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Logo of bmcmidmBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Medical Informatics and Decision Making
 
BMC Med Inform Decis Mak. 2012; 12: 60.
Published online 2012 July 2. doi:  10.1186/1472-6947-12-60
PMCID: PMC3416666

Applying the theory of planned behaviour to multiple sclerosis patients’ decisions on disease modifying therapy – questionnaire concept and validation

Abstract

Background

Patients making important medical decisions need to evaluate complex information in the light of their own beliefs, attitudes and priorities. The process can be considered in terms of the theory of planned behaviour.

Decision support technologies aim at helping patients making informed treatment choices. Instruments assessing informed choices need to include risk knowledge, attitude (towards therapy) and actual uptake. However, mechanisms by which decision support achieves its goals are poorly understood.

Our aim was therefore to develop and validate an instrument modeling the process of multiple sclerosis (MS) patients’ decision making about whether to undergo disease modifying (immuno-)therapies (DMT).

Methods

We constructed a 30-item patient administered questionnaire to access the elaboration of decisions about DMT in MS according to the theory of planned behaviour. MS-patients’ belief composites regarding immunotherapy were classified according to the domains “attitude”, “subjective social norm” and “control beliefs” and within each domain to either “expectations” or “values” yielding 6 sub-domains. A randomized controlled trial (n = 192) evaluating an evidence based educational intervention tested the instrument’s predictive power regarding intention to use immunotherapy and its sensitivity to the intervention.

Results

The psychometric properties of the questionnaire were satisfactory (mean item difficulty 62, mean SD 0.9, range 0–3). Responses explain up to 68% of the variability in the intention to use DMT was explained by up to 68% in the total sample. Four weeks after an educational intervention, predictive power was higher in the intervention (IG) compared to the control group (CG) (intention estimate: CG 56% / IG 69%, p = .179; three domains CG 56% / IG 74%, p = .047; six sub-domains CG 64% / IG 78%, p = .073). The IG held more critical beliefs towards immunotherapy (p = .002) and were less willing to comply with social norm (p = .012).

Conclusions

The questionnaire seems to provide a valid way of explaining patients’ inherent decision processes and to be sensitive towards varying levels of elaboration. Similar tools based on the theory of planned behaviour could be applied to other decision making scenarios.


Articles from BMC Medical Informatics and Decision Making are provided here courtesy of BioMed Central