Skip to main content

Effects of publicly funded and quality of life on attendance rate among methadone maintenance treatment patients in Taiwan: an 18-month follow-up study



Methadone maintenance treatment programs (MMTPs) are important public health intervention to control the human immunodeficiency virus (HIV) and the drug use problems. For expanding treatment coverage, publicly funded programs may be necessary for heroin users with low socio-economic status. We evaluated the difference of demographics, clinical features, and quality of life (QoL) of heroin users enrolled in publicly funded and self-paid MMTP and explored determinants influencing their attendance rate, respectively, for these two groups.


A total of 234 heroin users enrolled in MMTP (129 in publicly funded and 105 in self-paid) between 2006 and 2008 self-reported the Taiwan version of the World Health Organization Quality of Life Instrument, Brief Version (WHOQOL-BREF) at baseline. Data regarding demographic and clinical features were collected during baseline interview. Methadone per 3-month attendance rates up to 18 months were conducted for each participant beginning from the index date.


Self-paid group had a better QoL but lower treatment adherence than did the publicly funded group. Male and living alone were positive predictors on attendance rate for publicly funded group, and age of first heroin use and hepatitis C virus (HCV) seropositive were negative predictors. However, predictors on attendance rate for self-paid group were different from publicly funded group: HCV seropositive was a positive predictor and social QoL was a negative predictor.


Findings of this study should be concerned with modifying original funding eligibility. Additional measures to explore what could impede treatment adherence are needed.


Taiwan implemented a National Health Insurance (NHI) program from March 1995, offering a comprehensive, unified, and universal health insurance program to all citizens [1]. The coverage includes outpatient service, inpatient care, Chinese medicine, dental care, childbirth, physical therapy, preventive health care, home care, and rehabilitation for chronic mental illness. In addition, the NHI program covers as high as 99 % of Taiwan population [2]. However, the cost on items directly related to substance use, such as the methadone maintenance treatment (MMT), is not covered by the NHI. MMT is a primary treatment for opioid-dependent people who have significantly elevated mortality than their general counterparts [3], and opioid dependence makes global disease a burden [4]. Although numerous studies [59] report that MMT has encouraging results of reducing drug addiction, decreasing illegal activities, and improving the overall well-being for drug users, the MMT program (MMTP) was not permitted until 2006: The Taiwan Center for Disease Control (CDC) permitted MMTP for patients with opioid dependence in response to human immunodeficiency virus (HIV) epidemic [10]. Several publicly funded MMTPs were held due to the urge for inhibition of the HIV infection spread. The criteria of participating in a publicly funded MMTP were that the heroin users were HIV seropositive, ex-prisoners, or applying for deferred prosecution. The publicly funded MMTP provided free treatment for heroin users with HIV seropositive and 1-year service without payment for those who applied for deferred prosecution or who were ex-prisoners. However, those heroin users who did not fulfill the publicly funded criteria were charged around 100 US$ per month for the treatment (self-paid MMTP). Previous American studies [11, 12] found that Medicaid eligibility was strongly associated with enrollment in MMTP, and Medicaid clients had far greater access to MMTP than non-Medicaid counterparts after controlling their characteristic differences. However, studies with regard to differences between publicly funded and self-paid MMTP have been minimally addressed, especially in the East.

As for comparing the publicly funded and self-paid MMTP, we recommend using an important outcome index, quality of life (QoL). QoL refers to a subjective evaluation which is embedded in a cultural, social, and environmental context [13]. There were increasing evidences that a good QoL is associated with a better treatment outcome in patients with opioid dependence, e.g., [14, 16]. In addition, research has found that co-morbid infectious disease such as HIV and hepatitis C virus (HCV) and drug-related crimes which are frequent in heroin users may impair their QoL [1517]. Therefore, understanding the QoL and features of the two MMTP groups may provide clinicians useful information and help them make a critical clinical decision.

In addition to the QoL, adherence is another important issue for MMTP participants. Several studies from the West [1821] found that high methadone adherence is necessary for successful therapeutic outcomes. Furthermore, these studies [1821] used retention rate as an index to represent the adherence. However, if the policy provides no take-home dose for methadone maintenance patients (e.g., the MMTP in Taiwan), we suggested that treatment attendance, another adherence index, becomes essential for understanding treatment effectiveness. Successful MMT requires both long-term enrollment (retention duration) at an adequate dosage and on daily basis (regular attendance) [9]. In addition, to the best of our knowledge, studies reporting the factors influencing on methadone adherence in Asia are still scarce. Therefore, investigating the factors that influence on MMTP attendance rate in an East-Asian country (say, Taiwan) is necessary.

Using an 18-month follow-up data from one psychiatric center in south Taiwan, this observational study aimed to (1) examine the QoL difference between methadone maintenance patients presented for publicly funded and self-paid MMTP and (2) explore determinants influencing MMTP adherence using attendance rate, respectively, for these two groups.


Data sources

A retrospective cohort study was conducted, and all recruited participants between March 2006 and July 2008 were diagnosed as opioid dependence by a board-certified psychiatrist from the Jianan Psychiatric Center research team. The inclusion criteria were as follows: (1) being more than 20 years old; (2) meeting the DSM-IV (Diagnostic and statistical manual of mental disorders, fourth edition) criteria for opioid dependence; (3) having sufficient mental competence to understand and sign an informed consent; (4) residing near our treatment service site (i.e., Tainan City); and (5) no other MMTP contraindication, such as severe liver cirrhosis, severe cognitive impairment, or behavioral disturbances. None of the participants had participated in any MMTP before the intake interview. At the intake interview, the participants were identified as publicly funded MMTP (n = 129) or self-paid MMTP (n = 105) groups based on whether they met the publicly funded eligibility criteria: (a) as a function of HIV status; (b) applying for deferred prosecution; and (c) had been incarcerated due to the Drug Act before and discharged during the recruited period. Methadone attendance of 18 months was conducted for each participant from the index date, and we divided the study period into six phases of 3 months duration each. The Hospital Ethics Committee of Jianan Psychiatric Center approved this study (IRB number, JMH9601).

Quality of life

We used the World Health Organization Quality of Life Assessment, Brief Version (WHOQOL-BREF), which contains 28 items with 26 standard items from the original WHOQOL-BREF, and two Taiwanese national items [22]. In addition, the WHOQOL-BREF Taiwan version includes four domains (physical, seven items; psychological, six items; social, four items, and environment, nine items) and two generic items which did not belong to any domain (“overall QoL” and “general health”). Domain scores are calculated into a 4-to-20 range, and a higher score represents a better QoL. Moreover, the psychometric properties of WHOQOL-BREF are satisfactory in Taiwan population [22], including those with a mental illness [2325].

Demographics and lab tests

In addition to the WHOQOL-BREF, each MMTP patient completed a background information sheet including his or her birth date, gender, living status (alone vs. with others), educational years, age of first heroin use, heroin using years, employment status (fixed or not), and family drug using. After completing the WHOQOL-BREF and the background information sheet, each patient underwent a series of laboratory tests, including HIV, HBV, and HCV tests.

Data analysis

Baseline characteristics and QoL scores between publicly funded and self-paid MMTP groups were compared using χ 2 tests (for frequency comparisons) and independent t tests (for mean comparisons). In addition, QoL scores of the two groups were separately compared with QoL scores of Taiwan population using one-sample t tests. The mean (±SD) QoL scores of Taiwan population are 14.06 ± 2.34 for the physical, 13.23 ± 2.15 for the psychological, 13.56 ± 2.29 for the social, and 12.72 ± 2.07 for the environment domains [26].

Generalized estimating equation (GEE) was used to examine the effects of several predictors on attendance rate. Because each participant had one to six attendance rates (i.e., the attendance rates for 3, 6, 9, 12, 15, and 18 months) from participating in the MMT program to 18 months later, using the GEE is adequate. All the analyses were done using SPSS 15.0 (SPSS Inc., Chicago, IL.).


No significant differences were found between the publicly funded and self-paid MMTP participants in their demographic data, except for heroin using years (t = 3.59, P < 0.001) and HIV carrier (χ 2 = 45.35, P < 0.001). The publicly funded group had significantly more heroin using years (9.25 ± 6.77 vs. 6.48 ± 3.86) and HIV carriers (n = 45 vs. 0) than the self-paid group. In addition, the self-paid MMTP participants had significantly higher QoL scores than the publicly funded MMTP participants in all QoL domains (Table 1).

Table 1 The baseline characteristics and QoL scores comparisons using independent t tests (for continuous variables) or χ 2 tests (for categorical variables) between publicly funded and self-paid methadone maintenance treatment patients

As compared with Taiwan population, the publicly funded MMTP participants had all but the environment domain scores significantly lower than the scores of Taiwan population. In addition, the self-paid MMTP participants had significantly lower QoL score in the physical domain and higher score in the environment domain (Table 2).

Table 2 Comparisons using one-sample t tests between methadone maintenance treatment patients and Taiwan population

Different predictors of attendance rate were found between publicly funded and self-paid groups. Significant predictors for the publicly funded group were gender (reference = female; β = −0.115, P < 0.05), living alone (reference = no; β = 0.088, P < 0.01), age of first heroin use (β = −0.007, P < 0.05), and HCV carriers (reference = seronegative; β = −0.068, P < 0.05). As for the self-paid group, significant predictors were HCV carriers (reference = seronegative; β = 0.224, P < 0.01) and social QoL scores (β = −0.020, P < 0.05) (Table 3).

Table 3 Predictors of attendance rate on the heroin-dependent individuals receiving methadone maintenance treatment using generalized estimating equation models


Our results are consistent with previous studies: heroin users had lower QoL scores as compared with the general population [27]. This also echoes the findings in other research that heroin users often find themselves in a crisis situation at the MMTP intake and attend treatment in poor condition, resulting in low QoL scores at admission [28, 29]. However, unlike the publicly funded group who had all domains of QoL but environment QoL significantly lower than the Taiwan general population, the self-paid group only had its physical QoL lower than the Taiwan general population. One possible explanation is that the eligibility of free treatment covered heroin users who contracted HIV or applying for deferred prosecution make the reasons of seeking treatment different. Although our treatment modality only provided methadone maintenance, we hypothesized that self-paid heroin users choose to attend MMTP mainly for their physical discomfort suffering, especially the heroin withdrawal syndrome. This hypothesis may correspond with one study in China that reported that MMTP-related misconception (e.g., one could be completely detoxified and quit methadone treatment for the coming months) are very common among newly admitted first-time participants and misconception found at admission of MMTP predicted subsequent dropout during the treatment period [30]. That is, the heroin users dropped out the MMTP when they released their physical pain. In addition, a much higher retention rate of our publicly funded group than that of the self-paid group (18 months retention rate was 31.0 % for publicly funded and 11.0 % for the self-paid group) may also indirectly support our hypothesis. Further investigation regarding the perception and opinion toward MMTP among heroin users in Taiwan are also needed.

We found no demographic differences between heroin users under coverage of publicly funded and those of self-paid MMTP. However, QoL among publicly funded methadone patients was even worse. Although there was no demographic disparity between the publicly funded and self-paid MMTP, the publicly funded group had longer heroin abusing length and more HIV-seropositive patients than the self-paid group. This may explain the lower QoL (including physical, psychological, social, and environment QoL) of the publicly funded group than that of the self-paid group. Previous studies indicate that people who have longer heroin use or who are HIV seropositive are more likely to have worse health status and QoL than their counterparts with shorter heroin use or HIV seronegative [14, 17].

The most interesting finding is that predictors for MMTP attendance rate were different between publicly funded and self-paid groups. Our results of educational years and employment status as non-significant predictors are comparable to previous studies [3134]. However, our results of gender as a significant predictor for publicly funded group contradict other research’s findings [3134]. The most possible reason is the difference between publicly funded and self-paid groups. We pooled all the participants and redid a GEE analysis, and our results showed that gender cannot significantly predict attendance rate in the pooled sample (β = −0.054, 95 % CI = −0.124 to 0.016, P = 0.133). Gender difference of attendance pattern in our publicly funded group echo another recent finding [35] that persistent drug-related stigmatization paired with HIV-related discrimination among male heroin users hindered their employment and exacerbated their struggles with addiction. Although our publicly funded male participants remained on treatment, their low socio-economic status often forced them to struggle between job and regular attendance.

In addition to the demographic factors mentioned above, good social QoL and HCV seropositive were good predictors for worse and better methadone attendance, respectively, in our self-paid group. The negative influence of social QoL on the attendance rate could be explained by the misconception toward MMTP among their peer group, though we did not have solid evidences to justify this explanation, and future studies are warranted. Another explanation for the negative influence could be the good social interaction in the self-paid group. With good social interaction, the self-paid group tended to receive heroin from their friends and became less motivated to take methadone. On the other hand, the positive impact of HCV seropositive may be due to the prevalence and awareness of the self-paid patients. Methadone patients are found to have high prevalence but low awareness of HCV infection while attending MMTP [36], and their motivation to regular attendance would be enhanced through psycho-education and counseling. In contrast to the self-paid group, however, HCV seropositive had a negative influence on attendance rate of the publicly funded participants. However, because HIV infection was a covariate in the GEE model for the publicly funded group, a possibility was that the effect of HCV infection influenced by that of HIV infection. In order to clarify the role of HCV infection in the publicly funded group, we additionally did a GEE model without the covariate of HIV for the publicly funded group, and a similar result was found (β = −0.068, P = 0.012). Therefore, we tentatively concluded that attendance pattern could be different between methadone patients contracted HCV and co-morbid HIV-HCV infection. However, certain baseline variables found to have an effect on the self-paid group used to predict attendance rate may have little effect on the publicly funded MMTP group. Further studies to examine the disparity between heroin users attending publicly funded and self-paid MMTP are urgently needed for policy makers.

Although our results shed some light on the issues of QoL and treatment adherence for heroin users engaging in a MMTP, clinicians should interpret our results, including those in Tables 1, 2, and 3, in cautions because the two MMTP groups consisted of different baselines. In addition, clinicians should also understand that the publicly funded MMTP patients in Taiwan were quite different from those in the USA: the publicly funded MMTP in Taiwan currently is a kind of (partly) compulsory legal act and is not comparable with that of the Medicaid eligibility in the USA. Therefore, all publicly funded MMTP patients in this study had the situations of either with a legal issue or with HIV infection. In contrast, the self-paid MMTP patients did not have the problems that the publicly funded MMTP patients confronted. Thus, the comparisons between the two groups may be inappropriate, and our results are highly likely to be biased.

The strength of this study was that newly admitted MMTP participants with better retention were our participants, while regular attendance could indicate better treatment outcome only under the circumstance of long enough treatment retention (e.g., 1-year retention). Another advantage is that our study collected two kinds of important determinants (WHOQOL-BREF for measuring generic QoL and blood sample for confirming the chronic infectious disease) at baseline to predict attendance rate up to 18 months.

However, this study has some limitations. First, our study involved only one site, limiting the generalization of its findings. Based on this limitation, readers need to know that our comparison results between MMTP patients and Taiwan general population were biased. Second, the study employed a cross-sectional design at the intake interview and the attendance rate may be affected by some potential important ongoing or time-dependent factors. Although previous Taiwan study reported no significant difference between HIV-positive and HIV-negative methadone patients [37], it should still be interpreted with caution because our publicly funded eligibility covered all heroin users with HIV seropositive. In addition, our predictors of QoL were time-dependent factors as well. Therefore, the predictive ability of our proposed QoL factors is very likely to be changed overtime, and the predicting effect of QoL on attendance rates should be used in cautions. Third, self-stigma [38, 39], another important factor that could impact patients’ volition to attend MMT, was not measured in this study. Future studies may want to use validated questionnaire, e.g., Internalized Stigma of Mental Illness Scale [40] and Self-Stigma Scale-Short [41] to understand the impact of self-stigma on attendance rate. Fourth, some co-payment MMTPs which have had executed after the recruited period might enhance the methadone adherence among our self-paid group. Lastly, self-reported data were used. Despite we guaranteed the privacy, reporting bias may still exist.


To the best of our knowledge, this is the first study comparing the QoL between publicly funded and self-paid heroin users and identifying their association of methadone attendance rate during 18 months follow-up. MMT is undoubtedly the key public health measures to control the HIV and the drug use problems. For treatment to be effective, regular attendance is necessary for reducing social costs in terms of drug-related legal and medical expenses. Previous study [42] has reported that drug users do not primarily associate QoL with health, but rather with social inclusion and self-determination. Under the circumstance of the impact of methadone maintenance was very similar in these MMTPs, if participants attend regularly. Measures to further explore what could potentially impede methadone attendance are needed. However, cautions are needed when clinicians and/or researchers interpret our results due to the different natures of our MMTP patients.



Center for Disease Control


Diagnostic and statistical manual of mental disorders, fourth edition


generalized estimating equation


hepatitis C virus


human immunodeficiency virus


methadone maintenance treatment


methadone maintenance treatment program


National Health Insurance


quality of life


World Health Organization Quality of Life Assessment, brief version


  1. 1.

    Chien IC, Chou YJ, Lin CH. Prevalence of psychiatric disorders among national health insurance enrollees in Taiwan. Psychiatr Serv. 2004;55:691–7.

    Article  PubMed  Google Scholar 

  2. 2.

    Chien IC, Chang KC, Lin CH, Chou YJ, Chou P. Prevalence of diabetes in patients with bipolar disorder in Taiwan: a population-based national health insurance study. General Hospital Psychiatry. 2010;32:138–41.

    Article  Google Scholar 

  3. 3.

    Degenhardt L, Bucello C, Mathers B, Briegleb C, Ali H, Hickman M, et al. Mortality among regular or dependent users of heroin and other opioids: a systematic review and meta-analysis of cohort studies. Addiction. 2011;106:32–51.

    Article  PubMed  Google Scholar 

  4. 4.

    Degenhardt L, Charlson F, Mathers B, Hall W, Johns N, Flaxman A, et al. The global epidemiology and burden of disease attributable to opioid dependence: findings from the Global Burden of Disease Study 2010. Addiction. 2014;109:1320–33.

    Article  PubMed  Google Scholar 

  5. 5.

    Clausen T, Anchersen K, Waal H. Mortality prior to, during and after opioid maintenance treatment (OMT): a national prospective cross-registry study. Drug Alcohol Depend. 2008;94:151–7.

    Article  PubMed  Google Scholar 

  6. 6.

    Gowing L, Farrell M, Bornemann R, Sullivan L, Ali R. Substitution treatment of injecting opioid users for prevention of HIV infection. Cochrane Database Syst Rev. 2008;2:CD004145.

    PubMed  Google Scholar 

  7. 7.

    Hedrich D, Alves P, Farrell M, Stöver H, Møller L, Mayet S. The effectiveness of opioid maintenance treatment in prison settings: a systematic review. Addiction. 2012;107:501–17.

    Article  PubMed  Google Scholar 

  8. 8.

    Marsch LA. The efficacy of methadone maintenance interventions in reducing illicit opiate use, HIV risk behavior and criminality: a meta-analysis. Addiction. 1998;93:515–32.

    Article  CAS  PubMed  Google Scholar 

  9. 9.

    Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;3:CD002209.

    PubMed  Google Scholar 

  10. 10.

    Chen YM, Kuo SH. HIV-1 in Taiwan. Lancet. 2007;369:623–5.

    Article  PubMed  Google Scholar 

  11. 11.

    Deck D, Carlson MJ. Retention in publicly funded methadone maintenance treatment in two Western States. J Behav Health Ser Res. 2005;32:43–60.

    Article  Google Scholar 

  12. 12.

    Deck D, Wiitala W, McFarland B, Campbell K, Mullooly J, Krupski A, et al. Medicaid coverage, methadone maintenance, and felony arrests: outcomes of opiate treatment in two states. J Addict Dis. 2009;28:89–102.

    PubMed Central  Article  PubMed  Google Scholar 

  13. 13.

    Skevington SM, Lotfy M, O’Connell KA. The World Health Organization’s WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. A report from the WHOQOL group. Qual Life Res. 2004;13:299–310.

    Article  CAS  PubMed  Google Scholar 

  14. 14.

    Wang PW, Wu HC, Yen CN, Yeh YC, Chung KS, Chang HC, et al. Change in quality of life and its predictors in heroin users receiving methadone maintenance treatment in Taiwan: an 18-month follow-up study. Am J Drug Alcohol Abuse. 2012;38:213–9.

    Article  PubMed  Google Scholar 

  15. 15.

    Astals M, Domingo-Salvany A, Buenaventura CC, Tato J, Vazquez JM, Martin-Santos R, et al. Impact of substance dependence and dual diagnosis on the quality of life of heroin users seeking treatment. Subst Use Misuse. 2008;43:612–32.

    Article  PubMed  Google Scholar 

  16. 16.

    Deng CF, Ma X, Zhou H, Liu QL, Yang Y, Song Z, et al. Quality of life of heroin dependent patients with methadone maintenance therapy. Sichuan Da Xue Xue Bao Yi Xue Ban. 2009;40:539–43.

    PubMed  Google Scholar 

  17. 17.

    Korthuis PT, Zephyrin LC, Fleishman JA, Saha S, Josephs JS, McGrath MM, et al. Health-related quality of life in HIV-infected patients: the role of substance use. AIDS Patient Care STDs. 2008;22:859–67.

    PubMed Central  Article  PubMed  Google Scholar 

  18. 18.

    Bangsberg DR, Hecht FM, Charlebois ED, Zolopa AR, Holodniy M, Sheiner L, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS. 2000;14:357–66.

    Article  CAS  PubMed  Google Scholar 

  19. 19.

    Low-Beer S, Yip B, O’Shaughnessy MV, Hogg RS, Montaner JS. Adherence to triple therapy and viral load response. J Acquir Immune Defic Syndr. 2000;23:360–1.

    Article  CAS  PubMed  Google Scholar 

  20. 20.

    McHutchison JG, Manns M, Patel K, Poynard T, Lindsay KL, Trepo C, et al. Adherence to combination therapy enhances sustained response in genotype-1-infected patients with chronic hepatitis C. Gastroenterology. 2002;123:1061–9.

    Article  CAS  PubMed  Google Scholar 

  21. 21.

    Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133:21–30.

    Article  CAS  PubMed  Google Scholar 

  22. 22.

    Yao G, Chung C-W, Yu C-F, Wang J-D. Development and verification of validity and reliability of the WHOQOL-BREF Taiwan version. J Formos Med Assoc. 2002;101:342–51.

    PubMed  Google Scholar 

  23. 23.

    Su C-T, Ng H-S, Yang A-L, Lin C-Y. Psychometric evaluation of the Short Form 36 Health Survey (SF-36) and the World Health Organization Quality of Life Scale Brief Version (WHOQOL-BREF) for patients with schizophrenia. Psychol Assess. 2014;26:980–9.

    Article  PubMed  Google Scholar 

  24. 24.

    Chang K-C, Wang J-D, Tang H-P, Cheng C-M, Lin C-Y. Psychometric evaluation using Rasch analysis of the WHOQOL-BREF in heroin-dependent people undergoing methadone maintenance treatment: further item validation. Health Qual Life Out. 2014;12:148.

    Article  Google Scholar 

  25. 25.

    Fu TS, Tuan Y-C, Yen M-Y, Wu W-H, Huang C-W, Chen W-T, et al. Psychometric properties of the world health organization quality of life assessment—brief in methadone patients: a validation study in northern Taiwan. Harm Reduct J. 2013;10:37.

    PubMed Central  Article  PubMed  Google Scholar 

  26. 26.

    The WHOQOL-Taiwan Group. Development of the World Health Organization Quality of Life Scale Brief Version, Taiwan version, and using manual. 2nd ed. Taipei: The WHOQOL-Taiwan Group; 2005.

    Google Scholar 

  27. 27.

    De Maeyer J, Vanderplasschen W, Broekaert E. Quality of life among opiate-dependent individuals: a review of the literature. Int J Drug Policy. 2010;21:364–80.

    Article  PubMed  Google Scholar 

  28. 28.

    Hser Y. Evaluation of drug abuse treatment. A repeated measures design assessing methadone maintenance. Evaluation Review. 1988;12:547–70.

    Article  Google Scholar 

  29. 29.

    Reno RR, Aiken LS. Life activities and life quality of heroin addicts in and out of methadone treatment. Int J Addict. 1993;28:211–32.

    CAS  PubMed  Google Scholar 

  30. 30.

    Gu J, Xu H, Lau JT, Hao Y, Zhong Y, Fan L, et al. Misconceptions predict prospectively dropout and poor adherence among newly admitted first-time methadone maintenance treatment clients in Guangzhou, China. Addiction. 2012;107:1641–9.

    Article  PubMed  Google Scholar 

  31. 31.

    Che Y, Assanangkornchai S, McNeil E, Li J, You J, Chongsuvivatwong V. Patterns of attendance in methadone maintenance treatment program in Yunnan Province, China. Am J Drug Alcohol Abuse. 2011;37:148–54.

    Article  PubMed  Google Scholar 

  32. 32.

    Esteban J, Gimeno C, Barril J, Aragonés A, Climent JM, Dela Cruz Pellín M. Survival study of opioid addicts in relation to its adherence to methadone maintenance treatment. Drug Alcohol Depend. 2003;70:193–200.

    Article  PubMed  Google Scholar 

  33. 33.

    Peles E, Schreiber S, Adelson M. Factors predicting retention in treatment: 10-year experience of a methadone maintenance treatment (MMT) clinic in Israel. Drug Alcohol Depend. 2006;82:211–7.

    Article  PubMed  Google Scholar 

  34. 34.

    Magura S, Nwakeze PC, Demsky S. Pre- and in-treatment predictors of retention in methadone treatment using survival analysis. Addiction. 1998;93:51–60.

    Article  CAS  PubMed  Google Scholar 

  35. 35.

    Tomori C, Go VF, Tuan LN, Huong NM, Binh NT, Zelaya CE, et al. "In their perception we are addicts": social vulnerabilities and sources of support for men released from drug treatment centers in Vietnam. Int J Drug Policy. 2014;25:897–904.

    PubMed Central  Article  PubMed  Google Scholar 

  36. 36.

    Ng MH, Chou JY, Chang TJ, Lee PC, Shao WC, Lin TY, et al. High prevalence but low awareness of hepatitis C virus infection among heroin users who received methadone maintenance therapy in Taiwan. Addict Behav. 2013;38:2089–93.

    Article  PubMed  Google Scholar 

  37. 37.

    Lee TS, Shen HC, Wu WH, Huang CW, Yen MY, Wang BE, et al. Clinical characteristics and risk behavior as a function of HIV status among heroin users enrolled in methadone treatment in northern Taiwan. Subst Abuse Treat Prev Policy. 2011;6:6.

    PubMed Central  Article  PubMed  Google Scholar 

  38. 38.

    Chang C-C, Su J-A, Tsai C-S, Yen C-F, Liu J-H, Lin C-Y. Rasch analysis suggested three unidimensional domains for Affiliate Stigma Scale: additional psychometric evaluation. J Clin Epidemiol 2015;doi:10.1016/j.jclinepi.2015.01.018.

  39. 39.

    Link BG, Struening EL, Rahav M, Phelan JC, Nuttbrock L. On stigma and its consequences: evidence from a longitudinal study of men with dual diagnoses of mental illness and substance abuse. J Health Soc Behav. 1997;38:177–90.

    Article  CAS  PubMed  Google Scholar 

  40. 40.

    Chang C-C, Wu T-H, Chen C-Y, Wang J-D, Lin C-Y. Psychometric evaluation of the Internalized Stigma of Mental Illness Scale for patients with mental illnesses: measurement invariance across time. PLoS One. 2014;9:e98786.

    Article  Google Scholar 

  41. 41.

    Wu T-H, Chang C-C, Chen C-Y, Wang J-D, Lin C-Y. Further psychometric evaluation of the Self-Stigma Scale-Short: measurement invariance across mental illness and gender. PLoS One. 2015;10:e0117592.

    PubMed Central  Article  PubMed  Google Scholar 

  42. 42.

    De Maeyer J, Vanderplasschen W, Broekaert E. Exploratory study on drug users’ perspectives on quality of life: more than health-related quality of life? Soc Indic Res. 2009;90:107–26.

    Article  Google Scholar 

Download references


This study was supported by grants DOH96-NNB-1032 and DOH98-NNB-1036 from the Taiwan Department of Health. This research was supported in part by (received funding from) the Headquarters of University Advancement at the National Cheng Kung University, which is sponsored by the Ministry of Education, Taiwan, ROC. The article processing charges for this article was funded by the following: United Nations Joint Programme on AIDS (UNAIDS); United Nations Office on Drugs and Crime (UNODC); World Bank Group; Open Society Foundations; Global Fund Against AIDS, Tuberculosis and Malaria; and World Health Organisation. The article has undergone the journal’s full standard peer-review process.

Author information



Corresponding author

Correspondence to Chung-Ying Lin.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

CK-C and LC-Y designed and conceptualized the study. LC-Y analyzed the data, and CK-C drafted the manuscript. LC-Y critically reviewed the manuscript. Both authors approved the final manuscript.

Authors’ information

CK-C is an attending psychiatrist in the Department of General Psychiatry, Jianan Psychiatric Center, Ministry of Health and Welfare. He is currently working on his PhD degree in the Department of Public Health, National Cheng Kung University, Tainan, Taiwan. His interest includes but not limited to exploring the patient-reported outcomes of drug abusers, examining the treatment effects for drug abusers, and some society issues raised by drug misuse.

LC-Y is a postdoctoral researcher in the Department of Public Health, National Cheng Kung University, Tainan, Taiwan. He also is an occupational therapist. His interests focus on the psychometric properties of several different patient-reported outcome measures and the use of patient-reported outcome measures on patients with mental illnesses.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chang, KC., Lin, CY. Effects of publicly funded and quality of life on attendance rate among methadone maintenance treatment patients in Taiwan: an 18-month follow-up study. Harm Reduct J 12, 40 (2015).

Download citation


  • Methadone maintenance treatment
  • Publicly funded
  • Quality of life
  • Self-paid
  • Substance abuse