Mental Health: Global Challenges Journal

https://www.sciendo.com/journal/MHGCJ

ISSN 2612-2138

Measuring Medication Adherence in Chronic

Diseases: The Psychometric Properties of Simplified

Medication Adherence Questionnaire in Patients

with Chronic Diseases in Rural Greece

Evangelos C. Fradelos1,2, Aikaterini Toska1, Maria Kavadia2, Angeliki Gratsani2, Victoria Alikari3

Stella Zetta1, Kyriakos Souliotis4, Maria Saridi,1

1University of Thessaly, Larissa Greece

2Hellenic Open University, Patra, Greece

3University of West Attica Athens, Greece

4Department of Social and Educational Policy, Korinthos, Greece

Abstract

Introduction: Medication adherence is one of the most important factors in the effectiveness of

treatment, especially for patients with chronic diseases. This study aims to assess the adherence

of patients with chronic diseases and investigate the parameters that influence it. It will also

examine the psychometric properties of the SMAQ scale, a tool used to assess adherence.

Purpose: The study's main purpose was to assess the psychometric properties of the SMAQ scale,

including its reliability and validity, to evaluate the adherence of patients with medication and to

analyse

the factors that shape it, focusing on the influence of gender, diagnosis, level of

education, marital status, and living conditions.

Methodology: The study was based

on a sample of patients with chronic diseases, such as

cardiovascular diseases, rheumatoid arthritis, and systemic lupus erythematosus. The patient's

compliance with medication was assessed using the SMAQ scale. Statistical analysis included chi-

square analysis to examine the association between participant characteristics and compliance,

while logistic regression analysis was also performed to assess the parameters that predict non-

compliance.

Results: The chi-square analysis revealed significant associat

ions between compliance and

parameters such as gender, type of disease, level of education, and marital status. Men and

patients with cardiovascular diseases showed better compliance. Logistic regression indicates

that diagnosis is the most important factor in predicting non-

compliance. Regarding the

psychometric properties of the SMAQ, the scale showed satisfactory reliability with Cronbach’s

Alpha = 0.717 and stability (Intraclass Correlation Coefficient = 0.525). Confirmatory factor

analysis (CFA) confirmed the unidimensional structure of the scale, with good fit values (CFI, TLI,

GFI > 0.9).

Conclusions: The results of the study provide valuable data on the factors that influence the

compliance of patients with chronic diseases. The diagnosis appears to be the most important

predictor of non-compliance, while the evaluation of the SMAQ scale indicates that it is a reliable

and valid tool for measuring compliance. The study highlights the need for strategies that will

improve compliance, especially for patients with chronic diseases who may face psychological

and social challenges. Limitations of the study include the sample size and the absence of data

on other psychological parameters, such as mental health, which should be addressed in future

research.

Keywords

Mental Health, Adherence, Patients with Chronic Disease, Rural Greece, Psychometric Properties,

Simplified Medication Adherence Questionnaire

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Address for correspondence: Evangelos

C. Fradelos, University of Thessaly.

Gaiopolis Campus, Larissa - Trikala Ring Road, 41500, Larissa, GREECE

Email: efradelos@uth.gr

This work is licensed under a Creative Commons Attribution-Non-Commercial 4.0 International

License (CC BY-NC 4.0).

©Copyright: Fradelos et al., 2024

Publisher: Sciendo (De Gruyter)

DOI:

https://doi.org/10.56508/mhgcj.v

i1.

247

Submitted for publication: 07

May 2024

Revised: 17 September 2024

Accepted for publication: 24

November 2024

Introduction

Treatment adherence, as well as the causes

and consequences of non-adherence, has

garnered significant research interest in the

scientific community over the years. Many

researchers focus on the concepts of adherence,

compliance, persistence, and concordance as

terms commonly used to describe a person’s

commitment to a therapeutic regimen (Sabaté,

2003; Sharif-Nia et al., 2024; Alikari et al., 2017).

Treatment adherence refers to the extent to which

an individual’s behavior—such as taking

medication, adopting a diet, and changing their

lifestyle—aligns with the recommendations of a

health professional and results from an agreement

with the patient (Sabaté, 2003).

Adherence emphasizes the collaborative

patient-physician relationship and the patient’s

participation in making decisions about their

treatment. In contrast, compliance describes the

patient’s passive role, where they simply “follow the

doctor’s instructions,” imparting a paternalistic

character to the therapeutic relationship

(Chakrabarti, 2014). The concept of concordance

focuses on a more egalitarian relationship, where

the patient and doctor work together to make

mutually acceptable treatment decisions (Martin

et al., 2005). The practice of adhering to a

medication regimen for the entire recommended

period is known as medication persistence,

defined as "the duration of time from initiation to

discontinuation of therapy" (Cramer et al., 2008).

These constructs, however, are considered distinct

rather than interchangeable (Cramer et al., 2008).

Adherence and concordance are seen as

more modern terms, recognizing the importance

of active patient involvement enhanced through

effective communication with healthcare

professionals. Conversely, compliance is now

viewed as an outdated concept.

According to Burnier (2024), non-adherence in

therapeutic regimens poses significant challenges

in managing chronic diseases, resulting in poor

disease control and increased risks of

complications. Factors such as complex

medication plans, patients' limited understanding

of their disease, and socioeconomic status

influence adherence levels (Burnier, 2024;

Romash, 2023). Nfor and Warri (2024), in a

qualitative study, identified factors contributing to

non-adherence among hypertensive patients.

These included limited knowledge about the

disease and its treatment, negative attitudes

toward disease management, time constraints,

lack of social support, and poor relationships with

healthcare professionals (Nfor & Warri, 2024).

A systematic review by Gast and Mathes (2019)

explored factors influencing adherence to

medication for chronic conditions. The findings

revealed that higher educational levels and

employment positively correlate with adherence,

while ethnic minority status, unemployment, and

high drug costs negatively impact adherence,

highlighting social inequalities in healthcare.

Additional factors, such as age, disease duration,

and treatment complexity, showed inconsistent

results, while drug costs consistently had a

negative effect. These results underscore the need

for targeted interventions in vulnerable populations

to improve adherence (Gast & Mathes, 2019).

While various methods exist to assess treatment

adherence, self-reported measures are

commonly used in healthcare settings. One such

tool is the Simplified Medication Adherence

Questionnaire (SMAQ), known for its simplicity and

validity in clinical settings. The SMAQ quickly

evaluates adherence, making it particularly

suitable for time-constrained environments. It has

demonstrated reliability and validity, with high

sensitivity and specificity in detecting non-

adherence based on patient self-reporting

(Knobel et al., 2002).

SMAQ evaluates various aspects of

adherence, including missed doses (intentional or

unintentional), medication timing, dosage

changes, and subjective compliance

assessments. Its multidimensional approach

enables its application across diverse populations

and conditions, facilitating comparisons and

customization to individual needs. Moreover, it

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Mental Health: Global Challenges Journal

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ISSN 2612-2138

serves as a risk detection tool, aiding clinicians in

identifying patients with low adherence and

implementing tailored interventions. SMAQ’s

importance lies in enhancing adherence, a

critical factor for successful treatment in chronic

diseases requiring long-term medication use

(Agala et al., 2020; VATREN et al., 2011).

Purpose

Despite extensive international research on

medication adherence, data on patients with

chronic conditions in rural areas of Greece remain

limited. Therefore, the purpose of this study is to

examine the psychometric properties of a Greek-

adapted SMAQ in patients with chronic diseases

and identify demographic factors associated with

treatment adherence.

Methodology

Study setting and participants

From January 2024 to August 2024, individuals

suffering from cardiovascular or rheumatic

disease located in Trikala and Heraklion took part

in an anonymous survey using the convenience

sample approach. Inclusion criteria were to have

a diagnosis of one of the diseases, be able to read

and speak Greek and be free of serious mental

health disorders.

Data collection

Data were collected via an anonymous

questionnaire consisting of two parts:

The first part contained questions regarding

demographic and clinical characteristics such as

gender, age, diagnosis, etc.

The second part was the simplified medication

adherence questionnaire. The Simplified

Medication Adherence Questionnaire (SMAQ) is a

tool that assesses patients’ adherence to their

medication therapy, providing a quick and easy

way to assess compliance, particularly in chronic

diseases such as HIV, diabetes, and hypertension.

It consists of 6 questions that focus on missed

doses, frequency of missed doses, changes in

dosage, difficulty in taking medication at specific

times, recent missed doses, and subjective

assessment of compliance. Responses are

typically binary (Yes/No), and even a single

negative indication (e.g., missed dose or change

in dosage) can classify the patient as non-

compliant. The SMAQ has the advantage of being

quick and easy to administer, understandable by

patients with low educational levels, and suitable

for use in time-constrained settings. However, it

depends on the honesty of the responses, is less

detailed than other tools, such as the Morisky

scale, and can be influenced by socially desirable

responses. It is used both in clinical studies and in

daily clinical practice to detect patients who need

more support (Agala et al., 2020; VATREN et al.,

2011).

The translation and cultural adaptation

process

Adhering to WHO's guidelines (WHO, 2012) the

translation and cultural adaptation of the SMAQ

involved several stages. Initially, two independent

bilingual translators, both healthcare professionals,

translated the English version into Greek. These

translations were then merged and revised by a

third translator to create a single Greek version. This

Greek version was then translated into English by

two separate individuals who were proficient in

English. The resulting English versions were

combined into a single version by a third translator.

This final English version was administered to ten

patients diagnosed with one of the mentioned

diseases, and the cognitive interview method was

employed. During this process, patients shared

whether they encountered any confusing or

challenging aspects. Generally, nine out of the ten

patients reported no such issues.

Statistical analysis

Descriptive and inferential statistics are applied

to this study. The data was examined using

descriptive statistics (frequency, mean values, and

standard deviations) and inductive statistics to

address all the research questions. Analyses of

variance (ANOVA), independent t-tests, spearman

and Pearson correlation, regressions, internal

consistency (Cronbach's coefficient), and

confirmatory factor analyses were carried out

using SPSS26.0 and JASP. The significance level

was set to p ≤0.05

Ethics

The study was approved by the ethics

committee. Participants were approached by the

researchers, who provided them with the

necessary information, assured them of their

anonymity, and clarified that they could withdraw

from the study at any time.

Results

Most of the sample comprises females (73.1%)

and participants diagnosed with cardiovascular

disease (53.8%). Over half of the participants are

married (55.0%), and most live with others (69.9%).

The study includes a notable proportion of

individuals with rheumatoid arthritis (28.5%) and

widowed individuals (28.1%), reflecting diverse

living arrangements and social statuses among

the sample. Detailed participants' characteristics

are presented in Table 1

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Over half (54.8%) are reporting that consistently

take their medication on time, but 54% have

discontinued medication when feeling unwell,

and 57.2% have forgotten doses. Most

participants (77.9%) missed a dose 1-2 times in the

past week, and 58.4% have never forgotten

medication during weekends. Regarding

adherence in the past three months, 83.5%

missed medication up to two times, while 16.5%

missed it more than twice

Table 1. Participants Characteristics

Variable Group1 N Percentage

Gender

Male

26.9

Female

182

73.1

Diagnosis

Rheumatoid Arthritis

28.5

Systemic Lupus Erythematosus

17.7

Marital Status

Cardiovascular Disease

134

53.8

Single

10.0

Married

137

55.0

Divorced

6.8

Living arrangement

Widowed

28.1

alone

30.1

Cohabited

172

69.9

Considering that, according to the SMAQ

scoring system, a patient is classified as non-

adherent if they report missing even a single dose

of medication, the adherence rate in our sample

is 27.2%. Detailed statistics are presented in Table

Reliability analysis of the SMAQ

The test-retest method was applied to explore

the test-retest repeatability of the SMAQ. Τwenty-

five patients completed the questionnaire at

baseline and two weeks later.

Table 2. Participants' Medication Adherence Behaviors

Items

Do you always take your medication at the

appropriate time?

Responses

Percentage

YES

137

54.8

When you feel bad, have you ever discontinued

taking your medication?

113

45.2

YES

135

Have you ever forgotten to take your medication?

115

YES

143

57.2

107

42.8

In the LAST WEEK, HOW MANY TIMES did you fail to

take your prescribed dose?

Never

1-2 times

194

77.9

3-5 times

17.7

6-10 times

More than 10

times

0.4

Have you ever forgotten to take your medications

during the weekend?

146

58.4

In the past 3 months, how many days did you not

take your medication at all?

Yes

104

41.6

up to two times

208

83.5

More than two

times

16.5

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This interval is interposed so that the

individuals do not recall their answers. Upon the

analysis, significant correlations were observed

between the two-administration (p<0.001) facts

(Intraclass Correlation Coefficients = 0.525) that

reveal that the scale is stable through time. In

addition, Cronbach’s Alpha had a value of 0.717

suggesting acceptable internal consistency of

the scale. Moreover, the value of Cronbach’s

Alpha will not increase if the scale discarded

items. All items exhibited strong correlations to

the total score. This fact adds to the excellent

internal consistency of the scale.

Construct validity of SMAQ

Finally, we performed a CFA to test the one-

factor structure of the scale. Regarding CFA, the

model tested was equivalent to the original

factorial structure of the SMAQ as proposed by

other authors. The model presented a

reasonably good fit to the data. Tucker-Lewis

index (TLI) was near 0.9, comparative fit index

(CFI) and goodness of fit index (GFI) were above

0.9 and standardized root mean square residual

(SRMR) was 0.075 and lower than 0.10. Overall,

our CFA confirmed the unidimensional structure

of the scale.

Bivariate analysis

The results in Table 3 summarize the

association between patient characteristics and

treatment adherence, as assessed by chi-

square tests. Gender, type of disease,

educational status, marital status, and living

arrangements were significantly associated with

adherence. Male patients and those with

cardiovascular disease were more adherent,

while lower adherence was observed among

those with rheumatoid arthritis lower educational

levels, and individuals living alone.,

Logistic Regression analysis

The logistic regression model examines

predictors of non-adherence to treatment,

considering factors such as gender, age,

education, marital status, living arrangement,

and type of disease. Among the variables

analyzed, type of disease showed a statistically

significant association with non-adherence to

treatment (p < .001), with a negative estimate

indicating reduced adherence for certain

disease types. Other factors, such as gender,

age, education, marital status, and living

arrangements, were not statistically significant

predictors (p > 0.05). Detailed information is

presented in Table 4.

The table 4 includes parameter estimates,

standard errors, z-values, Wald statistics,

confidence intervals, and p-values for each

variable. Non-adherence is coded as class 1.

Confidence intervals reflect the range of effect

estimates at a 95% confidence level.

Table 3: Chi-Square Results on Adherence to Treatment and Patient Characteristics

Adhering to

treatment

Not adhering

to treatment

Chi-

Square

p-value

Gender

Male

6.103

0.013

Female

140

Type of Disease

Rheumatoid Arthritis

65.812

< 0.001

Systemic Lupus

Erythematosus

Cardiovascular

Disease

Educational

Classes in primary

school

34.068

<0 .001

Status

Primary school

Junior High school

High school

University

Postgraduate

Marital

Single

16. 936

<0 .001

Status

Married

109

Divorced

Widowed

Living

arrangement

Alone

7.114

0,008

Cohibated

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Discussion

Interpretation of Findings

The results of our study show that medication

adherence is strongly influenced by disease

type, as demonstrated by both correlations and

logistic regression. Patients with rheumatoid

arthritis and systemic lupus erythematosus are

more likely to be non-adherent, highlighting the

need for targeted interventions in these groups.

In addition, low education and living alone

emerged as important factors associated with

non-adherence. These findings reinforce the

literature on the need for an individualized

approach to patient support.

The sample of our study has high

heterogeneity in terms of diagnosis, marital

status, and living conditions, a fact that

strengthens our results. Despite the heterogeneity

in our study most participants were women

(73.1%) and were diagnosed with cardiovascular

disease (53.8%), reflecting the prevalence of

these diseases and the participation of women

in relevant studies. Notara, Kokkou, and

Panagiotakos (2024) discuss the prevalence of

cardiovascular disease in women and highlight

that women's cardiovascular health is often

neglected in scientific research, with women

being underrepresented in relevant clinical trials.

This has led to a lack of understanding of the

specific risks faced by women, which are

influenced by factors such as pregnancy,

menopause, and hormonal changes. The "Go

Red for Women" initiative, also discussed in the

article, emphasizes the need to strengthen

prevention and awareness of cardiovascular

diseases in women while promoting their

participation in research. At the same time, the

Hellenic Cardiological Society highlights that

women face increased risks after menopause

due to increased lipids and cholesterol, while

conditions such as preeclampsia during

pregnancy increase the risk of future heart

disease. Representation of women in studies is

crucial for improving treatment approaches,

developing targeted prevention measures, and

ensuring equal care regardless of gender

(Notara, Kokkou, & Panagiotakos, 2024).

Despite the general consistency (54.8%) in

adhering to the medication schedule, there is a

high percentage of participants who have

forgotten or skipped doses, especially during

difficult times (57.2% missed doses, 54%

stopped medication when feeling unwell).

Prabahar et al. (2021) explored the factors

influencing medication adherence in patients

with chronic diseases in Tabuk, Saudi Arabia,

emphasizing the challenges that patients face in

managing their treatment regimens. From the

Table 4. Logistic regression analysis predicting non-adherence to treatment.

95% Confidence interval

Estimate

Standard

Error

Wald

Statistic

Lower

bound

Upper

bound

(Intercept)

8.688

2.281

3.808

14.503

4.216

13.159

< .001

Gender

0.207

0.399

0.517

0.268

0.576

0.990

0.605

Age

0.005

0.021

0.242

0.058

0.036

0.047

0.809

Educational

Status

-0.180

0.153

1.182

1.396

0.480

0.119

0.237

Marital

Status

-0.266

0.246

1.083

1.172

0.749

0.216

0.279

Living

arrangement

-0.017

0.446

0.038

0.001

0.891

0.857

0.970

Type of

disease

-2.704

0.682

3.965

15.722

4.041

-1.367

< 0.001

Non-Adhered coded as class 1.

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total of 208 participants 159 (76.44%)

participants were adherent to their medications

and nearly one-quarter of patients were

nonadherent to their medications. According to

their results, significant differences between

male and female patients regarding their

medication adherence were observed. A recent

systematic review from Chen, Gao, and Lu

(2024) suggests that patients’ adherence to

treatments is influenced by psychological and

emotional factors, such as the perception of

illness or the difficulties patients face during their

difficult times (Chen, Gao, & Lu, 2024). This shows

that adherence depends not only on the

patient’s habits but also on emotional and

psychological states that can cause medication

omissions or discontinuation. For example, while

patients may have the intention to follow their

prescription, factors such as the perception of

the severity of the condition or emotional

reactions to symptoms can be an obstacle to full

compliance. This reinforces the importance of

addressing not only the routine of taking

medications but also the psychological aspects

of the illness, to improve treatment adherence

rates. The findings of the chi-square analysis in

this study indicate that medication adherence is

significantly associated with the gender,

education, marital status, and living conditions of

patients. Men and patients with cardiovascular

diseases showed better adherence, while

patients with rheumatoid arthritis and systemic

lupus erythematosus showed lower adherence.

Also, patients with lower levels of education and

those living alone were more likely to not adhere

to the medication schedule. These findings

agree with other studies examining factors that

influence medication adherence. According to

the review by Gast and Mathes (2019), factors

such as socioeconomic status, family support,

and patient perception of treatment are

determinants of adherence. Their studies

suggest that patients with chronic diseases, such

as hypertension and diabetes, are more prone

to relapse and non-compliance with medication

recommendations when social factors and

family support are insufficient. The study by Al-

Noumani et al. (2023) reinforces these findings,

showing that social factors and family support

are also important factors affecting compliance

in patients with chronic diseases in Oman.

Patients with less family support had higher rates

of non-compliance, which indicates the

importance of family support in the

management of chronic diseases. According to

the research by Alikari et al. (2015), family support

and social factors are also associated with

compliance in patients undergoing

hemodialysis. Their study showed that patients

with better social support had better

compliance, highlighting the importance of

social support in enhancing medication

adherence. Furthermore, the study by Alikari et

al. (2015) is in agreement with the findings of the

present study, as patients who live alone or have

limited social support are more prone to non-

adherence. Men, as also reported in the review

by Gast and Mathes (2019), appear to be more

likely to adhere to their medication regimen

compared to women, highlighting the

importance of gender as a factor in adherence.

These results highlight the need to consider

socioeconomic and psychological factors in

developing strategies to promote medication

adherence, particularly for patients with chronic

diseases.

The results of the analysis of the stability and

internal consistency of the SMAQ scale in the

present study are encouraging. The Internal

Consistency Coefficient (Cronbach's Alpha =

0.717) indicates good internal consistency of the

scale, while the stability through Intraclass

Correlation Analysis (Intraclass Correlation

Coefficient = 0.525) is acceptable and confirms

the reliability of the scale for repeated

measurements at repeated intervals. These

findings agree with other studies focusing on the

validity and reliability of the Simplified Medication

Adherence Questionnaire (SMAQ). The study by

Knobel et al. (2002), for example, validated the

SMAQ scale in patients with HIV, confirming the

validity of the scale and its good consistency in

a large group of patients. The authors found that

the SMAQ scale was reliable in assessing

medication adherence in these patients, which

reinforces its suitability in other populations with

chronic diseases. Ortega Suárez et al. (2011) also

validated the SMAQ scale in kidney transplant

patients receiving tacrolimus, highlighting the

validity of the scale for use in different types of

patients with different treatments. The results

showed that the SMAQ scale was a good fit and

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was reliable in assessing adherence in patients

with kidney disease. Finally, the study by Soares

et al. (2024) in Brazil validated a Portuguese

version of the SMAQ scale in adults with

hypertension and found that the scale also had

high internal consistency and stability, confirming

the general reliability of the scale in populations

from different geographical areas and medical

conditions. All these studies support the utility

and reliability of the SMAQ scale for assessing

medication adherence in diverse population

groups, which strengthens its validity and use in

the present study.

Strengths and Limitations

Strengths of the study include the reliability of the

methodology, the variety of participant

characteristics, and the use of reliable statistical

tools, such as chi-square analysis and logistic

regression. However, limitations include the size

and homogeneity of the sample, the reliance on

self-reported data, and the lack of data on other

factors such as mental health or socioeconomic

status (Gast & Mathes, 2019; Al-Noumani et al.,

2023). Nevertheless, the findings enhance our

understanding of the parameters that influence

adherence and provide useful information for

improving adherence promotion strategies in

patients with chronic diseases.

Conclusions

The study findings indicate that patients'

compliance with medication is influenced by

important factors such as gender, diagnosis,

level of education, and living conditions. Men

and patients with cardiovascular diseases

showed better compliance, whereas a diagnosis

of rheumatoid arthritis or systemic lupus

erythematosus was associated with lower levels

of adherence. The results of the logistic

regression analysis confirm that the type of

disease is the strongest predictor of non-

compliance. In addition, the use of the SMAQ

scale proved to be reliable, offering a useful tool

for assessing compliance. Despite the potential

of the study, limitations such as sample size and

the lack of data on other factors (e.g., mental

health) limit the generalizability of the results.

Despite these limitations, the study provides

valuable evidence for improving adherence in

the treatment of chronic diseases.

Conflict of interest

The authors declare no conflict of interes.

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