Factors associated with abstinence in addiction inpatient treatment cohort: a five-year follow-up

ABSTRACT

Background

Overcoming addiction is characterized by a long-term recovery process and a high rate of relapse. This study aimed to identify factors associated with relapse and long-term abstinence in patients with substance use disorders or behavioral addictions (SUDs/BA) five years after completing the inpatient addiction treatment based on the Apolinar model.

Methods

In this 5-year prospective cohort study, 366 (female 32.5%) patients with diagnosed SUDs/BA (ICD-10) who were treated between March 2004 and April 2008 in Czechia were studied. Data were collected using a non-standardized questionnaire and structured telephone interviews. Outcome measures were (i) relapse and (ii) long-term abstinence (at least one full year of continuous abstinence). Logistic regression was used to assess the effect of socio-demographic and treatment-related characteristics on outcome measures.

Results

In a 5-year follow-up period, 70.2% of patients relapsed, while 46.7% relapsed within the first six months after completing the baseline treatment. Long-term abstinence was observed in 63.9% of patients. Of the treatment-related factors, early discontinuation of treatment, shorter treatment duration, and absence of early aftercare services predicted relapse in patients. A positive effect of early aftercare attendance on long-term abstinence was found.

Conclusions

These findings support the importance of treatment compliance and aftercare to prevent relapse in addiction-treated patients.

KEYWORDS:

• Substance use disorders
• addiction treatment
• relapse
• continuous abstinence
• Apolinar model
• behavioral addictions

Introduction

Addiction, including substance use disorders and behavioral addictions (SUDs/BA), is a chronic and recurring disease causally linked to a range of adverse health consequences and premature death (Degenhardt et al., 2018). Overcoming addiction is typically characterized by a long-term recovery process and a high rate of relapse (Dennis & Scott, 2007; Dennis et al., 2005; Fleury et al., 2016; White et al., 2002). Despite extensive research on relapse predictors, the number of patients experiencing relapse after treatment remains high (Dennis et al., 2005; Sinha, 2011; Sliedrecht et al., 2019; Witkiewitz & Marlatt, 2004). Studying relapse within different addiction treatment models may help distinguish less effective treatment approaches from those leading to successful and stable remission from addiction.

Traditionally, clinically managed addiction recovery is abstinence-based. The number of patients abstaining in the post-treatment period is perceived as an important indicator of treatment quality (Krausz et al., 2015). Although relapse prevention is an integral part of recovery in most addiction treatment approaches, high relapse rates remain a major concern in addiction treatment. Longitudinal studies have shown that the first three months are a particularly vulnerable period for relapse and that most patients return to psychoactive substance use by the end of the first year after discharge (Dawson et al., 2007; Hunt et al., 1971; Sinha, 2011). In addition, previous studies looking at patient treatment trajectories have revealed that it usually takes many years of drug use and repeated treatments to achieve stable long-term remission from SUD (Dennis et al., 2005; Fleury et al., 2016; Hser et al., 2001; Kelly et al., 2019). Fleury et al. (2016) estimated in their meta-analysis that 35% to 54.4% of individuals with SUD reach remission at least six months after a mean of 17 years of drug use. In a recent study, Kelly et al. (2019) found that the mean number of recovery attempts in 2,002 abstaining adults was as high as 5.4 (SD = 13.4), with a median equal to 2.

In terms of predictors, relapse is considered a multifactorial phenomenon determined by a combination of intrapersonal and interpersonal ascendants (Sliedrecht et al., 2019; Witkiewitz & Marlatt, 2004). The most prominent psychosocial risk factors associated with relapse include psychiatric comorbidity, severe addiction, drug craving, negative emotions, illicit drug use, poor health, and disadvantaged social background. In contrast, increased social support, self-efficacy, coping skills, and spirituality are considered important protective factors preventing relapse (Sliedrecht et al., 2019; Witkiewitz & Marlatt, 2004). Several studies have suggested the relationship between relapse and a number of treatment-related factors, namely treatment completion (Bottlender & Soyka, 2005; Decker et al., 2017; Haver et al., 2001; Stark, 1992) and aftercare attendance (Fiorentine & Hillhouse, 2000; Gossop et al., 2003; Hambley et al., 2010).

Many models and approaches to addiction treatment are recognized nowadays (e.g., contingency management therapy, cognitive behavioral therapy, or mindfulness) (Carroll & Onken, 2005; Li et al., 2017; McHugh et al., 2010). In general, these approaches differ in the principles on which they are based, the intensity and duration of the treatment process, and the range of therapeutic activities and interventions. Therefore, varying clinical efficacy reflected in relapse rates may be expected (De Crescenzo et al., 2018; Minozzi et al., 2016).

Apolinar treatment model

The Apolinar treatment model was built on the fundamentals of the residential treatment model that had existed in Czechia since 1911 (Šejvl & Miovský, 2017). Since 1948, the Apolinar model became one of the most widely utilized inpatient addiction treatment models in Czechia and Slovakia. The model conceptualization is also well-known abroad (Sejvl et al., 2019; Šejvl et al., 2021).

The Apolinar treatment model combines the principles of the treatment in a therapeutic community and behavioral approaches (Sejvl et al., 2019; Šejvl et al., 2021). Inpatient treatment implementing this model is typically characterized by a highly structured and demanding abstinence-oriented treatment regimen with a sophisticated scoring system, a high level of the patient-provider hierarchy, and an emphasis on the patient community setting. Each patient participates and is responsible for daily activities management (daily community reporting, cleaning, cooking, grocery, and essentials shopping). For their activity and behavior, patients are either rewarded or penalized with points recorded in the scoring system. Accumulation of negative points may result in discharge from treatment. The goal is to achieve physical and mental stabilization, motivation to change, maintain abstinence and relapse prevention, and social resocialization in patients. A multidisciplinary team that consists of various medical and health professionals (psychiatrists, psychologists, addiction specialists, social workers, and general nurses) is an important element of the therapeutic process. The therapeutic process includes various psychotherapeutic methods, pharmacotherapy, physical, psychiatric, and social rehabilitation, social work, education, occupational therapy, and sport (Kalina, 2001; Miovský, 2013; Šejvl et al., 2021).

In recent years, some features of the Apolinar treatment model have been criticized for bearing traces of the authoritarian regime persisting from the Czechoslovakian Communist era when the model originated. Specifically, paternalism, a high level of hierarchy and directiveness in the patient-provider relationship, a high degree of patient control, unified treatment disrespecting of individual patient needs, collectivism, limited contact with the patient environment, and utilization of power tools in treatment (penalty scoring system). In today’s perspective, such features are criticized for not adhering to the current concept of effective addiction treatment (patient-centered approach, self-management support, balanced patient-provider relationship) (National Institute on Drug Abuse, 2018). In many Czech inpatient treatment programs, however, some of these controversial features persist to some extent nowadays (Dvořáček, 2020; Kalina, 2021).

Some previous studies investigated treatment outcomes of patients receiving treatment according to the Apolinar treatment model. Csémy et al. (2012) examined long-term abstinence and its predictors in 150 female patients with alcohol use disorder undergoing inpatient addiction treatment based on the Apolinar model. The prevalence of abstinence was 47.4% 1-year and 56.8% 3-years after the baseline treatment. Depression disorder pharmacotherapy, treatment completion, and social support had positive effects on patient abstinence, while psychiatric comorbidity had a negative effect. Our two previous studies (Tibenská et al., 2008, 2016) described abstinence outcomes in male and female patients 2- and 5 years after mid-term inpatient treatment based on the Apolinar model.

Despite its long tradition in Central Europe, the long-term effectiveness of the Apolinar treatment model in addiction treatment has not been sufficiently studied yet. Understanding the factors in predicting relapse is of clinical relevance and essential to establishing evidence-based programs for addiction recovery and improving patient treatment outcomes. Therefore, this study aimed to identify factors associated with (1) relapse and (2) long-term abstinence in patients with SUDs/BA five years after completing the mid-term inpatient treatment based on the Apolinar treatment model.

Materials and methods

Design and setting

In this 5-year observational prospective follow-up study, we analyzed data from a cohort of 366 patients with SUDs/BA entering mid-term inpatient addiction care in a psychiatric hospital in Czechia between March 2004 and April 2008.

Sample and data collection

The subject of research of this study were patients with SUDs/BA entering mid-term inpatient treatment between 2004–2008. Data on participant abstinence outcomes were collected from their designated relatives.

Patients were invited to participate in the study if they met the following inclusion criteria: (1) fulfilled the diagnostic criteria for mental and behavioral disorders due to psychoactive substance use (F10-F19) or habit and impulse disorders (F63) according to ICD-10, (2) undergoing treatment in mid-term inpatient care for at least 60 days (2 months), (3) giving consent to contact their relatives to obtain data on their abstinence outcomes, and (5) providing contact details of their relatives for post-treatment follow-up. To observe the actual treatment effect on patient outcomes, two months was established as the minimum treatment duration requirement for patients to be included in the study. Patients with severe mental illness (schizophrenia, bipolar disorder, major depressive disorder with suicidal ideation) were excluded from the study.

Prior to enrollment in the study, all patients were thoroughly informed about the extent and nature of the data that would be collected from their relatives. Only those patients who gave written informed consent to the data collection were included in the study. Participants had the right to withdraw from the study at any time during the follow-up period based on a written or telephone statement. Data were collected through structured telephone interviews with the participants’ relatives using a self-designed questionnaire. The reason for selecting patient relatives as the primary source of information was the potentially higher response validity and retention of the study sample. Four waves of data collection took place 6 months, 1 year, 2 years, and 5 years after participant discharge from baseline treatment. In total, 366 patients out of 468 eligible at baseline (78.2%) participated in the fourth wave of data collection at a 5-year follow-up.

Measures

Individual data on the gender, age, type of addiction, completion of treatment, and treatment duration of participants were obtained from their medical records at the baseline. Data on abstinence outcomes and aftercare attendance were collected from authorized relatives of patients.

Outcome variables

Our main outcome variables were (1) relapse and (2) long-term abstinence.

Relapse/Continuous abstinence

Relapse was defined as a violation of abstinence from psychoactive substance use and addictive behavior that was the primary concern of treatment of any duration and severity during the follow-up period (the period between discharge from the baseline treatment and the fourth wave of follow-up). Continuous abstinence, considered the opposite of relapse, was defined as complete abstinence from psychoactive substance use and addictive behavior that was the primary concern of treatment without any lapses or relapses.

Long-term abstinence

Long-term abstinence was defined as complete abstinence from psychoactive substance use and addictive behavior that was the primary concern of treatment for at least one full year during the follow-up period.

Data analysis

We used binomial logistic regression to estimate the probability of relapse and long-term abstinence (outcome variables) based on socio-demographic and treatment-related variables (predictors). Crude odds ratios with their 95% confidence intervals and p-values were calculated. Variables with a p-value below an alpha level of .05 were considered statistically significant predictors.

Statistical analyses were calculated using IBM SPSS Statistics 23.

Ethics

The study has been reviewed and approved by the responsible Ethics Committee of the University Hospital Hradec Králové (no. 202202PO4).

Results

For complete descriptive results on patient abstinence outcomes after 2- and 5 years of follow-up, see Tibenská et al. (2008) and Tibenská et al. (2016), respectively.

Sample description

Table 1 shows the characteristics of the participants. Out of 366 patients, 247 (67.5%) were men; the mean age of participants was 37.2 ± 12 years. The majority (61.2%) were patients with alcohol use disorder (AUD), 18.9% were patients with other substance use disorders (SUDs), 11.5% were patients with polydrug use (the use of more than one drug or type of drug), and 8.5% were patients with BA (gambling or gaming). Treatment duration ranged from 60 to 163 days with a mean of 106.8 ± 19.3 days (~3.5 months).

Table 1. Cohort characteristics.

	Total
	N	%
Gender
Men	247	67.5
Women	119	32.5
Age
Mean (SD)	37.15	11.95
18–30 years	134	36.6
31–45years	126	34.4
≥46 years	106	29
Type of SUD/BA
AUD	224	61.2
SUD	69	18.9
Behavioral	31	8.5
Polydrug*	42	11.5
Completion of treatment
Full treatment	257	70.2
Early discontinuation	109	29.8
Treatment duration
Mean (SD)	106.78	19.32
Early aftercare attendance
Yes	182	49.73
No	184	50.27
Continuous abstinence
Abstinence	109	29.8
Relaps	257	70.2
Long-term abstinence
Yes	234	63.9
No	132	36.1
Mortality
Survived	336	91.8
Died	30	8.2

*The use of more than one drug or type of drug.

Overall, 29.8% of the participants reported continuously abstaining from psychoactive substance use or addictive behavior over the 5-year follow-up period, while 70.2% experienced one or more episodes of relapse of varying length and severity. The number of continuous abstainers has gradually declined over the years; while 53.3% of participants abstained for the first half-year after the treatment completion, it was only 29.8% after five years. The percentage of relapsing patients decreased every six months (from 7.7% 0.5 to 1 year after basic treatment to 0.3% 4.5 years to 5 years after treatment). Long-term abstinence (at least one full year of continuous abstinence) was reported by 63.9% of the participants.

A total of 30 (8.2%) participants died within 5 years of surveillance; the mean age of the deceased was 47.7 ± 9.8 years. In most cases (93.3%), the cause of death was related to the failure of physiological functions, suicide, or fatal accidents in connection with relapse.

Prevalence and factors associated with relapse and long-term abstinence

Table 2 shows the results of binomial logistic regression models for relapse and long-term abstinence.

Table 2. Binomial logistic regression models for relapse and long-term abstinence.

	Relaps						Long-term abstinence						Mortality
				95% CI						95% CI						95% CI		p
	B	SE	OR	Lower	Upper	p	B	SE	OR	Lower	Upper	p	B	SE	OR	Lower	Upper
Gender
Men
Women	0.086	0.246	1.090	0.674	1.764	.725	−0.324	0.230	0.723	0.461	1.134	.158	0.355	0.391	1.427	0.664	3.068	.363
Age	−0.005	0.010	0.995	0.976	1.014	.588	−0.011	0.009	0.989	0.972	1.007	.243	0.089	0.019	1.093	1.052	1.135	<.001
Type of SUD/BA
AUD	−0.183	0.237	0.833	0.524	1.325	.441	−0.417	0.228	0.659	0.421	1.030	.067	2.303	0.740	10.000	2.344	42.667	.002
SUD	0.135	0.298	1.144	0.638	2.050	.651	0.568	0.299	1.765	0.982	3.171	.057	−1.996	1.026	0.136	0.018	1.015	.052
Behavioral	−0.285	0.394	0.752	0.347	1.628	.469	0.921	0.468	2.512	1.003	6.291	.049
Polydrug	0.493	0.395	1.637	0.755	3.549	.212	−0.433	0.331	0.648	0.339	1.241	.191	−1.394	1.031	0.248	0.033	1.870	.176
Completion of treatment
Full treatment
Early discontinuation	0.937	0.284	2.553	1.462	4.457	.001	−0.318	0.235	0.728	0.459	1.154	.176	0.496	0.392	1.643	0.762	3.539	.205
Treatment duration	−0.013	0.006	0.987	0.975	.999	.029	0.007	0.006	1.007	0.995	1.018	.248	−0.016	0.010	0.984	0.965	1.003	.102
Early aftercare attendance
Yes
No	1.071	0.241	2.917	1.819	4.678	<.001	−1.321	0.233	0.267	0.169	.421	<.001	0.907	0.413	2.476	1.102	5.565	.028

Socio-demographic factors

Overall, 69.6% of men and 71.4% of women experienced at least one relapse during the 5-year follow-up period. The difference was not statistically significant (OR = 1.090, 95% CI [0.674, 1.764], p = ns). Long-term abstinence was more prevalent in men than women (66.4% vs. 58.8%) but the difference was not statistically significant (OR = 0.723, 95% CI [0.461, 1.134], p = ns).

In terms of the distribution of age categories, the highest percentage of participants who experienced relapse was in the age category up to 30 years (76.1%). Relapse was also reported by 64.3% of patients aged between 31–45 years and 69.8% of patients 46 years old and over. Relapse was not significantly associated with age (in years) of the participants (OR = 0.995, 95% CI [0.976, 1.014], p = ns). Long-term abstinence was reported by 67.2% of patients aged 18–30 years, 62.7% of patients aged 31–45 years, and 61.3% of patients aged 46 years and over. Long-term abstinence was not significantly associated with age (in years) of the participants (OR = 0.989, 95% CI [0.972, 1.007], p = ns).

Type of addiction

Relapse experienced 68.8% of participants with AUD, 72.5% of participants with other SUDs, 78.6% of participants with polydrug use and 64.5% of participants with BA. Relapse was not significantly associated with any of the individual types of addiction, specifically AUD (OR = 0.833, 95% CI [0.524, 1.325], p = ns), other SUDs (OR = 1.144, 95% CI [0.638, 2.050], p = ns), polydrug use (OR = 1.637, 95% CI [0.755, 3.549], p = ns) or BA (OR = 0.752, 95% CI [0.347, 1.628], p = ns). The prevalence of long-term abstinence was 60.3% for participants with AUD, 73.9% for participants with other SUDs, 54.8% for participants with polydrug use and 80.7% for participants with BA. There was a significant association between long-term abstinence and BA (OR = 2.512, 95% CI [1.003, 6.291], p < .05); participants with BA were more likely to abstain from addictive behavior for at least one full year. The difference was not statistically significant for AUD (OR = 0.659, 95% CI [0.421, 1.030], p = ns), SUDs (OR = 1.765, 95% CI [0.982, 3.171], p = ns) and polydrug use (OR = 0.648, 95% CI [0.339, 1.241], p = ns).

Treatment completion

Overall, 65% of participants who received the full treatment and 82.6% of participants who discontinued the treatment experienced relapse. The difference was statistically significant (OR = 2.553, 95% CI [1.462, 4.457], p < .001); participants who drop-out from baseline treatment had higher odds of relapse. Long-term abstinence was more prevalent in participants who received full treatment than those who discontinued the treatment (66.2% vs. 58.7%) but the difference was not statistically significant (OR = 0.728, 95% CI [0.459, 1.154], p = ns).

Treatment duration

Participants spent 3.5 months on average in baseline treatment. The likelihood of relapse decreased with increasing treatment duration (OR = 0.987, 95% CI [0.975, 0.999], p < .05). Treatment duration was not significantly associated with long-term abstinence (OR = 1.007, 95% CI [0.995, 1.018], p = ns).

Early aftercare attendance

Relapse experienced 59.3% of participants who attended aftercare and 81% of those who did not attend any aftercare within the first year after the baseline treatment. There was a significant association between relapse and early aftercare attendance (OR = 2.917, 95% CI [1.819, 4.678], p < .001); participants who did not attend aftercare were more likely to experience a relapse during the 5-year follow-up. Long-term abstinence was more prevalent in participants who attended aftercare than those who did not (78.6% vs. 49.5%) and the difference was statistically significant (OR = 0.267, 95% CI [0.169, 0.421], p < .001). Participants who did not attend aftercare had lower odds of long-term abstinence.

Interaction effect between significant predictors of relapse

We calculated the interaction effect of aftercare attendance and completion of treatment on relapse to estimate whether a combination of these two factors has a significant potentiating effect on relapse (Table 3). Logistic regression showed that the interaction is not statistically significant; the effect of aftercare attendance is probably not reinforced by the effect of completion of treatment.

Table 3. Logistic regression models estimating the interaction effect of aftercare attendance and completion of treatment on relapse.

	Relaps
				95% CI
	B	SE	OR	Lower	Upper	p
Aftercare attendance
Yes
No	1.208	0.282	3.348	1.925	5.823	<.001
Completion of treatment
Full treatment
Early discontinuation	1.242	0.411	3.463	1.548	7.746	.002
Aftercare attendance * Completion of treatment	−0.862	0.581	0.422	0.135	1.319	.138

Discussion

Over a 5-year follow-up period, 70.2% of patients with SUDs/BA experienced one or more episodes of relapse, with 46.7% relapsing within the first 6 months after completing the baseline treatment. On the other hand, nearly two-thirds (63.9%) managed to continuously abstain for at least one full year. Increased odds of relapse were observed in patients who discontinued treatment, spent less time in treatment and did not receive any aftercare within the first year after baseline treatment. Moreover, we found a positive effect of early aftercare attendance on long-term abstinence. The comparison with other existing addiction treatment models and approaches is difficult due to variations in relapse and long-term abstinence definitions and should be made with caution.

Previous studies emphasized that the first months after the treatment are the most vulnerable period for patients to relapse (Bottlender & Soyka, 2005; Haver et al., 2001; Hunt et al., 1971). The high prevalence of relapse following the inpatient treatment completion may be related to the lack of skills and support when exposed to high-risk situations for relapse. In general, low-effective relapse prevention delivered in inpatient treatment or the absence of aftercare may be the ones to blame.

With regards to aftercare, previous studies found that participation in self-supporting fellowships, counseling and other types of aftercare significantly decreases patient substance use and helps them to maintain long-term abstinence after leaving inpatient treatment (Fiorentine & Hillhouse, 2000; Gossop et al., 2003; Hambley et al., 2010). Our study showed that early aftercare has a protective effect on relapse. In this respect, future treatment professionals should be educated about the importance of aftercare services (Miovsky et al., 2015; Pavlovska et al., 2017).

One of the other factors consistently linked with positive treatment outcomes is treatment completion (Brorson et al., 2013; Stark, 1992). Our finding that discontinuation of treatment increases the likelihood of relapse is in line with previous studies demonstrating that treatment drop-out has a negative impact on abstinence (Bottlender & Soyka, 2005; Csémy et al., 2012; Decker et al., 2017; Haver et al., 2001; Stark, 1992). Self-efficacy and supportive social networks are some of the most important protective factors of relapse (DiClemente, 1986; Sliedrecht et al., 2019; Witkiewitz & Marlatt, 2004).

In addition, we found that the number of days spent in treatment also plays a protective role against relapse. This could indicate that long-term addiction treatment programs lasting several weeks to months may lead to better abstinence outcomes than programs of shorter duration.

In accordance with previous findings (Sliedrecht et al., 2019), neither the gender nor the age of the patients at baseline predicted relapse and long-term abstinence. This suggests that these factors are equally distributed between men and women and do not change with age. With regard to the type of addiction, patients with BA were more likely to abstain for at least one full year. Otherwise, we found no relationship between the type of addiction and relapse or long-term abstinence.

Strengths and limitations

Our results are of clinical importance for mid-term inpatient addiction programs by expanding the evidence on treatment-related factors and their association with long-term abstinence outcomes in addiction-treated patients.

A response rate of 78.2% at a 5-year follow-up could be considered high. We interviewed relatives instead of patients themselves to collect data on patient outcomes to minimize self-report bias. This approach might be advantageous in that we were able to collect data on abstinence/relapse outcomes even from relapsed patients who might otherwise be reluctant to do so or would be out of reach for interviewing. On the other hand, it could have potentially led to inaccurate responses from patient relatives.

Our study has some limitations. Data are not representative of the entire population of patients with addiction entering the mid-term inpatient treatment, because the participants came from one specific facility instead of being randomly selected from multiple facilities. Moreover, our study reflected only one type of treatment setting (the Apolinar model) and findings should not be generalized to different existing treatment settings and modalities (e.g., outpatient treatment).

In the study, we did not consider the psychiatric comorbidities of the patients when analyzing the data. Since psychiatric comorbidity is one of the most important factors for relapse (Sliedrecht et al., 2019), this could potentially influence the results. However, the mental health of all patients was examined by a psychologist and psychiatrist before entering the study and patients with severe mental illness were excluded from participation.

It should be noted that we used very strict criteria to define relapse; in this study, relapse was considered any violation of abstinence, including the one-time slips. It is likely that the prevalence of relapse would be lower if we differentiate between laps and relapse. Moreover, although considered relapsed in this study, a large proportion of patients could have significantly improved their behavior regarding SUDs/BA while not reaching our criteria for 5-year continuous abstinence. Finally, it is important to emphasize that because treatment outcomes were the primary focus of this study, it is not appropriate to make any conclusions about patients’ quality of life and health outcomes based on these findings.

Conclusions

In conclusion, this study found that post-treatment relapse, especially within the vulnerable period of 6 months after the baseline treatment, is considerably high in patients with SUDs/BA of mid-term inpatient care based on the Apolinar model. Treatment-related factors, specifically early discontinuation from treatment, shorter treatment duration, and absence of post-treatment early aftercare may contribute to less favorable abstinence outcomes in long term. Our findings support the importance of treatment compliance and aftercare to prevent relapse in patients treated for addiction. Finally, future research might consider investigating relapse prevention interventions in aftercare.

Acknowledgments

We would like to thank Prof. Jan Libiger, Jiří Čížek, M.D., Cyril Martínek, M.A. for designing the study and data collection.

Disclosure statement

Roman Gabrhelík is the shareholder of Adiquit Ltd., which is currently developing apps for addictions recovery. Nevertheless, no funding was related to this study and the activities had no role in the study design or the data collection, analysis, and interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. The remaining authors have no conflicts of interest to declare.

Data availability statement

The data that support the findings of this study are available from the corresponding author, [GR], upon reasonable request.

Additional information

Funding

This study was supported by the Ministry of Health of the Czech Republic [NU20-09-00066]; Charles University institutional support program Cooperacio, research area HEAS; UNCE VITRI: Charles University Research Center, program number 9; Charles University, project GA UK [452122].