173 research outputs found
MultipleCar: A Graphical User Interface MATLAB Toolbox to Compute Multiple Correspondence Analysis
In this paper we present the toolbox MultipleCar, which was designed using a graphical
user interface, a general program for computing Multiple Correspondence Analysis. The
procedures implemented in MultipleCar are the usual ones that are already available
in other applications, plus some additional procedures. MultipleCar makes it possible
to compute (1) joint correspondence analysis, and (2) orthogonal and oblique rotation
of coordinates. Although MultipleCar was developed in MATLAB, we compiled it as a
standalone application for Windows operative systems based on graphical user interfaces.
The users can decide whether to use the advanced MATLAB version of MultipleCar, or
the standalone version (which does not require any programming skills)
The psychometric characteristics of the revised depression attitude questionnaire (R-DAQ) in Pakistani medical practitioners: a cross-sectional study of doctors in Lahore
BACKGROUND: Depression is common mental health problem and leading contributor to the global burden of disease. The attitudes and beliefs of the public and of health professionals influence social acceptance and affect the esteem and help-seeking of people experiencing mental health problems. The attitudes of clinicians are particularly relevant to their role in accurately recognising and providing appropriate support and management of depression. This study examines the characteristics of the revised depression attitude questionnaire (R-DAQ) with doctors working in healthcare settings in Lahore, Pakistan.
METHODS: A cross-sectional survey was conducted in 2015 using the revised depression attitude questionnaire (R-DAQ). A convenience sample of 700 medical practitioners based in six hospitals in Lahore was approached to participate in the survey. The R-DAQ structure was examined using Parallel Analysis from polychoric correlations. Unweighted least squares analysis (ULSA) was used for factor extraction. Model fit was estimated using goodness-of-fit indices and the root mean square of standardized residuals (RMSR), and internal consistency reliability for the overall scale and subscales was assessed using reliability estimates based on Mislevy and Bock (BILOG 3 Item analysis and test scoring with binary logistic models. Mooresville: Scientific Software, 55) and the McDonald's Omega statistic. Findings using this approach were compared with principal axis factor analysis based on Pearson correlation matrix.
RESULTS: 601 (86%) of the doctors approached consented to participate in the study. Exploratory factor analysis of R-DAQ scale responses demonstrated the same 3-factor structure as in the UK development study, though analyses indicated removal of 7 of the 22 items because of weak loading or poor model fit. The 3 factor solution accounted for 49.8% of the common variance. Scale reliability and internal consistency were adequate: total scale standardised alpha was 0.694; subscale reliability for professional confidence was 0.732, therapeutic optimism/pessimism was 0.638, and generalist perspective was 0.769.
CONCLUSIONS: The R-DAQ was developed with a predominantly UK-based sample of health professionals. This study indicates that this scale functions adequately and provides a valid measure of depression attitudes for medical practitioners in Pakistan, with the same factor structure as in the scale development sample. However, optimal scale function necessitated removal of several items, with a 15-item scale enabling the most parsimonious factor solution for this population
Exploration of experiences in therapeutic groups for patients with severe mental illness: development of the Ferrara group experiences scale (FE-GES)
The study has been supported by the University of Ferrara (University Funds for Scientific Research 2008–2009
Development of an international survey attitude scale: measurement equivalence, reliability, and predictive validity
Declining response rates worldwide have stimulated interest in understanding what may be influencing this decline and how it varies across countries and survey populations. In this paper, we describe the development and validation of a short 9-item survey attitude scale that measures three important constructs, thought by many scholars to be related to decisions to participate in surveys, that is, survey enjoyment, survey value, and survey burden. The survey attitude scale is based on a literature review of earlier work by multiple authors. Our overarching goal with this study is to develop and validate a concise and effective measure of how individuals feel about responding to surveys that can be implemented in surveys and panels to understand the willingness to participate in surveys and improve survey effectiveness. The research questions relate to factor structure, measurement equivalence, reliability, and predictive validity of the survey attitude scale. The data came from three probability-based panels: the German GESIS and PPSM panels and the Dutch LISS panel. The survey attitude scale proved to have a replicable three-dimensional factor structure (survey enjoyment, survey value, and survey burden). Partial scalar measurement equivalence was established across three panels that employed two languages (German and Dutch) and three measurement modes (web, telephone, and paper mail). For all three dimensions of the survey attitude scale, the reliability of the corresponding subscales (enjoyment, value, and burden) was satisfactory. Furthermore, the scales correlated with survey response in the expected directions, indicating predictive validity
Unidimensional scales for fears of cancer recurrence and their psychometric properties : the FCR4 and FCR7
Funding: Support was received from SUPAC (NCRI) Early Career Fund to complete this study. NCRI Supportive & Palliative Care (SuPaC) Research Collaboratives Capacity Building Grant Scheme: G Ozakinci (PI), G Humphris, M Sharpe.Background:Â The assessment of fear of recurrence (FCR) is crucial for understanding an important psychological state in patients diagnosed and treated for cancer. The study aim was to determine psychometric details of a seven question self-report scale (FCR7) and a short form (FCR4) based upon items already used in various extensive measures of FCR. Methods:Â Two consecutive samples of patients (breast and colorectal) were recruited from a single specialist cancer centre. The survey instrument contained the FCR7 items, Hospital Anxiety and Depression Scale (HADS), and demographic details. Clinical information was obtained from patient hospital records. Statistical analyses were performed using classical test and item response theory approaches, to demonstrate unidimensional factor structure and testing key parameters. Construct validity was inspected through nomological and theoretical prediction. Results:Â Internal consistency was demonstrated by alpha coefficients (FCR4: 0.93 and FCR7: 0.92). Both scales (FCR7 & FCR4) were associated with the HADs subscales as predicted. Patients who experienced chemotherapy, minor aches/pains, thought avoidance of cancer and high cancer risk belief were more fearful. Detailed inspection of item responses profile provided some support for measurement properties of scales. Conclusion: The internal consistency, and pattern of key associations and discriminability indices provided positive psychometric evidence for these scales. The brief measures of FCR may be considered for audit, screening or routine use in clinical service and research investigations.Publisher PDFPeer reviewe
A structured overview of simultaneous component based data integration
<p>Abstract</p> <p>Background</p> <p>Data integration is currently one of the main challenges in the biomedical sciences. Often different pieces of information are gathered on the same set of entities (e.g., tissues, culture samples, biomolecules) with the different pieces stemming, for example, from different measurement techniques. This implies that more and more data appear that consist of two or more data arrays that have a shared mode. An integrative analysis of such coupled data should be based on a simultaneous analysis of all data arrays. In this respect, the family of simultaneous component methods (e.g., SUM-PCA, unrestricted PCovR, MFA, STATIS, and SCA-P) is a natural choice. Yet, different simultaneous component methods may lead to quite different results.</p> <p>Results</p> <p>We offer a structured overview of simultaneous component methods that frames them in a principal components setting such that both the common core of the methods and the specific elements with regard to which they differ are highlighted. An overview of principles is given that may guide the data analyst in choosing an appropriate simultaneous component method. Several theoretical and practical issues are illustrated with an empirical example on metabolomics data for <it>Escherichia coli </it>as obtained with different analytical chemical measurement methods.</p> <p>Conclusion</p> <p>Of the aspects in which the simultaneous component methods differ, pre-processing and weighting are consequential. Especially, the type of weighting of the different matrices is essential for simultaneous component analysis. These types are shown to be linked to different specifications of the idea of a fair integration of the different coupled arrays.</p
Native American Children and Their Reports of Hope: Construct Validation of the Children's Hope Scale
Child reports of hope continue to be utilized as predictors of positive adjustment; however, the utilization of the hope construct has not been assessed within the culturally diverse Native American child group. The present study investigated the applicability of the Hope theory among 96 Native American children in the Midwest. Measures included the Children’s Hope Scale and a Hope Interview. Native American children in the current sample appear to conceptualize hope as a way to reach goals as did the children in the normative sample. Results from the factor analysis demonstrate that the factor structure found in the current study was similar to the factor structure found in the standardization sample. Because of the similar Hope theory conceptualization and factor structure, interventions focused on the positive psychology construct of hope may be applicable within a Native American child population
Multiattribute perceptual mapping with idiosyncratic brand and attribute sets
This article proposes an extremely flexible procedure for perceptual mapping based on multiattribute ratings, such that the respondent freely generates sets of both brands and attributes. Therefore, the brands and attributes are known and relevant to each participant. Collecting and analyzing such idiosyncratic datasets can be challenging. Therefore, this study proposes a modification of generalized canonical correlation analysis to support the analysis of the complex data structure. The model results in a common perceptual map with subject-specific and overall fit measures. An experimental study compares the proposed procedure with alternative approaches using predetermined sets of brands and/or attributes. In the proposed procedure, brands are better known, attributes appear more relevant, and the respondent's burden is lower. The positions of brands in the new perceptual map differ from those obtained when using fixed brand sets. Moreover, the new procedure typically yields positioning information on more brands. An empirical study on positioning of shoe stores illustrates our procedure and resulting insights. Finally, the authors discuss limitations, potential application areas, and directions for research
The Greek-Orthodox version of the Brief Religious Coping (B-RCOPE) instrument: psychometric properties in three samples and associations with mental disorders, suicidality, illness perceptions, and quality of life
Background: The B-RCOPE is a brief measure assessing religious coping. We aimed to assess the psychometric properties of its Greek version in people with and without long-term conditions (LTCs). Associations between religious coping and mental illness, suicidality, illness perceptions, and quality of life were also investigated.
Methods: The B-RCOPE was administered to 351 patients with diabetes, chronic pulmonary obstructive disease (COPD), and rheumatic diseases attending either the emergency department (N = 74) or specialty clinics (N = 302) and 127 people without LTCs. Diagnosis of mental disorders was established by the MINI. Associations with depressive symptom severity (PHQ-9), suicidal risk (RASS), illness perceptions (B-IPQ), and health-related quality of life (WHOQOL-BREF) were also investigated.
Results: The Greek version of B-RCOPE showed a coherent two-dimensional factor structure with remarkable stability across the three samples corresponding to the positive (PRC) and negative (NRC) religious coping dimensions. Cronbach’s alphas were 0.91–0.96 and 0.77–0.92 for the PRC and NRC dimensions, respectively. Furthermore, NRC was associated with poorer mental health, greater depressive symptom severity and suicidality, and impaired HRQoL. In patients with LTCs, PRC correlated with lower perceived illness timeline, while NRC was associated with greater perceived illness consequences, lower perceived treatment control, greater illness concern, and lower illness comprehensibility.
Conclusions: These findings indicate that the Greek-Orthodox B-RCOPE version may reliably assess religious coping. In addition, negative religious coping (i.e., religious struggle) is associated with adverse illness perceptions, and thus may detrimentally impact adaptation to medical illness. These findings deserve replication in prospective studies
- …