Confirmatory factor analysis of the Beck Depression inventory in obese individuals seeking surgery

Background : The Beck Depression Inventory (BDI) is frequently employed as measure of depression in studies of obesity. The aim of the study was to assess the factorial structure of the BDI in obese patients prior to bariatric surgery.

Methods : Confirmatory factor analysis was conducted on the current published factor analyses of the BDI. Three published models were initially analysed with two additional modified models subsequently included. A sample of 285 patients presenting for Lap-Band® surgery was used.

Results : The published bariatric model by Munoz et al. was not an adequate fit to the data. The general model by Shafer et al. was a good fit to the data but had substantial limitations. The weight loss item did not significantly load on any factor in either model. A modified Shafer model and a proposed model were tested, and both were found to be a good fit to the data with minimal differences between the two. A proposed model, in which two items, weight loss and appetite, were omitted, was suggested to be the better model with good reliability.

Conclusions : The previously published factor analysis in bariatric candidates by Munoz et al. was a poor fit to the data, and use of this factor structure should be seriously reconsidered within the obese population. The hypothesised model was the best fit to the data. The findings of the study suggest that the existing published models are not adequate for investigating depression in obese patients seeking surgery.

Meaning in life in earlier and later older-adulthood : confirmatory factor analysis and correlates of the meaning in life questionnaire

OBJECTIVE: To validate the Meaning in Life Questionnaire (MLQ) in earlier and later older-adulthood, and examine its correlates. METHOD: Participants in earlier (n = 341, M age = 68.5) and later older-adulthood (n = 341, M age = 78.6) completed the MLQ and other measures. Confirmatory multigroup analysis, correlations, and regression models were conducted. RESULTS: A two-factor (presence and search), eight-item model of the MLQ had a good fit and was age-invariant. Presence and search for meaning were largely unrelated. Meaning was associated with life satisfaction, well-being across a range of domains, and psychological resources. Searching for meaning correlated negatively with these variables, but to a lesser degree in later older-adulthood. DISCUSSION: The MLQ is valid in older-adulthood. Meaning in life is psychologically adaptive in older-adulthood. Searching for meaning appears less important, especially in later older-adulthood. Findings are discussed in the context of aging and psychosocial development.

Factor analysis of partners' commitment to risk management in public-private partnership projects

Purpose – The purpose of this paper is to investigate and uncover key determinants that could explain partners' commitment to risk management in public-private partnership projects so that partners' risk management commitment is taken into the consideration of optimal risk allocation strategies.

Design/methodology/approach – Based on an extensive literature review and an examination of the purchasing power parity (PPP) market, an industry-wide questionnaire survey was conducted to collect the data for a confirmatory factor analysis. Necessary statistical tests are conducted to ensure the validity of the analysis results.

Findings – The factor analysis results show that the procedure of confirmatory factor analysis is statistically appropriate and satisfactory. As a result, partners' organizational commitment to risk management in public-private partnerships can now be determined by a set of components, namely general attitude to a risk, perceived one's own ability to manage a risk, and the perceived reward for bearing a risk.

Practical implications – It is recommended, based on the empirical results shown in this paper, that, in addition to partners' risk management capability, decision-makers, both from public and private sectors, should also seriously consider partners' risk management commitment. Both factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects. Future research may therefore explore how to form optimal risk allocation strategies by integrating organizational capability and commitment, the determinants and measurement of which have been established in this study.

Originality/value – This paper makes an original contribution to the general body of knowledge on risk allocation in large-scale infrastructure projects in Australia adopting the procurement method of public-private partnership. In particular, this paper has innovatively established a measurement model of organisational commitment to risk management, which is crucial to determining optimal risk allocation strategies and in turn achieving project success. The score coefficients of all obtained components can be used to construct components by linear combination so that commitment to risk management can be measured. Previous research has barely focused on this topic.

Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model

Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.

Testing the factor structure of the behavioral-intentions battery: an empirical study of the Australian banking industry

The five-factor ‘Behavioural-Intentions Battery’ was developed by Zeithaml, Berry and Parasuraman (1996), to measure customer behavioural and attitudinal intentions. The structure of this model was re-examined by Bloomer, de Ruyter and Wetzels (1999) across different service industries. They concluded that service loyalty is a multi dimensional construct consisting of four, not five, distinct dimensions. To date, neither model has been tested within a banking environment. This research independently tested the ‘goodness of fit’ of both the four and five-factor models, to data collected from branch bank customers. Data were collected via questionnaire with a sample of 348 banking customers. A confirmatory factor analysis was conducted upon the two opposing factor structures, revealing that the five-factor structure has a superior model fit; however, the fit is ‘marginal’.

The factor structure of the strengths and difficulties questionnaire

The Strengths and Difficulties Questionnaire (SDQ) has been widely adopted as a measure of child and adolescent mental health and behavioral problems. However, despite an impressive number of studies demonstrating its psychometric properties, appropriate analyses of the instrument's underlying structure have not been reported. We conducted confirmatory factor analyses on matched data obtained from a large community sample of 7-17-year-olds, their parents, and their teachers. The analyses indicated that the reputed factor structure was not supported, with none of the subscales being unidimensional. Further, each informant group appeared to respond differently to the questionnaire. Considering the findings in relation to the stringency of the tests used to evaluate the SDQ, its utility, and previous research on its clinical validity, it is suggested that the SDQ be used with caution and in conjunction with other forms of assessment.

The effects of clustered data on standard error estimates in covariance structure analysis : a field data application

Purpose – The purpose of this article is to present an empirical analysis of complex sample data with regard to the biasing effect of non-independence of observations on standard error parameter estimates. Using field data structured in the form of repeated measurements it is to be shown, in a two-factor confirmatory factor analysis model, how the bias in SE can be derived when the non-independence is ignored.

Design/methodology/approach – Three estimation procedures are compared: normal asymptotic theory (maximum likelihood); non-parametric standard error estimation (naïve bootstrap); and sandwich (robust covariance matrix) estimation (pseudo-maximum likelihood).

Findings – The study reveals that, when using either normal asymptotic theory or non-parametric standard error estimation, the SE bias produced by the non-independence of observations can be noteworthy.

Research limitations/implications – Considering the methodological constraints in employing field data, the three analyses examined must be interpreted independently and as a result taxonomic generalisations are limited. However, the study still provides “case study” evidence suggesting the existence of the relationship between non-independence of observations and standard error bias estimates.

Originality/value – Given the increasing popularity of structural equation models in the social sciences and in particular in the marketing discipline, the paper provides a theoretical and practical insight into how to treat repeated measures and clustered data in general, adding to previous methodological research. Some conclusions and suggestions for researchers who make use of partial least squares modelling are also drawn.

Analysis of satisfaction at Gallipoli on ANZAC day, 2007 : results of a survey of event participants

This paper explores the critical success factors of special events, in this case the Anzac Day commemorations at Gallipoli, Turkey. This event has become increasingly popular in recent years with crowd numbers growing to around 20,000 people traveling to attend the 2005 Dawn Service at historic Anzac Cove on Anzac day. The aim of this research is to investigate the success factors associated with Anzac Day commemorations at Gallipoli and to assess how these influence visitor satisfaction. Data was collected from 331 attendees of Anzac Day commemorations at Gallipoli while they were in transit from Gallipoli to Istanbul on 25 April 2007. The analysis of this data was undertaken using exploratory and confirmatory factor analysis as a basis to the development of a model of satisfaction using structural equation modeling. In this case constructs relating to amenities, transport, ceremonies and recommending behavior were found to be significant predictors of event satisfaction. These issues during the event were found to be of equal importance for both genders and all age groups.

Assessing indicant directionality of a media consumption construct using confirmatory tetrad analysis

When assessing the psychometric properties of measures and estimate relations among latent variables, many studies in the social sciences (including marketing) often fail to comprehensively appraise the directionality of indicants. Such failures can lead to model misspecification and inaccurate parameter estimates (Jarvis et al. 2003). In order to further assess the correct directionality of a ‘media consumption’ construct’s indicants, this paper employs confirmatory tetrad analysis (CTA). Previous studies advocate this construct being best viewed as formative. However, our CTA suggests it could be modelled using a reflective orientation. We then conclude the paper drawing recommendations for future studies advocating that when assessing item directionality researchers should implement pre and post hoc tests.

A Rasch analysis of the teachers music confidence scale

This article presents a new measure of teachers’ confidence to conduct musical activities with young children; Teachers Music Confidence Scale (TMCS). The TMCS was developed using a sample of 284 in-service and pre-service early childhood teachers in Hong Kong Special Administrative Region (HKSAR). The TMCS consisted of 10 musical activities. Teachers rated their confidence levels to conduct each activity on a scale from 1 (Not confident at all) to 5 (Very confident). An exploratory factor analysis retained a 10-item single factor that was replicated using confirmatory factor analysis procedures. All items of the TMCS fitted the Rasch model adequately. In-service teachers showed higher confidence levels to conduct several musical activities with young children than pre-service teachers. Implications of these findings for measuring teachers’ confidence to conduct musical activities with young children were discussed.

Channel estimation of dual-hop MIMO relay system via parallel factor analysis

The optimal source precoding matrix and relay amplifying matrix have been developed in recent works on multiple-input multiple-output (MIMO) relay communication systems assuming that the instantaneous channel state information (CSI) is available. However, in practical relay communication systems, the instantaneous CSI is unknown, and therefore, has to be estimated at the destination node. In this paper, we develop a novel channel estimation algorithm for two-hop MIMO relay systems using the parallel factor (PARAFAC) analysis. The proposed algorithm provides the destination node with full knowledge of all channel matrices involved in the communication. Compared with existing approaches, the proposed algorithm requires less number of training data blocks, yields smaller channel estimation error, and is applicable for both one-way and two-way MIMO relay systems with single or multiple relay nodes. Numerical examples demonstrate the effectiveness of the PARAFAC-based channel estimation algorithm.