Article Text

Original research
Effect of psychosocial aspects on medication adherence in patients with heart failure amid socioeconomic challenges
  1. Hiba Deek1 and
  2. Angela Massouh2
  1. 1Nursing, Beirut Arab University, Beirut, Lebanon
  2. 2Hariri School of Nursing, American University of Beirut, Beirut, Lebanon
  1. Correspondence to Dr Hiba Deek; h.deek{at}bau.edu.lb

Abstract

Objective To evaluate stress, depression and quality of life among community-dwelling patients with heart failure (HF) and evaluate their effect on perceived medication adherence in a socioeconomically challenged setting.

Design A cross-sectional design with self-administered questionnaire with data collected between October 2021 and September 2022.

Methods Patients with confirmed diagnosis of HF were sought for data collection in the community and cardiology clinics through an electronic platform. Confirmation of cases was done through the ejection fraction, medication list and frequent symptoms of the patients. The Patient Health Questionnaire-9, the COVID-19 Stress Scale, the Minnesota Living with HF Questionnaire and the Lebanese Medication Adherence Scale were used to evaluate depression, stress, quality of life and medication adherence, respectively. Univariate analysis was done to present the descriptive statistics, whereas bivariate and multivariate analyses were done to evaluate the relationship between the variables.

Results A total of 237 participants were included in the final analysis. The mean age was 61.3±17.36 years, and the majority (57.8%) were male participants. Only 44.7% were on ACE inhibitors/angiotensin receptor blockers and 54.9% on beta-blockers. The mean scores for stress, depression, quality of life and medication adherence were 75.86 (SD=24.5), 14.03 (SD=5.7), 55.73 (SD=23.05) and 6.79 (SD=6.93), respectively, indicating high stress levels, depression, poor quality of life and medication adherence. Those with a history of hypertension and depression were significantly more adherent to their medications than those who were not. Multivariate analysis showed that anxiety, medical follow-up, quality of life and functionality class were predictors of medication adherence.

Conclusion The study showed the population with HF in Lebanon to have psychological health problems with these variables acting as predictors for medication adherence. Sociodemographic characteristics also played a role on the outcome, which can be targeted when planning interventions to improve outcomes. Future studies should compare prescribed medication with consumed medication through longitudinal approaches and medical refilling techniques when possible.

  • Medication Adherence
  • DEPRESSION
  • COVID-19
  • HEART FAILURE

Data availability statement

Data are available upon reasonable request. Raw data will be available upon request.

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WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Medication adherence is affected by the patients’ perception of the disease, availability of the medication and cultural aspects. The involvement of family members in the intervention is pivotal in a collectivist society where the family and inclusion are valued.

WHAT THIS STUDY ADDS

  • Medication adherence rates have decreased significantly over the years in the population with heart failure. This may have been due to the escalating challenges faced by this population in terms of finance, politics and society. Controllable variables such as chronic medical conditions were associated with medication adherence in addition to other outcomes. Sociodemographic characteristics also contributed to medication adherence.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • Adequate assessment of the patients’ sociodemographic and medical background is important in structuring the subjective education interventions regarding self-care and medication adherence. Patient education and proper follow-up can contribute to improving the adherence rates among patients living in challenging conditions.

Introduction

The worldwide heart failure (HF) prevalence is estimated to be 64.34 million cases corresponding to 9.91 million years lost due to disability.1 In 2023, HF remains an emerging global threat with its global burden constantly increasing, especially in the older adult population and people living in low-income to middle-income societies. This population burden translates into an augmented worldwide expenditure for managing patients with HF, which is estimated to reach US$400 billion in 2030.1

Patients with HF are expected to comply with self-care strategies, and key to these strategies is adherence to pharmacological therapy. Research trials aimed at achieving optimal medication efficacy will only prove effective when translated into the real world where adherence is achieved in the general population.2 Unfortunately, medication adherence among patients with HF remains poor, in turn leading to reduced functionality and increased exacerbation, hospital readmissions and death.3 4 It is estimated that at least one in four patients with HF do not adhere to their medication regimen,5 which is linked to greater HF symptom burden and worse cardiac event-free survival.6 Medication adherence interventions in HF were found to significantly reduce mortality risk and decrease the odds of hospital readmission.7 The lack of studies limits the availability of recommendations specific to the population with HF in a sociopolitically challenged country such as Lebanon.

In Lebanon, medication adherence studies are scarce. In one study on patients with diabetes, medication adherence was found to be low, leading to poor glycaemic control in about 70% of the participants.8

In an earlier study on chronic illnesses, only about 42% of the sample were classified as adherent. Statistically significant predictors of high medication adherence included good physician–patient relationship, a high level of health-related quality of life (QOL) and a high level of perceived health. Predictors of low adherence included a worsening memory, anxiety and depression, low drug knowledge and postponing physician appointments.9

Both studies precede Lebanon’s economic crisis. In 2019, many calamities took a radical impact on Lebanon and all of its sectors including the healthcare sector.10 Massive numbers of healthcare professionals left Lebanon since the economic decline and the port blast seeking financially worthwhile offers in places where political and economic stability is offered.10 Medication prices have increased to reach as much as four times their original price in Lebanese pounds despite a large number of individuals not being able to afford their necessities. With a minimal wage of less than US$30 currently and decreasing, Lebanese people are choosing to consume their salaries on basic supplies and avoid the cost of therapies. Emergency department presentations have increased dramatically due to the medication non-adherence secondary to their high prices.

The study aims to evaluate the levels of stress, depression and QOL among community-dwelling patients with HF and evaluate the effect of these variables on perceived medication adherence in a country with rapid sociodemographic changes.

Methods

Design

This was a cross-sectional design study that used a self-administered questionnaire given to patients diagnosed with HF. Following ethical approval, data were collected electronically between October 2021 and September 2022 from participants in the community.

Study setting and sampling

Assuming a prevalence of 39%11 for medication adherence in chronic conditions, the sample size needed was calculated at 208 based on the below formula of sample size calculation for a cross-sectional study design.12 The error rate was set for 0.05 to a standard normal variate of 1.96. Assuming an attrition rate of 25% due to incomplete data or inaccurate diagnosis of HF, a target sample size was set to 260 participants.

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Inclusion criteria

Patients living with HF and aged 18 years and above were invited to participate in this study. Confirmation of cases was done through the ejection fraction (EF), HF medication list and frequent symptoms of the patients based on the Framingham criteria. Through these criteria, HF diagnosis is confirmed when two major or one major and minor criteria are presented on the patient.13 This was done pre-data collection by the research team which includes graduate and postgraduate-level nurses working in clinical settings trained to conduct this study. The participants were sought from different regions of the country to provide a geographical representation of the population with HF including urban and rural areas. Participants were excluded if HF diagnosis was not confirmed or were aged less than 18 years.

Data source, data collection and instrument

The data collection form was generated on a link in Google Forms and circulated in the community among the research team acquaintances. Data were also sought from cardiology clinics where patient presented for follow-up and chronic management. Additionally, data were collected from stable inpatients in hospital wards. The data collection form was provided in easy Arabic for fifth graders to comprehend considering the low literacy levels among the population with HF in the study setting.14 No changes were made to the validated scales in Arabic as they were already evaluated for clarity and easiness in previous studies as presented below. The form included the following sections (online supplemental file A):

Sociodemographic characteristics and health profile

This section included questions on age, gender, nationality, living region, social status, occupation, income and educational status. Additionally, the medical and surgical history was sought from the participants including the physical and psychological medical history and current home medication (medication they are currently taking as presented directly from the participants). Medication sources and reasons for non-adherence were also asked in the questionnaires through options. The medical history was based on previous diagnosis of the participants including depression and anxiety. The HF-specific elements were also sought to include the EF, New York Heart Association (NYHA) functional classification and years since diagnosis. EF concept is explained to the patients at the time of diagnosis and is followed up with the patients at every hospital visit when imaging is done; therefore, reporting of EF by patients was assumed to be accurate. The NYHA class was simplified to four options as follows: (1) I am free of shortness of breath; (2) I have minimal shortness of breath with activity; (3) I have severe shortness of breath with activity and (4) I have shortness of breath while seated.

Patient Health Questionnaire

This surveillance tool is an easy-to-administer tool that evaluates depression though nine questions around the sleeping and eating habits, interest, tiredness, concentration and suicidal ideation. The findings of the tool can highlight those at high risk of developing this condition or have developed it without being medically diagnosed. Each of the nine items is rated on a 4-point Likert scale ranging from (0) not at all to (3) nearly every day with a summative score of 27 and higher scores indicating severe depression.15 Scores ranging between 0 and 4 indicate minimal or no depression, between 5 and 9 indicate mild depression, between 10 and 14 indicate moderate depression, between 15 and 19 indicate moderately severe depression and between 20 and 27 indicate severe depression. The Patient Health Questionnaire (PHQ)-9 has been translated to multiple languages and used in multiple settings16–18 including the Arabic, which showed good psychometric properties.19 This tool had been administered previously to the population with HF and proved to be easy to administer with no encountered difficulties.20

The COVID-19 Stress Scale

The COVID-19 Stress Scale is a 36-item tool used to evaluate stress over five dimensions. These dimensions are (1) danger and contamination (12 items), (2) socioeconomic consequences (6 items), (3) xenophobia (6 items), (4) compulsive checking and reassurance seeking (6 items), and (5) traumatic stress symptoms about COVID-19 (6 items). The items are rated on a 5-point Likert scale ranging from 0 (not at all) to 4 (extremely) with higher cumulative scores indicating higher levels of stress with no cut-off score to indicate a dichotomous variable of stressed versus not.21 The Arabic version of the scale was previously used in the Saudi setting and evaluated for its psychometric properties which were found to be valid and reliable. The Cronbach’a alpha for the Arabic scale was 0.94 with scores higher than 0.86 for every subscale.22 The choice of this scale lies in the context and the time the study was conducted. This was during the COVID-19 pandemic and it was one way to outline a part of the psychosocial challenges faced by patients during this period.

The Minnesota Living with HF Questionnaire

The Minnesota Living with HF Questionnaire (MLHFQ) is a multidimensional scale used to evaluate QOL in patients diagnosed with HF. It consists of 21 items rated on a 6-point Likert scale ranging from (0) no to (5) very much with no cut-off score and higher scores indicating poorer QOL. This QOL questionnaire showed good psychometric properties in previous studies.23 The MLHFQ was previously translated to Arabic and validated in the Lebanese setting to prove good psychometric properties with a Cronbach’s alpha of 0.9.24

The Lebanese Medication Adherence Scale

The Lebanese Medication Adherence Scale (LMAS) is a 14-item scale used to evaluate medication adherence. The development of this Arabic scale was inspired by the Morisky Medication Scale-825 in addition to items that consider the sociodemographic and cultural characteristics of the Lebanese society. The items of the LMAS are rated on a 4-point Likert scale ranging between (0) no and (3) yes in all but two questions which have other answers towards non-adherence. The items of the scale address forgetfulness in times of busy schedules or when outside home; skipping doses because of a known side effect or a certain restriction while taking the medication; stopping the medications when feeling better or seeing improvement on laboratory results; stopping the medication because of its price, long-term treatment or polypharmacy. Therefore, non-adherence here is stopping or skipping doses intentionally. The total summative score is 42 with higher scores indicating non-adherence. A cut-off score of 38 was used to categorise patients as adherent or not. The psychometric properties were evaluated and it was found to have good reliability and validity with a sensitivity of 82.9% and a specificity of 36.9%.26

Data analysis

Data were analysed using V.24 of the SPSS. Descriptive statistics were presented as means and SD for continuous variables and as frequencies and percentages when categorical. Group comparison was done using χ2 test for categorical variables and independent sample t-test for continuous variables. Normality was determined using the one-sample Kolmogorov-Smirnov test. A logistic regression model was generated to determine predictors of adherence through a multivariate analysis. The number of variables included was within the recommendation of at least 10 participants for each variable.27 After several trials, the best-fitting model included six variables which is compatible with the recommendation. The p value was set to less than 0.05 for significance.

Results

Baseline characteristic of patient participants

A total of 375 participants completed the online questionnaire sent out to the community. Out of which, only 237 met the inclusion criteria. The remaining participants were either hypertensive or had a cardiac event without reaching HF. The mean age of the 237 included participants was 61.3±17.36 years with the majority being male participants (n=137, 57.8%). More than half (n=124, 54%) were residents of the capital Beirut and 77.6% (n=184) were Lebanese in nationality. Almost two-thirds were married (n=143, 60.3%) and the majority (n=178, 75.1%) were non-workers or retired. Slightly over half (n=124, 52.3%) were smokers and less than 10% (n=23) consumed alcohol. In terms of medical history, 84% (n=199) had hypertension, 62.4% (n=148) hypercholesterolaemia, 52.7% (n=125) were diabetic and 45.6% (n=108) had coronary artery disease (CAD). In terms of psychological health, 24.9% (n=59) reported having depression and much more (n=136, 57.4%) reported anxiety. The majority had their medical condition controlled by their physician before (n=205, 86.5%) and during (n=183, 77.2%) the pandemic. Almost two-thirds had a surgical history (n=162, 68.4%). The mean EF was 39.77%±12.49 with the majority having HF with reduced EF (HFrEF) (n=96, 41.7%) and NYHA class of II (n=102, 43%) and III (n=78, 32.9%). The mean time since diagnosis was almost 7 years. The sociodemographic details and medical profile of the study participants are presented in table 1. When looking at the medication list reported by the patients, it was found that 44.7% (n=106) were on ACE inhibitors (ACEI)/angiotensin receptor blockers (ARBs), 54.9% (n=130) were on beta-blockers and 13.1% (31) were on mineralocorticoid receptor antagonists (MRAs) as presented in table 2. When doing further analysis, there was no significant difference between the EF subcategories in terms of medication intake except in the antiplatelet aggregation as presented in online supplemental file B.

Table 1

Sociodemographic characteristics and medical profile of the study participants (N=237)

Table 2

Logistic regression findings predicting medication adherence (N=237)

COVID-19 stress, depression and QOL levels among patients with HF in relation to their medication adherence

In the absence of a cut-off score, it is difficult to determine COVID-19 stress among the study participants. The mean total COVID-19 stress score was 75.86±24.5 with mean scores of the subscales to be 14.14±5.8, 31.58±10.59, 11.93±7.04, 5.95±5.18 and 9.27±5.67 for the fear socioeconomic consequences (SES), danger, xenophobia, compulsions and trauma, respectively. COVID-19 stress levels did not seem to have any significant association with the perceived medication adherence status of the study participants except in the total score of the subscale of danger and contamination in addition to item number 2 of the trauma subscale. On the other hand, the mean depression score was 14.03±5.7 and the MLHFQ score was 55.73±23.05. The former scale significantly influenced adherence where those that scored higher depression were significantly more adherent to their medications. No disgnificant difference was noted between the groups in terms of QOL. Details of the depression, COVID-19 stress and QOL items and scores between the two groups are presented in online supplemental file C.

Medication adherence

The mean LMAS score was 6.79±6.93 reflecting severely low adherence with less than 1% (n=2) categorized as being adherent. Reasons for non-adherence were mostly due to the non-availability of the medications (n=69, 29.1%), and the absence of financial resources (n=14, 5.9%) or caregivers (n=9, 3.8%). With the absence of the medications, the majority (n=104, 43.9%) had access to their medication from sources outside the country, while almost 40% (n=93) stored their medications for later use. Details about medication adherence and reasons for the lack of which are presented in table 3.

Table 3

Medication adherence and related factors among the study participants (N=237)

The effect of sociodemographic variables and medical profile on medication adherence

Neither age nor gender had any significance on perceived medication adherence. Although insignificant, medication adherence was higher among Lebanese participants in comparison with non-Lebanese participants residing in Lebanon. Low income was evident in most of the participants, although lower income surprisingly indicated significantly higher adherence to medication. In terms of comorbidities, those with a history of hypertension were significantly more adherent to their medication in comparison with those without this medical condition. Similarly, those having anxiety were significantly more adherent to their medications when compared with those without this mental disorders. In terms of medical follow-up, it was noted that those who are less adherent were more strict about their medical appointments than their counterparts before and during the pandemic. In terms of disease-specific factors, EF had no association with the medication adherence. This was explained by the EF ranges where more were non-adherent to medication when being categorised as having reduced or preserved EF, while those categorised as having mid-range EF were found to be more adherent. The details of the differences between those who are adherent to their medications and those who are not are presented in table 1.

Looking at the variables that were significant at the bivariate level and those that were found significant in the literature to affect medication adherence, a logistic regression model was generated. The best fitting variables were anxiety, current medical follow-up during the pandemic, NYHA class and HF categorization in terms of HF. All variables were entered into the model together proving a significant model (χ2=45.643, df=7; p=0.00). The Hosmer and Lemeshow test was insignificant (χ2=7.976, df=8; p=0.436) showing that the model had good fit to the data. The model classified 71.3% of the overall cases which were higher for the adherent (83.8%) than the non-adherent (55%). The Negelkerke R2 suggested a moderate variance explaining a 24.1% likelihood of being adherent. As presented in table 3, all the entered variables proved to be predictors of good medication adherence with NYHA class II and HF categories of HFrEF and HFpEF.

Discussion and conclusion

Discussion

The aim of the current study was to evaluate the effect of COVID-19 stress, depression and QOL among community-dwelling Lebanese patients with HF on perceived medication adherence. Despite all the new challenges in the country, depression scores remained elevated but unchanged over the years,20 while QOL scores doubled from 24.84 in 201824 to 55.73 in the current study. Although still low, this improvement in QOL is puzzling considering all the health and social challenges this population is currently facing. When looking deeply at the characteristics of the two samples, it was noted that the current sample is sicker, reflected by a worse NYHA class, and more depressed than the previous sample (PHQ-9 mean scores 14 vs 7.46, respectively). Additionally, the current sample holds a higher number of current smokers in comparison with the previous sample (52.3% vs 19%, respectively) despite that smoking is negatively associated with QOL.28 These findings should be interpreted with caution since these were yielded from two different cohorts and warrant further investigations to understand the relationship between QOL, COVID-19 stress, resilience and depression in patients with HF.

Adherence scores were found to be below average among the study participants. In fact, when rating on the LMAS, it was found that less than 1% were adherent. This shows a steep decline in adherence which was scored to be 82.4% in 2018 and 77.6% in 2016.26 29 The lower rates are assumed to be due to the limited availability of medications in the country and their inflated cost when available. Despite that, it was shown that those with lower income had better adherence than the participants with slightly higher income. This could be explained by the fact that more than 40% of the participants received their medications from outside the country as seen in this study. Despite the financial restraint being a reason for non-adherence, it was noted that Lebanese participants were more adherent than their non-Lebanese counterparts despite the support that non-Lebanese have from international organisations.30 The baseline data were similar in both groups in terms of social and demographic characteristics except for the income. The similarity in these baseline variables shows the homogeneity in the compared groups at many levels. The income is no longer a significant finding as the currency change in Lebanon marks both categories of this variable as low income.31

Previous studies have shown how poorly self-care is practised among patients with HF and how dependent they can be on their healthcare providers.32 Poor self-care is evident in this sample with the low rates of vaccination against influenza. In fact, vaccination is one of the items used to evaluate self-care maintenance in the HF self-care scales.33 While self-care scores are low, more than 80% of the participants followed up on their medical conditions with their medical team with significantly more follow-up in the non-adherent group compared with the adherent group, which also reflects how reliant these patients can be on their medical teams.

Although mental health conditions were seen as a challenge to medication adherence in previous studies, especially depression and anxiety,9 this study group showed otherwise. Those who had depression were significantly more likely to be adherent to their medications as found in the bivariate analysis. This significance was lost in the regression analysis. The same was seen with anxiety disorders where those who had anxiety were more likely to be adherent to their medications than their counterparts. This was also evident in the multivariate analysis. Medication adherence might be a therapeutic method to alleviate these participants’ anxiety, or symptoms of depression, by following their medical teams’ advice in a challenged society such as Lebanon. Other variables found to be significant in the multivariate analysis were the HF categorization and the NYHA classification. The latter seems to be in line with the literature where a positive relationship was noticed between the two variables.5 A positive relationship was also noted between the history of hypertension and functional class with medication adherence indicating that patients with older medical history and perceived more severe symptoms were more likely to adhere to their medication regimen. This is also in line with the literature.34 An interesting finding was the higher levels of medication adherence among the mid-range HF population in comparison with the HFrEF and HF with preserved EF groups. A similar finding was reported previously showing the lower rates of medication adherence of the HFrEF group in comparison with the mid-range HF group in a large national registry involving almost 100 000 patients hospitalised for HF in the USA over a period of 8 years.35 Overall, research on this group of patients is growing fast and future studies will provide better understanding about the mid-range HF phenotype.

The basic medication therapy recommended by the European guidelines includes the ACEI/ARB, beta-blockers, MRAs, angiotensin receptor neprilysin inhibitor and sodium-glucose co-transporter 2 inhibitor.36 The current rates of medications were low in comparison with those reported in previous studies in the same setting. In fact, a sharp decline was noted over the years in the list of prescribed/home medication for this study population. Beta-blockers were reported as a prescribed medication in 83% of the patients in 201337 and 70% in 201920 in comparison with 54.9% in the current study. Similarly, ACEI/ARB prescription dropped from 78.1% in 2011,37 68% in 201314 and 44.7% in the current study. MRAs were reported by the patients in 201137 to be 32.1%, which dropped down to 13.1% in the current study. This decline shows how poor adherence is to the international guidelines in terms of medical therapy. Additionally, the first three drugs were looked into this study and comparison was provided from the same setting in the literature. The latter two drugs should be looked into in future studies.

Limitations and recommendations for future research

Based on the findings of the LMAS, there was a limited number of participants who were adherent to their medication. This made it difficult to evaluate the factors influencing the adherence in an objective manner. Therefore, the perceived adherence which was then used, reflects the subjective view of the participants. The other limitation lies in the design of the study which does not capture the trends in management and medication prescription but rather the immediate occurrences of these factors as reported by the participants. For example, the reported numbers of medications do not necessarily reflect prescriptions by their physicians but rather the list of medication these patients are currently on or reported to be on. It would be difficult to capture the gap between prescriptions and adherence through a cross-sectional design which could be studied in future longitudinal studies. However, it is expected that prescriptions abide by the international guidelines for the management of HF. These guidelines state that beta-blockers and ACEI/ARBs should be tapered to the highest tolerated doses and the loop diuretic to the lowest possible dose based on the expert opinion.36 Additionally, previous studies addressing this population suggest the high dependence on the medical team as yielded from the self-management scores and items of the Self-care HF Index.32 With all this mentioned, it is safe to assume that prescribed medications are those that are consumed by the participants unless faced with one of the financial or availability issues that are addressed in this paper. Another limitation is the social desirability effect where participants provide the assumed desired answers rather than the actual occurrence. This warrants cautious interpretation of the results. Another limitation is the small sample size with limited representation form the North and Beqaa Region. Although the challenges faced in the country apply to all the regions, a future study with a generalisable sample of the regions should be conducted.

Conclusion

In conclusion, the study showed patients with HF residing in Lebanon to have physical and psychological health problems that are worthy of follow-up to control for their complications. Among these were anxiety, depression and COVID-19 stress. These variables, along with sociodemographic and medical characteristics, were found to be predictors of medication adherence. These findings can be targeted when planning for interventions to improve patient outcomes including medication adherence. Future studies should compare prescribed medication with consumed medication through longitudinal approaches and medical refilling techniques when possible.

Innovation

The role of nurses is evident from the findings of the current study. As it seemed that the cost and availability of the medications were not the only causes for non-adherence, rather sociodemographic variables such as gender and nationality also contributed to the findings. Additionally, physical and psychological chronic conditions and current HF status also contributed to the adherence status. Patient education through nurse-led interventions has shown significant improvement on medication adherence and medication knowledge in multiple studies.38 39 Involving the family caregiver was also seen as a novel approach for improving patient outcomes in previous studies.14 This is especially true in collectivist societies.40 Additionally, adequate follow-up with patients having HF by specialised HF nurses significantly improved their outcomes in terms of hospitalisation and medication adherence.41 These practices can contribute to improving the adherence rates among patients living in challenging conditions.

Data availability statement

Data are available upon reasonable request. Raw data will be available upon request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants. Ethical approval was secured from the Institutional Review Board from Beirut Arab University (approval code: 2021-H-130-HS-R-0462). Prior to the questions, a consent paragraph was included which stated the aims of the study, potential benefits and the expected duration for completion. An option was added to continue with the questions or end the questionnaire if consent was not granted. Therefore, consent was assumed when participants completed the questionnaire.

Acknowledgments

The authors would like to acknowledge the work of the research assistants who were involved in the data collection. Additionally, special thanks to the authors and translators of the tools used in this study.

References

Supplementary materials

Footnotes

  • Twitter @DeekHiba

  • Contributors Both authors have contributed to the conceptualisation of the study and drafting of the paper and approved the final version. Study design—HD and AM. Data collection—HD and AM. Data analysis—HD and AM. Study supervision—HD. Manuscript writing—HD and AM. Critical revisions for important intellectual content—HD and AM. HD is the guarantor and accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.