio-cultural contexts. It is concluded that the outcome indices are valuable tools for increasing understanding of influences on children’s development, and for guiding policy and practice to optimize children’s life chances.
Resumo:
The Longitudinal Study of Australian Children (LSAC) is a major national study examining the lives of Australian children, using a cross-sequential cohort design and data from parents, children, and teachers for 5,107 infants (3–19 months) and 4,983 children (4–5 years). Its data are publicly accessible and are used by researchers from many disciplinary backgrounds. It contains multiple measures of children’s developmental outcomes as well as a broad range of information on the contexts of their lives. This paper reports on the development of summary outcome indices of child development using the LSAC data. The indices were developed to fill the need for indicators suitable for use by diverse data users in order to guide government policy and interventions which support young children’s optimal development. The concepts underpinning the indices and the methods of their development are presented. Two outcome indices (infant and child) were developed, each consisting of three domains—health and physical development, social and emotional functioning, and learning competency. A total of 16 measures are used to make up these three domains in the Outcome Index for the Child Cohort and six measures for the Infant Cohort. These measures are described and evidence supporting the structure of the domains and their underlying latent constructs is provided for both cohorts. The factorial structure of the Outcome Index is adequate for both cohorts, but was stronger for the child than infant cohort. It is concluded that the LSAC Outcome Index is a parsimonious measure representing the major components of development which is suitable for non-specialist data users. A companion paper (Sanson et al. 2010) presents evidence of the validity of the Index.
Resumo:
The present study used a university sample to assess the test-retest reliability and validity of the Australian Propensity for Angry Driving Scale (Aus-PADS). The scale has stability over time, and convergent validity was established, as Aus-PADS scores correlated significantly with established anger and impulsivity measures. Discriminant validity was also established, as Aus-PADS scores did not correlate with Venturesomeness scores. The Aus-PADS has demonstrated criterion validity, as scores were correlated with behavioural measures, such as yelling at other drivers, gesturing at other drivers, and feeling angry but not doing anything. Aus-PADS scores reliably predicted the frequency of these behaviours over and above other study variables. No significant relationship between aggressive driving and crash involvement was observed. It was concluded that the Aus-PADS is a reliable and valid tool appropriate for use in Australian research, and that the potential relationship between aggressive driving and crash involvement warrants further investigation with a more representative (and diverse) driver sample.