Health behaviour
When activation changes, what else changes? the relationship between change in patient activation measure (PAM) and employees’ health status and health behaviors

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Abstract

Objective

To test whether changes in the patient activation measure (PAM) are related to changes in health status and healthy behaviors.

Methods

Data for this secondary analysis were taken from a group-randomized, controlled trial comparing a traditional health promotion program for employees with an activated consumer program and a control program. The study population included 320 employees (with and without chronic disease) from two U.S. companies: a large, integrated health care system and a national airline. Survey and biometric data were collected in Spring 2005 (baseline) and Spring 2007 (follow-up).

Results

Change in PAM was associated with changes in health behaviors at every level (1–4), especially at level 4. Changes related to overall risk score and many of its components: aerobic exercise, safety, cancer risk, stress and mental health. Other changes included frequency of eating breakfast and the likelihood of knowing about health plans and how they compare.

Conclusion

Level 4 of patient activation is not an end-point. People are capable of continuing to make significant change within this level.

Practice implications

Interventions should be designed to encourage movement from lower to higher levels of activation. Even people at the most activated level improve health behaviors.

Introduction

Health care providers are increasingly recognizing that advances in medical technologies are not enough to improve the quality and length of people's lives. Individuals must be active participants in their health care to reap the benefits of these advances [1]. The need for greater patient involvement will be magnified as an aging population inexorably produces a higher prevalence of chronic conditions and as health care costs increasingly shift to the individual. This shift in accountability for self-health management will lead to a need for individuals to engage in health care consumer behaviors and self-care skills that many may not be ready to assume.

The complexity of understanding and improving health-related behaviors cannot be underestimated given the many factors that influence how individuals change behaviors to improve their health. Numerous psychological, behavioral and sociological models have been developed to help health education practitioners understand how individuals make decisions related to their health [2]. Concepts of patient activation have provided an additional framework with which to understand an individual's capacity for health behavior change. Patient activation is defined as an individual's ability and willingness to take on the role of managing his or her health and health care [3]. A relatively new construct, the patient activation measure (PAM) was developed to assess an individual's knowledge, skills and confidence in managing his or her health [4]. According to Hibbard and colleagues, activation occurs at four levels. Level 1: does not yet grasp the need to play an active role in personal health. Level 2: lacks knowledge and confidence to act. Level 3: is beginning to take action. Level 4: has adopted new behaviors but may not be able to maintain them under stress.

Individuals with higher PAM scores have been shown to be more likely to perform self-management behaviors, use self-management services and report higher medication adherence [5]. Findings from one longitudinal study of individuals with chronic disease revealed that positive changes in activation were related to positive changes in a variety of self-management skills such as engaging in regular exercise, managing stress, paying attention to diet and taking diabetes medications [6]. Further analysis of the PAM scores in a population with at least one chronic disease has shown that activation level is correlated with disease-specific behaviors. Highly activated individuals with diabetes were found to be more likely to a take medication as directed, read food labels and read side effects when prescribed a new medication. Similar behaviors were observed in highly activated patients with cardiovascular disease [7]. In a study of a worksite population, the PAM was shown to have a strong positive relationship with measures of health behavior, health information-seeking and readiness-to-change [8].

To extend understanding of the PAM, we used longitudinal data to investigate how changes in PAM scores are related to changes in health behavior and health status in an employer-based population of individuals with and without chronic disease. In addition, we examined how changes in activation levels contributed to changes in health status and behavior at each of the four levels of activation.

Section snippets

Study design and subjects

Data for this secondary analysis were taken from survey and biometric information collected during a group-randomized, controlled trial in Spring 2005 (baseline) and Spring 2007 (follow-up) [9]. This trial tested two different employer-based health-promotion programs—a traditional health promotion program and an activated consumer program—compared with a control program. The traditional health improvement program topics included physical activity, nutrition, injury prevention and stress

Overall changes in activation

The PAM change score had a range of −33–50. The mean change was 4.31; the median was 3.0.

Gains in PAM decreased as the baseline stage increased (Fig. 1). Those at baseline in Level 1 (N = 27) made the greatest gains; their average PAM score increased from 44.2 to 61.5 (P < 0.0001). The PAM score for those in level 2 at baseline (N = 29) increased from 51.8 to 63.9 (P < 0.0001). The average PAM score for participants in level 3 (N = 95) at baseline increased from 61.0 to 68.1 (P < 0.0001). For those in

Discussion

In the underlying study from which our data are drawn, PAM scores significantly improved, with a mean change of 4.31. A change of more than 4 points has been shown to be associated with important differences in health behaviors in cross-sectional analyses, such as frequency of eating breakfast and ability to recognize reliable health websites [8]. Cross-sectional information, while suggestive, is not sufficient to understand potential causal pathways. The data presented here help to explore the

Conflict of interest

None.

Acknowledgments

This study was funded by grant #1 RO1 DP000104-01 from the Centers for Disease Control and Prevention. Additional support was provided by the Park Nicollet Institute. The authors thank Judith Hibbard for advice on use of the patient activation measure.

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