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A Rasch and confirmatory factor analysis of the General Health Questionnaire (GHQ) - 12
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The General Health Questionnaire (GHQ) - 12 was designed as a short questionnaire to assess psychiatric morbidity. Despite the fact that studies have suggested a number of competing multidimensional factor structures, it continues to be largely used as a unidimensional instrument. This may have an impact on the identification of psychiatric morbidity in target populations. The aim of this study was to explore the dimensionality of the GHQ-12 and to evaluate a number of alternative models for the instrument.
The data were drawn from a large heterogeneous sample of cancer patients. The Partial Credit Model (Rasch) was applied to the 12-item GHQ. Item misfit (infit mean square >or= 1.3) was identified, misfitting items removed and unidimensionality and differential item functioning (age, gender, and treatment aims) were assessed. The factor structures of the various alternative models proposed in the literature were explored and optimum model fit evaluated using Confirmatory Factor Analysis.
The Rasch analysis of the 12-item GHQ identified six misfitting items. Removal of these items produced a six-item instrument which was not unidimensional. The Rasch analysis of an 8-item GHQ demonstrated two unidimensional structures corresponding to Anxiety/Depression and Social Dysfunction. No significant differential item functioning was observed by age, gender and treatment aims for the six- and eight-item GHQ. Two models competed for best fit from the confirmatory factor analysis, namely the GHQ-8 and Hankin's (2008) unidimensional model, however, the GHQ-8 produced the best overall fit statistics.
The results are consistent with the evidence that the GHQ-12 is a multi-dimensional instrument. Use of the summated scores for the GHQ-12 could potentially lead to an incorrect assessment of patients' psychiatric morbidity. Further evaluation of the GHQ-12 with different target populations is warranted.
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... While the GHQ-12 is widely employed and is considered a well-validated and highly reliable instrument (Werneke et al., 2000), the literature contains various ongoing debates, notably concerning the dimensionality analysis of the instrument (Smith et al., 2010). Focusing on the structure of the GHQ-12, although the original instrument focuses solely on a unidimensionality test, a considerable volume of literature based on the evidence of exploratory and confirmatory factor analysis suggests that the GHQ-12 has a twoor three-factor structure (A. ...
... Dimensionality, meanwhile, considers whether a single-factor model can effectively capture the entire variance in the data, essentially addressing whether the instrument is unidimensional or not. This can be estimated through principal component analysis (PCA) of the residuals once the Rasch factor has been extracted (Bond & Fox, 2015;Smith et al., 2010). Moreover, Rasch (Rasch, 1960) suggested that the validity and reliability of the items in a research instrument can also be determined using the Rasch measurement model. ...
The General Health Questionnaire (GHQ-12) is widely accepted as an instrument used to examine diagnosable psychiatric disorders. It is also routinely used as a measure of psychological morbidity. This study aimed to assess and establish the psychometric properties of the GHQ-12 among Indian teenagers. The tool was administered to 212 adolescents aged from 12 to 18 years. Following two-stage cluster sampling, the data were collected from Aligarh district, India. Fleiss Kappa analysis was used to determine test reliability and showed an overall value of 0.94, based on the rater agreement for the instrument. Furthermore, the Rasch measurement model was used, with values of 0.79 and 0.83 for person and item reliability, respectively. Moreover, the value of unidimensionality was found to be 37.9%. Additionally, item fit statistics and item analysis were conducted for the instrument. Based on the preliminary data and findings, the study provides primary evidence for the reliability and validity of GHQ-12. Hence, the questionnaire can lead to more multi-site studies in India.
... Among the various versions of this questionnaire, the GHQ-12 is the most commonly utilized, consisting of 12 items to evaluate mental health [11]. Extensive research examining the psychometric properties of the GHQ-12 [10,[12][13][14][15][16] has consistently shown its accuracy, specificity, and reliability [17,18]. Although initially designed as a unidimensional scale, researchers have investigated the factor structure of the GHQ-12. ...
... Confirmatory factor analysis (CFA) was utilized to identify three components: GHQ-12A (consisting of six items measuring social dysfunction and anhedonia), GHQ-12B (comprising four items measuring anxiety and depression), and GHQ-12C (including two items measuring loss of confidence). The three-factor structure found in this study aligns with previous research that identified three elements within the GHQ-12 structure [10,[12][13][14][15][16]. The factor loadings observed in the current investigation were notably high, as presented in Table 2. ...
Although previous studies have investigated the presence of psychometric comorbidities in individuals with emphysema, our understanding of the impact of emphysema on general mental health and specific dimensions of mental health, such as social dysfunction and anhedonia, depression and anxiety, and loss of confidence, remains limited. This research aims to examine the influence of emphysema on general mental health and its dimensions using the GHQ-12 assessment. By employing confirmatory factor analysis (CFA), the predictive normative approach, and one-sample t-test, we analyzed data from Understanding Society: the UK Household Longitudinal Study (UKHLS), including 97 individuals clinically diagnosed with emphysema and 8980 individuals without a clinical diagnosis of emphysema. The findings of this study indicate that individuals with clinically diagnosed emphysema experience poorer general mental health (t(96) = 8.41, p < 0.001, Cohen's d = 0.12, 95% C.I. [0.09, 0.15]), increased levels of social dysfunction and anhedonia (t(96) = 6.02, p < 0.001, Cohen's d = 0.09, 95% C.I. [0.06, 0.11]), heightened depression and anxiety (t(96) = 7.26, p < 0.001, Cohen's d = 0.11, 95% C.I. [0.08, 0.14]), as well as elevated loss of confidence (t(96) = 6.40, p < 0.001, Cohen's d = 0.09, 95% C.I. [0.07, 0.12]). These findings suggest the need for intervention programs aimed at improving the mental health of individuals with emphysema.
... The most commonly used version is the 12-item GHQ (GHQ-12). Various studies have tested the psychometric properties of this questionnaire (del Pilar Sánchez-López and Dresch, 2008;Hankins, 2008;Salama-Younes et al., 2009;Smith et al., 2010;Vasconcelos-Raposo et al., 2012). Additionally, research has demonstrated that the GHQ-12 exhibits good sensitivity, specificity, and reliability (Daradkeh et al., 2001;Endsley et al., 2017). ...
Objective: Our objective was to the longitudinal associations between e-cigarette use and general mental health, social dysfunction & anhedonia, depression &
anxiety, and loss of confidence in a sample from the UK.
Methods: We analyzed data of 19,706 participants from Wave 9 (collected from 2017 to 2018) and Wave 10 (collected from 2018 to 2019) of the Understanding
Society: the UK Household Longitudinal Study using a confirmatory factor analysis, linear mixed effect model, and one-sample t-tests.
Results: We found that there is a significant time by e-cigarette use status interaction on mental health issues (b = 0.32, p < 0.001, 95 % C.I. [0.15, 0.49]), social
dysfunction & anhedonia (b = 0.36, p < 0.001, 95 % C.I. [0.18, 0.54]), and loss of confidence (b = 0.24, p < 0.01, 95 % C.I. [0.06, 0.41]). Indeed, participants who
became e-cigarette smokers at Wave 10 had worse mental health (t(107) = 2.64, p < 0.01, 95 % C.I. [0.07, 0.48], Cohen's d = 0.28), social dysfunction & anhedonia
(t(107) = 3.16, p < 0.01, 95 % C.I. [0.12, 0.52], Cohen's d = 0.32), and loss of confidence (t(107) = 2.08, p < 0.05, 95 % C.I. [0.01, 0.37], Cohen's d = 0.19)
comparing to one year ago.
Limitation: Limitations of this study included its self-report measures, unclassified e-cigarette type, limited generalizability to other populations, and lack of
experimental manipulations.
Conclusion: We revealed longitudinal associations between e-cigarette initiation and adverse general and dimensions of mental health except for depression and
anxiety, which have significant implications for public health, specifically in terms of e-cigarette product regulation and advertising.
... The 12-item version of the general health questionnaire (GHQ-12) is a self-administered questionnaire consisting of 12 items, each assessed using a Likert scale. Extensive research in the field has examined the psychometric properties of this questionnaire and has demonstrated its reliability, sensitivity, and specificity as a valid measure of mental health [31][32][33][34][35][36][37][38]. However, there is a debate regarding whether the GHQ-12 should be utilized as a unidimensional scale or as a multidimensional structure. ...
Epilepsy, a severe neurological disorder impacting approximately 50 million individuals worldwide, is associated with a high prevalence of mental health issues. However, existing research has predominantly examined the relationship between epilepsy and depression or anxiety, neglecting other dimensions of mental health as assessed by factor scores from the general health survey (GHQ), such as the GHQ-12. This study aimed to explore how epilepsy affects both general mental health and specific dimensions of mental health. By employing a factor analysis and a predictive normative modeling approach, the study examined 426 epilepsy patients and 39,171 individuals without epilepsy. The findings revealed that epilepsy patients experienced poorer general mental health and specific aspects of mental health. Consequently, this study highlights the validity of GHQ-12 as a measure of mental health problems in epilepsy patients and emphasizes the importance of considering the impact of epilepsy on various dimensions of mental health, rather than focusing solely on depression or anxiety. Clinicians should incorporate these study results into the development of interventions aimed at enhancing mental well-being in epilepsy patients, ultimately leading to improved outcomes.
... Other authors have found that the GHQ-12 is, in fact, ultimately a unidimensional measure (e.g. Hankins, 2008;Smith et al., 2010;Ye, 2009). There is much inconsistency between authors' opinions of whether the GHQ-12 is uni-or multi-dimensional. ...
Literature investigating first-generation students (FGS) locally is lacking despite patterned enrolment. The study established a psycho-social profile of FGS contributing to our understanding of academic success. This triangulated institutional-level investigation identified significant predictors of academic success from socio-demographic variables.
Findings contradicted international literature. FG cohorts did not differ statistically from continuing generations with similar psychosocial profiles. The findings underscore the impact of patterned enrolment at institutions. Academic success interventions must consider institutional context, enrolment patterns, and psychosocial profiles of students. A strengths-based approach at an institutional level will foster our attempts to understand and support students from disadvantaged communities.
... The psychometric properties of the GHQ-12 have been examined in the literature [30][31][32][33][34][35]. Moreover, research suggests that the GHQ-12 is characterized by good specificity, reliability, and sensitivity [36,37]. ...
Objectives:
Mental health conditions in patients with coronary heart disease (CHD) are closely related to clinical outcomes. Thus, this study's goal is to investigate how CHD affects general and specific aspects of mental health.
Methods:
We analyzed data from Wave 10 Understanding Society: the UK Household Longitudinal Study (UKHLS), which were collected between 2018 and 2019. After removing people who had missing data, there were 450 participants who indicated that they have CHD, and 6138 age- and sex-matched healthy participants indicated that they were not clinically diagnosed with CHD.
Results:
The main findings were that participants with CHD had more mental health problems, as shown by the GHQ-12 summary score (t (449) = 6.00, p < 0.001, 95% C.I. [0.20, 0.40], Cohen's d = 0.30), social dysfunction and anhedonia, (t (449) = 5.79, p < 0.001, 95% C.I. [0.20, 0.40], Cohen's d = 0.30), depression and anxiety (t (449) = 5.04, p < 0.001, 95% C.I. [0.15, 0.33], Cohen's d = 0.24), and loss of confidence (t (449) = 4.46, p < 0.001, 95% C.I. [0.11, 0.30], Cohen's d = 0.21).
Conclusion:
This study implies that GHQ-12 is a valid assessment of mental health problems in CHD patients, and there is a need to consider how different aspects of mental health are affected by CHD rather than solely focusing on depression or anxiety problems alone in patients with CHD.
Background
The current study aimed to examine how the general and dimensions of psychological distress are affected by angina.
Methods
First, a confirmatory factor analysis (CFA) was used to produce the three-factor solution of the GHQ-12. Second, a predictive normative modeling approach to predict the expected scores for 1,081 people with angina based on a model trained on demographics from 8,821 age and sex-matched people without angina. Finally, one-sample t-tests were used to determine the differences between the actual psychological distress scores and expected psychological distress scores in participants with angina.
Results
There were three underlying structures of the GHQ-12 labeled as GHQ-12A (social dysfunction & anhedonia), GHQ-12B (depression & anxiety), and GHQ-12C (loss of confidence). Moreover, participants with angina had more psychological distress as indicated by the GHQ-12 summary score (Cohen’s d = 0.31), GHQ-12A (Cohen’s d = 0.34), GHQ-12B (Cohen’s d = 0.21), and GHQ-12C (Cohen’s d = 0.20) comparing to controls.
Conclusion
The current study implies that GHQ-12 is a valid measure of psychological distress in people with angina, and there is a need to consider the dimensions of psychological distress in angina rather than solely focusing on certain dimensions of psychological distress such as depression or anxiety issues in people with angina. Clinicians should come up with interventions to reduce psychological distress in people with angina which can then lead to better outcomes.
Individuals are different in a relatively constant pattern of thoughts, feeling, and behaviors, which are called personality traits. Mental health is a condition of well-being in which people may reach their full potential and deal effectively with stress, work efficiently, and contribute to their communities. Indeed, the link between personality and mental health as indicated by the 12-item version of the general health questionnaires (GHQ-12) has been well-established according to evidence found by decades of research. However, the GHQ-12 comprises many questions asking about different dimensions of mental health. It is unclear how personality traits relate to these dimensions of mental health. In this paper, we try to address this question. We analyzed data from 12,007 participants from the British Household Panel Study (BHPS) using a confirmatory factor analysis (CFA) and generalized linear models. We replicated the factor structure of GHQ-12 labeled as GHQ-12A (social dysfunction & anhedonia; 6 items), GHQ-12B (depression & anxiety; 4 items), and GHQ-12C (loss of confidence; 2 items). Moreover, Neuroticism was positively related to all dimensions of mental health issues, Extraversion was negatively related to GHQ-12A (social dysfunction & anhedonia) and GHQ-12B (depression & anxiety), Agreeableness and Conscientiousness were negatively related to GHQ-12A (social dysfunction & anhedonia) and GHQ-12C (loss of confidence), and Openness was negatively related to GHQ-12B (depression & anxiety). These results contribute to theories including the predisposition/vulnerability model, complication/scar model, pathoplasty/exacerbation model, and the spectrum model, which propose that personality traits are linked to mental health and explained possible reasons. Psychologists may use results from this study to identify individuals who may be at high risk of developing various non-psychiatric mental health issues and intervene to avoid negative outcomes.
Doctors' communication with patients is commonly hampered by lack of training in this core skill. This study aimed to assess the efficacy of an intensive 3-day training course on communication skills in a randomised controlled trial with a two-by-two factorial design and several outcomes. METHODS: 160 oncologists from 34 UK cancer centres were randomly allocated to four groups: written feedback followed by course; course alone; written feedback alone; and control. At each of two assessment periods, consultations with six to ten consecutive, consenting patients per doctor were videotaped. 2407 patients participated. Outcome measures included objective and subjective ratings made by researchers, doctors, and patients. The primary outcomes were objective improvements after the intervention in key communication skills. Course content included structured feedback, videotape review of consultations, role-play with simulated patients, interactive group demonstrations, and discussion led by a trained facilitator. FINDINGS: In Poisson regression analysis of counts of communication behaviours, course attendance significantly improved key outcomes. The estimated effect sizes corresponded to higher rates of use of focused questions (difference between course attenders [n=80] and non-attenders [n=80] 34%, p=0.003), focused and open questions (27%, p=0.005), expressions of empathy (69%, p=0.003), and appropriate responses to patients' cues (38%, p=0.026), and a 24% lower rate of use of leading questions (p=0.11). There was little evidence for the effectiveness of written feedback. INTERPRETATION: The communication problems of senior doctors working in cancer medicine are not resolved by time and clinical experience. This trial shows that training courses significantly improve key communication skills. More resources should be allocated to address doctors' training needs in this vital area.
The GHQ12 has become a popular screening instrument used by both clinicians and researchers. To date there have been a number of studies investigating the factor structure of the GHQ12. Most have identified a factorial structure to the instrument but there has been little consistency in the factors identified. One reason for this may be that different investigators are using different scoring methods and this could impact the structure identified. This study used structured equation modeling (LISREL 8.7) to carry out a confirmatory factor analysis, with a large sample of 8,732 university staff, on four 3-factor and one unitary model solutions using the three most common scoring methods (Classical, Corrected, and Likert). It was found that the method of scoring substantially affects model estimation and suggestions were made as to the best scoring method for future use.
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The present study assessed a variety of factor structures identified by Various authors as underlying the 12-item General Health Questionnaire and proposed an alternative structure based on an analysis of item content. Using confirmatory factor analytic techniques (LISREL), the data indicated that the presently proposed factor structure, comprising three factors (Self-esteem, Stress, and Successful Coping), fits better than structures previously identified. The findings contribute to understanding of the 12-item General Hearth Questionnaire by separating Self-esteem and Stress, two dimensions often treated as one factor, and by identifying a third dimension of Successful Coping which is proposed to reflect individuals' perceived efficacy in interacting with the environment.
The large-sample statistical theory for latent-variable structural equation models offers little solace to the developmental psychologist, who is often confronted with less than optimally large sample sizes. This article reviews previously proposed alternatives to the sample-size and goodness-of-fit issue in latent-variable structural equation models. Various nonparametric fit indices for latent-variable systems are reviewed with their strengths and weaknesses discussed. An alternative estimation strategy called ME2 estimation is introduced as a possible alternative solution to the small-sample problem.
This article considers single sample approximations for the cross-validation coefficient in the analysis of covariance structures. An adjustment for predictive validity which may be employed in conjunction with any correctly specified discrepancy function is suggested. In the case of maximum likelihood estimation under normality assumptions the coefficient obtained is a simple linear function of the Akaike Information Criterion. Results of a random sampling experiment are reported.
Written in an accessible style, this book facilitates a deep understanding of the Rasch model. Authors Bond and Fox review the crucial properties of the Rasch model and demonstrate its use with a wide range of examples including the measurement of educational achievement, human development, attitudes, and medical rehabilitation. A glossary and numerous illustrations further aid the reader's understanding. The authors demonstrate how to apply Rasch analysis and prepare readers to perform their own analyses and interpret the results. Updated throughout, highlights of the Second Edition include: a new CD that features an introductory version of the latest Winsteps program and the data files for the book's examples, preprogrammed to run using Winsteps;, a new chapter on invariance that highlights the parallels between physical and human science measurement;, a new appendix on analyzing data to help those new to Rasch analysis;, more explanation of the key concepts and item characteristic curves;, a new empirical example with data sets demonstrates the many facets of the Rasch model and other new examples; and an increased focus on issues related to unidimensionality, multidimensionality, and the Rasch factor analysis of residuals. Applying the Rasch Model is intended for researchers and practitioners in psychology, especially developmental psychologists, education, health care, medical rehabilitation, business, government, and those interested in measuring attitude, ability, and/or performance. The book is an excellent text for use in courses on advanced research methods, measurement, or quantitative analysis. Significant knowledge of statistics is not required. © 2007 by Lawrence Erlbaum Associates, Inc. All rights reserved.