Abstract
Background/Objectives: The consumption of opioids is a public health problem that significantly affects quality of life. In Spain, 7585 people are enrolled in the Methadone Maintenance Programme (MMP), which is an effective intervention with a low adherence rate. In this study, factors associated with the quality of life of MMP users, especially perceived social support and treatment adherence, were analysed. We hypothesised that low levels of adherence and social support would be associated with poorer quality of life. Methods: This was a cross-sectional observational study with an analytical approach. Quality of life (WHOQoL-BREF), perceived social support (DUKE-UNC-11), and treatment adherence (MMAS-8) among MMP users were studied, and data on sociodemographic and clinical characteristics were collected through ad hoc questionnaires and a review of electronic medical records. Linear and logistic regression models were used. Results: A total of 70 individuals were included in this study. The mean age was 56.9 years, and 83% of the participants were male. The perceived quality of life was low in the four domains evaluated (range of 47.4–48.2). A total of 38.57% of the participants had low perceived social support. Treatment adherence was low or moderate in 77.1% of the participants. Greater perceived social support was associated with better quality of life in all domains (p < 0.05). Quality of social life was negatively associated with the use of nonbenzodiazepine neuroleptics and HIV status. Treatment adherence was lower in insulin therapy users. Conclusions: Social support is a key determinant of the quality of life of MMP users. Health policies should promote social support networks as a strategy to improve the well-being of this population.
Keywords: quality of life, methadone, substance-related disorders, addictive behaviour, social support, treatment adherence and compliance, community health services, public health, social determinants of health, vulnerable populations
1. Introduction
The use of opioids constitutes a large public health problem, with clinical, social, and economic consequences. There were an estimated 60 million heroin and opioid users worldwide in 2022, 30 million of whom used heroin. In 2020, the prevalence of high-risk users was estimated to be 860,000 in Europe alone [1,2]. Opioid use disorder is associated with high premature morbidity and mortality [3]. The World Health Organization estimates approximately 125,000 deaths from opioid use per year [4].
In Spain, the prevalence of heroin use has remained at 0.1% since 1995 [5]. Heroin use tends to coexist with mental disorders, infectious diseases, and polydrug use, which increases the clinical, psychological, and social vulnerability of these individuals [6,7,8]. In addition, factors such as social exclusion, unemployment, and crime reflect the multidimensional impact of the problem. The approach to this problem entails a high cost, not only for the public health system but also for social, penitentiary, and administrative services [9,10]. Reintegrating this population into society and the workforce is usually a process that requires a long period of readjustment due to polyconsumption problems, less social support, less economic means, and criminal records [11,12].
The Methadone Maintenance Programme (MMP) is the main drug replacement strategy recommended for the treatment of opioid use disorders. The effectiveness of this programme has been widely demonstrated, not only in reducing consumption but also in reducing morbidity and mortality, the transmission of infectious diseases, and crime rates. However, the treatment involves more than just prescribing methadone and requires a comprehensive approach that considers the associated risks, such as clinical complications, relapses, the psychosocial sphere, and quality of life [13,14,15].
In this sense, psychosocial support is an essential component of the MMP. Therapeutic adherence is a challenge, especially in the initial phases, owing to factors such as stigma, the obligation to obtain medication daily, and interference with daily life [16]. Anxiety is one of the most frequently occurring symptoms during treatment, involving frequent psychiatric comorbidities and an elevated risk of suicide. Factors such as a low educational level, the use of benzodiazepines, or unemployment increase the risk of anxiety [17,18].
Quality of life has become a key indicator of health, and its measurement in MMP users makes it possible to assess the impact of interventions beyond the control of consumption [19]. A higher degree of life satisfaction is associated with greater adherence to treatment. However, individuals with opioid use usually have a low level of social support caused by the loss of family ties, friendships, or financial aid [20,21,22]. This lack of support increases the risk of treatment abandonment and increases the vulnerability of people in the MMP at the personal, social, and economic levels [21]. Opioid users are among the most marginalised groups that use illegal substances [2].
No evidence linking the three outcome variables of this study within the MMP population has been found; however, associations among them have been documented in other population groups [23,24]. Theoretical frameworks such as the stress-buffering hypothesis suggest that social support can mitigate the negative effects of chronic stress on health outcomes. Additionally, behavioural models emphasise the influence of social and contextual factors on health behaviours like treatment adherence. Empirically, associations have been found between social support and treatment adherence [25,26], as well as between social support and quality of life [27,28]. This provides a conceptual and empirical foundation to investigate such an association in MMP users.
Despite the impact of opioid consumption and its high health care and social burdens, in Spain, there is little scientific evidence that addresses the quality of life in this population and the relationship of quality of life with social support and therapeutic adherence. Although international studies have been conducted, their applicability to the Spanish context is limited due to sociocultural differences.
In 2022, 7585 people were admitted to the MMP in Spain. Of these individuals, 2089 (27.3%) were from the province of Cádiz, which represents only 2.65% of the total Spanish population [29,30,31,32]. This marked disparity highlights the need for targeted interventions and region-specific strategies in Cadiz.
Therefore, the objective of this study was to explore the relationships among quality of life, perceived social support, and treatment adherence in a sample of MMP users in Spain. We hypothesised that this population would have low adherence and perceived social support, which would be significantly associated with lower quality of life across all domains. The results are intended to provide evidence to guide future community interventions focused on the overall well-being of this population.
2. Materials and Methods
2.1. Design
This cross-sectional observational study was carried out with an analytical approach in the Campo de Gibraltar region (Spain) at the health centres responsible for dispensing the substitution treatment (methadone).
The inclusion criteria were individuals older than 18 years, individuals who had participated in the MMP for at least 6 months at the beginning of this study, individuals who attended the medication collection meeting in person and on time, and individuals who signed the informed consent form. People with an acute episode of mental illness, cognitive impairment, or language barriers that prevented them from providing informed consent or completing the questionnaires were excluded.
No formal sample size calculation or probability sampling was performed since participation was offered to all users who met the eligibility criteria. Ultimately, 70 people were included in this study. Figure 1 represents the flow chart of this selection process.
Figure 1.
Flow chart.
The STROBE checklist is available as Appendix A.
2.2. Variables and Information Collection
Data were collected through self-administered questionnaires in health centres between July 2024 and March 2025. Three scales that have been validated in Spain [33,34,35] were used to measure the main outcome variables: (I) The World Health Organization Quality of Life Instrument—Short Version (WHOQoL-BREF) is a 26-item instrument that measures quality of life across four domains: physical health, psychological well-being, social relationships, and the environment. Each domain is scored on a scale from 0 to 100, with higher scores indicating better perceived quality of life [36]. (II) The Morisky Medication Adherence Scale (MMAS-8) is an 8-item scale that measures self-reported medication adherence. Total scores range from 0 to 8, with higher scores indicating better adherence, which is categorised as follows: high adherence (score = 8), medium adherence (score of 6–8), and low adherence (score < 6) [37]. (III) The Duke–UNC Functional Social Support Questionnaire (DUKE-UNC-11) is an 11-item scale that evaluates the perception of functional social support. Total scores range from 11 to 55, and lower scores indicate lower perceived social support. In Spain, a score below 32 is considered indicative of low social support [38].
In addition, an ad hoc questionnaire (Appendix B) was used to collect data on sociodemographic variables (age, sex, educational level, marital status, number of children, employment status, nationality, coexistence status, and prison history) and a variable related to the treatment (duration of participation in the MMP). The coexistence variable was recategorised as “alone”, “family”, and “sharing a home”.
Information on drug treatment (dispensing frequency, methadone dose, and use of benzodiazepines, antihypertensives, neuroleptic anxiolytics, inhalers, gastric drugs, oral antidiabetics, insulin therapy, nonopioid analgesia, opioid analgesia, and/or antiplatelet drugs) and comorbidities (hepatitis C, hepatitis B, human immunodeficiency virus (HIV), and cardiac, mental, respiratory, oncological, and/or neurological pathologies) was extracted from electronic medical records.
2.3. Statistical Analysis
A descriptive analysis of the sociodemographic and clinical characteristics of the population was carried out using absolute and relative frequencies for qualitative variables and measures of central tendency and dispersion (mean and standard deviation) for quantitative variables. Chi-square tests were used to compare proportions to study the associations between variables, and Student’s t-tests or ANOVA were used to compare means according to the number of groups.
Linear regression models adjusted for age and sex were developed to study the possible associations of sociodemographic and clinical variables with quality of life and therapeutic adherence. A logistic regression model adjusted for age and sex was developed to analyse the possible associations of sociodemographic and clinical variables with perceived social support (dichotomised into “low” and “normal” according to the validated cut-off point). The magnitude of the association is presented as the beta coefficient and odds ratio (OR), with their respective 95% confidence intervals. The selection of variables for each model was based on those that showed statistically significant associations in the bivariate analyses and those considered clinically relevant on the basis of previous evidence or expert judgement.
Multicollinearity between the independent variables included in the models was not examined, as each variable provides distinct information, allowing us to isolate the individual contribution of each factor.
No imputation was necessary, as the primary variables of interest were complete. Complete-case analysis was used.
Stata 15 statistical software was used in this study.
3. Results
A total of 70 people, with a mean age of 56.9 years (7.61), participated in this study. A total of 83% of the participants were male. The sociodemographic characteristics of the sample are presented in Table 1. The unemployment rate was high (90%), and 60% of the participants had prison records. The most common educational level was primary education (32.86%), and 41.43% of the participants were single.
Table 1.
Sociodemographic characteristics.
| Men (n = 58; 83%) |
Women (n = 12; 17%) |
Total (n = 70) |
|
|---|---|---|---|
| Age x̄ (SD) | 57.34 (7.79) | 55 (6.59) | 56.94 (7.61) |
| Educational level-n (%) | |||
| Did not finish school | 14 (24.14%) | 2 (16.67%) | 16 (22.86%) |
| Primary education | 17 (29.31%) | 6 (50%) | 23 (32.86%) |
| Secondary education | 17 (29.31%) | 3 (25%) | 20 (28.57%) |
| Baccalaureate | 5 (8.62%) | 1 (8.33%) | 6 (8.57%) |
| University | 5 (8.62%) | 0 (0%) | 5 (7.14%) |
| Marital status-n (%) | |||
| Single | 27 (46.55%) | 2 (16.67%) | 29 (41.43%) |
| Married | 4 (6.9%) | 1 (8.33%) | 5 (7.14%) |
| Divorced/Separated | 12 (20.69%) | 2 (16.67%) | 14 (20%) |
| Widowed | 4 (6.9%) | 1 (8.33%) | 5 (7.14%) |
| Has a partner | 11 (18.97%) | 6 (50%) | 17 (24.29%) |
| Occupation-n (%) | |||
| Employed | 5 (8.62%) | 2 (16.67%) | 7 (10%) |
| Unemployed | 53 (91.38%) | 10 (83.33%) | 63 (90%) |
| Number of children-n (%) | |||
| 0 | 19 (32.76%) | 2 (16.67%) | 21 (30%) |
| 1 | 14 (24.14%) | 3 (25%) | 17 (24.29%) |
| 2 | 15 (25.86%) | 3 (25%) | 18 (25.71%) |
| 3 | 6 (10.34%) | 0 (0%) | 6 (8.57%) |
| 4 | 1 (1.72%) | 2 (16.67%) | 3 (4.29%) |
| 5 or more | 3 (5.17%) | 2 (16.67%) | 5 (7.14%) |
| Prison history-n (%) | |||
| Yes | 38 (65.52%) | 4 (33.33%) | 42 (60%) |
| No | 20 (34.48%) | 8 (66.67%) | 28 (40%) |
| Nationality-n (%) | |||
| Spanish | 57 (98.28%) | 12 (100%) | 69 (98.57%) |
| German | 1 (1.72%) | 0 (0%) | 1 (1.43%) |
| Coexistence-n (%) | |||
| Alone | 19 (32.76%) | 2 (16.67%) | 21 (30%) |
| With a partner | 8 (13.79%) | 6 (50%) | 14 (20%) |
| With a partner and children | 1 (1.72%) | 0 (0%) | 1 (1.43%) |
| With children | 1 (1.72%) | 0 (0%) | 1 (1.43%) |
| Shares a house | 29 (50%) | 3 (25%) | 32 (45.71%) |
| Street situation | 0 (0%) | 1 (8.33%) | 1 (1.43%) |
In terms of the duration of treatment, 36.23% of the participants had a duration of participation in the MMP between 20 and 30 years. The most prevalent comorbidities were hepatitis C (44.93%), cardiovascular disease (24.64%), and HIV (17.39%). The most common pharmacological treatment used was benzodiazepines (68.12%), followed by neuroleptic anxiolytics (34.78%). Table 2 summarises the clinical characteristics of the participants.
Table 2.
Clinical characteristics.
| Men (n = 57; 82.61%) |
Women (n = 12; 17.39%) |
Total * (n = 69) |
|
|---|---|---|---|
| Duration of participation in the MMP-n (%) | |||
| <1 year | 3 (5.17%) | 2 (16.67%) | 5 (7.25%) |
| 1–5 years | 5 (8.62%) | 1 (8.33%) | 6 (8.70%) |
| 5–10 years | 6 (10.34%) | 1 (8.33%) | 7 (10.14%) |
| 10–20 years | 11 (18.97%) | 2 (16.67%) | 13 (18.84%) |
| 20–30 years | 22 (37.93%) | 3 (25%) | 25 (36.23%) |
| >30 years | 11 (18.97%) | 3 (25%) | 14 (20.29%) |
| Methadone treatment dose in mg/day—median (IQR) | 50 (30–80) | 40 (17.5–70) | 45 (30–80) |
| Delivery interval between doses in days—median (IQR) | 7 (7–14) | 7 (1–7) | 7 (7–14) |
| 1 day, n (%) | 7 (12.28%) | 4 (33.33%) | 11 (15.94%) |
| 7 days, n (%) | 28 (49.12%) | 6 (50%) | 34 (49.28%) |
| 14 days, n (%) | 19 (33.33%) | 2 (16.67%) | 21 (30.43%) |
| 28 days, n (%) | 3 (5.26%) | 0 (0%) | 3 (4.35%) |
| Comorbidities-n (%) | |||
| Hepatitis C | 27 (47.37%) | 4 (33.33%) | 31 (44.93%) |
| Hepatitis B | 1 (1.75%) | 0 (0%) | 1 (1.45%) |
| HIV | 11 (19.30%) | 1 (8.33%) | 12 (17.39%) |
| Cardiovascular disease | 16 (28.07%) | 1 (8.33%) | 17 (24.64%) |
| Mental pathology | 11 (19.30%) | 3 (25%) | 14 (20.29%) |
| Respiratory pathology | 9 (15.79%) | 2 (16.67%) | 11 (15.94%) |
| Musculoskeletal pathology | 10 (17.54%) | 1 (8.33%) | 11 (15.94%) |
| Oncological pathology | 3 (5.26%) | 0 (0%) | 3 (4.38%) |
| Neurological pathology | 4 (7.02%) | 0 (0%) | 4 (5.80%) |
| Pharmacological treatments-n (%) | |||
| Benzodiazepines | 41 (71.93%) | 6 (50%) | 47 (68.12%) |
| Antihypertensives | 12 (21.05%) | 1 (8.33%) | 13 (18.84%) |
| Neuroleptic anxiolytics | 20 (35.09%) | 4 (33.33%) | 24 (34.78%) |
| Inhalers | 14 (24.56%) | 2 (16.67%) | 16 (23.19%) |
| Gastric drugs | 15 (26.32%) | 4 (33.33%) | 19 (27.54%) |
| Oral antidiabetics | 6 (10.53%) | 3 (25%) | 9 (13.04%) |
| Insulin therapy | 3 (5.26%) | 2 (16.67%) | 5 (7.25%) |
| Non-opioid analgesia | 13 (22.81%) | 4 (33.33%) | 17 (24.64%) |
| Opioid analgesia | 7 (12.28%) | 0 (0%) | 7 (10.14%) |
| Platelet antiaggregant | 7 (12.28%) | 0 (0%) | 7 (10.14%) |
* One participant did not have an electronic medical record.
The general items of the WhoQoL-BREF indicated a global perception of quality of life and moderately low satisfaction with the state of health (Figure 2 and Figure 3). In the specific domains, the mean values ranged from 47 to 48 points (Figure 4). Nevertheless, the general perception of quality of life was rated at least as “neither poor nor good” by 67.1% of the participants, which contrasts with the results obtained in the specific domains of the scale. In terms of the state of health, 41.4% of the participants reported that they were “dissatisfied” or “very dissatisfied”, whereas only 24.2% reported that they were “satisfied” or “very satisfied”. Most of the participants perceived a moderate level of social support, although 38.57% perceived a low level of social support (Figure 5). Regarding therapeutic adherence (MMAS-8 score), 15.71% of the participants had low treatment adherence, and 61.43% had moderate treatment adherence (Figure 6).
Figure 2.
Item 1 of the WhoQoL-BREF scale.
Figure 3.
Item 2 of the WhoQoL-BREF scale.
Figure 4.
Quality of life of the participants (WhoQoL-BREF).
Figure 5.
Perceived social support of the participants (Duke-UNC-11).
Figure 6.
Treatment adherence of the participants (MMAS-8).
Linear and logistic regression models adjusted for age and sex were developed to analyse the factors associated with the main variables (quality of life, perceived social support, and treatment adherence). The results are presented in Table 3, Table 4, Table 5, Table 6, Table 7 and Table 8.
Table 3.
Physical quality of life (linear regression model).
| CRL * | 95% CI ** | p | |
|---|---|---|---|
| Perceived social support | 8.12 | 0.51; 15.72 | 0.037 |
| Platelet antiaggregant | −11.32 | −23.36; 0.71 | 0.065 |
| Inhalers (respiratory therapy) | −9.37 | −17.97; −0.77 | 0.033 |
| R2 Adjusted = 0.1435 | |||
* Coefficient of linear regression. ** 95% CI: 95% confidence interval. Numbers in Bold means significant values.
Table 4.
Psychological quality of life (linear regression model).
| CRL * | 95% CI ** | p | |
|---|---|---|---|
| Perceived social support | 13.08 | 4.47; 21.69 | 0.003 |
| Mental pathology | 7.68 | −2.53; 17.89 | 0.138 |
| R2 Adjusted = 0.1123 | |||
* Coefficient of linear regression. ** 95% CI: 95% confidence interval. Numbers in Bold means significant values.
Table 5.
Social quality of life (linear regression model).
| CRL * | 95% CI ** | p | |
|---|---|---|---|
| Perceived social support | 17.78 | 9.32; 26.23 | 0.000 |
| Anxiolytics (nonbenzodiazepines)/neuroleptics | −13.64 | −22.22; −5.05 | 0.002 |
| HIV | −13.61 | −24.26; −2.96 | 0.013 |
| R2 Adjusted = 0.2731 | |||
* Coefficient of linear regression. ** 95% CI: 95% confidence interval. Numbers in Bold means significant values.
Table 6.
Environmental quality of life (linear regression model).
| CRL * | 95% CI ** | p | |
|---|---|---|---|
| Perceived social support | 12.97 | 6.22; 19.72 | 0.000 |
| R2 Adjusted = 0.1479 | |||
* Coefficient of linear regression. ** 95% CI: 95% confidence interval. Numbers in Bold means significant values.
Table 7.
Treatment adherence (linear regression model).
| CRL * | 95% CI ** | p | |
|---|---|---|---|
| Insulin therapy | −0.65 | −1.20; −0.10 | 0.020 |
| R2 Adjusted = 0.086 | |||
* Coefficient of linear regression. ** 95% CI: 95% confidence interval.
Table 8.
Perceived social support (logistic regression model).
| OR * | 95% CI ** | p | |
|---|---|---|---|
| Coexistence (family) | 0.73 | 0.18; 2.99 | 0.661 |
| Coexistence (sharing a home) | 3.84 | 1.07; 13.83 | 0.040 |
| Employment | 6.99 | 0.65; 75.04 | 0.109 |
| Pseudo R2 = 13.56 | |||
* Odds ratio. ** 95% CI: 95% confidence interval.
Higher perceived social support was significantly associated with higher scores in the physical domain of quality of life (8.12; 95% CI 0.51; 15.72). In addition, the use of inhalers and antiplatelet agents was negatively associated with the scores in this domain (Table 3).
Perceived social support was significantly associated with a higher score in the psychological domain of quality of life (13.08; 95% CI 4.47; 21.69). The presence of a mental pathology showed a nonsignificant positive association with perceived social support (Table 4).
In the social domain, perceived support was positively associated with quality of life (17.78; 95% CI 9.32; 26.23). In contrast, the use of nonbenzodiazepine anxiolytics and neuroleptics was associated with a lower quality of social life, as was HIV status (Table 5).
The level of perceived social support was significantly associated with a higher score in the environmental domain of quality of life (12.97; 95% CI 6.22; 19.72) (Table 6).
A negative association was observed between insulin therapy use and therapeutic adherence (−0.65; 95% CI −1.20; −0.10), indicating lower adherence in people with diabetes treated with insulin (Table 7).
The type of coexistence was significantly associated with the level of perceived social support. Sharing a home without family ties was associated with a greater probability of having perceived social support (OR = 3.84; CI95% 1.07;13.83). Living with relatives and employment showed no association (Table 8).
4. Discussion
A lower quality of life among the participants was observed in the present study, with lower values in all its domains in the study population than in the general Spanish population. The latter presents physical, psychological, social, and environmental quality of life scores of 90.38, 81.94, 81.06, and 63.75, respectively [39]. Prospective cohort studies conducted in China and Norway have also shown that individuals enrolled in the MMP report quality of life scores below the national average [40,41]. These results are consistent with those of other studies conducted in different sociocultural contexts [15,19,22,42]. The perceived social support score was 26% lower than that in the general population, with an average of 33.86 points versus 48.21 points [43]. According to the results of other studies [44], this difference suggests a possible lack of support networks and social resources among MMP users, which could affect their therapeutic process and their overall well-being. Regarding therapeutic adherence, only 22.9% of the participants presented adequate adherence, whereas 49.9% of the general Spanish population had adequate adherence [45]. This figure is notably lower than that reported in other studies, such as transversal studies carried out in Vietnam, where an optimal adherence rate of 34.4% was observed [46].
In terms of sociodemographic elements, the unemployment rate was 90% for the MMP users in this study, which was much higher than the rate of 59.3% reported for MMP users in Andalusia [47]. These unemployment rates are also substantially higher than those reported in other studies, such as a prospective cohort study conducted in China, which reported an unemployment rate of 70%, a cross-sectional study carried out in Myanmar, which reported a rate of 8.7%, and a study conducted in Vietnam, which reported a rate of 7% [22,40,46]. This difference could be explained in part by the local context of the study, which was carried out in the towns of La Línea de la Concepción and Algeciras, with unemployment rates of 32.39% and 25.68%, respectively, compared with the national average of 10.61% and the Andalusian average of 15.76. Both municipalities are among the Spanish localities with the highest unemployment rates among those with more than 45,000 inhabitants [48,49]. Cross-sectional studies conducted in other sociocultural contexts have established an association between unemployment and lower quality of life [50,51]. The profile of an MMP user is a male of approximately 44 years of age who has previously received some type of substitution treatment, with a primary education level, in a situation of unemployment, and who goes to treatment of his own free will [29,47]. In terms of coexistence, no differences were observed with respect to the MMP population of Andalusia (21.4% of participants lived alone and 61.8% coexisted) [47]. Sixty per cent of the sample had a prison record, a figure that contrasts sharply with the 2.98% estimated for individuals in the general Spanish population who served prison time between 2009 and 2019 [52,53]. Substance use has been identified as a risk factor for criminal conduct [12,52].
Among the comorbidities, hepatitis C and HIV stood out. Among the participants, 44.29% tested positive for hepatitis C, whereas 1.7% of the general population in Spain tested positive for hepatitis C [54]. The prevalence of HIV was 17.14%, whereas it was 0.32% at the national level [55]. In another cross-sectional study conducted in Myanmar, even higher rates were reported: 47.97% for hepatitis C and 37% for HIV [22]. Injecting drug use, poor health habits, and poor health conditions could explain this exponential increase [54].
All these factors are related to quality of life, so they must be accounted for when interpreting the results [53,56,57].
In a descriptive analytical study carried out in a Spanish population (n = 523) with a mean age of 46.67 years (compared to 56.94 years in our study) and 80.5% of male participants (similar to 83% in this study), the scores were greater in terms of quality of life [58]. The scores in the aforementioned studies were 57.38 for physical quality of life, 51.63 for psychological quality of life, 47.38 for social quality of life, and 54.19 for environmental quality of life [59]. These differences may be due to the sample size of both studies, as the study was carried out mainly in Madrid, whose socioeconomic situation is different, or the age difference between the two samples [60]. In other countries with MMP populations, such cross-sectional studies have reported greater quality of life scores across all domains than those of the population in our study [22,61].
Other studies have reported a relationship among the duration of participation in the MMP, dosage, and quality of life; however, this relationship could not be examined in our study because of the sample size [15,62,63].
Perceived social support was revealed as a key factor throughout the study. As reflected by the linear regression models, perceived social support is positively associated with all domains of quality of life. In the regression model for physical quality of life, perceived social support, antiplatelet treatment use, and inhaler use were associated with each other. It was decided to use different types of pharmacological treatment as independent variables instead of the base pathologies, since they did not allow us to discriminate the clinical severity, which limited their explanatory use. These medications are commonly used by individuals with respiratory or cardiac conditions, which are known to be associated with poorer quality of life [64,65]. In the psychological domain, perceived social support and the presence of mental illness are associated with quality of life. Although the positive association between mental disorders and quality of life may seem surprising, it could be explained by the sample size, active treatment for these conditions, and the adjustment of health-related quality of life expectations [66]. The quality of social life, perceived social support, the use of nonbenzodiazepine/neuroleptic anxiolytics, and the diagnosis of HIV were related to this domain. The negative association of drugs could be due to the effect of the underlying pathology on social relationships. On the other hand, the social stigma associated with HIV can contribute to a greater perception of social isolation [67]. In the environmental domain, perceived social support was the only variable with a significant association. The logistic regression model for perceived social support revealed a greater probability of adequate perceived social support among those who shared a home with nonfamily members and among those who were employed. This last finding was included because of its clinical relevance. These results coincide with those of previous studies that indicate the positive effects of employment and coexistence on the subjective perception of social support [68,69].
Although perceived social support and quality of social life seem to overlap, they actually belong to different dimensions. Perceived social support refers to “the availability and subjective adequacy of social connections” [70], whereas the quality of social life refers to “an individual’s perception of their life situation, since, in the context of their culture and value systems and in relation to their objectives, expectations, standards and concerns regarding their social relationships, their social support and their sexual sphere” [71]. These results support the development of integrated community interventions combining pharmacological treatment with peer support, job training, and stigma-reduction strategies, particularly for those with comorbidities such as HIV or mental health disorders.
Strengths and Limitations of the Study
The main limitation of this study was the lack of attendance at the referral centre on the day of methadone dispensing (29.07% of the potential sample). To overcome this limitation, multiple follow-up contacts were made with each centre via the reference nurses. In addition, data collection coincided with medication delivery, preventing additional travel for the participants. Another limitation was the proportion of users (14.28%) whose methadone was obtained by a family member.
One of the limitations of this study is the obligatory nature of adherence to treatment for the MMP users. This may have conditioned their responses, leading to desirability bias. To reduce this risk, the questionnaires were not carried out while the reference nurses were present at the dispensation; rather, the MMP users were taken to a separate room.
In addition, there are limitations inherent to the use of secondary sources, such as electronic medical records. Data on the main outcome variables were collected to minimise the impact.
Finally, the absence of a formal sample size calculation and the relatively modest sample of 70 participants included may limit the generalisability of our findings. Possible selection and information biases are acknowledged as methodological limitations. We recommend that future studies consider including larger, multicentre samples to allow for broader comparisons and subgroup analyses.
The main strength of this study is that the entire accessible population of the participating areas was invited to participate, accounting for 3.4% of the total number of people enrolled in the MMP in Spain [72] and 12% of the total number of MMP users in Andalusia [47].
5. Conclusions
The findings of this research can contribute to decision-making regarding public health policies, allowing the optimisation of intervention strategies aimed at the population enrolled in the MMP and focusing attention on the most vulnerable aspects identified. In particular, perceived social support has been shown to significantly affect quality of life across all domains. As such, intervention strategies should incorporate social and community-based components, including active employment support, vocational training, and initiatives to foster social networks and reduce stigma. Additionally, multidisciplinary approaches that include psychological support and address adherence to treatment may improve outcomes in this population. These findings provide valuable insight for tailoring public health responses to better meet the complex needs of people enrolled in the MMP.
Acknowledgments
We thank all the nurses, security personnel, coordinators, managers, and centre directors for facilitating the field work and accompanying us during recruitment. During the preparation of this manuscript, the authors used ChatGPT 4 to improve the readability and language of the manuscript. The authors have reviewed and edited the output and take full responsibility for the content of this publication.
Abbreviations
The following abbreviations are used in this manuscript:
| MMP | Methadone Maintenance Program |
| IQR | Interquartile range |
| CRL | Coefficient of linear regression |
| OR | Odds ratio |
| 95% CI | 95% confidence interval |
| HIV | Human immunodeficiency virus |
Appendix A
STROBE Checklist
| Item | Recommendation | Page | |
| Title and abstract | 1 | (a) Indicate the study’s design with a commonly used term in the title or the abstract | 1 |
| (b) Provide in the abstract an informative and balanced summary of what was done and what was found | 1 | ||
| Introduction | |||
| Background/rationale | 2 | Explain the scientific background and rationale for the investigation being reported | 2 |
| Objectives | 3 | State specific objectives, including any prespecified hypotheses | 2–3 |
| Methods | |||
| Study design | 4 | Present key elements of study design early in the paper | 3 |
| Setting | 5 | Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection | 3 |
| Participants | 6 | (a) Give the eligibility criteria, and the sources and methods of selection of participants | 3 |
| Variables | 7 | Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable | 3 |
| Data sources/measurement | 8 * | For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group | 3 |
| Bias | 9 | Describe any efforts to address potential sources of bias | 13 |
| Study size | 10 | Explain how the study size was arrived at | 3 |
| Quantitative variables | 11 | Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why | 3–4 |
| Statistical methods | 12 | (a) Describe all statistical methods, including those used to control for confounding | 3–4 |
| (b) Describe any methods used to examine subgroups and interactions | 4 | ||
| (c) Explain how missing data were addressed | N/A * | ||
| (d) If applicable, describe analytical methods taking account of sampling strategy | N/A * | ||
| (e) Describe any sensitivity analyses | N/A * | ||
| Results | |||
| Participants | 13 * | (a) Report numbers of individuals at each stage of study—e.g., numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed | 3 |
| (b) Give reasons for non-participation at each stage | 3 | ||
| (c) Consider use of a flow diagram | 3 | ||
| Descriptive data | 14 * | (a) Give characteristics of study participants (e.g., demographic, clinical, social) and information on exposures and potential confounders | 4–7 |
| (b) Indicate number of participants with missing data for each variable of interest | 7 | ||
| Outcome data | 15 * | Report numbers of outcome events or summary measures | 7–11 |
| Main results | 16 | (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (e.g., 95% confidence interval). Make clear which confounders were adjusted for and why they were included | 4 |
| (b) Report category boundaries when continuous variables were categorized | 4 | ||
| (c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period | N/A * | ||
| Other analyses | 17 | Report other analyses done—e.g., analyses of subgroups and interactions, and sensitivity analyses | N/A * |
| Discussion | |||
| Key results | 18 | Summarise key results with reference to study objectives | 11 |
| Limitations | 19 | Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias | 13 |
| Interpretation | 20 | Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence | 11–13 |
| Generalisability | 21 | Discuss the generalisability (external validity) of the study results | 11–13 |
| Other information | |||
| Funding | 22 | Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based | 13 |
| * N/A: Not applicable. | |||
Appendix B
Ad Hoc Questionnaire
Instructions: Next, we will ask you a few personal questions that will be treated with absolute confidentiality according to current legislation. You will mark the box to the right of the option that is suitable for you with an X.
If you do not wish to answer any of the questions, you are free not to do so. If you have any doubts, consult the investigator in charge.
-
1.What studies have you done?
- I did not finish school.
- I only went to school.
- I only completed secondary education.
- I only completed high school.
- I went to college or higher.
-
2.What is your current marital status?
- Single
- Married
- Divorced/Separated
- Widowed
- With a partner
-
3.Are you currently working?
- Yes
- No
-
4.How many children do you have?
- 0
- 1
- 2
- 3
- 4
- 5 or more
-
5.Have you been in jail?
- Yes
- No
-
6.Where are you from?
- Spain
- Other (Indicate where on the dotted line) …………………………………………….
-
7.Do you currently live with someone?
- I live alone.
- I live with my partner.
- I live with my partner and my children.
- I live with my children.
- I share a house.
- I am currently living on the street.
-
8.How long have you been enrolled in the methadone program? Approximately
- Less than 1 year
- Between 1 year and 5 years
- Between 5 years and 10 years
- Between 10 years and 20 years
- Between 20 years and 30 years
- More than 30 years
Author Contributions
Conceptualisation, P.L.-P., I.E.-B. and R.S.-R.; methodology, P.L.-P., R.S.-R. and M.R.-B.; selection of participants and data collection, P.L.-P. and I.E.-B.; formal analysis, P.L.-P., R.S.-R., R.R.-B. and M.R.-B.; data curation, P.L.-P., I.E.-B., R.S.-R. and R.R.-B.; writing—original draft preparation, P.L.-P., I.E.-B. and R.S.-R.; writing—review and editing, all authors; supervision, M.R.-B.; funding acquisition, R.S.-R. and M.R.-B. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Cádiz Research Ethics Committee (CEIC) with the code SICEIA-2024-001059 on 8 July 2024. Authorisation was obtained from the ethics committee for consultation and the use of the electronic health records for research purposes.
Informed Consent Statement
Informed consent was obtained from all the participants involved in the study. Written informed consent was obtained from the participants to publish this paper.
Data Availability Statement
The Ethics Committee approved this research without considering the option of data sharing. The data can be requested by contacting the main author. However, each new project on the basis of these data must be previously submitted to the Ethics Committee for approval.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Funding Statement
The development of this research received no external funding. The translation of this manuscript was funded by the Foundation for Biosanitary Research and Innovation in Primary Care (FIIBAP).
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
References
- 1.Agency EUD Heroin and Other Opioids-the Current Situation in Europe (European Drug Report 2025) 2025. [(accessed on 4 June 2025)]. Available online: https://www.euda.europa.eu/publications/european-drug-report/2025/heroin-and-other-opioids_en#edr25-section-heroin-market.
- 2.United Nations World Drug Report 2024. 2024. [(accessed on 4 June 2025)]. Available online: https://www.unodc.org/documents/data-and-analysis/WDR_2024/2410189S.pdf.
- 3.Delargy I., Crowley D., Van Hout M.C. Twenty years of the methadone treatment protocol in Ireland: Reflections on the role of general practice. Harm Reduct. J. 2019;16:5. doi: 10.1186/s12954-018-0272-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.OMS International Statistical Classification of Diseases and Related Health Problems—11th Version. 2019. [(accessed on 4 June 2025)]. Available online: https://www.who.int/standards/classifications/classification-of-diseases.
- 5.Ministerio de Sanidad, Delegación del Gobierno para el Plan Nacional Sobre Drogas [(accessed on 4 June 2025)];Observatorio Español de las Drogas y las Adicciones. Estadísticas 2023. Alcohol, Tabaco y Drogas Ilegales en España. Madrid; 2023. Available online: https://pnsd.sanidad.gob.es/
- 6.Fredericksen R.J., Baker R., Sibley A., Estadt A.T., Colston D., Mixson L.S., Walters S., Bresett J., Levander X.A., Leichtling G., et al. Motivation and context of concurrent stimulant and opioid use among persons who use drugs in the rural United States: A multi-site qualitative inquiry. Harm Reduct. J. 2024;21:74. doi: 10.1186/s12954-024-00986-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Ovservatorio Español de las Drogas las Adicciones Informe 2024. Alcohol, Tabaco y Drogas Ilegales en España. [(accessed on 7 June 2025)];2024 Available online: https://pnsd.sanidad.gob.es/
- 8.Family H.E., Vojt G., Poulter H., Bailey C.P., Abdala Sheikh A.P., Cavallo D., Karimi S., Booth N., Da Silva P., Aitken L., et al. A qualitative study of benzodiazepine/z-drug and opioid co-use patterns and overdose risk. Harm Reduct. J. 2025;22:24. doi: 10.1186/s12954-025-01153-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Rivera B., Casal B., Currais L. The social cost of illicit drugs use in Spain. Int. J. Drug Policy. 2017;44:92–104. doi: 10.1016/j.drugpo.2017.03.012. [DOI] [PubMed] [Google Scholar]
- 10.Roncero C., Barral C., Rodríguez-Cintas L., Pérez-Pazos J., Martinez-Luna N., Casas M., Torrens M., Grau-López L. Psychiatric comorbidities in opioid-dependent patients undergoing a replacement therapy programme in Spain: The PROTEUS study. Psychiatry Res. 2016;243:174–181. doi: 10.1016/j.psychres.2016.06.024. [DOI] [PubMed] [Google Scholar]
- 11.Dematteis M., Auriacombe M., D’Agnone O., Somaini L., Szerman N., Littlewood R., Alam F., Alho H., Benyamina A., Bobes J., et al. Recommendations for buprenorphine and methadone therapy in opioid use disorder: A European consensus. Expert Opin. Pharmacother. 2017;18:1987–1999. doi: 10.1080/14656566.2017.1409722. [DOI] [PubMed] [Google Scholar]
- 12.Pérez E., Ruiz S., Pérez E., Ruiz S. El consumo de sustancias como factor de riesgo para la conducta delictiva: Una revisión sistemática. Acción Psicológica. [(accessed on 10 June 2025)];Accion Psicol. 2017 14:33–50. doi: 10.5944/ap.14.2.20748. Available online: https://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S1578-908X2017000200003&lng=es&nrm=iso&tlng=es. [DOI] [Google Scholar]
- 13.Carr M.M., Mannes Z.L., Oberleitner L.M.S., Oberleitner D.E., Beitel M., Gazzola M.G., Madden L.M., Zheng X., Barry D.T. The impact of body image dissatisfaction on psychological distress and health-related quality of life among patients in methadone treatment. Am. J. Addict. 2023;32:460–468. doi: 10.1111/ajad.13432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.SAMHSA Treatment Improvement Protocol: Medications for Opioid Use Disorder. [(accessed on 7 June 2025)];2021 Available online: https://library.samhsa.gov/sites/default/files/pep21-02-01-002.pdf.
- 15.Hosseini S.H., Fendereski F., Yazdani F., Hamzehgardeshi Z. Exploring perceived quality of life in long-term methadone-dependent patients: A qualitative study. Harm Reduct. J. 2024;21:225. doi: 10.1186/s12954-024-01140-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Pascual-Pastor F., Muñoz Á., Oraa R., Flórez G., Notario P., Seijo P., Gonzalvo B., Assaf C., Gómez M., Casado M.Á. Satisfacción y experiencia de pacientes en tratamiento con sustitutivos opiodes en España. Estudio PREDEPO. [(accessed on 13 June 2025)];Adicciones. 2023 35:433–444. doi: 10.20882/adicciones.1684. Available online: http://www.adicciones.es. [DOI] [PubMed] [Google Scholar]
- 17.Cao P., Zhang Z., Zhong J., Xu S., Huang Q., Fan N. Effects of treatment status and life quality on anxiety in MMT patients. Subst Abus. Treat. Prev. Policy. 2021;16:9. doi: 10.1186/s13011-021-00343-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Xu Y.M., Zhong B.L., Chen W.C., Zhu J.H., Lu J. Suicidal ideation among Chinese methadone-maintained patients: Prevalence and correlates. Oncotarget. 2017;8:86181–86187. doi: 10.18632/oncotarget.21032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Aghayan S., Amiri M., Chaman R., Khosravi A. Quality of life in methadone maintenance treated patients in Iran. Int. J. High Risk Behav. Addict. 2015;4:e22275. doi: 10.5812/ijhrba.22275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Diaz-Negrete D.B., Velázquez-Altamirano M., Benítez-Villa J.L., Fernández-Cáceres C. Psychosocial reintegration process in patients who receive maintenance treatment with methadone: A qualitative analysis. Salud Ment. 2019;42:173–184. doi: 10.17711/SM.0185-3325.2019.023. [DOI] [Google Scholar]
- 21.Zhou K., Li H., Wei X., Li X., Zhuang G. Relationships between perceived social support and retention among patients in methadone maintenance treatment in mainland China. Psychol. Health Med. 2016;22:493–500. doi: 10.1080/13548506.2016.1164873. [DOI] [PubMed] [Google Scholar]
- 22.Tun S., Balasingam V., Singh D. Factors associated with quality of life (QOL) scores among methadone patients in Myanmar. PLoS Glob. Public Health. 2022;2:e0000469. doi: 10.1371/journal.pgph.0000469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kollerits E., Zsila Á., Matuszka B. Quality of life, social support, and adherence in female patients with thyroid disorders. [(accessed on 16 July 2025)];BMC Women’s Health. 2023 23:567. doi: 10.1186/s12905-023-02718-0. Available online: https://pubmed.ncbi.nlm.nih.gov/37919706/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Ivarsson B., Hesselstrand R., Rådegran G., Kjellström B. Health-related quality of life, treatment adherence and psychosocial support in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension. Chronic Respir. Dis. 2018;16:1479972318787906. doi: 10.1177/1479972318787906. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Sun H., Francis H.M., Polo J., Esposito C., Papia K., Yeley J., Brant M., Huenger A., Wang J., Brown C., et al. The Impact of Personal-Level Social Networks on Treatment Adherence, Depression, Anxiety, and Perceived Stigma Among Adults with Cystic Fibrosis: An Egocentric Network Analysis. Int. J. Behav. Med. 2025 doi: 10.1007/s12529-025-10382-x. online ahead of print . [DOI] [PubMed] [Google Scholar]
- 26.Merchant T., DiTosto J.D., Gomez-Roas M., Williams B.R., Niznik C.M., Feinglass J., Grobman W.A., Yee L.M. The Role of Social Support on Self-Management of Gestational Diabetes Mellitus: A Qualitative Analysis. J. Midwifery Women’s Health. 2025 doi: 10.1111/jmwh.13782. online ahead of print . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Hoang V.L., Green T., Bonner A. Examining social support, psychological status and health-related quality of life in people receiving haemodialysis. [(accessed on 16 July 2025)];J. Ren. Care. 2022 48:102–111. doi: 10.1111/jorc.12380. Available online: https://pubmed.ncbi.nlm.nih.gov/34041850/ [DOI] [PubMed] [Google Scholar]
- 28.Szymczak H., Brandstetter S., Blecha S., Dodoo-Schittko F., Rohr M., Bein T., Apfelbacher C. Social support and recovery in acute respiratory distress syndrome survivors: A prospective cohort study. [(accessed on 16 July 2025)];ERJ Open Res. 2025 11:01113-2024. doi: 10.1183/23120541.01113-2024. Available online: https://pubmed.ncbi.nlm.nih.gov/40661929/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ministerio de Sanidad, Delegación del Gobierno para el Plan Nacional Sobre Drogas [(accessed on 12 July 2025)];Observatorio Español de las Drogas y las Adicciones. Informe 2022 Alcohol, Tabaco y Drogas Ilegales en España. Madrid; 2022. Available online: https://pnsd.sanidad.gob.es/
- 30.INE Población de Cádiz. 2025. [(accessed on 11 July 2025)]. Available online: https://www.ine.es/jaxi/Tabla.htm?path=/t20/e242/p03/a2001/l0/&file=mun11.px&L=0.
- 31.Servicio Provincial de Drogodependencia de Cádiz Informe de Memoria 2020. [(accessed on 10 July 2025)]. Available online: https://www.dipucadiz.es/export/sites/default/drogodependencias/.galeria_ficheros/documentos/Memoria-completa-SPD-Cadiz-2020.pdf.
- 32.Servicio de Drogodependencias de la Diputación de Cádiz Informe sobre el Indicador Admisiones a Tratamiento a Sustancias o por Comporta Mentales en Cádiz 2020. 2021. [(accessed on 15 July 2025)]. Available online: https://www.dipucadiz.es/export/sites/default/drogodependencias/.galeria_ficheros/documentos/Informe-sobre-el-Indicador-de-Admisiones-a-Tratamiento-2020.pdf.
- 33.Badia X., Salamero M., Alonso J. La Medida de la Salud: Guía de Escalas de Medición en Español. Tecnología y Ediciones del Conocimiento; Barcelona, Spain: 2007. [Google Scholar]
- 34.De las Cuevas C., Peñate W. Psychometric properties of the eight-item Morisky Medication Adherence Scale (MMAS-8) in a psychiatric outpatient setting. Int. J. Clin. Health Psychol. 2015;15:121–129. doi: 10.1016/j.ijchp.2014.11.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Lozano-Hernández C.M., Cladellas Y.P., Gil Conesa M., Garin O., Forés M.F., del Cura-González I. Functional social support: A systematic review and standardized comparison of different versions of the DUFSS questionnaire using the EMPRO tool. PLoS ONE. 2023;18:e0291635. doi: 10.1371/journal.pone.0291635. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.WHO WHOQOL-BREF: Introduction, Administration, Scoring and Generic Version of the Assessment: Field Trial Version. 1996. [(accessed on 15 July 2025)]. Available online: https://www.who.int/publications/i/item/WHOQOL-BREF.
- 37.Chaves Torres N.M., Echeverri Sarmiento J.E., Ballesteros D.A., Quijano Rodriguez J., Camacho D. Validación de la escala de Morisky de 8 ítems en pacientes con enfermedad renal crónica. Revista Med. 2016;24:23–32. doi: 10.18359/rmed.2627. [DOI] [Google Scholar]
- 38.Bellón-Saameño J.A., Delgado-Sánchez A., de Dios Luna del Castillo J., Claret P.L. Validez y fiabilidad del cuestionario de apoyo social funcional Duke-UNC-11. Aten Primaria. 1996;18:153–163. [PubMed] [Google Scholar]
- 39.Lucas-Carrasco R. The WHO quality of life (WHOQOL) questionnaire: Spanish development and validation studies. Qual. Life Res. 2012;21:161–165. doi: 10.1007/s11136-011-9926-3. [DOI] [PubMed] [Google Scholar]
- 40.Zhou K., Wang D., Li H., Wei X., Yin J., Liang P., Kou L., Hao M., You L., Li X., et al. Bidirectional relationships between retention and health-related quality of life in Chinese mainland patients receiving methadone maintenance treatment. PLoS ONE. 2017;12:e0179009. doi: 10.1371/journal.pone.0179009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Aas C.F., Vold J.H., Skurtveit S., Lim A.G., Ruths S., Islam K., Askildsen J.E., Løberg E.-M., Fadnes L.T., Johansson K.A. Health-related quality of life of long-term patients receiving opioid agonist therapy: A nested prospective cohort study in Norway. Treat. Prev. Policy. 2020;15:68. doi: 10.1186/s13011-020-00309-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Chang H.M., Huang M.C., Fang S.C., Lin S.K. Quality of life and associated factors of heroin-dependent patients receiving methadone and buprenorphine maintenance treatment. Neuropsychopharmacol. Rep. 2023;43:607–615. doi: 10.1002/npr2.12402. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Ministerio de Sanidad Consumo y Bienestar Social Encuesta Nacional de Salud—España 2017 (ENSE 2017); 2018. [(accessed on 12 July 2025)]; Available online: https://www.sanidad.gob.es/estadEstudios/estadisticas/encuestaNacional/encuesta2017.htm.
- 44.Nguyen H.T.T., Tran D.Q., Dinh D.X. Social support status and associated factors among methadone maintenance patients: A multicentre, cross-sectional study in Vietnam during the COVID-19 pandemic. BMJ Open. 2024;14:e081519. doi: 10.1136/bmjopen-2023-081519. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Farmaindustria F. Encuesta Sobre Adherencia Terapéutica en España. 2015. [(accessed on 28 July 2025)]. Available online: https://www.farmaindustria.es/web/wp-content/uploads/sites/2/2016/12/Informe-Estudio-de-adherencia-anx.pdf.
- 46.Nguyen L.H., Nguyen H.T.T., Nguyen H.L.T., Tran B.X., Latkin C.A. Adherence to methadone maintenance treatment and associated factors among patients in Vietnamese mountainside areas. Subst. Abus. Treat. Prev. Policy. 2017;12:31. doi: 10.1186/s13011-017-0115-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Ballesta-Gómez R., Millán-Jimenez A., Tena-Aguilar M., Ruiz-Benítez B., Alaminos-Romeo F.J., Montero-López O. La Población Andaluza Ante las Drogas XV. Cáritas Española; Madrid, Spain: 2022. [Google Scholar]
- 48.INE Datos Estadísticos de paro Registrado y Contratos por Municipios y Actividad Económica (más de 45.000 Habitantes y Capitales) | Servicio Público de Empleo Estatal. 2025. [(accessed on 29 June 2025)]. Available online: https://www.sepe.es/HomeSepe/que-es-el-sepe/estadisticas/datos-estadisticos/municipios-capitales/2025/febrero.html.
- 49.INE Encuesta de Población Activa (EPA) Cuarto Trimestre 2024. 2024. [(accessed on 4 July 2025)]. Available online: https://www.ine.es/dyngs/Prensa/EPA4T24.htm.
- 50.Tran B.X., Nguyen L.H., Nong V.M., Nguyen C.T., Phan H.T.T., Latkin C.A. Behavioral and quality-of-life outcomes in different service models for methadone maintenance treatment in Vietnam. Harm Reduct. J. 2016;13:4. doi: 10.1186/s12954-016-0091-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Van Nguyen H., Nguyen H.L.T., Mai H.T., Le H.Q., Tran B.X., Hoang C.D., Le H.T., Nguyen C.T., Tran T.D., Latkin C.A., et al. Stigmatization among methadone maintenance treatment patients in mountainous areas in northern Vietnam. Harm Reduct. J. 2017;14:1. doi: 10.1186/s12954-016-0127-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.INE Penas de Prisión Según Duración de la pena, sexo, edad y Nacionalidad. 2025. [(accessed on 12 July 2025)]. Available online: https://www.ine.es/jaxiT3/Datos.htm?t=25715#_tabs-tabla%20/
- 53.Ministerio del Interior Estudio de Reincidencia Penitenciaria 2009–2019. [(accessed on 28 June 2025)];2022 Available online: https://www.interior.gob.es/opencms/pdf/archivos-y-documentacion/documentacion-y-publicaciones/publicaciones-descargables/instituciones-penitenciarias/Estudio_de_reincidencia_penitenciaria_2009-2019_DP-30_126220415.pdf.
- 54.Ministerio de Sanidad Servicios Sociales e Igualdad Plan Estratégico para el Abordaje de la Hepatitis C en el Sistema Nacional de Salud. 2015 June. [(accessed on 12 July 2025)]; Available online: https://www.sanidad.gob.es/ciudadanos/enfLesiones/enfTransmisibles/hepatitisC/PlanEstrategicoHEPATITISC/docs/plan_estrategico_hepatitis_C.pdf.
- 55.Ministerio de Sanidad Plan Estratégico para la Prevención y Control de la Infección por el VIH y las ITS en España. 2021–2030. [(accessed on 30 March 2025)];2023 Available online: https://cpage.mpr.gob.es.
- 56.Muller A.E. A Systematic Review of Quality of Life Assessments of Offenders. Int. J. Offender Ther. Comp. Criminol. 2020;64:1364–1397. doi: 10.1177/0306624X19881929. [DOI] [PubMed] [Google Scholar]
- 57.OECD Education at a Glance 2024: OECD Indicators. 2024. [(accessed on 11 July 2025)]. Available online: [DOI]
- 58.Velaithan V., Tan M.M., Yu T.F., Liem A., Teh P.L., Su T.T. The Association of Self-Perception of Aging and Quality of Life in Older Adults: A Systematic Review. Gerontol. 2024;64:gnad041. doi: 10.1093/geront/gnad041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Pedrero-Pérez E.J., Barreda-Marina M.A., Bartolomé-Gil C., Bosque-Coro S., Callejo-Escobar J., Ema-López I., Dominguez-Aranda M.A., Ferrero-Herreros Y.E., Galera-García Ó., Garrido-Ureña B., et al. Calidad de vida en pacientes tratados con metadona: El WHOQOL-BREF, estudio psicométrico y resultados de aplicación. An. Psicol. 2018;34:251–257. doi: 10.6018/analesps.34.2.282971. [DOI] [Google Scholar]
- 60.INE Renta por Persona y Unidad Consumo por Comunidades Autónomas. 2025. [(accessed on 6 July 2025)]. Available online: https://www.ine.es/jaxiT3/Datos.htm?t=9947#_tabs-tabla.
- 61.Ali N., Aziz S.A., Nordin S., Mi N.C., Abdullah N., Paranthaman V., Mahmud M., Yee A., Danaee M. Evaluation of Methadone Treatment in Malaysia: Findings from the Malaysian Methadone Treatment Outcome Study (MyTOS) Subst. Use Misuse. 2018;53:239–248. doi: 10.1080/10826084.2017.1385630. [DOI] [PubMed] [Google Scholar]
- 62.Pedrero-Pérez E.J., MethaQoL G. Dosis de metadona y su relación con calidad de vida, satisfacción, psicopatología, rendimiento cognitivo y consumo adicional de sustancias no prescritas. Adicciones. 2016;29:37–54. doi: 10.20882/adicciones.831. [DOI] [PubMed] [Google Scholar]
- 63.Fei J.T.B., Yee A., Habil M.H.B., Danaee M. Effectiveness of Methadone Maintenance Therapy and Improvement in Quality of Life Following a Decade of Implementation. J. Subst. Abus. Treat. 2016;69:50–56. doi: 10.1016/j.jsat.2016.07.006. [DOI] [PubMed] [Google Scholar]
- 64.Hurst J.R., Skolnik N., Hansen G.J., Anzueto A., Donaldson G.C., Dransfield M.T., Varghese P. Understanding the impact of chronic obstructive pulmonary disease exacerbations on patient health and quality of life. Eur. J. Intern. Med. 2020;73:1–6. doi: 10.1016/j.ejim.2019.12.014. [DOI] [PubMed] [Google Scholar]
- 65.Saqlain M., Riaz A., Ahmed A., Kamran S., Bilal A., Ali H. Predictors of Health-Related Quality of Life Status Among Elderly Patients with Cardiovascular Diseases. Value Health Reg. Issues. 2021;24:130–140. doi: 10.1016/j.vhri.2020.11.003. [DOI] [PubMed] [Google Scholar]
- 66.Chuang S., Wu J., Wang C. Resilience and Quality of Life in People with Mental Illness: A Systematic Review and Meta-Analysis. Neuropsychiatr. Dis. Treat. 2023;19:507–514. doi: 10.2147/NDT.S392332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Brennan-Ing M. Diversity, stigma, and social integration among older adults with HIV. Eur. Geriatr. Med. 2018;10:239–246. doi: 10.1007/s41999-018-0142-3. [DOI] [PubMed] [Google Scholar]
- 68.Romero-Serrano R., Casado Mejía R., Rebollo Catalán M.A., García-Iglesias J.J., Gómez-Salgado J., Lancharro Tavero I. Influencia de las redes de apoyo sociofamiliares en el cuidado de las personas mayores dependientes: Un estudio cualitativo. Rev. Española Salud Pública. 2023;97:e202311095. [PMC free article] [PubMed] [Google Scholar]
- 69.Perez Torres V. Ph.D. Thesis. Universidad Rey Juan Carlos; Madrid, Spain: 2011. Percepción de Apoyo Social Dentro y Fuera del Entorno Laboral y su Relación con las Actitudes Hacia el Trabajo y los Riesgos Psicosociales en Trabajadores con Discapacidad. [Google Scholar]
- 70.Lakey B., Orehek E. Relational regulation theory: A new approach to explain the link between perceived social support and mental health. Psychol. Rev. 2011;118:482–495. doi: 10.1037/a0023477. [DOI] [PubMed] [Google Scholar]
- 71.Division of Mental Health and Prevention of Substance, World Health Organization . Programme on Mental Health. WHOQOL User Manual. WHO; Geneva, Switzerland: 2012. [Google Scholar]
- 72.Ministerio de Sanidad, Delegación del Gobierno para el Plan Nacional sobre Drogas Observatorio Español de las Drogas y las Adicciones. Informe 2021. Alcohol, Tabaco y Drogas Ilegales en España. Madrid. [(accessed on 10 July 2025)];2021 Available online: https://pnsd.sanidad.gob.es/
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The Ethics Committee approved this research without considering the option of data sharing. The data can be requested by contacting the main author. However, each new project on the basis of these data must be previously submitted to the Ethics Committee for approval.