Compliance: Speaking the Patient's Language
Drs. Kathryn Lauten and Ulla Connor explain how insights from linguistic and behavioral research can help predict and improve adherence.
By on Apr 6, 2010Drs. Kathryn Lauten and Ulla Connor explain how insights from linguistic and behavioral research can help predict and improve adherence.
A recent position paper asserts that current adherence theories are better at explaining than at improving. This is a central theme for Kathryn Lauten, associate director at the Indiana Center for Intercultural Communication (ICIC). She has extensively researched the role of linguistics in treatment adherence, in a population of diabetes patients.
Lautens research comprises qualitative interviews, in which patients were questioned about their health and treatment, and more directed questioning on, for example, sources of information they found helpful. All of this is based on a definition of health literacy as the degree to which individuals have the capacity to obtain, process and understand basic health information and services needed to make appropriate health decisions. Lauten says this indicates a need to know your patient.
Health literacy and adherence
For example, there is no point in referring patients to a Website if they don't use the Internet (yes, there are people who don't). Various authorities have drawn attention to the variation in health literacy among segments of the population. But health literacy alone, while a huge part of the equation, does not have a causal relationship necessarily with adherence, or if it does there are other factors involved, says Lauten. While good research has been done to show that improving poor health literacy does improve adherence, there are other issues that need to be understood.
Therefore the research at ICIC focuses on the relationships between patient-related factors and adherence, which means understanding what the patient factors are, Lauten explains. Adherence is a function of many things, including knowledge about the disease (in this case, diabetes), personal worldviews, confidence to act, and emotions.
Adherence and type 2 diabetes patients
The research was designed to explain non-adherence among type 2 diabetes patients, which required determining how information was obtained and used by patients, and to understand the construct of adherence through the lens of the patients' life stories, according to Lauten. The latter is underpinned by the application of linguistic and behavioral theories.
Lauten describes the development of an adherence model that tests the association between self-reported adherence and several components of health literacy, based on previously published studies. Lauten reports the emergence of extraordinarily rich data from the study. In particular, she highlights the need for plain language communication by providers and the elimination of jargon.
The rich data largely come from the extremely detailed analysis of patient interviews, with non-verbal communication captured and coded along with the words. In this way, the affective (emotional) aspects can be analyzed. This is well-established linguistic practice, explains Lauten, which has resulted in the development of a model that can predict adherence and improve it.
The psychology of adherence
Dr. Ulla Connor, ICIC director, explains that the development of the prediction model fell into two stages. The first stage started with psychological constructs previously shown to be associated with adherence. These are life orientation, agency, and emotion. We [then] used current linguistic theories to determine linguistic patterns in patients' life stories, she says. These linguistic features were correlated with the constructs and associated with adherence data.
For example, language patterns in the life orientation construct are divided into internal adherence related concepts (patients feel in control) and external ones (patients feel others are controlling them). Connor defines agency as referring to patients' language about actions regarding health.
Again, language divides patients into two agentive' domains. The more agentive patients are concerned with following advice and do it well, whereas the less agentive worry about what they should do and do it poorly.
Life stories
Within the emotion construct, Connor also identifies two domains. In the diabetes study, negative patients reacted badly to their diagnosis, whereas positive patients built good relationships with their doctors and were motivated by progress, by losing weight, for example. Overall, the methodology has been validated by using independent raters and shows good inter-rater validity.
The second stage of development involved the translation of patients' life stories', using linguistic analysis, into a 15-minute predictor survey. Connor explains that the process can be compressed to such an extent because the questions in the survey enable the patient to identify with the language of the questions. The predictor is available from Connor's company Comac Analytics. Although validated in diabetes, it is adaptable to other diseases. It enables the doctor to know more about what motivates a patient, she concludes.