Adherence
Adherence has been defined by the World Health Organization (WHO) as: ‘The degree to which the person’s behaviour corresponds with the agreed recommendations from a health care provider’.
Non-adherence can be categorized into three different types:
Primary Non-Adherence: When a doctor writes a prescription, but the medication is never collected.
Non-Persistence: When a patient begins taking medication but stops without medical advice, often unintentionally due to misunderstandings or external factors such as cost or access.
Non-Conforming: When medication is not taken as prescribed, for example, missing doses or taking incorrect dosages.
In the UK, the rates of failing to attend GP appointments range from 2.9% to 11.7%, while in the USA, this can range from 5% to 55%.
Waste of Medication: Leads to economic consequences and the patient might not recover.
Time Lost: Healthcare workers spend time on patients who do not follow their treatment plans, instead of attending to those in need.
Progression of Illness: Patients may experience a worsening of their condition.
Increased Use of Medical Resources: Potential need for hospitalization, which is more expensive.
Reduced Functional Abilities: Illness may limit the patient's ability to work or care for dependents.
Lower Quality of Life: Resulting from the patient's decline in health.
Impact on Medical Research: Non-adherence hampers research due to incomplete data on treatment efficacy.
Taylor (1990): Suggested that 93% of patients fail to adhere to some aspect of treatment.
Sarafino (1994): Argued adherence is around 78% for short-term treatments and drops to 54% for chronic illnesses.
Becker (1972): Examined adherence in children taking antibiotics; found that over half the mothers stopped medication midway through a 10-day treatment.
Rational non-adherence refers to a deliberate choice to adjust medication due to factors including side effects, perceived effectiveness, and cost.
Aim: To identify factors contributing to rational non-adherence and examine the influence of specific medicines and backgrounds.
Sample: Representative online sample of 161 Australian participants across various demographics.
Method: Participants completed an online survey with three sections:
Questions on current medication use and attitudes.
Discrete Choice Experiment presenting hypothetical medication scenarios.
Background information collection.
Results:
No significant effect of symptom severity or alcohol use on adherence.
Background characteristics had negligible impact.
Monthly cost of medication was significant for those without private insurance.
Participants preferred medications that required less frequent administration but prioritized medication reducing health risks over convenience.
58% of participants prioritized harms over benefits in adherence decisions.
Conclusion: The risk of immediate side effects was deemed more critical than long-term effects, while medication effectiveness against mortality was prioritized.
Strengths:
Utilizes a representative sample enhancing generalizability.
Simulates real-world decision-making through the Discrete Choice Experiment.
Weaknesses:
Specificity to Australian culture may limit applicability elsewhere.
Potential exclusion of individuals with limited internet access.
Risk of response bias from socially desirable answering.
Reviewed multiple studies to assess cost-benefit analyses concerning adherence.
Investigated elderly patients with hypertension, considering both physical and psychological effects of medication.
Findings: Identified that side effects often outweigh perceived benefits, impacting patient adherence. Asymptomatic conditions present greater adherence challenges.
Limitations of Review Methodology: Older research may lack current relevance.
Benefits: Cross-comparison allows identifying patterns over time, enhancing holistic understanding.
Explains non-adherence via various factors:
Perceived Severity: Greater seriousness of illness correlates with higher adherence.
Perceived Susceptibility: Lower perceived risk leads to lower adherence.
Perceived Benefits: Doubts about treatment effectiveness reduce adherence likelihood.
Perceived Barriers: Financial, situational, or discomfort barriers negatively affect adherence.
Cues to Action: Triggers like personal experience with illness can enhance adherence.
Self-Efficacy: Confidence in managing treatment can improve adherence rates.
The model posits adherence is influenced by:
Evaluation of health threats.
A cost-benefit analysis of adherence versus non-adherence.
A study from 1971 involving 125 children showed how adherence correlated with parental concern for their child's health and trust in healthcare providers.
Real-World Application: Understanding non-adherence aids in developing interventions to improve adherence rates.
Individual vs. Situational Explanations: Laba’s approach includes individual and situational factors, while the Health Belief Model focuses on personal reasoning.
Reductionism vs. Holism: These studies highlight multifaceted reasons for non-adherence, challenging overly simplistic views.
Idiographic vs. Nomothetic: Laba employs quantitative methods while the Health Belief Model uses qualitative analysis, providing a nomothetic perspective to adherence issues
Adherence has been defined by the World Health Organization (WHO) as: ‘The degree to which the person’s behaviour corresponds with the agreed recommendations from a health care provider’.
Non-adherence can be categorized into three different types:
Primary Non-Adherence: When a doctor writes a prescription, but the medication is never collected.
Non-Persistence: When a patient begins taking medication but stops without medical advice, often unintentionally due to misunderstandings or external factors such as cost or access.
Non-Conforming: When medication is not taken as prescribed, for example, missing doses or taking incorrect dosages.
In the UK, the rates of failing to attend GP appointments range from 2.9% to 11.7%, while in the USA, this can range from 5% to 55%.
Waste of Medication: Leads to economic consequences and the patient might not recover.
Time Lost: Healthcare workers spend time on patients who do not follow their treatment plans, instead of attending to those in need.
Progression of Illness: Patients may experience a worsening of their condition.
Increased Use of Medical Resources: Potential need for hospitalization, which is more expensive.
Reduced Functional Abilities: Illness may limit the patient's ability to work or care for dependents.
Lower Quality of Life: Resulting from the patient's decline in health.
Impact on Medical Research: Non-adherence hampers research due to incomplete data on treatment efficacy.
Taylor (1990): Suggested that 93% of patients fail to adhere to some aspect of treatment.
Sarafino (1994): Argued adherence is around 78% for short-term treatments and drops to 54% for chronic illnesses.
Becker (1972): Examined adherence in children taking antibiotics; found that over half the mothers stopped medication midway through a 10-day treatment.
Rational non-adherence refers to a deliberate choice to adjust medication due to factors including side effects, perceived effectiveness, and cost.
Aim: To identify factors contributing to rational non-adherence and examine the influence of specific medicines and backgrounds.
Sample: Representative online sample of 161 Australian participants across various demographics.
Method: Participants completed an online survey with three sections:
Questions on current medication use and attitudes.
Discrete Choice Experiment presenting hypothetical medication scenarios.
Background information collection.
Results:
No significant effect of symptom severity or alcohol use on adherence.
Background characteristics had negligible impact.
Monthly cost of medication was significant for those without private insurance.
Participants preferred medications that required less frequent administration but prioritized medication reducing health risks over convenience.
58% of participants prioritized harms over benefits in adherence decisions.
Conclusion: The risk of immediate side effects was deemed more critical than long-term effects, while medication effectiveness against mortality was prioritized.
Strengths:
Utilizes a representative sample enhancing generalizability.
Simulates real-world decision-making through the Discrete Choice Experiment.
Weaknesses:
Specificity to Australian culture may limit applicability elsewhere.
Potential exclusion of individuals with limited internet access.
Risk of response bias from socially desirable answering.
Reviewed multiple studies to assess cost-benefit analyses concerning adherence.
Investigated elderly patients with hypertension, considering both physical and psychological effects of medication.
Findings: Identified that side effects often outweigh perceived benefits, impacting patient adherence. Asymptomatic conditions present greater adherence challenges.
Limitations of Review Methodology: Older research may lack current relevance.
Benefits: Cross-comparison allows identifying patterns over time, enhancing holistic understanding.
Explains non-adherence via various factors:
Perceived Severity: Greater seriousness of illness correlates with higher adherence.
Perceived Susceptibility: Lower perceived risk leads to lower adherence.
Perceived Benefits: Doubts about treatment effectiveness reduce adherence likelihood.
Perceived Barriers: Financial, situational, or discomfort barriers negatively affect adherence.
Cues to Action: Triggers like personal experience with illness can enhance adherence.
Self-Efficacy: Confidence in managing treatment can improve adherence rates.
The model posits adherence is influenced by:
Evaluation of health threats.
A cost-benefit analysis of adherence versus non-adherence.
A study from 1971 involving 125 children showed how adherence correlated with parental concern for their child's health and trust in healthcare providers.
Real-World Application: Understanding non-adherence aids in developing interventions to improve adherence rates.
Individual vs. Situational Explanations: Laba’s approach includes individual and situational factors, while the Health Belief Model focuses on personal reasoning.
Reductionism vs. Holism: These studies highlight multifaceted reasons for non-adherence, challenging overly simplistic views.
Idiographic vs. Nomothetic: Laba employs quantitative methods while the Health Belief Model uses qualitative analysis, providing a nomothetic perspective to adherence issues