Reliability and validity of the patient activation measure in hospitalized patients
Introduction
The concept of “patient engagement” has become increasingly important in recent years [1]. Patient engagement is a construct that includes self-efficacy, behavior, and knowledge, and has been shown to predict a variety of health behaviors [2]. Engaging patients in their care is the focus of many public- and private-sector initiatives and programs [3], [4], [5]. There is no single definition of patient engagement, nor is there a universally agreed-upon tool for measuring this concept. To date, the most frequently used instrument for measuring patient engagement is the Patient Activation Measure (PAM) [6], [7], [8], [9].
The PAM-13 is a 13-item self-reported measure designed to assess patients’ knowledge, skills and confidence in managing their health. The PAM-13 also describes the extent to which patients are informed and involved in their healthcare [6]. The PAM-13 has been validated in multiple outpatient populations including multi-morbid older adults and multiple sclerosis patients, and in relation to employee health characteristics [10], [11], [12]. It has strong psychometric properties, with high internal consistency and construct validity [10], [11], [12]. Recent studies involving the PAM have found that higher patient activation levels were correlated with improved health outcomes over time including better clinical indicators (e.g., not being obese, having high-density lipoprotein and triglycerides in normal ranges), more healthy behaviors, better self-management, greater use of preventive screening tests, and lower use of costly healthcare services [13], [14].
While the PAM has become a widely used tool in outpatient care settings, its applicability to patients in the hospital is not well established [15]. Validating the PAM-13 in the inpatient setting is important as there are over 35 million hospital admissions each year [16] and interventions to impact patient engagement in the hospital are becoming more commonplace [8], [17], [18], [19]. The purposes of this paper are 1) to describe the psychometric properties (internal consistency reliability and construct validity) of the PAM-13 for hospitalized cardiology and oncology patients with planned and unplanned admissions; and 2) conduct an exploratory analysis to examine the predictors of low activation in the same population.
Section snippets
Study design
We first evaluated the internal consistency reliability of the PAM-13 in the inpatient setting. The construct validity of the PAM-13 was then assessed using two approaches: expected known-groups differences of PAM-13 levels and convergence of PAM-13 levels with other measures.
The purpose of validation using known-group differences was to systematically evaluate whether the PAM-13 instrument would discriminate between two known groups (unplanned admissions versus planned admissions) expected to
Results
Participant characteristics are described in Table 1. The average age in our cohort was 64 years, (range = 22–102). The majority of the participants were male (65%), 13% were black, 9% were Asian, 9% reported their race as “other” or were multi-racial, and 16% were Hispanic/Latino. Almost one-fifth (18%) of the participants reported their income level as “not having enough money to make ends meet”.
Discussion
This study provides evidence for the internal consistency reliability and the construct validity of the PAM-13 instrument for use in the inpatient setting. The study also confirms that type of admission is important to consider when analyzing PAM levels. There was a significant difference in PAM levels between hospitalized patients with unplanned compared to planned admissions, no differences in the PAM levels between cardiology and oncology service lines, and specific demographic variables
Conflicts of interest
None.
Funding
This study was funded by the Agency for Healthcare Research and Quality [R01-HS021816]. The authors gratefully acknowledge funding for Dr. Ruth Masterson Creber by the National Institute of Nursing Research (NINR) of the National Institutes of Health (NIH) under Award Number, K99NR016275, “mHealth for Heart Failure Symptom Monitoring.” Her post-doctoral funding was also funded by NIH/NINR (T32NR007969) at Columbia University School of Nursing. The content is solely the responsibility of the
Acknowledgments
None.
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