The variable was scored as a count variable. Health locus of control: These data were measured using the Multidimensional Health Locus of Control (MHLC) 18-item test [36]. MHLC is a measurement instrument that includes three six-point Likert scales: Internal (MHLC-I), Chance externality (MHLC-C) and Powerful others (MHLC-PO).

The different scales, or levels, were analyzed separately. In this study, the MHLC scales were treated as index only in the correlation matrix. Beliefs about medicines: Results were measured using NCF based on the Beliefs about Medicines Questionnaire-Specific (BMQ-S) [19]. BMQ-S is a validated 10-item test instrument which assesses beliefs about perceived medication necessity and perceived medication concerns on five-point Likert scales. BMQ is a two-scale construction and is also available to use as an index. In this click here study, the index was only used in the correlation matrix. The BMQ questionnaire has been translated into Swedish, with a back translation approved by the original author of the questionnaire,

and has been previously used in Sweden [40], [41], [42] and [43]. Medication adherence: These data were self-reported using the Morisky scale of adherence (MSA) in a four-item form [44]. The MSA is a count variable and the first question is: “Do you ever forget to take your medicine?”. selleck compound The Morisky scale was originally designed to evaluate medication adherence in hypertensive Farnesyltransferase patients, but has subsequently been found to be reliable in a variety of adherence studies [45] and [46]. In previous statin studies, the MSA used was binary, with only two categories [47]. Patients who answered “no” to all questions were categorized as highly adherent, while patients who answered “yes” to at least one question were categorized as having low adherence. This categorization

system is consistent with what was used when developing the original scale, as well as how it has been used in several adherence studies [47] and [48]. The Statistical Package for the Social Sciences version 19 (Chicago, IL, USA) was used for descriptive statistics, factor analysis, to measure the variance inflation factor (VIF), and Chi-square and Mann–Whitney U tests. WarpPLS vs. 2.0 was used for structural equation modeling (SEM) analysis with the partial least squares (PLS) estimation technique [49]. SEM is a combination of confirmatory factors and path analysis, which allows the inclusion of latent variables (LV) that are not directly measured [50]. SEM works with both continuous and discrete observed variables as indicators (LVs).