Abstract

BackgroundBased 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.MethodsThe 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.ResultsA 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.ConclusionsFuture 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.

Highlights

  • Based on the general approach of locus of control, health locus of control (HLOC) concerns controlbeliefs due to illness, sickness and health

  • Polychoric correlations of subsample A are presented in an additional file, we added polychoric correlations of subsample B into this file

  • Previous factor analyses of clinical data focused on the condition-specific construct of HLOC due to the Multidimensional Health Locus of Control scales (MHLC)-C, while we examined the general construct of HLOC

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Summary

Introduction

Based on the general approach of locus of control, health locus of control (HLOC) concerns controlbeliefs due to illness, sickness and health. HLOC research results provide an improved understanding of health related behaviour and patients’ compliance in medical care. 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. Health locus of control (HLOC) is a psychological concept concerning control beliefs in relation to illness, sickness and health. This concept is based on the general approach of locus of control (LOC) developed within the social learning theory by Rotter [1,2]. One main interest of this field of research concerns the compliance of patients in medical care in order to understand patients’ adherence to recommended treatments including medication and health related behaviour [9]

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