Treatment Compliance

Treatment compliance is defined as the degree to which patients’ behaviors (e.g., attending follow-up appointments, engaging in preventive care, following recommended medical regimens) correspond with the professional medical advice prescribed. The terms compliance and adherence are often used interchangeably; however, because compliance may carry a negative connotation, some prefer to use adherence to emphasize patients’ active roles in healthcare management as opposed to the submissiveness suggested in the definition of compliance. This distinction in definition acknowledges that patients and providers can move away from the patriarchal model of health care, promotes patient autonomy, and takes into account evidence suggesting that those who adhere steadfastly to providers’ instructions may not be the healthiest psychologically or physically. While the patient’s active role is considered vital in committing to a treatment regimen, for the purposes of this overview, the term compliance is utilized to maintain consistency.

Treatment Compliance Rates and Consequences of Noncompliance

When adults are diagnosed with chronic illnesses, they are often inundated with treatment options. Outright refusal to accept treatment is rare. Many who initially refuse later comply. As M. Robin DiMatteo found, on average, 75.2% of adults with chronic illnesses comply with prescribed treatments. While compliance rates for behavioral interventions (e.g., exercise regimens, smoking cessation) are consistently lower than this average (ranging from 40% to 75%), patients attend scheduled appointments at higher rates (up to 90%). Interestingly, despite the shift toward greater patient decision-making autonomy, across treatment regimens compliance rates have increased from 62.6% prior to 1980 to 76.3% thereafter. Among adults, highest compliance rates are documented for human immunodeficiency virus (HIV), arthritis, and gastrointestinal disorders. While an estimated 50% of children and adolescents with chronic illnesses fully comply with medical recommendations, rates fluctuate depending on the illness. Among children and adolescents with cancer, compliance ranges from 40% to 66%. Compliance for sickle cell disease ranges from 49% to 79%; approximately 66% of patients with cystic fibrosis and diabetes fully comply.

The consequences of noncompliance lie on a continuum ranging from relatively no direct patient risk to severely increased morbidity and mortality and an increased global threat of treatment-resistant diseases. Additionally, noncompliance results in medical resource waste and large-scale medical industry monetary losses exceeding $100 billon per year.

Assessing Treatment Compliance

Self-Reports

Self-reports are commonly used to assess compliance. Examples include Likert scale questionnaires, handheld computers, and phone diaries. Although self-report measures are the simplest measures to use, report bias and recall precision issues often make results inaccurate. These inaccuracies can result in over-reporting, because patients may answer questionnaires consistently with what they believe promotes support and approval from providers. Underreporting is also concerning, with some research suggesting higher compliance when using objective measures as compared to self-reports. Despite challenges involved and acknowledgment that self-reports should be interpreted cautiously, because of their practicality, research supports using self-reports in clinical settings.

Objective Measures

Pill counts, electronic bottles, and urine or blood serum levels are examples of objective measures of compliance. Although these measures can be expensive, many lessen opportunities for recall bias and human error via electronic tracking (e.g., counting number of puffs pressed on an inhaler). While they cannot guarantee that the patient completed the treatment, increased accuracy has been reported when using objective measures of compliance. Parents also report feeling more comfortable allowing their children to take control of treatment protocols when such devices are utilized.

Collateral Reports

A third method of measuring compliance is through reports by family and healthcare providers. Although this method is rarely used, except with young children, it can be valuable to compare self-reports to reports from third parties.

Correlates and Predictors of Treatment Compliance

Adults

Compliance increases when patients believe treatments are necessary and important. Healthcare providers play a critical role in this process by helping patients weigh the risks and benefits while taking into consideration social contexts and perceived barriers. Successful compliance also requires that an individual develops the motivation and self-efficacy required to confront a long-term stressor.

Decision-making autonomy enables the patient to feel more control and self-responsibility, perceive treatments as valuable, and achieve increased quality of life (QOL). Noncompliance risk factors include distress, perceived vulnerability, patient characteristics (e.g., demographics, social support), disease and treatment variables (e.g., complexity, side effects), contextual factors (e.g., provider-patient relationship, media exposure), and cognitive functioning (e.g., memory).

Examples of predictors of compliance are readily available. Online surveys find that most cancer patients and providers believe good communication promotes compliance; unfortunately, relatively few providers are comfortable discussing alternative or complementary therapies. Additionally, research among HIV/AIDS (acquired immune deficiency syndrome) patients suggests that poor social support, underestimation of illness severity, lack of factual information (e.g., not knowing the difference between HIV and AIDS), healthcare system distrust, side effects, and beliefs that medications are ineffective all decrease compliance.

Most research shows no major differences in compliance based on gender, marital status, country of birth, or primary language. Although conflicting findings exist with respect to the relationship between ethnicity and compliance across chronic illnesses, as compared to European Americans, fewer minority HIV-positive patients comply with treatment. Income-specific factors combined with high treatment costs also play a role in lower compliance rates, and many patients state that they must cut back on necessities like food or heat to pay for medications.

Children and Adolescents

For children and adolescents, treatment compliance is influenced by numerous factors. In general, females are more compliant than males, and adolescents are less compliant than younger children. Among adolescents, researchers report that compliance may be related to adolescents’ needs for independence combined with their willingness (or lack thereof) to accept the authority of healthcare providers. For example, research suggests that a cancer diagnosis coupled with cognitive impairments resulting from aggressive treatments predicts poorer decision-making abilities, including higher incidences of high-risk behaviors (e.g., smoking, drug use). Self-esteem, cognitive and social functioning, lower socioeconomic status, lower parent education, feelings of invincibility, illness knowledge, perceived vulnerability, treatment complexity, emotional problems, and prevailing psychiatric illness also relate to compliance.

The overall strength of the parent-child relationship, including communication and familial organization, is crucial in successfully treating chronic illnesses. Parents must be prepared to complete a variety of tasks ranging from administering medications to assisting medical staff with invasive procedures. A lack of cooperation between parents and children and parenting inconsistency can result in added emotional distress, exacerbation of behavioral problems, and lowered compliance with medical protocols and other daily tasks. When anxious parents are overly restrictive, adolescents are less likely to follow prescribed treatments.

Predictors and correlates of compliance also vary by specific illness. For asthma patients, inadequate healthcare access, limited disease knowledge, inability to seek emergency care, conflicts with healthcare providers, family dysfunction, and poverty are all barriers. Among childhood cancer patients, noncompliance is more likely once maintenance therapy is introduced, because the most acute phase of treatment is administered by professionals, making noncompliance less probable. Children with sickle cell disease or juvenile rheumatoid arthritis are usually compliant with pain management interventions but may not comply with behavioral exercises and other treatments due to side effects and the amount of time required. In addition to time constraints, cystic fibrosis treatment can promote family conflict. Regardless of the specific illness, children and adolescents with chronic illness often report fears that compliance will interrupt typical life activities and change how they are perceived by peers.

Theory and Interventions Promoting Treatment Compliance

Adults

Several extant theories suggest factors fostering treatment compliance. Often these theories serve as foundations for interventions designed to increase behavioral compliance. Examples include the health belief model by Marshall Becker and colleagues, which states that compliance is related to beliefs about illness severity and treatment regimen benefits as well as vulnerability perceptions. Irwin Rosenstock and colleagues’ health benefits model add that patients will weigh the treatment costs and benefits before deciding whether to perform the recommended behaviors. Individuals who view themselves as more vulnerable or who view their illness as very serious are likely to exhibit greater compliance with health behaviors, thereby promoting positive outcomes. The role of self-efficacy, included in models such as Howard Leventhal’s self-regulatory model of illness and Ronald Roger’s protection motivation theory, is also salient in that patients displaying higher levels of confidence in their ability to complete treatment are more likely to succeed.

The way in which treatment is offered to patients can help promote compliance. Home health care increases compliance by increasing satisfaction with staff and decreasing treatment administration wait times. As com-pared to home health care, similar improvements in compliance are identified through educational interventions aimed at enhancing disease and treatment knowledge and through behavioral interventions, which assist with pain management and pill-taking procedures. Healthcare providers often also emphasize relaxation therapy and systematic desensitization to control side effects and promote compliance, although these approaches are less empirically supported.

A recent review of interventions targeting hypertension, schizophrenia and psychosis, asthma, depression, HIV, diabetes, rheumatoid arthritis, and epilepsy found that certain interventions work better for specific illnesses. Complex interventions involving care at the worksite, special pill containers, counseling sessions, phone calls, information pamphlets, workbooks, and support groups successfully increase compliance for hypertension and asthma. For patients with diabetes, self-care educational calls with a nurse work well, whereas individual counseling promotes compliance among HIV and epilepsy patients. Disease and drug informational pamphlets and teaching self-monitoring techniques also enhance compliance among those with epilepsy. Family therapy and individual educational sessions work best for individuals with schizophrenia and psychosis. Among patients with depression, informational pamphlets and drug counseling decrease depressive symptoms, decrease relapses, and increase compliance. When patients are depressed and have a chronic illness, behavioral therapies have successfully extinguished depressive symptomology and increased reinforcement of healthy behaviors, including treatment compliance.

Children and Adolescents

As Dennis Drotar argued, when developing interventions promoting compliance among children and adolescents, special considerations are required. Specifically, it is necessary to include the entire family in facilitating change. A well-developed intervention sets its own unique objectives, identifies risk factors, and works to enhance resilience factors and competencies. The underlying theory must be identifiable. If an intervention is successful but the theory cannot be identified, it will be nearly impossible to identify the mechanism of change. Many competing theories involving the entire family have been utilized to explain barriers to compliance. Examples include models that aim to separate risk factors, such as psychological stressors and functional independence, from resilience factors, such as dispositional traits and coping ability (James Varni and Jan Wallander’s disability, stress, and coping model) and models focusing on the family’s level of stress and burden as predictors of aversive outcomes (Reuben Hill’s ABCX family crisis model).

Three primary strategies exist in intervening to encourage compliance. Educational interventions focus on teaching families about the child’s disease, treatment requirements, and self-management proficiencies. Organizational interventions work to modify the physical healthcare setting to make it more welcoming and accommodating. This may include decreasing wait times and increasing the frequency of follow-up care. Behavioral interventions include stimulus control techniques that utilize visual cues and written reminders, self-control techniques (i.e., self-monitoring medication use), and reinforcement control techniques (i.e., token economies).

Treatment plans and interventions must be determined with a great deal of individualization based on the needs of each child. For example, among children with asthma, compliance is often problematic, because the disease can be unpredictable with long symptom-free periods. Plans for preventive care, avoidance of triggers, and promotion of medication compliance are all necessary and are enhanced through simple behavioral interventions such as teaching how and when to use medications, goal-setting techniques, and self-management skill development. Healthcare providers must also be taught to provide developmentally appropriate written or pictorial explanations of their recommendations. Across varying types of chronic illnesses, healthcare providers who are willing to spend extra time communicating, supporting, and supervising care are more likely to achieve better compliance.

Future Research Considerations

For interventions to be effective, researchers and healthcare providers must first understand the predictors of successful compliance and factors encouraging noncompliance, including the patient’s emotional status, culture, and belief system. Healthcare providers often play a primary role in influencing a patient’s belief systems. It is commonly understood that patients must trust healthcare providers before complying with treatment; however, research must work to specify precisely how variables such as rapport, mutual respect, empathy, and humanism impact compliance. The examination of what types of information patients can absorb at certain stages of their diagnoses and treatments and how practitioners engage patients in the decision-making process are also pertinent. There are many other questions that remain unanswered as well. Several of these questions center on patient beliefs such as determining the role of prognosis, illness severity, denial, guilt, and alternative or homeopathic therapies on compliance. Practical matters like daily chronic stressors, motivation, peer influences, emotional distress, family dysfunction, and family cohesiveness also require further investigation.

References:

  1. DiMatteo, M. R. (2004). Variations in patients’ adherence to medical recommendations: A quantitative review of 50 years of research. Medical Care, 42, 200-209.
  2. Drotar, D. (Ed.). (2006). Psychological interventions in childhood chronic illness. Washington, DC: American Psychological Association.
  3. Horne, R., & Weinman, J. (1998). Predicting treatment adherence: An overview of theoretical models. In L. B. Myers & K. Midence (Eds.), Adherence to treatment in medical conditions (pp. 25-50). Amsterdam: Harwood Academic.
  4. Ievers-Landis, C. E., & Drotar, D. (2000). Parental and child knowledge of the treatment regimen for childhood chronic illnesses: Related factors and adherence to treatment. In D. Drotar (Ed.), Promoting adherence to medical treatment in chronic childhood illness: Concepts, methods, and interventions (pp. 259-285). Mahwah, NJ: Lawrence Erlbaum.
  5. Kennard, B. D., Stewart, S. M., Olvera, R., Bawdon, R. E., hAilin, A. O., Lewis, C. P., et al. (2004). Nonadherence in adolescent oncology patients: Preliminary data on psychological risk factors and relationships to outcome. Journal of Clinical Psychology in Medical Settings, 11, 30-39.
  6. Lemanek, K. L. (2004). Adherence. In R. T. Brown (Ed.), Handbook of pediatric psychology in school settings (pp. 129-148). Mahwah, NJ: Lawrence Erlbaum.
  7. Manne, S. L., Miller, D. L., & Meyers, P. (1999). Difficulties completing treatment tasks among newly diagnosed children with cancer. Children’s Health Care, 28, 255-276.
  8. McDonald, H. P., Garg, A. X., & Haynes, R. B. (2002). Interventions to enhance patient adherence to medication prescriptions: Scientific review. Journal of the American Medical Association, 288, 2868-2879.
  9. Oggins, J. (2003). Notions of HIV and medication among multiethnic people living with HIV. Health & Social Work, 28, 53-62.
  10. Peterman, A. H., & Cella, D. F. (1998). Adherence issues among cancer patients. In S. A. Shumaker, E. B. Schron, J. K. Ockene, & W. L. McBee (Eds.), The handbook of health behavior change (2nd ed., pp. 462-182). New York: Springer.
  11. Quittner, A. L., & Espelage, D. L. (2000). Measuring adherence to medical treatments in childhood chronic illness: Considering multiple methods and sources of information. Journal of Clinical Psychology in Medical Settings, 7, 41-54.
  12. Roberts, C., Benjamin, H., & Chen, L. (2005). Assessing communication between oncology professionals and their patients. Journal of Cancer Education, 20, 113-118.
  13. Simoni, J. M., Frick, P. A., & Huang, B. (2006). A longitudinal evaluation of a social support model of medication adherence among HIV-positive men and women on antiretroviral therapy. Health Psychology, 25, 74-81.
  14. Taylor, S. E., Kemeny, M. E., Reed, G. M., Bower, J. E., & Gruenewald, T. L. (2000). Psychological resources, positive illusions, and health. American Psychologist, 55, 99-109.

See also: