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Article

Health Literacy, Self-Perceived Health, and Substance Use Behavior among Young People with Alcohol and Substance Use Disorders

1
Department of Addictology, First Faculty of Medicine and General University Hospital in Prague, Charles University, Apolinářská 4, 128 00 Prague 2, Czech Republic
2
Center for Applied Economic Research, Faculty of Management and Economics, Tomas Bata University in Zlín, Mostní 5139, 760 01 Zlín, Czech Republic
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(8), 4337; https://doi.org/10.3390/ijerph18084337
Submission received: 16 February 2021 / Revised: 12 April 2021 / Accepted: 13 April 2021 / Published: 19 April 2021
(This article belongs to the Special Issue Health Literacy, Patient Empowerment and Preventive Medicine)

Abstract

:
Licit and illicit substance use is one of the major public health issues with severe negative health consequences for individuals and society. Health literacy is essential for improving one’s health and navigation in the healthcare system. However, the evidence of health literacy in people with substance use disorders is limited. This study aims to examine health literacy and its socio-demographic, health-related, and substance use-related correlates in young people with alcohol (AUD) and substance use disorders (SUD). In this study, cross-sectional data of young people undergoing addiction treatment for AUD (N = 201, mean age 37.6) and SUD (N = 165, mean age 31.1) were used. Health literacy was assessed using the HLS-EU-Q47. Simple and multiple linear regression was performed to estimate the correlates of health literacy. In total, 37.8% of participants with AUD and 41.8% of SUD had limited health literacy. In participants with AUD, living condition factors, self-perceived health indicators, and frequency of alcohol use showed a significant effect on health literacy. In participants with SUD, financial factors, self-perceived health indicators, and injection sharing showed a significant effect. Increasing health literacy might contribute to improved health outcomes and decreased high-risk substance use-related behavior in people undergoing addiction treatment.

1. Introduction

Licit and illicit substance use is one of the main public health issues with severe negative health consequences for individuals and society [1,2]. Harmful substance use is causally linked to hundreds of physical and mental illnesses and is, therefore, classified among the greatest risk factors for preventable morbidity and mortality [3,4]. Morbidity and mortality related to substance use also affect economic parameters, e.g., in the form of lost productivity and higher cost of diagnostic and treatment processes [5,6,7]; total expenditure attributable to alcohol, tobacco, illicit drugs, and gambling is estimated at up to 3.05–3.15% of GDP in the Czech Republic [8]. However, harmful substance use not only has negative health consequences but also affects social and family relationships, whose quantification for individuals and society is methodologically highly complex [9].
Substance use is a complex phenomenon that has been subjected to extensive research for decades. Its intensity is determined by the complexity and variability of individual socio-economic factors, lifestyle dynamics, globalization processes, and other factors; thus, high heterogeneity in the focus of these studies situated in medical, social, economic, psychological, and other disciplines is observable [10,11,12]. Due to severe negative consequences of the persisting trend of harmful substance use in the population, it is necessary to verify existing knowledge about this phenomenon and seek new ones. The current trend is to investigate complex risk factors that can create strong negative links and complicate prevention or even treatment of substance use disorders.
Health literacy, a multidimensional concept addressing the use of health information, has recently been associated with various risky health behaviors, including substance use [13,14,15,16,17,18]. Currently, several conceptual frameworks of health literacy exist, as the concept has evolved. Health literacy was originally linked to the basic literacy skills of reading, writing, and numeracy in a medical context [19,20]. Recently, a shift to a broader—comprehensive—concept, including a wide range of individual, social, and cognitive competencies, is noticeable [16].
Previous evidence showed that health literacy decreases with age and lower levels of education. Higher percentages of low health literacy were found between socioeconomically disadvantaged people and those who belong to ethnic minorities [21,22]. Moreover, health literacy is considered an important determinant of individual and population health [19,23,24]. Low health literacy is consistently related to poor health status, higher mortality rates, more hospitalization and emergency care use, lower use of preventive activities, poor medication adherence, and poor ability to interpret written health information [23]. Therefore, promoting health literacy can potentially prevent risky health behavior, improve health outcomes, decrease health inequalities, and improve navigation in the healthcare system.
People with alcohol (AUD) or substance use disorder (SUD) are at risk of lower health literacy due to multiple negative health, psychosocial, and economic factors related to substance use behavior [3,25]. Degan et al. (2019) examined health literacy and its association with a number of socio-economic and health-related factors in a mixed sample of people with AUD and SUD (N = 298), finding the prevalence of inadequate health literacy 87%. Low health literacy was associated with higher psychological distress, poor social support, mental health, and quality of life [26]. Rolová et al. (2018) assessed health literacy in people with AUD undergoing inpatient and outpatient addiction treatment (N = 113), finding the prevalence of low health literacy at 46.9% [27]. Most recently, Dahlman et al. (2020) examined health literacy in patients in opioid substitution treatment (OST) (N = 286, including the invalid questionnaires). They reported a prevalence of low health literacy of 22%, but the actual prevalence is likely higher because they added one third of invalid questionnaires into the calculation [28]. Neither did Rolová et al. (2018) nor Dahlman et al. (2020) find any association between health literacy and investigated socio-economic factors [27,28].
Overall, to our knowledge, only three studies examined multidimensional health literacy and its correlates in a disadvantaged population of people with substance use disorders. Previous evidence is limited by bivariate analysis of the data, without controlling for the contribution of other variables in the significant relationship.
Therefore, we aim to (1) describe health literacy in young people with AUD and SUD using a multidimensional measuring tool and (2) investigate the association between health literacy and socio-demographic characteristics, self-perceived health indicators, and substance use behavior in both samples.

2. Methods

In this cross-sectional study, we examine and compare the health literacy in young people undergoing residential addiction treatment for AUD and SUD in the Czech Republic. We used part of the data (N = 394) from a cross-sectional survey on health literacy in people undergoing residential addiction treatment. For detailed methodology, see Rolová (2020) [29].

2.1. Study Sample and Data Collection

Sampling and data collection were conducted between May and December 2019. Institutions of residential addiction treatment (N = 50), i.e., detoxification units with dedicated detoxification beds offering medical detoxification programs, state-run psychiatric hospitals offering long-term institutional treatment, and therapeutic communities offering socio-therapeutic care for individuals with addiction, served as a sampling frame. Of those, 16 (32%) gave us permission to carry out the recruitment of the participants.
Original inclusion criteria included men or women, 15 years old and older, fluent in Czech, and diagnosed with alcohol and other substance use disorders or addictive behaviors. In the present study, only those aged between 18 and 45 years and with a diagnosis of AUD or SUD were included in the analysis.
Data were collected on-site of the involved facilities through anonymous paper-and-pencil questionnaires from all eligible individuals. Participants gave oral consent concerning their involvement in the questionnaire survey prior to the data collection and further expressed their willingness to participate in the survey by completing and submitting the questionnaires to the administrator. Written informed consent requiring personal data of participants was not collected to preserve the anonymity of those involved.
Prior to the statistical analysis, participants were divided into one of two study groups, according to the following criteria: The AUD sample comprises those who reported alcohol as their drug of the first; the SUD sample comprises those who reported any of the illicit substances (cannabinoids, MDMA/ecstasy, methamphetamine, and other amphetamines, cocaine, heroin, buprenorphine and methadone, hallucinogens, inhalants, prescription medications, new psychoactive substances, other) as their drug of the first choice.

2.2. Dependent Variable

This study follows the conceptual framework elaborated by Sørensen [16]. The health literacy of the participants was assessed using the 47-item version of the European Health Literacy Survey Questionnaire (HLS-EU-47) [30]. A Czech translation of the HLS-EU-Q47 was officially acquired from the National Institute of Public Health of the Czech Republic (Ref. PID UK1LF18G/03010 001).
The questionnaire assesses the perceived difficulty of various health-related tasks on a 4-point Likert scale ranging from “very easy” to “very difficult”. Health literacy score (general health literacy index) and three additional indices for sub-domains of health literacy—healthcare, disease prevention, and health promotion—were calculated using the following formula:
Index = (mean − 1) × (50/3)
where Index is the specific index calculated, mean is the mean of all participating items for each individual, 1 is the minimal possible value of the mean, 3 is the range of the mean, and 50 is the chosen maximum value of the new metric. Index 0 represents the lowest possible health literacy and 50 the highest health literacy [31].
In addition, four levels of health literacy were defined according to the recommended cut-offs as “inadequate” (0–25), “problematic” (>25–33), “sufficient” (>33–42), and “excellent” (>42–50) to describe the distribution of health literacy in the study samples. The inadequate and problematic levels correspond to “limited health literacy”; the sufficient and problematic levels correspond to “adequate health literacy” [31].

2.3. Independent Variables

Measurement of socio-demographic characteristics, self-perceived health indicators, and substance use behavior of the participants are described in Rolová (2020) [29]. Socio-demographic characteristics include gender, age, marital status, housing condition, household size, educational attainment, employment status, household net income, debt situation, and size of place of residence.
Self-perceived health indicators of general health status, mental health status, physical condition, and quality of life were measured by single-item questions with the five Likert-type responses (1—bad, 2—rather bad, 3—neither bad nor good, 4—rather good, 5—good). Self-perceived health indicators were treated as continuous variables in regression analysis. Psychiatric comorbidity was assessed by self-report.
Substance use behavior includes cigarette smoking, past-year frequency of alcohol use, binge drinking (use of 5 or more glasses of alcohol on one occasion), and alcohol intoxication, lifetime and past-year illicit drug use, the drug of the first choice, age at onset of alcohol use, alcohol intoxication, marijuana use, and illicit drug use, and a number of premature addiction treatment terminations. Participants with substance use disorders were asked to report the preferred method of drug administration, age at onset of intravenous application, injection sharing, and drug-related infectious diseases.

2.4. Statistical Analysis

We analyzed the data using descriptive statistics, correlation analyses, and linear regression. Indices of health literacy were calculated and categorized to describe the distribution of health literacy in the study samples. Pearson’s chi-square test (for categorical variables) and one-way ANOVA (for continuous variables) were used to determine the differences between the study samples.
Linear regression was performed to estimate health literacy correlates. Simple (univariate) linear regression was used to investigate the relationship between the score of the health literacy assessment (dependent variable) and socio-demographic characteristics, self-perceived health indicators, and substance use behavior. Multiple regression analysis was used to explain the contribution of variables in the health literacy score when controlled for other variables. We did not adjust the multiple analysis for all significant variables to prevent over-fitting of the regression model. The variables entering the regression model were selected based on a priori theoretical knowledge, the empirical importance of variables for this research, and with the aim that each variable category is represented by at least one variable. Previous studies in general and clinical populations found a relationship between health literacy and gender, age, employment status, financial deprivation, and mental health [21,22,26,32]. Regarding the substance use behavior, we included frequency of alcohol use (for AUD) and injection sharing (for SUD) as our variables of interest.
The adjusted R-squared was used to measure the proportion of variation in health literacy score explained by correlates. In all levels, the variables with the alpha level of 0.50 were considered to be statistically significant outcomes. Statistical analyses were performed using IBM SPSS Statistics 23 (IBM Corp., Armonk, NY, USA).

3. Results

Overall, 394 young people (18–45 years old) undergoing residential addiction treatment, of which 201 were people with AUD (24.9% of women, mean age 37.6, median 39) and 165 people with SUD (19.4% of women, mean age 31.1, median 31), were selected for this study. The majority in both samples were men, non-married, with stable housing, living in multi-person households, and with household net income between EUR 1317–2249. In terms of socio-demographic characteristics, study samples differed in terms of age, educational attainment, marital and employment status, and debt situation (Table 1).

3.1. Distribution of Health Literacy

Participants with AUD achieved a mean score (i.e., general health literacy index) of 34.8 (SD = 6.4) out of a potential 50 in HLS-EU-Q47. Overall, 6% of participants with AUD had inadequate, 31.8% problematic, 47.8% sufficient, and 14.4% excellent health literacy. When the scale was dichotomized into two levels, 37.8% of participants with AUD fell into the category of limited health literacy. Participants achieved a mean score of 37.7 (SD = 6.5) in healthcare, 34.6 (SD = 7.5) in disease prevention, and 32.1 (SD = 7.9) in health promotion.
Participants with SUD achieved a mean score of 34.5 (SD = 6.9) in HLS-EU-Q47. Overall, 9.1% of participants with SUD had inadequate, 32.7% problematic, 41.8% sufficient, and 16.4% excellent health literacy; 41.8% of participants fell into the category of limited health literacy. Participants achieved a mean score of 36.6 (SD = 6.5) in healthcare, 34.4 (SD = 8.2) in disease prevention, and 32.5 (SD = 8.6) in health promotion.
There were no statistically significant differences in health literacy scores between the samples (see Table 1).

3.2. Correlates of Health Literacy in People with AUD

Simple linear regression (Table 2) showed a negative significant relationship between health literacy and household condition (p = 0.008), household size (p = 0.024), employment status (p = 0.028), alcohol use (p = 0.032), and binge drinking (p = 0.034). A positive relationship was found between health literacy and general health status (p = 0.009), mental health status (p = 0.001), physical condition (p = 0.002), and quality of life (p = 0.002). Participants with stable housing, living in a multi-person household, employed or short-term unemployed, drinking less than daily, binge drinking less than daily, with better general health status, mental health status, physical condition, and quality of life scored significantly higher in HLS-EU-Q47.
Multiple linear regression (see Table 2) showed that after adjusting for gender, age, housing condition, employment status, mental health status, and alcohol use, health literacy remained significantly associated with housing condition (b = 4.06, 95% CI [−7.47, −0.66], p = 0.020), alcohol use (b = 2.02, 95% CI [−3.85, −0.19], p = 0.031), and mental health status (b = 1.40, 95% CI [0.56, 2.25], p = 0.001). Employment status dropped out of significance.
In people with AUD, multiple regression explained 10.4% of the variance in health literacy score (R2adj = 0.104).

3.3. Correlates of Health Literacy in People with SUD

Simple linear regression (Table 3) showed a positive significant relationship between health literacy and household net income (p = 0.040), general health status (p = 0.028), mental health status (p = 0.001), physical condition (p = 0.023), and quality of life (p = 0.033). A negative significant relationship was found between health literacy and debt situation (p = 0.021) and injection sharing (p = 0.011). Participants with higher household net income, better general health status, mental health status, physical condition, quality of life, without debts, and not involved in injection sharing scored significantly higher in HLS-EU-Q47.
Multiple linear regression (see Table 3) showed that after adjusting for gender, age, debt situation, mental health status, and injection sharing, health literacy remained significantly and positively associated only with mental health status (b = 1.58, 95% CI [0.58, 2.57], p = 0.002). Debt situation and injection sharing dropped out of significance.
In people with SUD, multiple regression explained 11.0% of the variance in health literacy score (R2adj = 0.110).

4. Discussion

Our study focused on health literacy and its correlates in young people undergoing addiction treatment for AUD and SUD. Using the HLS-EU-Q47, we comprehensively assessed the health literacy of a well-defined clinical population of young people with substance use disorders in Central Europe. We used multiple regression to examine a wide range of health literacy correlates, focusing specifically on health- and substance use-related factors.
In total, 37.8% of participants with AUD and 41.8% with SUD had limited health literacy when assessed with the HLS-EU-Q47. Previous studies in substance-using populations using a multidimensional approach to health literacy are inconsistent on this matter; the reported prevalence of lower health literacy ranges between 22 and 87% [26,27,28]. This inconsistency may be related to the different methodologies used or the characteristics of study samples in these studies.
We did not observe any significant differences in health literacy scores of participants with AUD and SUD despite their differences in socio-demographic backgrounds. Individuals with AUD and SUD in long-term addiction treatment (treatment duration is usually between 3–12 months) undergo the treatment process together. They are in daily contact with healthcare providers and regularly educated on various health topics. It is, therefore, reasonable to assume that receiving addiction treatment may improve patients’ health literacy to the point where differences in their health-related competencies are eliminated. It would be interesting to explore to what extent different addiction treatment programs can promote the health literacy of the patients.
In participants with AUD, lower health literacy was associated with being homeless, living alone, and being long-term unemployed. In accordance with our findings, previous research found that homeless persons with mental illness tend to have low health literacy [32]. Homeless persons are disadvantaged in access to healthcare and lack the medical support of healthcare professionals [33,34], which are the factors known to negatively affect health literacy [35]. In terms of the relationship between health literacy and household size, this finding highlights the importance of social and family relationships in the transfer of health-related information and skills [36]. As regards the relationship between health literacy and employment status, long-term unemployment is consistently linked to poor health status, mental illness in particular [37], which is associated with low health literacy [23,26]. In addition, lower health literacy was associated with daily drinking and daily binge drinking in people with AUD, indicating the higher severity of AUD in individuals with low health literacy. We assume that the negative effects of excessive alcohol consumption on cognitive functioning may be the reason for the lower health literacy of those with severe AUD [38]. However, this must be confirmed by other studies that will examine this relationship using the standardized multi-item instruments to measure the severity of AUD.
In participants with SUD, lower health literacy was associated with lower household net income, being burden with debts, and using injection materials previously used by other users. In a previous large-scale population-based study, financial deprivation was found to be one of the strongest predictors of low health literacy [22]. It could be explained by the fact that socioeconomically disadvantaged individuals may not have the financial resources to make healthier choices, e.g., to buy healthy food, health-related literature, attend sport or educational courses, etc., [39,40]. In terms of health literacy and injection sharing, the relationship indicates that substance users with low health literacy might be more inclined to a certain high-risk substance use behavior. Increasing health literacy and drug-related literacy in people with SUD might result in less risky substance use and reduce the spread of drug-related infectious diseases. However, the association between health literacy and the burden of drug-related infectious diseases was not confirmed in this study, more evidence is, therefore, needed on this relationship.
In accordance with other studies in diverse and addicted populations, self-perceived general health status, mental health status, physical condition, and quality of life were positively associated with health literacy in both samples of participants with AUD and SUD [13,23,26]. In both groups, mental health status was found to be the strongest predictor of health literacy. The relationship between health literacy and health outcomes is well established; health literacy is recognized as an independent social determinant of health. Moreover, the evidence suggests that the relationship between health literacy and health indicators is at least partially mediated by health knowledge, self-efficacy, norms, and perceived stigma [23].
Our findings support both the improvement of existing health literacy-promoting programs as well as the development of new ones tailored to the needs of the patients in the healthcare setting. Health literacy-promoting programs, as a quality, comprehensive, long-term tool for improving the health of the population and increasing the efficiency of the healthcare service, must be developed conceptually and systemically. It is to be directly linked to existing concepts of health literacy and tailored to the demographic, health, geographical, social, and other characteristics of its recipients. There is potential in well-designed health literacy-promoting programs to eliminate the emergence of repeated morbidity that impact the healthcare system’s economic resources, which are exhaustible.
Programs of addiction treatment provide therapeutic care with varying durations; therefore, it is assumed that longer use of therapeutic healthcare processes will also affect patients’ health literacy. In treatment programs of shorter duration, there is also a space to promote the health literacy of patients, but it is important to identify the factors that most influence it.
Investigation of patient’s socio-economic characteristics that might influence health literacy during the treatment regardless of its length or type of health or social service program also comes to attention. Unstable and absent family background or housing, long-term unemployment, and income loss remain strong risk factors for returning to addictive behavior, prompting the need to examine new social trajectories in relation to health literacy among patients during treatment. Therefore, we suggest that future research should continue to investigate the correlates of health literacy in people with addictions with the special emphasis on health indicators, living conditions, and financial factors.
Finally, this study has several limitations that must be acknowledged. The cross-sectional design of the study does not allow causality between health literacy and its correlates to be established. Regarding the measurement tool, health literacy was measured using the self-administered tool. Subjective questionnaires are known to be prone to social desirability and recall bias [41]; therefore, the level of health literacy in the participants may not be estimated correctly. Moreover, Finbråten (2018) recently pointed out some psychometric shortcomings (violation of multidimensionality and response dependence) of HLS-EU-Q47 [42]. On the other hand, other previous studies tested psychometric properties of HLS-EU-Q47 with satisfactory outcomes [30,43]. The Czech translation of HLS-EU-Q47 was not systematically validated for the Czech population. However, the Czech version of the questionnaire was tested in the representative population-based study of Kučera et al. (2016) [44]. As for the study sample, both study samples are rather small; therefore, studies with larger samples are needed to confirm our results. Nevertheless, given the specific characteristics of this population, the study may offer valuable insight into this issue. Self-selection of study participants could have resulted in biased results; although, the overall response rate to the recruitment process was high. The proportion of those involved from all eligible individuals was 86%.

5. Conclusions

In this study, we examine health literacy in a clinical population of young people with substance use disorders in the Czech Republic. Our results suggest that a considerable proportion of young people undergoing addiction treatment with AUD and SUD might not be able to use health information to take care of their health and navigate the healthcare system effectively. Health literacy should be systematically promoted in residential addiction treatment programs to improve the health outcomes of patients. We identified a number of related factors that might influence or be influenced by health literacy in people with substance use disorders. Furthermore, this study highlights the importance of the investigation of complex risk factors in the research of substance use.

Author Contributions

Conceptualization, G.R.; methodology, G.R. and B.P.; software, G.R.; validation, G.R., B.G., and B.P.; formal analysis, G.R. and B.P.; investigation, G.R.; resources, B.G.; data curation, G.R.; writing—original draft preparation, G.R., B.G., and B.P.; writing—review and editing, B.G. and B.P.; visualization, G.R.; supervision, B.G.; project administration, G.R.; funding acquisition, G.R. and B.G. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Charles University, project GA UK No. 8119: “Health literacy in people undergoing treatment for drug addiction”; Specific Academic Research Projects Competition (SVV) No. 260500; Progres No. Q06/LF1. This research was funded by the RO/2020/05 Internal Grant Scheme of the Tomas Bata University in Zlin under name “Economic quantification of marketing processes aimed at increasing value for the patient in the process of construction of system in order to measure and to manage performance in healthcare facilities in the Czech Republic”.

Institutional Review Board Statement

This study was approved by the Ethics Committee of the General University Hospital in Prague (Ref. 88/18 Grant GA UK 1. LF UK). The study was carried out with respect to the seventh revision of the World Medical Association Declaration of Helsinki [45] and the second revision of the Farmington Consensus [46].

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available in aggregated form on request from the first author due to privacy reasons.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. United Nations Office on Drugs and Crime. World Drug Report 2020; United Nations Office on Drugs and Crime: Vienna, Austria, 2020. [Google Scholar]
  2. World Health Organization. Global Status Report on Alcohol and Health 2018; World Health Organization: Geneva, Switzerland, 2019. [Google Scholar]
  3. Degenhardt, L.; Charlson, F.; Ferrari, A.; Santomauro, D.; Erskine, H.; Mantilla-Herrara, A.; Whiteford, H.; Leung, J.; Naghavi, M.; Griswold, M.; et al. The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Psychiatry 2018, 5, 987–1012. [Google Scholar] [CrossRef] [Green Version]
  4. Rehm, J.; Baliunas, D.; Borges, G.L.; Graham, K.; Irving, H.; Kehoe, T.; Parry, C.D.; Patra, J.; Popova, S.; Poznyak, V.; et al. The relation between different dimensions of alcohol consumption and burden of disease: An overview. Addiction 2010, 105, 817–843. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Andlin-Sobocki, P. Economic evidence in addiction: A review. Eur. J. Health Econ. 2004, 5, S5–S12. [Google Scholar] [CrossRef] [PubMed]
  6. Megyesiová, S.; Gavurová, B. Analysis of Alcohol Consumption and Death Rates Resulting from Alcohol Consumption in EU and OECD Countries. Adiktologie 2019, 19, 179–187. [Google Scholar] [CrossRef]
  7. Sopko, J.; Kočišová, K. Key Indicators and Determinants in the Context of the Financial Aspects of Health Systems in Selected Countries. Adiktologie 2019, 19, 189–202. [Google Scholar] [CrossRef]
  8. Gavurova, B.; Kulhanek, A.; Gabrhelik, R.; Tarhanicova, M. The Economic Costs of Alcohol, Tobacco and Illicit Drugs in Czech Republic; Department of Addictology, First Faculty of Medicine and General University Hospital in Prague: Prague, Czech Republic, 2021. [Google Scholar]
  9. Lander, L.; Howsare, J.; Byrne, M. The impact of substance use disorders on families and children: From theory to practice. Soc. Work. Public Health 2013, 28, 194–205. [Google Scholar] [CrossRef]
  10. Galea, S.; Nandi, A.; Vlahov, D. The social epidemiology of substance use. Epidemiol. Rev. 2004, 26, 36–52. [Google Scholar] [CrossRef] [Green Version]
  11. Volkow, N.D.; Baler, R.D. Addiction science: Uncovering neurobiological complexity. Neuropharmacology 2014, 76, 235–249. [Google Scholar] [CrossRef] [Green Version]
  12. West, R. EMCDDA Insights: Models of Addiction; European Monitoring Centre for Drugs and Drug Addiction: Lisbon, Portugal, 2013. [Google Scholar]
  13. Aaby, A.; Friis, K.; Christensen, B.; Rowlands, G.; Maindal, H.T. Health literacy is associated with health behaviour and self-reported health: A large population-based study in individuals with cardiovascular disease. Eur. J. Prev. Cardiol. 2017, 24, 1880–1888. [Google Scholar] [CrossRef] [Green Version]
  14. Geboers, B.; Reijneveld, S.A.; Jansen, C.J.M.; de Winter, A.F. Health Literacy Is Associated with Health Behaviors and Social Factors Among Older Adults: Results from the LifeLines Cohort Study. J. Health Commun. 2016, 21, 45–53. [Google Scholar] [CrossRef]
  15. Husson, O.; Mols, F.; Fransen, M.P.; Van De Poll-Franse, L.V.; Ezendam, N.P.M. Low subjective health literacy is associated with adverse health behaviors and worse health-related quality of life among colorectal cancer survivors: Results from the profiles registry. Psycho-Oncology 2015, 24, 478–486. [Google Scholar] [CrossRef]
  16. Sørensen, K.; Van Den Broucke, S.; Fullam, J.; Doyle, G.; Pelikan, J.; Slonska, Z.; Brand, H. Health literacy and public health: A systematic review and integration of definitions and models. BMC Public Health 2012, 12, 80. [Google Scholar] [CrossRef] [Green Version]
  17. Von Wagner, C.; Knight, K.; Steptoe, A.; Wardle, J. Functional health literacy and health-promoting behaviour in a national sample of British adults. J. Epidemiol. Community Health 2007, 61, 1086–1090. [Google Scholar] [CrossRef]
  18. Wolf, M.S.; Gazmararian, J.A.; Baker, D.W. Health Literacy and Health Risk Behaviors among Older Adults. Am. J. Prev. Med. 2007, 32, 19–24. [Google Scholar] [CrossRef]
  19. Nutbeam, D. The evolving concept of health literacy. Soc. Sci. Med. 2008, 67, 2072–2078. [Google Scholar] [CrossRef]
  20. Peerson, A.; Saunders, M. Health literacy revisited: What do we mean and why does it matter? Health Promot. Int. 2009, 24, 285–296. [Google Scholar] [CrossRef] [Green Version]
  21. Paasche-Orlow, M.K.; Parker, R.M.; Gazmararian, J.A.; Nielsen-Bohlman, L.T.; Rudd, R.R. The prevalence of limited health literacy. J. Gen. Intern. Med. 2005, 20, 175–184. [Google Scholar] [CrossRef]
  22. Sørensen, K.; Pelikan, J.M.; Röthlin, F.; Ganahl, K.; Slonska, Z.; Doyle, G.; Fullam, J.; Kondilis, B.; Agrafiotis, D.; Uiters, E.; et al. Health literacy in Europe: Comparative results of the European health literacy survey (HLS-EU). Eur. J. Public Health 2015, 25, 1053–1058. [Google Scholar] [CrossRef] [Green Version]
  23. Berkman, N.D.; Sheridan, S.L.; Donahue, K.E.; Halpern, D.J.; Crotty, K. Low health literacy and health outcomes: An updated systematic review. Ann. Intern. Med. 2011, 155, 97–107. [Google Scholar] [CrossRef]
  24. Mårtensson, L.; Hensing, G. Health literacy—A heterogeneous phenomenon: A literature review. Scand. J. Caring Sci. 2012, 26, 151–160. [Google Scholar] [CrossRef]
  25. Gomez, R.; Thompson, S.J.; Barczyk, A.N. Factors associated with substance use among homeless young adults. Subst. Abus. 2010, 31, 24–34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Degan, T.J.; Kelly, P.J.; Robinson, L.D.; Deane, F.P. Health literacy in substance use disorder treatment: A latent profile analysis. J. Subst. Abus. Treat. 2019, 96, 46–52. [Google Scholar] [CrossRef]
  27. Rolová, G.; Barták, M.; Rogalewicz, V.; Gavurová, B. Health literacy in People Undergoing Treatment for Alcohol Abuse—A Pilot Study. Kontakt 2018, 20, e394–e400. [Google Scholar] [CrossRef]
  28. Dahlman, D.; Ekefäll, M.; Garpenhag, L. Health literacy among Swedish patients in opioid substitution treatment: A mixed-methods study. Drug Alcohol Depend. 2020, 214, 108186. [Google Scholar] [CrossRef]
  29. Rolová, G. Health Literacy in Residential Addiction Treatment Programs: Study Protocol of a Cross-Sectional Study in People with Substance Use Disorders. Adiktologie 2020, 20, 145–150. [Google Scholar] [CrossRef]
  30. Sørensen, K.; Van den Broucke, S.; Pelikan, J.M.; Fullam, J.; Doyle, G.; Slonska, Z.; Kondilis, B.; Stoffels, V.; Osborne, R.H.; Brand, H. Measuring health literacy in populations: Illuminating the design and development process of the European Health Literacy Survey Questionnaire (HLS-EU-Q). BMC Public Health 2013, 13, 948. [Google Scholar] [CrossRef] [Green Version]
  31. Pelikan, J.; Röthlin, F.; Ganahl, K. Comparative Report of Health Literacy in Eight EU Member States. 2012. Available online: http://cpme.dyndns.org:591/adopted/2015/Comparative_report_on_health_literacy_in_eight_EU_member_states.pdf (accessed on 16 April 2021).
  32. Farrell, S.J.; Dunn, M.; Huff, J. Examining Health Literacy Levels in Homeless Persons and Vulnerably Housed Persons with Mental Health Disorders. Commun. Ment. Health J. 2019, 56, 1–7. [Google Scholar] [CrossRef]
  33. Baggett, T.P.; O’Connell, J.J.; Singer, D.E.; Rigotti, N.A. The unmet health care needs of homeless adults: A national study. Am. J. Public Health 2010, 100, 1326–1333. [Google Scholar] [CrossRef]
  34. Elwell-Sutton, T.; Fok, J.; Albanese, F.; Mathie, H.; Holland, R. Factors associated with access to care and healthcare utilization in the homeless population of England. J. Public Health 2017, 39, 26–33. [Google Scholar] [CrossRef] [Green Version]
  35. Levy, H.; Janke, A. Health literacy and access to care. J. Health Commun. 2016, 21, 43–50. [Google Scholar] [CrossRef]
  36. Ishikawa, H.; Kiuchi, T. Association of health literacy levels between family members. Front. Public Health 2019, 7, 169. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Norström, F.; Virtanen, P.; Hammarström, A.; Gustafsson, P.E.; Janlert, U. How does unemployment affect self-assessed health? A systematic review focusing on subgroup effects. BMC Public Health 2014, 14, 1310. [Google Scholar] [CrossRef] [PubMed]
  38. Bernardin, F.; Maheut-Bosser, A.; Paille, F. Cognitive impairments in alcohol-dependent subjects. Front. Psychiatry 2014, 5, 78. [Google Scholar] [CrossRef] [PubMed]
  39. Phelan, J.C.; Link, B.G.; Tehranifar, P. Social conditions as fundamental causes of health inequalities: Theory, evidence, and policy implications. J. Health Soc. Behav. 2010, 51, S28–S40. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Stormacq, C.; Van den Broucke, S.; Wosinski, J. Does health literacy mediate the relationship between socioeconomic status and health disparities? Integrative review. Health Promot. Int. 2019, 34, e1–e17. [Google Scholar] [CrossRef]
  41. Latkin, C.A.; Edwards, C.; Davey-Rothwell, M.A.; Tobin, K.E. The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland. Addict. Behav. 2017, 73, 133–136. [Google Scholar] [CrossRef]
  42. Finbråten, H.S. Measuring Health Literacy. Evaluating Psychometric Properties of the HLS-EU-Q47 and the FCCHL, Suggesting Instrument Refinements and Exploring Health Literacy in People with Type 2 Diabetes and in the General Norwegian Population. Ph.D. Thesis, Department of Health Sciences, Faculty of Health, Science and Technology, Karlstad University, Karlstad, Sweden, 2018. [Google Scholar]
  43. Toçi, E.; Burazeri, G.; Sørensen, K.; Kamberi, H.; Brand, H. Concurrent validation of two key health literacy instruments in a South Eastern European population. Eur. J. Public Health 2015, 25, 482–486. [Google Scholar] [CrossRef] [Green Version]
  44. Kučera, Z.; Pelikan, J.; Šteflová, A. Zdravotní gramotnost obyvatel ČR—Výsledky komparativního reprezentativního šetření [Health literacy in Czech population—Results of the comparative representative research]. Cas. Lék. Ceských 2016, 155, 233–241. [Google Scholar]
  45. World Medical Association. World Medical Association Declaration of Helsinki—Ethical Principles for Medical Research Involving Human Subjects. 2013. Available online: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects (accessed on 23 September 2020).
  46. International Society of Addiction Journal Editors. The Farmington Consensus. 2017. Available online: http://www.isaje.net/farmington-consensus.html (accessed on 23 September 2020).
Table 1. Socio-demographic, health-related, and substance use-related characteristics of participants with AUD and SUD and the differences between the study samples.
Table 1. Socio-demographic, health-related, and substance use-related characteristics of participants with AUD and SUD and the differences between the study samples.
AUD
(N = 201)
SUD
(N = 165)
CharacteristicsN (* mean)% (* SD)N (* mean)% (* SD)p
Health literacy
General health literacy *34.86.434.56.90.674
Healthcare *37.76.536.66.50.110
Disease prevention *34.67.534.48.20.794
Health promotion *32.17.932.58.60.615
Gender 0.260
Man15175.113380.6
Woman5024.93219.4
Age *37.65.931.16.4<0.001
Type of treatment <0.001
Detoxification3316.42515.2
Long-term inpatient care13667.79859.4
Therapeutic community115.53521.2
Follow-up inpatient care2110.474.2
Marital status <0.001
Married3617.963.6
Other16582.115996.4
Housing condition 0.009
Stable housing18290.513179.4
Without home168.02817.0
Household size *2.261.32.631.50.178
Single-person7939.34929.7
Multi-person11356.210664.2
Educational attainment <0.001
Primary2914.46841.2
Secondary and higher171859658.2
Employment status <0.001
Employed12562.26941.8
<6 months4622.93521.2
≥6 months2210.94627.9
Household net income 0.159
EUR <5623416.93420.6
EUR 563–13168140.35030.3
EUR 1317–22495426.94225.5
EUR >22492010.02515.2
Debt situation <0.001
Debts6532.38752.7
No debts13567.27746.7
Psychiatric comorbidity 0.136
Yes4120.44527.3
No15778.111770.9
General health status *3.71.13.81.00.137
Bad or rather bad2512.41911.5
Neither bad nor good6029.94225.5
Good or rather good11557.210261.8
Mental health status *3.51.13.61.00.144
Bad or rather bad3517.42615.8
Neither bad nor good6431.84326.1
Good or rather good10150.29457.0
Physical condition *3.61.03.71.00.124
Bad or rather bad3316.42313.9
Neither bad nor good5728.44024.2
Good or rather good11155.210161.2
Quality of life *3.11.13.11.00.279
Bad or rather bad5929.44124.8
Neither bad nor good7235.86640.0
Good or rather good6934.35734.5
Cigarette smoking 0.512
Non-smoker4622.93118.8
<15 cigarettes3818.93621.8
≥15 cigarettes10853.79557.6
Alcohol use <0.001
Less than daily8240.811770.9
Daily11456.74627.9
Binge drinking <0.001
Less than daily11054.712877.6
Daily8642.83320.0
Alcohol intoxication 0.041
Less than daily17386.115392.7
Daily2311.495.5
Lifetime illicit drug use N/A
No4723.400
Yes9245.815292.1
Past year illicit drug use <0.001
No10351.263.6
Yes9245.815292.1
First alcohol use *15.23.613.62.50.024
First alcohol intoxication *16.44.114.22.3<0.001
First marijuana use *18.05.014.82.4<0.001
First illicit drug use *20.05.217.73.8<0.001
Premature treatment termination *0.71.61.32.40.106
Intravenous drug administration N/A
Yes005432.7
No20110010966.1
First intravenous administration * 19.14.1N/A
Injection sharing N/A
Yes 6438.8
No 9758.8
Drug-related infectious diseases N/A
Yes 3521.2
No 12676.4
Note: AUD = alcohol use disorder; SUD = substance use disorder; N = number of cases; SD = standard deviation; p = p-value, * = continuous variable. Pearson’s chi-square test (for categorical variables) and one-way ANOVA (for continuous variables) were used to determine the statistical differences between the samples.
Table 2. Simple (univariate) and multiple linear regression models for health literacy (dependent variable) and socio-demographic, health-related, and substance use-related correlates for the sample of people with AUD.
Table 2. Simple (univariate) and multiple linear regression models for health literacy (dependent variable) and socio-demographic, health-related, and substance use-related correlates for the sample of people with AUD.
UnivariateMultiple (N = 186)
Factorb (95% CI)SEpb (95% CI)SEp
Gender
Woman−0.01 (−2.06, 2.05)1.00.994−0.78 (−2.89, 1.33)1.10.468
Man (ref.)
Age−0.03 (−0.18, 0.12)0.10.708−0.02 (−0.17, 0.13)0.10.759
Type of treatment
Detoxification1.45 (−0.99, 3.90)1.20.242
Therapeutic community−0.63 (−4.57, 3.32)2.00.755
Follow-up inpatient care1.45 (−1.51, 4.40)1.50.335
Long-term inpatient care (ref.)
Marital status
Married1.13 (−1.19, 3.44)1.20.338
Other (ref.)
Housing condition
Without home−4.34 (−7.55, −1.12)1.60.008−4.06 (−7.47, −0.66)1.70.020
Stable housing (ref.)
Household size
Single-person−2.11 (−3.94, −0.29)0.90.024
Multi-person (ref.)
Educational attainment
Primary−0.03 (−2.55, 2.49)1.30.983
Secondary and higher (ref.)
Employment status
Long-term unemployed−3.18 (−6.00, −0.35)1.40.028−1.99 (−4.86, −0.88)1.50.172
Employed/short-term unemployed (ref).
Household net income0.20 (−0.06, 0.46)0.10.135
Debt situation
Debts1.28 (−0.62, 3.17)1.00.185
No debts (ref.)
Psychiatric comorbidity
Yes−0.33 (−2.54, 1.88)1.10.770
No (ref.)
General health status1.12 (0.29, 1.96)0.40.009
Mental health status1.37 (0.55, 2.20)0.40.0011.40 (0.56, 2.25)0.40.001
Physical condition1.31 (0.47, 2.15)0.40.002
Quality of life1.29 (0.47, 2.06)0.40.002
Cigarette smoking
Non-smoker−0.18 (−2.32, 1.96)1.10.868
<15 cigarettes1.98 (−0.32, 4.27)1.20.091
≥15 cigarettes (ref.)
Alcohol use
Daily−1.95 (−3.73, −0.17)0.90.032−2.02 (−3.85, −0.19)0.90.031
Less than daily (ref.)
Binge drinking
Daily−1.91 (−3.68, −0.15)0.90.034
Less than daily (ref.)
Lifetime illicit drug use
No−0.62 (−2.73, 1.50)1.10.566
Yes (ref.)
Past year illicit drug use
Yes0.57 (−1.24, 2.37)0.90.538
No (ref.)
First alcohol use0.07 (−0.19, 0.33)0.10.594
First alcohol intoxication−0.05 (−0.28, 0.18)0.10.685
Premature treatment termination−0.01 (−0.61, 0.59)0.30.971
Note: b: unstandardized coefficient; CI: confidence interval; SE: standard error; p: p-value; ref.: reference group.
Table 3. Simple (univariate) and multiple linear regression models for health literacy (dependent variable) and socio-demographic, health-related, and substance use-related correlates for the sample of people with SUD.
Table 3. Simple (univariate) and multiple linear regression models for health literacy (dependent variable) and socio-demographic, health-related, and substance use-related correlates for the sample of people with SUD.
UnivariateMultiple (N = 160)
Factorb (95% CI)SEpb (95% CI)SEp
Gender
Woman−2.19 (−4.85, 0.48)1.40.107−2.29 (−4.96, 0.38)1.40.093
Man (ref.)
Age0.05 (−0.11, 0.22)0.10.5290.06 (−0.11, 0.22)0.10.484
Type of treatment
Detoxification1.32 (−1.73, 4.37)1.60.395
Therapeutic community−1.15 (−3.84, 1.53)1.40.397
Follow-up inpatient care1.02 (−4.31, 6.34)2.70.707
Long-term inpatient care (ref.)
Housing condition
Without home−1.97 (−4.81, 0.87)1.40.172
Stable housing (ref.)
Household size
Single-person−1.28 (−3.62, 1.05)1.20.280
Multi-person (ref.)
Educational attainment
Primary−0.89 (−3.05, 1.28)1.10.420
Secondary and higher (ref.)
Employment status
Long-term unemployed−0.75 (−3.16, 1.66)1.20.541
Employed/short-term unemployed (ref).
Household net income0.30 (0.01, 0.59)0.10.040
Debt situation
Debts−2.49 (−4.59, −0.29)1.10.021−2.01 (−4.15, 0.13)1.10.066
No debts (ref.)
Psychiatric comorbidity
Yes−2.19 (−4.55, 0.18)1.20.070
No (ref.)
General health status1.17 (0.13, 2.22)0.50.028
Mental health status1.67 (0.68, 2.67)0.50.0011.58 (0.58, 2.57)0.50.002
Physical condition1.18 (0.16, 2.18)0.50.023
Quality of life1.16(0.10, 2.22)0.50.033
Cigarette smoking
Non-smoker1.26 (−1.53, 4.05)1.40.374
<15 cigarettes1.68 (−0.97, 4.32)1.30.212
≥15 cigarettes (ref.)
Alcohol use
Daily0.37 (−2.01, 2.74)1.20.760
Less than daily (ref.)
Binge drinking
Daily−0.91 (−3.54, 1,73)1.30.498
Less than daily (ref.)
First alcohol use0.20 (−0.25, 0.64)0.20.391
First alcohol intoxication0.27 (−0.21, 0.75)0.20.267
First marijuana use0.26 (−0.18, 0.70)0.20.247
First illicit drug use0.16 (−0.12, 0.44)0.10.258
Premature treatment termination0.06 (−0.41, 0.52)0.20.813
Intravenous drug administration
Yes−0.88 (−3.15, 1.39)1.20.444
No (ref.)
First intravenous administration−0,36 (−0.73, 0.02)0.20.065
Injection sharing
Yes−2.84 (−5.00, −0.67)1.10.011−1.89 (−4.06, 0.27)1.10.086
No (ref.)
Drug-related infectious diseases
Yes−0.16 (−2.79, 2.46)1.30.902
No (ref.)
Note: b: unstandardized coefficient; CI: confidence interval; SE: standard error; p: p-value; ref.: reference group.
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Rolova, G.; Gavurova, B.; Petruzelka, B. Health Literacy, Self-Perceived Health, and Substance Use Behavior among Young People with Alcohol and Substance Use Disorders. Int. J. Environ. Res. Public Health 2021, 18, 4337. https://doi.org/10.3390/ijerph18084337

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Rolova G, Gavurova B, Petruzelka B. Health Literacy, Self-Perceived Health, and Substance Use Behavior among Young People with Alcohol and Substance Use Disorders. International Journal of Environmental Research and Public Health. 2021; 18(8):4337. https://doi.org/10.3390/ijerph18084337

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Rolova, Gabriela, Beata Gavurova, and Benjamin Petruzelka. 2021. "Health Literacy, Self-Perceived Health, and Substance Use Behavior among Young People with Alcohol and Substance Use Disorders" International Journal of Environmental Research and Public Health 18, no. 8: 4337. https://doi.org/10.3390/ijerph18084337

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