Validation of the 8-item Attitudes Towards Gambling Scale (ATGS-8) in a British population survey

Introduction. Public opinions concerning gambling are an important factor in shaping public policy. Little empirical attention has been given to assessing gambling attitudes within the general population. The aim of the present study is to validate the 8-item Attitudes Towards Gambling Scale (ATGS-8) in British individuals and to investigate associations of these attitudes with frequency of gambling and gambling problems. Methods. Data were derived from 7746 individuals participating in the British Gambling Prevalence Survey 2010, a comprehensive interview-based survey conducted in Great Britain between November 2009 and May 2010. Confirmatory factor analysis and separate regression analyses were applied. Results. The one-dimensional structure of the ATGS-8 was confirmed in the community sample and by gender. Furthermore, more positive attitudes towards gambling were positively related to frequency of gambling and gambling problems. Conclusions. The present study extends the previous evaluations of the scale by providing detailed evidence for the utility and usefulness of the ATGS-8 in a community sample and across gender. The ATGS-8 is a valid instrument to assess public opinion on gambling among the general population

Validation of a social cohesion theoretical framework: a multiple group SEM strategy

Social cohesion dates back to the end of the nineteenth century. Back then, society experienced epochal transformations, as are also happening nowadays. Whenever there are epochal changes, a social order (cohesion) matter arises. The paper provides a conceptual scheme of social cohesion identifying its constituent dimensions subdivided by three spheres (macro, meso, micro) and two perspectives (objective and subjective). The overarching aim is to test the validity of the operationalization of the social cohesion model provided. Firstly, we conducted an exploratory factor analysis introducing an approach implemented in Mplus named exploratory structural equation modeling that shows several useful characteristics. Afterward, through a structural equation modeling approach, we performed several confirmatory factor analyses adopting a multiple group SEM strategy in order to cross-validate the social cohesion model

Structural equation modeling in medical research: a primer

<p>Abstract</p> <p>Background</p> <p>Structural equation modeling (SEM) is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables. Similar but more powerful than regression analyses, it examines linear causal relationships among variables, while simultaneously accounting for measurement error. The purpose of the present paper is to explicate SEM to medical and health sciences researchers and exemplify their application.</p> <p>Findings</p> <p>To facilitate its use we provide a series of steps for applying SEM to research problems. We then present three examples of how SEM has been utilized in medical and health sciences research.</p> <p>Conclusion</p> <p>When many considerations are given to research planning, SEM can provide a new perspective on analyzing data and potential for advancing research in medical and health sciences.</p

Coping and sickness absence

Objectives: The aim of this study is to examine the role of coping styles in sickness absence. In line with findings that contrast the reactive-passive focused strategies, problem-solving strategies are generally associated with positive results in terms of well-being and overall health outcomes; our hypothesis is that such strategies are positively related to a low frequency of sickness absence and with short lengths (total number of days absent) and durations (mean duration per spell). Methods: Using a prospective design, employees' (N = 3,628) responses on a self-report coping inventory are used to predict future registered sickness absence (i.e. frequency, length, duration, and median time before the onset of a new sick leave period). Results and conclusions: In accordance with our hypothesis, and after adjustment for potential confounders, employees with an active problem-solving coping strategy are less likely to drop out because of sickness absence in terms of frequency, length (longer than 14 days), and duration (more than 7 days) of sickness absence. This positive effect is observed in the case of seeking social support only for the duration of sickness absence and in the case of palliative reaction only for the length and frequency of absence. In contrast, an avoidant coping style, representing a reactive-passive strategy, increases the likelihood of frequent absences significantly, as well as the length and duration of sickness absence. Expression of emotions, representing another reactive-passive strategy, has no effect on future sickness absenteeism. The median time before the onset of a new episode of absenteeism is significantly extended for active problem-solving and reduced for avoidance and for a palliative response. The results of the present study support the notion that problem-solving coping and reactive-passive strategies are inextricably connected to frequency, duration, length and onset of sickness absence. Especially, active problem-solving decreases the chance of future sickness absence. © Springer-Verlag 2007

Multiple dimensions of health locus of control in a representative population sample: ordinal factor analysis and cross-validation of an existing three and a new four factor model

<p>Abstract</p> <p>Background</p> <p>Based on the general approach of locus of control, health locus of control (HLOC) concerns control-beliefs due to illness, sickness and health. HLOC research results provide an improved understanding of health related behaviour and patients' compliance in medical care. HLOC research distinguishes between beliefs due to Internality, Externality powerful Others (POs) and Externality Chance. However, evidences for differentiating the POs dimension were found. Previous factor analyses used selected and predominantly clinical samples, while non-clinical studies are rare. The present study is the first analysis of the HLOC structure based on a large representative general population sample providing important information for non-clinical research and public health care.</p> <p>Methods</p> <p>The standardised German questionnaire which assesses HLOC was used in a representative adult general population sample for a region in Northern Germany (N = 4,075). Data analyses used ordinal factor analyses in LISREL and Mplus. Alternative theory-driven models with one to four latent variables were compared using confirmatory factor analysis. Fit indices, chi-square difference tests, residuals and factor loadings were considered for model comparison. Exploratory factor analysis was used for further model development. Results were cross-validated splitting the total sample randomly and using the cross-validation index.</p> <p>Results</p> <p>A model with four latent variables (Internality, Formal Help, Informal Help and Chance) best represented the HLOC construct (three-dimensional model: normed chi-square = 9.55; RMSEA = 0.066; CFI = 0.931; SRMR = 0.075; four-dimensional model: normed chi-square = 8.65; RMSEA = 0.062; CFI = 0.940; SRMR = 0.071; chi-square difference test: p < 0.001). After excluding one item, the superiority of the four- over the three-dimensional HLOC construct became very obvious (three-dimensional model: normed chi-square = 7.74; RMSEA = 0.059; CFI = 0.950; SRMR = 0.079; four-dimensional model: normed chi-square = 5.75; RMSEA = 0.049; CFI = 0.965; SRMR = 0.065; chi-square difference test: p < 0.001). Results were confirmed by cross-validation. Results based on our large community sample indicated that western general populations separate health-related control-beliefs concerning formal and informal assistance.</p> <p>Conclusions</p> <p>Future non-clinical HLOC studies in western cultures should consider four dimensions of HLOC: Internality, Formal Help, Informal Help and Chance. However, the standardised German instrument needs modification. Therefore, confirmation of our results may be useful. Future research should compare HLOC structure between clinical and non-clinical samples as well as cross-culturally.</p

Modification of the Catastrophic Cognitions Questionnaire (CCQ-M) for Normals and Patients: Exploratory and LISREL Analyses

The recently developed Catastrophic Cognitions Questionnaire (CCQ) was further inestigated using both student and anxiety patient samples. LISREL confirmatory factor analyses was used. The results showed that the CCQ could be explained by a three-factor oblique solution. These are Emotional Catastrophes, Physical Catastrophes, and Mental Catastrophes. The modified version of CCQ (CCQ-M) revealed good internal consistency, test-retest reliability, and concurrent validity. It has also good discriminant validity. The CCQ-M can therefore be used with both normal and anxiety-disordered patients

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale)

OBJECTIVE: The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. DESIGN: Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. STUDY SAMPLE: 1220 people who have attended MRC IHR over the last decade. RESULTS: We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed "speech understanding", "spatial perception", and "clarity, separation, and identification". Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, "effort and concentration", representing two more questions. CONCLUSIONS: These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores