Usefulness scale for patient information material (USE) - development and psychometric properties

Lars P Hölzel, Zivile Ries, Jörg Dirmaier, Jördis M Zill, Levente Kriston, Christian Klesse, Martin Härter, Isaac Bermejo, Lars P Hölzel, Zivile Ries, Jörg Dirmaier, Jördis M Zill, Levente Kriston, Christian Klesse, Martin Härter, Isaac Bermejo

Abstract

Background: One economical way to inform patients about their illness and medical procedures is to provide written health information material. So far, a generic and psychometrically sound scale to evaluate cognitive, emotional, and behavioral aspects of the subjectively experienced usefulness of patient information material from the patient's perspective is lacking. The aim of our study was to develop and psychometrically test such a scale.

Methods: The Usefulness Scale for Patient Information Material (USE) was developed using a multistep approach. Ultimately, three items for each subscale (cognitive, emotional, and behavioral) were selected under consideration of face validity, discrimination, difficulty, and item content. The final version of the USE was subjected to reliability analysis. Structural validity was tested using confirmatory factor analysis, and convergent and divergent validity were tested using correlation analysis. The criterion validity of the USE was tested in an experimental design. To this aim, patients were randomly allocated to one of two groups. One group received a full version of an information brochure on depression or chronic low back pain depending on the respective primary diagnosis. Patients in the second group received a reduced version with a lower design quality, smaller font size and less information. Patients were recruited in six hospitals in Germany. After reading the brochure, they were asked to fill in a questionnaire.

Results: Analyzable data were obtained from 120 questionnaires. The confirmatory factor analysis supported the structural validity of the scale. Reliability analysis of the total scale and its subscales showed Cronbach's α values between .84 and .94. Convergent and divergent validity were supported. Criterion validity was confirmed in the experimental condition. Significant differences between the groups receiving full and reduced information were found for the total score (p<.001) and its three subscales (cognitive p<.001, emotional p=.001, and behavioral p<.001), supporting criterion validity.

Conclusions: We developed a generic scale to measure the subjective usefulness of written patient information material from a patient perspective. Our construct is defined in line with current theoretical models for the evaluation of written patient information material. The USE was shown to be a short, reliable and valid psychometric scale.

Figures

Figure 1
Figure 1
Structure of the theoretical model.

References

    1. Bunge M, Mühlhauser I, Steckelberg A. What constitutes evidence-based patient information? Overview of discussed criteria. Patient Education and Counseling. 2010;78:316–28. doi: 10.1016/j.pec.2009.10.029.
    1. Charnock D, Shepperd S, Needham G, Gann R. DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health. 1999;53:105–11. doi: 10.1136/jech.53.2.105.
    1. Moult B, Franck LS, Brady H. Ensuring quality information for patients: development and preliminary validation of a new instrument to improve the quality of written health care information. Health Expect. 2004;7:165–75. doi: 10.1111/j.1369-7625.2004.00273.x.
    1. Charvet-Berard AI, Chopard P, Perneger TV. Measuring quality of patient information documents with an expanded EQIP scale. Patient Educ Couns. 2008;70:407–11. doi: 10.1016/j.pec.2007.11.018.
    1. Doak CC, Doak LG, Root JH. Teaching Patients With Low Literacy Skills. Philadelphia: Lippincott Williams and Wilkins; 1985.
    1. Garner M, Ning Z, Francis J. A framework for the evaluation of patient information leaflets. Health Expect. 2012;15:283–94. doi: 10.1111/j.1369-7625.2011.00665.x.
    1. Dixon-Woods M. Writing wrongs? an analysis of published discourses about the use of patient information leaflets. Soc Sci Med. 2001;52:1417–32. doi: 10.1016/S0277-9536(00)00247-1.
    1. Bettinghaus EP. Health promotion and the knowledge-attitude-behavior continuum. Prev Med. 1986;15:475–91. doi: 10.1016/0091-7435(86)90025-3.
    1. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 1989;13:319–40. doi: 10.2307/249008.
    1. Venkatesh V. Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inform Syst Res. 2000;11:342–65. doi: 10.1287/isre.11.4.342.11872.
    1. Slawson DC, Shaughnessy AF, Bennett JH. Becoming a medical information master: feeling good about not knowing everything. J Fam Pract. 1994;38:505–13.
    1. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16:297–334. doi: 10.1007/BF02310555.
    1. Hölzel LP, Ries Z, Zill JM, Kriston L, Dirmaier J, Härter M, et al. Development and testing of culturally sensitive patient information material for Turkish, Polish, Russian and Italian migrants with depression or chronic low back pain (KULTINFO): study protocol for a double-blind randomized controlled trial. Trials. 2014;15:265. doi: 10.1186/1745-6215-15-265.
    1. Koo MM, Krass I, Aslani P. Evaluation of written medicine information: validation of the consumer information rating form. Ann Pharmacother. 2007;41:951–6. doi: 10.1345/aph.1K083.
    1. Pluye P, Granikov V, Bartlett G, Grad RM, Tang DL, Johnson-Lafleur J, et al. Development and Content Validation of the Information Assessment Method for Patients and Consumers. JMIR Res Protoc. 2014;3:e7. doi: 10.2196/resprot.2908.
    1. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling J. 1999;6:1–55. doi: 10.1080/10705519909540118.
    1. Kriston L, Günzler C, Harms A, Berner M. Confirmatory factor analysis of the german version of the international index of erectile function (iief): a comparison of four models. J Sex Med. 2008;5:92–9.
    1. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 7. New Jersey: Prentice Hall; 2009.
    1. Schweizer K. Some guidelines concerning the modeling of traits and abilities in test construction. Eur J Psychol Assess. 2010;26:1–2. doi: 10.1027/1015-5759/a000001.
    1. Kline RB. Principles and Practice of Structural Equation Modeling, Third Edition. 3. New York City: The Guilford Press; 2010.

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