Life Chaos and Intrinsic Motivation

Over the past decades, health services researchers have carefully investigated why patients have difficulty achieving optimal health outcomes. Initially, researchers focused on clear factors related to individuals and their social groups—gender, race/ethnicity, education level, socio-economic status. Consistently, researchers have found—across populations and countries—that the less resourced, less educated, and more marginalized the individual, the worse his or her health outcome. Yet, a spread of health outcomes existed within each of these socio-demographic groups. For instance, some disadvantaged patients are able to participate in their own chronic disease management, and have excellent health outcomes. Health services researchers then looked deeper, to the structure of patients’ life—their health beliefs, their ability to pay their bills, their personal support system, their familial environment, their degree of life chaos. Tools such as Matheny’s CHAOS scale (Confusion, Hubbub, and Order Scale) help measure the structure of patient’s lives, as they respond to statements such as: “my life is organized” or “my daily activities from week to week are unpredictable.” The addition of personal factors to demographic factors begins to account for a larger component of the variance in a person’s health outcomes, sometimes up to 20–30 %. Do health services researchers need to look deeper still, perhaps exploring how the structure of a person’s thoughts affects their behaviors? Insights into the relationship of confidence to behavioral outcomes has, for instance, led to new interventional techniques, such as motivational interviewing for tobacco cessation. Probing individual behavioral outcomes, Harvard psychologist Robert Kegan has asked: “Given reasonable intent, why do individuals have difficulty achieving their goals?” In other words, he asks: “Why do individuals seem immune to change?” His book, Immunity to Change, explores our intrinsic motivations and the hidden assumptions that drive our behaviors, considering how our mental frameworks shape our actions. He posits that many problems related to behavioral change stem from problems with adaptive change (adapting our mindset to influence our behaviors), as opposed to technical change (changing the structure of the task at hand). Moving an individual from a socialized mind, to a self-authoring mind, to a self-transforming mind may dramatically affect an individual’s ability to achieve their goals. Engaging and transforming individual intrinsic motivation may have broad applications for patient care, complimenting systems-level interventions to improve population health. This month in JGIM, authors explore health care outcomes variation in relationship to population-level health care delivery and personal patient factors. For instance, Okoro, et al., share the impact of increasing access to preventive services in Massachusetts as part of health care reform, showing a modest increase in preventive service utilization relative to other states.1 Schmidt’s capsule commentary expands on these thoughts, discussing other structural methods of increasing preventive services utilization, such as utilizing a patient-centered medical home model to engage patients.2 Anderson et al. explore the association between health care disparities and quality of care in different care models (accountable care organizations and smaller provider groups) for 3 million Medicare beneficiaries, finding that some quality measures varied based on provider structure (for instance, diabetic retinal examination), and varied unevenly based on patient characteristics, such as race.3 At a more personal level, Frank et al. explore the effects of life chaos on health care utilization, finding an almost twofold increase in emergency department visits amongst individuals who were recently incarcerated or paroled.4 Rose and Sanghani’s commentary on this study asks readers to consider the causal direction of these observed associations, exploring how health status (including mental health) may be related to criminality.5 In a qualitative study, Sabbatini et al. explore the nuanced trade-offs in health care utilization that physicians make while caring for their patients.6 They found that physicians consider not just best medical practice and relative cost of their decisions, but also patient time, preferences, logistics and constraints—to enable trust and care participation. Improving health care outcomes requires a multi-pronged approach of thoughtful system and personal engagement. As noted by studies in this month in JGIM, a keen understanding of patient behavioral drivers will facilitate targeted interventions by researchers and providers, to improve the health of patients and populations.