A New View: Treatment Adherence from a Marketing Perspective

A New View: Treatment Adherence from a Marketing Perspective

K. Thurlow

The problem of non-adherence is wide-spread across ages and illnesses and can be easily considered a health concern (Howren, 2013). According to Lopez-Larrosa (2013; page 286), adherence to treatment is typically defined as “the context in which the individual’s behavior agrees with the health-related recommendations.” Approximately 50 percent of patients do not adhere to prescribed medication regimens. Non-adherence has been associated with increased mortality risk, hospitalization rates and healthcare costs (Jihara et al, 2014). Medication non-adherence has been estimated to cost upwards of $300 billion annually in avoidable medical spending in the USA (Howren et al, 2013). In their article, Why People Do Not Always Follow the Doctor’s Orders, marketing professors Makarem, Smith, Mudambi, and Hunt explore treatment adherence from a consumer point of view, comparing commonly used adherence interventions and general marketing strategies.

Makarem et al begin with a discussion of the literature, focusing on a call for research emphasizing the need to focus on consumers’ social problems and challenges such as health and nutrition, specifically related to the concepts of hope and perceptions of control. Despite the fact that an operational definition of hope is not provided until 4 pages later on page 461, the authors note that while psychology has been reluctant to engage in hope-related research, marketing research has and found that it affects consumer coping styles, as well as decisional ability, risk perception, information processing, and product evaluation. Makarem et al encourage a more individualized approach to health behaviors since consumers are motivated by different emotional and cognitive factors, as well as differing lifestyles, and expectations of daily regimens.

It is noted, however, that a framework of the processes related to adherence has yet to be developed, which should include factors related to health status, behavioral intentions, motivation, perceptions/locus of control, complexity of medication regimen, and beliefs about illness severity. Makarem et al do not attempt such a feat in this study, instead focusing on predictors of health behaviors related to hope and perception of control, as well as peripheral factors related to health care cost/spending, and patient self-management.

Makarem et al identify 7 different hypothesis, with an additional 5 dimensions related to hypothesis 7. Their population was recruited from test data previously collected on 222 patients diagnosed with type 2 diabetes. Participants were asked to complete online surveys measuring levels of hope and perceptions of control, as well as adherence to diabetes treatment regimens. The majority of participant ages ranged from 46 to 65 years and were predominantly Caucasian. Ninety-eight percent of participants had at least a high school diploma. Results discussing nothing regarding the original hypothesis (hope will positively affect adherence to medical treatment), but briefly discussed significant results related to self-efficacy and locus of control.

The authors noted two limitations of their study: the use of a cross-sectional research design and use of quantitative data. However, despite the psychological concepts explored within the study, the team did not include either a mental health or medical practitioner even for consultation purposes. Participants were selected from a pre-existing study population, were of limited age ranges, and diagnosed with type 2 diabetes, ultimately limiting the ability to generalize any findings to a wider population. Reliability of reporting is also a limitation as participants were asked to complete self-report questionnaires online based off of subjective recall instead of providing concrete, real-time reporting (i.e. number of prescriptions filled, doctor visits missed, blood sugar levels, etc.). An additional limitation of the study is the amount of hypotheses examined, limiting the amount of specific information to be gained by focusing on a narrowed area of interest. The hypotheses grew to feel redundant and limited in scope, adding little information to the overall study results.

Strengths of the study include the novelty of the study’s approach, i.e. applying consumer/marketing approaches to mental health/medical concerns, as well as exploring the potential relationship between emotion and adherence.

Overall, Makarem et al provided a thorough review of the literature and a justifiable rationale for further study of the potential relationship between emotion, perception of control, and adherence, but were limited by the measures used and lack of medically and/or psychologically trained personnel. Future studies would do well to include team members familiar with the topic of study, as well as measures able to provide less subjective, more concrete data.


Howren, M. B., Van Liew, J. R., & Christensen, A. J. (2013). Advances in Patient Adherence to Medical Treatment Regimens: The Emerging Role of Technology in Adherence Monitoring and Management. Social and Personality Psychology Compass, 7(7), 427-443.

Jihara, N., Nishio, T., Okura, M., Anzai, H., Kagawa, M., Houchi, H, & Y. Kirino, Y. (2014). Comparing patient dissatisfaction and rational judgment in intentional medication non-adherence versus unintentional non-adherence. Journal of Clinical Pharmacy and Therapeutics, 39, 45-52.

Lopez-Larrosa, S. (2013). Quality of Life, Treatment Adherence, and Locus of Control: Multiple Family Groups for Chronic Medical Illness. Family Process, 52, 685-696.

Makarem, S. C., Smith, M. F., Mudambi, S. M., & Hunt, J. M. (2014). Why People Do Not Always Follow the Doctor’s Orders: The Role of Hope and Perceived Control. The Journal of Consumer Affairs, 457-485.