Treatment adherence is one of the many health barriers to disease infection control, especially for chronic conditions like TB and HIV/AIDS. Fernandez-Lazaro et al. (2019) define treatment adherence as the extent to which patients follow physician-prescribed medications and plans. Treatment programs that promote adherence mainly focus on the various health behaviors. This critical review looks at applying health behavior models on patients` adherence to the long-term treatments of TB and HIV/AIDS. Fernandez-Lazaro et al. (2019) further note that only a few existing interventions on treatment adherence for chronic illnesses integrate health behavior theories. Incorporating these theories could significantly contribute to developing more effective treatment adherence interventions, allowing them to be used across other health-related settings and issues.
Health behavior models can help design interventions by understanding the concerned issue and directing further research to transfer to other healthcare settings. Promoting TB and HIV/AIDS treatment adherence presents a challenge to health professionals and related programs. A study on long-term adherence to antiretroviral therapy in South Africa by Moosa et al. (2019) concluded that a <95% adherence level to treatment programs for chronic diseases can lead to drug resistance and reduced intervention efficacy, further increasing mortality and morbidity rates. TB and HIV/AIDS present varied challenges to treatment adherence. These two infectious diseases mainly affect vulnerable and marginalized populations, and they boast complex interventions and medications that can have severe side effects. Drug resistance for TB and HIV/AIDS poses a public health concern. At the same time, cultural and societal beliefs also affect the treatment adherence of TB and HIV/AIDS interventions, leading to stigmatization. Therefore, drug resistance and beliefs significantly make treatment adherence for TB and HIV/AIDS a health concern.
Delegate your assignment to our experts and they will do the rest.
Over the years, health professionals and researchers have designed interventions to foster long-term treatment adherence for chronic illnesses. However, Sheeran et al. (2017) note that only a few theories describe what these interventions do. There are many health behavior theories, making it hard to select an appropriate model when developing an intervention. This limitation impacts the progress health officials are pushing to promote patient adherence to long-term treatment plans and medication, especially where non-adherence behavior can lead to severe implications. There is a need to examine further the relevance of existing theories on long-term adherence for TB and HIV/AIDS interventions.
Long-term adherence to treatment can be categorized into several theoretical perspectives, each related to health behavior change. These theoretical perspectives include cognitive, behavioral, stage process, and self-regulatory. Sheeran et al. (2017) acknowledge that each perspective can have more than one theory. Moreover, Rahimi et al. (2019) indicate that the transtheoretical model is a new addition to the existing perspectives and has gained momentum in behavior change. Moving forward, this review will provide a brief analysis of each perspective and subsequent theories. The analysis will primarily focus on adherence to long-term treatment. Additionally, the analysis will describe each perspective's characteristics and evidence base, making relevant inferences to their applicability in treating TB and HIV/AIDS.
Behavioral Perspective
The behavioral perspective asserts that behavior change can be achieved through learning and conditioning. This perspective encompasses the behavior learning theory (BLT) that emphasizes the effect of the environment and the ability of the patient to learn skills critical to achieving adherence (Burgess et al., 2017). The learning perspective encompasses the principles of antecedents and consequences to influence behavior. In essence, antecedents are internal or external environmental cues that can influence patients to modify their behavior towards treatment. On the other hand, consequences are either rewards or punishments directed towards behavior change. The probability a patient will adhere to health-related instructions will depend on how they interact with the two principles.
Interventions that incorporate elements of this behavioral perspective can produce reasonable outcomes, especially in long-term treatment plans and medication for chronic diseases. Lisa (2020) notes that behavior-change-promoting strategies, such as reminders, can improve overall adherence to health issues, prevention, and treatment. However, Moosa et al. (2019) cautioned that interventions that include antecedents and rewards and approaches to behavior learning theory did not produce conclusive results. More research needs to be undertaken to ascertain the effectiveness of behavioral learning theories in treatment adherence. The behavior perspective has received much criticism for its inability to consider other influences on behavior change unrelated to antecedents and consequences (Lisa, 2020). For instance, the behavioral learning theory does not consider a patient's habits, past behavior, and difficulty accepting a diagnosis result. Moreover, the perspective does not incorporate an individualized approach to designing interventions. Improving interventions informed by this perspective must also integrate other theories and health behavior models.
Cognitive Perspective
The cognitive perspective in health behavior assumes that attitudes and beliefs along with future projections determine behavior change. Pagès-Puigdemont et al. (2016) highlight the social-cognitive theory (SCT), theory of reasoned action (TRA), health belief model (HBM), and the theory of planned behavior (TPB) as some theories of behavior change. Collectively, the cognitive perspective proposes that people will select an alternative action that will guarantee positive outcomes. However, the cognitive perspective shares a few weaknesses that impact its integration in designing health interventions. Theories under the cognitive perspective do not consider that non-volitional factors can also affect behavior change (Pagès-Puigdemont et al., 2016). Ultimately, the theories are ineffective in addressing the necessary skills required in fostering treatment adherence.
Health behavior model
The HBM has significantly been used to design interventions on disease prevention and health promotion. As the most commonly used model in describing health behaviors, it effectively predicts and explains the change. In essence, HBM asserts that behavioral change follows a rational approach that creates a balance between health barriers and an action plan (Tola et al., 2016). Further, the model's key elements primarily focus on a person's beliefs to predict their health behavior. Within the model, factors that influence a patient's health behavior include their perceived susceptibility, severity, benefits, benefits to action, cues to action, and self-efficacy (Tola et al., 2016). More specifically, the model ascertains that a person's susceptibility to an illness can influence their perceived threat to that health concern. At the same time, their perceived barriers and benefits of the disease also influence how they perceive the effectiveness of health behavior change.
In the HBM, socio-psychological characteristics impact the susceptibility and seriousness of the illness alongside the barriers and benefits of action. The perceived threat to disease is mainly influenced by internal or external action cues, such as symptom perception and health communication, respectively (Sheppard & Thomas, 2021). A high threat and benefit of action against a low barrier to action foster increased behavior change intervention engagement. In totality, each component of the HBM works independently to predict health behavior. The HBM is appropriate in designing long-term intervention programs, especially for TB and HIV/AIDS. The model can incorporate other theories for maximum effectiveness, with the recommended cues of action adequately communicated to the target population.
The HBM has received several criticisms that address its limitation in health behavior change and interventions. First, Tola et al. (2016) note that the relationship between the different variables of the model has not been clearly defined in recent literature. As such, assumptions are made to reflect how the variables are independent of each other. For instance, it is assumed that high perceived seriousness and low susceptibility are likely to lead to high action (Tola et al., 2016). This criticism is further aided by the assumption that people can access and share the same amount of information about the illness. In addition, the model assumes that the primary goal of any intervention using the HBM theoretical framework is healthy actions (Sheppard & Thomas, 2021). Secondly, HBM does not include individuals` social determinants of health behaviors. These determinants include their beliefs and attitudes that determine each person's acceptance of the health behavior.
Social-cognitive theory
The SCT emerged from the social learning theory and is one of the most comprehensive health behavioral models developed. SCT is a multifaceted model that is regulated by an individual's actions, motivation, and health. The theory also offers an implementation structure of adherence intervention and its promotional guidelines. Conn et al. (2016) acknowledge that this theory is guided by constant interaction between an individual's environment and behavior. According to the SCT, self-influences are equally significant alongside knowledge of the illness, risks, and benefits to achieve behavior change. Personal belief is one component of self-influences and plays a critical role in registering behavior change (Adefolalu, 2018). The result of a self-evaluation, either positive or negative health behavior, also falls under social determinant influences. Facilitators and perceived barriers are examples of other determinants, including social approval. Eliminating these barriers can lead to the desired behavioral change.
SCT proposes that behavior change occurs when an individual perceives control over the expected outcome in the long run. A strength of the SCT s that it can be easily implemented into many intervention designs. However, Conn et al. (2016) believe that the inability of SCT to consider other variables that could affect health behavior. More specifically, the theory only depends on the interactions between the individual, environment, and behavior. At the same time, SCT assumes that any environmental change will subsequently lead to behavioral change, a notion that might not be accurate (Adefolalu, 2018). Regardless of these limitations, SCT bases its perspective on learning, especially on human behavior. Behavior results from cognitive processes that humans acquire socially through knowledge gain (Adefolalu, 2018). The theory emphasizes that people act in a certain way after learning what to do and how to do it.
Bandura's conceptual model of reciprocal determinism, a central concept of SCT, further explains the interplay between an individual, the environment, and behavior. According to Adefolalu (2018), an individual interacts in cognitive, self-regulatory, and reflective processes to attain the desired outcome. In addition, behavior change is achieved through proactive control mechanisms on an individual's motivation, thought process, and actions. The conceptual model further asserts that when people do not aspire to change their behavior, they lose motivation and develop uncertainties over their capacity to enact change (Adefolalu, 2018). On the contrary, people who focus on achieving health promotion behaviors exhibit self-belief, controlling their actions, feelings, and thoughts. In the long run, people cautious of their self-management skills in health behavior can exercise cognitive processes that promote healthy lifestyles and well-being.
Knowledge acquisition of health risks alone cannot guarantee positive behavior change. Self-efficacy, a concept that posits that self-influences are essential in achieving the desired outcomes, is also a prerequisite of SCT (Adefolalu, 2018). In the long run, SCT as a theoretical framework can be implemented in long-term counseling interventions for patients diagnosed with chronic illnesses. TB and HIV/AIDS can utilize intervention-driven SCT to learn about these chronic diseases and what decisions need to be undertaken regarding their treatment challenges and long-term adherence. Additionally, HIV/AIDS support groups can use cognitive and behavioral strategies to motivate patients to manage challenges in antiretroviral therapy and its medication adherence, further fostering strong patient-physician relationships (Adefolalu, 2018). The support groups could also teach patients additional skills on self-belief and self-reflection, improving their overall clinical outcomes.
The theory of reasoned action/planned behavior
TPB and its associated TRA assert that appropriate behaviors are volitional and can be controlled by an individual. The person's intention to behave in a particular manner is a determinant and predictor for the change process. The TRA is well suited in exploring behavior from intention and its relationship with a person's beliefs, attitude, and overall behavior (Pagès-Puigdemont et al., 2016). Additionally, Rich et al. (2015) indicate that TPB is a modified version of TRA that includes a new construct to address its limitation. The additional construct, perceived behavioral control, explores an individual's belief to control a specific behavior. This new construct was included to gain an in-depth knowledge of behavior and related intentions beyond an individual's control.
Self-efficacy, norms, and attitudes influence TRA. Rich et al. (2015) note that behavioral intention is reflected by an individual's belief and attitude towards the behavior and whether people close to them approve of such intentions. Self-efficacy translates to a level of confidence the person exerts on performing or modifying a particular behavior. Social expectations and behavioral beliefs are two characteristics of TRA that further influence intention. An individual's view and attitude towards a specific health behavior, such as adherence to long-term treatment, are determined by their expectations of the outcome and how they value the result (Adefolalu, 2018). For instance, an individual will adopt a specific behavior to reduce the health risks when convinced of its intention and perceived outcomes.
The application of TRA and TPB in treatment adherence for TB and HIV/AIDS should consider several beliefs, attitudes, and social expectations within the target population. Adefolalu (2018) notes that such an intervention should measure previous adherence levels for chronic illnesses within that population, their intention to follow the medication and long-term treatment, and their attitude towards the initiative. Additionally, the intervention should encompass subjective norms and perceived behavioral control to ascertain its strengths and effectiveness in achieving the desired outcomes. Results from these interventions can inform health agencies and professionals on better ways to address attitudes, beliefs, and intentions, the three variables of TRA and TBA.
Self-Regulation Perspective
As the primary theory in this perspective, the self-regulatory theory focuses on the patient, examining a person's subjective experience on a health risk to understand how they respond and adapt to these threats. According to Phillips et al. (2016), individuals develop cognitive and emotional responses that combine new threats and previous experiences. These responses further determine the individual's coping mechanism, including the perceived consequences associated with past outcomes. Additionally, the theory assumes that people develop self-regulation against illnesses by avoiding health risk behaviors or immediately treating the disease. Achieving an equilibrium where the person forms coping strategies to manage health threats is influenced by cultural, social, and religious characteristics. The person's personality also plays a role in influencing coping strategies. While the self-regulatory theory offers an intuitive approach to designing health-related interventions, more research is needed to conceptualize how it can be implemented to address long-term treatment adherence to chronic illnesses.
The Stage Perspective
The transtheoretical model (TTM) falls under the stage perspective and posits that behavior change follows a series of steps to achieve the desired outcome. According to Rahimi et al. (2019), a person undergoes several pre-defined motivational steps of pre-contemplation, contemplation, determination, action, maintenance, and relapse. Additionally, the authors note that the model is not linear, and an individual can enter any of the named steps without following a specific path. For instance, a patient can enter the determination phase and relapse to previous stages immediately. TTM has been used to design many behavioral interventions for both individual and group sessions. However, Adefolalu (2018) cautions that people at different stages of the model exhibit different needs and preferences. As such, an effective behavioral intervention should be modeled to address the patient's specific needs at each step of the theoretical framework.
Applying Health Behavior Theories to Treatment Adherence for TB and HIV/AIDS
The o ptimal treatment adherence for chronic illnesses remains a contentious issue in health care. While several studies have explored the perception of treatment adherence to chronic diseases (Adefolalu, 2018; Fernandez-Lazaro et al., 2019; Moosa et al., 2019; Pagès-Puigdemont et al., 2016; Tola et al., 2016), literature on the adherence of TB and HIV.AIDS interventions remain limited. Given the limitations of these health behavior models to treatment adherence of chronic illnesses, further exploratory research is necessary to expand the existing knowledge on the application of health behavior models to treatment adherence for chronic illnesses. In addition, future research should also focus on examining the current theories rather than developing new ones. These existing theories have suggested several crucial attributes to health behavior change, including predicting and explaining behavioral change using modifiable factors (Adefolalu, 2018). The research should also explore the influence of non-volitional attributes on behavior change, more so external factors that individuals cannot control.
Conclusion
The adherence to treatment problems faced by patients diagnosed with chronic illnesses does not have a simple solution. Behavior change is a complex and multifaceted challenge to healthy lifestyles and patients` well-being. Health models provide an impulsive understanding of the underlying processes that foster change outcomes in adherence to medication. Theories of social-cognitive, behavioral learning, self-regulatory, transtheoretical model, planned behavior, and reasoned action are some frameworks behaviorists use to develop interventions for health behavior change. Each theoretical perspective has its advantages and limitations in addressing behavior change. Additionally, there is limited research on the applicability and effectiveness of these theories in designing interventions for long-term adherence treatment of TB and HIV/AIDS. The current health knowledge, beliefs, and attitudes cannot guarantee appropriate behavior change. However, individuals can influence behavior change through applying cognitive, behavioral, and social skills related to self-regulation and self-efficacy. TB and HIV/AIDS patients should demonstrate self-management skills and confidence in effecting behavior change. Moreover, they should foster positive beliefs towards their long-term treatment plans and interventions. Given the magnitude of adherence as a public health concern, especially for chronic illnesses, the theories provide a basis for understanding health risks and behavior change implications.
References
Adefolalu, A. O. (2018). Cognitive-behavioural theories and adherence: Application and relevance in antiretroviral therapy. Southern African Journal of HIV Medicine , 19 (1). https://doi.org/10.4102/sajhivmed.v19i1.762
Burgess, E., Hassmén, P., Welvaert, M., & Pumpa, K. (2017). Behavioural treatment strategies improve adherence to lifestyle intervention programmes in adults with obesity: A systematic review and meta-analysis. Clinical Obesity , 7 (2), 105-114. https://doi.org/10.1111/cob.12180
Conn, V. S., Enriquez, M., Ruppar, T. M., & Chan, K. C. (2016). Meta-analyses of theory use in medication adherence intervention research. American Journal of Health Behavior , 40 (2), 155-171. https://doi.org/10.5993/ajhb.40.2.1
Fernandez-Lazaro, C. I., García-González, J. M., Adams, D. P., Fernandez-Lazaro, D., Mielgo-Ayuso, J., Caballero-Garcia, A., Moreno Racionero, F., Córdova, A., & Miron-Canelo, J. A. (2019). Adherence to treatment and related factors among patients with chronic conditions in primary care: A cross-sectional study. BMC Family Practice , 20 (1). https://doi.org/10.1186/s12875-019-1019-3
Lisa, M. (2020). A Behavioral Learning Theory Public Health Education and Promotion Campaign Plan for COVID-19.
Moosa, A., Gengiah, T. N., Lewis, L., & Naidoo, K. (2019). Long-term adherence to antiretroviral therapy in a South African adult patient cohort: A retrospective study. BMC Infectious Diseases , 19 (1). https://doi.org/10.1186/s12879-019-4410-8
Pagès-Puigdemont, N., Mangues, M. A., Masip, M., Gabriele, G., Fernández-Maldonado, L., Blancafort, S., & Tuneu, L. (2016). Patients’ perspective of medication adherence in chronic conditions: A qualitative study. Advances in Therapy , 33 (10), 1740-1754. https://doi.org/10.1007/s12325-016-0394-6
Phillips, L. A., Cohen, J., Burns, E., Abrams, J., & Renninger, S. (2016). Self-management of chronic illness: The role of 'habit' versus reflective factors in exercise and medication adherence. Journal of Behavioral Medicine , 39 (6), 1076-1091. https://doi.org/10.1007/s10865-016-9732-z
Rahimi, A., Hashemzadeh, M., Zare-Farashbandi, F., Alavi-Naeini, A., & Daei, A. (2019). Transtheoretical model of health behavioral change: A systematic review. Iranian Journal of Nursing and Midwifery Research , 24 (2), 83. https://doi.org/10.4103/ijnmr.ijnmr_94_17
Rich, A., Brandes, K., Mullan, B., & Hagger, M. S. (2015). Theory of planned behavior and adherence in chronic illness: A meta-analysis. Journal of Behavioral Medicine , 38 (4), 673-688. https://doi.org/10.1007/s10865-015-9644-3
Sheeran, P., Klein, W. M., & Rothman, A. J. (2017). Health behavior change: Moving from observation to intervention. Annual Review of Psychology , 68 (1), 573-600. https://doi.org/10.1146/annurev-psych-010416-044007
Sheppard, J., & Thomas, C. B. (2021). Community pharmacists and communication in the time of COVID-19: Applying the health belief model. Research in Social and Administrative Pharmacy , 17 (1), 1984-1987. https://doi.org/10.1016/j.sapharm.2020.03.017
Tola, H. H., Shojaeizadeh, D., Tol, A., Garmaroudi, G., Yekaninejad, M. S., Kebede, A., Ejeta, L. T., Kassa, D., & Klinkenberg, E. (2016). Psychological and educational intervention to improve tuberculosis treatment adherence in Ethiopia based on health belief model: A cluster randomized control trial. PLOS ONE , 11 (5), e0155147. https://doi.org/10.1371/journal.pone.0155147
