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Men’s and women’s response to treatment and perceptions of outcomes in a randomized controlled trial… Palis, Heather; Marchand, Kirsten; Guh, Daphne; Brissette, Suzanne; Lock, Kurt; MacDonald, Scott; Harrison, Scott; Anis, Aslam H; Krausz, Michael; Marsh, David C; Schechter, Martin T; Oviedo-Joekes, Eugenia May 19, 2017

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RESEARCH Open AccessMen’s and women’s response to treatmentand perceptions of outcomes in arandomized controlled trial of injectableopioid assisted treatment for severe opioiduse disorderHeather Palis1,2, Kirsten Marchand1,2, Daphne Guh1, Suzanne Brissette3, Kurt Lock1, Scott MacDonald4,Scott Harrison4, Aslam H. Anis1, Michael Krausz5, David C. Marsh6, Martin T. Schechter1,2and Eugenia Oviedo-Joekes1,2*AbstractBackground: To test whether there are gender differences in treatment outcomes among patients receivinginjectable opioids for the treatment of long-term opioid-dependence. The study additionally explores whether menand women have different perceptions of treatment effectiveness.Methods: This study is a secondary analysis from SALOME, a double-blind, phase III, randomized controlled trialtesting the non-inferiorirty of injectable hydromorphone to injectable diacetylmorphine among 202 long-termstreet opioid injectors in Vancouver (Canada). Given this was a secondary analysis, no a priori power calaculationwas conducted. Differences in baseline characteristics and six-month treatment outcomes (illicit heroin use, opioiduse, crack cocaine use, non-legal activities, physical and psychological health scores, urine positive for street heroinmarkers, and retention) were analysed by gender using fitted models. Responses to an open ended question onreasons for treatment effectiveness were explored with a thematic analysis.Results: Men and women differed significantly on a number of characteristics at baseline. For example, women weresignificantly younger, presented to treatment with significantly higher rates of prior month sex work (31.5% vs. 0%),and used significantly more crack cocaine (14.71 vs. 8.38 days). After six-months of treatment there were no significantdifferences in treatment outcomes by gender, after adjusting for baseline values. For both men and women, improvedhealth and quality of life were the most common reasons provided for treatment effectiveness, however women weremore specific in the types of health improvements.(Continued on next page)* Correspondence: eugenia@cheos.ubc.ca1Centre for Health Evaluation & Outcome Sciences, Providence Health Care,St. Paul’s Hospital, 575- 1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada2School of Population and Public Health, University of British Columbia, 2206East Mall, Vancouver, BC V6T 1Z3, CanadaFull list of author information is available at the end of the article© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (, which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe 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.Palis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 DOI 10.1186/s13011-017-0110-9(Continued from previous page)Conclusions: Despite presenting to treatment with vulnerabilities not faced to the same extent by men, at six-monthswomen did not differ significantly from men in tested trial efficacy outcomes. While the primary outcome in the trialwas the reduction of illicit opioid use, in the open-ended responses both men and women focused their commentson improvement in health and quality of life as reasons for treatment effectiveness. The supervised model of care withinjectable medications provides a particularly suitable framework for providing care to opioid-dependent men andwomen not attracted or retained by other treatments. The absence of statistical differences reported in this secondaryanalysis may be due to lack of adequate statistical power to detect meaningful effects.Trial registration: This trial is registered with (NCT01447212) Registered: October 4, 2011 at thefollowing link: Opioid-dependence, Gender, Clinical trial, Patient perceptionsBackgroundOpioid-use disorder is a chronic relapsing conditioncharacterized by patterns of continued illicit drug use,periods of treatment, abstinence from street opioids, andrelapse, with a number of associated harms to the indi-vidual and to the community [1, 2]. Data on opioid usedisorder has shown this chronic condition to be moreprevalent among men than among women, and as such,conclusions derived primarily from the experiences ofmen are often extrapolated to women [3, 4]. Studies ofopioid-dependence consistently suggest that there arefew (although inconsistent) or no gender differences intreatment outcomes [5–9]. Nevertheless, in studies ofopioid use disorder, women are consistently found to befaced with elevated exposure to social and medicalvulnerabilities associated with their substance use, suf-fering more severe emotional and physical symptoms ascompared to men [6, 10–12].The concept of gender refers to the socially constructedbounds of being a “female” or a “male” in a society, and islinked to the social and political context [13, 14]. These so-cially constructed conceptions of gender and gender rolesinfluence human interactions, behaviours, and conceptionsof the physical body, ultimately producing gender identities[14]. Gender based analyses aim to assess potential differ-ences in treatment outcomes for men and women, and toidentify the possible impact of policies and programs inrelation to these differences [14].Studies that have investigated gender differences in sub-stance use treatment outcomes such as retention suggestfew or no differences [6, 15]. However, gender basedanalysis of outcomes among patients receiving injectabletreatments are limited, with only two studies [9, 16]. Forexample, the North American Opiate Medication Initiative(NAOMI) clinical trial compared supervised injectable di-acetylmorphine (pharmaceutical grade heroin) (DAM) withoral methadone maintenance treatment (MMT) amonglong-term opioid injectors in Vancouver and Montreal(Canada). In NAOMI, overall treatment retention rates didnot differ for women (64.8%) and men (75.4%). Further,among participants receiving DAM there were no signifi-cant gender differences in drug use or illegal activities [17].These findings indicated that among long-term opioiddependent women not benefiting from available treat-ments, DAM was more effective than MMT.It is pivotal to ground a discussion of men’s andwomen’s experiences of injectable opioid assisted treat-ment in the broader literature on structural vulnerability.Structural vulnerability refers to an individual’s conditionof being at risk of negative outcomes, through theirposition in relation to socioeconomic, political, andcultural normative hierarchies [18, 19]. Women presentto opioid assisted treatment with a number of vulner-abilities, for example, lower rates of education, moreprevalent histories of sexual abuse, higher rates of infec-tious disease, higher suicide rates, higher rates of crackcocaine use, sex work, and mental distress [4, 9, 16, 20].These vulnerabilities are a product of a number ofattributes, including gender [21].The present study was conducted with a sample of long-term opioid dependent women and men who were en-rolled in a unique model of care, receiving injectable opioidassisted treatment. Under this model of care, participantsreceived injectable medications under the supervision ofregistered nurses. This daily contact allows the opportunityfor comprehensive care, attending to the many complexneeds of the patients, thereby optimizing the provision ofservices that are in line with the construct of patient cen-tered care, where the needs of the patients are prioritized.A patient centered approach allows for the social positionsof patients to be recognized, and for the promotion ofcultural safety, both of which are more recent dimensionsof patient centered care being considered in the delivery ofservices for marginalized groups [22–24]. Such an ap-proach accounts for components of a patient’s position,including race, gender, sexuality, and socioeconomic status,so that treatments are responsive to the unique circum-stances with which patients experience care [25].In most clinical trials, patient outcome assessmentsare developed by clinicians and researchers and tend toPalis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 2 of 12neglect the perspectives of patients [26]. This is of con-cern, given the evidence suggesting that among patientsreceiving treatments for substance dependence, concep-tions of treatment effectiveness may differ greatly fromthose of clinicians and researchers [27, 28]. As such,there has been an increasing interest in collectingpatient perceptions of treatment outcomes. The presentstudy aims to 1) determine whether men and womendiffer in their response to treatment and; 2) to ex-plore men’s and women’s perceptions of treatmenteffectiveness.MethodsSetting, participants, study designThe Study to Assess Longer Term Opioid MedicationEffectiveness (SALOME) was a phase III, double blind clin-ical trial testing the non-inferiority of hydromorphone(HDM) to diacetylmorphine (DAM) for the treatment oflong-term opioid-dependence. Long-term injection opioidusers who were not sufficiently benefitting from avail-able treatments (i.e. continuing to inject illicit opioids)were recruited from the Lower Mainland of BritishColumbia, with most residing in the Downtown Eastsideof Vancouver. Applicants were excluded if they werepregnant, or planning on becoming pregnant, had animminent period of extended incarceration, or had severemedical conditions contraindicated for treatment withDAM or HDM (e.g. respiratory problems).Participants were randomly assigned to receive inject-able diacetylmorphine (n = 102) or hydromorphone(n = 100) for six months. These medications were deliv-ered under a “supervised model of care”, whereby regis-tered nurses supervised participants’ self-administrationof injectable opioids at the study site up to three timesper day. The supervised model of care operates withthree main objectives: 1) keeping patients and the com-munity safe by providing pharmaceutical-grade inject-able opioids under supervision (e.g. for prompt responsein case of an overdose) and keeping the medicationsonsite (to minimize the potential risk to others); 2)Building relationships with patients that foster trustthrough daily interactions; and 3) providing opportun-ities for comprehensive care. In SALOME, medicationswere provided at up to 400 mg per dose, and up to1000 mg per day [29]. Participants could adjust the doseand frequency of sessions in consultation with theirphysician. Doses were titrated individually in order toachieve a safe and effective dose for each participant.Doses were determined over a 3-day titration phase bythe participant and the nurse. In rare cases a slowertitration process was used based on the participantprior clinical experience or medical history [29]. Inconsultation with the study physician, participantscould add oral methadone to their care at any time.Additional details on the participant profile, screeningprocedures, study design and main results have beenpublished elsewhere [29–31].Study measuresAt baseline, prior to randomization, participants com-pleted questions on a series of standardized instrumentson topics such as drug use, and physical and psychologicalhealth [32, 33]. Treatment outcomes were self-reportedwith the exception of urinalyses, and were collected at6 months. Outcomes assessed included days of illicitheroin use, days of any illicit opioid use, days of non-legalactivities, days of crack cocaine use, the proportion ofurine samples positive for street heroin markers, theproportion of participants receiving treatment 28 daysor more in the prior month (retention), and measuresof physical and psychological health collected withthe Maudsley Addiction Profile [32]. Adverse eventswere recorded as described in further detail in themain SALOME trial results [29] and classified withMedDRA codes. Given this is a secondary analysis from anon-inferiority clinical trial testing two medications indouble blind conditions, there was no a priori powercalculation for the present analysis testing differencesin outcomes by gender.Data on perceptions of why the treatment is effectivecome from one interviewer-administered questionnaireconducted in reference to the first 6 months of treat-ment. As part of the questionnaire assessing blinding,participants were first asked: “Do you think this treat-ment was effective?” Participants could respond, “yes”,“no”, or “unsure”. Participants then provided open-ended responses to the question “why do you think thistreatment was/was not effective?” In a clinical trial, pro-tection of the blinding, and the collection of primaryoutcome data are prioritized [34]. Therefore, as to notinterfere with the clinical trial findings participants werenot prompted to provide an in-depth response. Instead,the interviewer posed the question and then recordedthe participant’s verbatim response. Responses rangedfrom a few words to a few sentences. While this doesnot provide in-depth qualitative data, it provides novelinformation, and a perspective on treatment effective-ness not typically captured in the context of stringentrandomized controlled trials.Statistical analysesBaseline characteristics were tested by gender using Chi-Square tests and Student’s t tests. At six months, differ-ences between men and women were tested on eightoutcome variables. Outcome variables were continuous(number of days in the prior month for illicit heroin use,any illicit opioid use, involvement in non-legal activity,crack cocaine use; MAP physical health score, and MAPPalis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 3 of 12psychological health score) and as proportions (urinepositive for street heroin markers, and at least 28 daysretention in treatment in the prior 30 days).A separate model was fitted for each outcome, asdependent variables, for the differences between womenand men. At six-months, there were a high proportionof participants reporting zero days in reference to prior30 day illicit heroin use, illicit opioid use, non-legalactivity, and crack cocaine use. As such, zero inflatedpoisson regression was used for these outcomes, giventhis model allows for the excess zeros, which cannot bepredicted by the standard poisson model [35]. Thesedata are presented as the mean difference (with confi-dence interval) in the number of days at six-months.Linear regression was performed for the physical andpsychological health variables, showing mean differencewith confidence intervals. Finally, odd ratios were calcu-lated using a logistic regression for the urine positivemarkers and retention variables.All models were adjusted for treatment arm and theaverage daily dose. Models were also adjusted for base-line values using analysis of covariance (ANCOVA) toaccount for gender difference at baseline [36]. This iswith the exception of the retention variable, and urinepositive for street heroin markers (there is no baselinevalue for retention, and as per inclusion criteria allpatients had urine positive for street opioids at baseline).For zero-inflated Poisson models, we compared themodel fit with ordinary Poisson regression. For the logis-tic regression model and multiple regression models,goodness-of-fit was assessed by comparing to the nullmodel. Residuals were also examined to identify potentialoutliers or misspecified models.There were 4 missed assessments at 6 months (2 de-ceased, 1 missed visit, and 1 lost to follow-up). Missingvalues were imputed with multiple imputation, exceptwhen data were missing due to death, thus avoidingassigning a score to a deceased participant [37].Types of non-legal activities and sources of income, formen and women at baseline and at six-months wereexplored using descriptive analysis. At each time point,differences between men and women in prior month legal,non-legal, and total sources of income were tested usingWilcoxon Rank Sum Tests. Differences in the proportionand days of non-legal activities were tested by genderusing Chi-Square tests and Student’s t tests. Thesedescriptive data are presented in Tables 3 and 4. Allstatistical analyses were conducted using SAS 9.4 [38].Two-sided tests were used with a significance level of 0.05.Thematic analysis of open-ended commentsThematic analysis of participant perceptions of treat-ment effectiveness was conducted. Two of the authorsindependently coded the transcripts (HP and KM). Aninductive approach was taken with each comment assigneda code based on its semantic content. Themes and rela-tionships across all participants’ comments were developedusing the strategy of constant comparison [39]. After initialindependent coding, the authors (HP and KM) met todiscuss and review the initial list of themes. Themes werethen further refined to ensure congruency between thecontent and the assigned theme (HP, KM, and EOJ).Analysis of open-ended comments was conducted usingNVivo software [40].Women’s and men’s perceptions of treatment effect-iveness were analysed together, rather than separately.Coders were blinded as to the gender of participants.Once the stages of coding were complete the number ofwomen and number of men making a reference to eachtheme was recorded. It is possible that one participantmade more than one reference at a given theme. Assuch, data presented are the number of participants thathave at least one reference coded in a given category.This ensures themes are not overinflated by one particu-lar participant’s references, and allows for the compari-son of the total number of women compared to menthat made a reference.ResultsOf the 202 SALOME participants, 62 self-identified aswomen (including 3 transgender participants identifyingas women), and 140 self-identified as men. At baseline,men and women differed on various socio-demographic,health, drug use, and treatment variables. Women weresignificantly younger than men . There were a significantlyhigher proportion of women self-identifying as Indigen-ous, and a significantly higher proportion of women com-pared to men that had ever been paid in exchange for sex.Men reported significantly more months incarcerated inlifetime. Women reported significantly higher symptomson the Maudsley Addiction Profile (MAP) physical andpsychological health scores, indicating poorer baselinehealth compared to men. There were nearly double theproportion of women with HIV compared to men, andwomen reported smoking significantly more days of crackcocaine in the prior month compared to men. Men andwomen reported similar patterns of prior month heroinand illicit opioid use (Table 1).Regarding 6-month treatment outcomes, after adjustingfor baseline values, dose, and treatment arm, there wereno differences found between men and women, with theexception of psychological health, where women’s healthat 6 months was significantly better than that of men:mean difference: -2.39 (95% CI: -4.72, −0.07) (Table 2).There were no significant differences between menand women in in the number of related adverse eventsor proportion of participants with at least one relatedevent in the DAM arm, nor in the HDM arm. The samePalis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 4 of 12results were found regarding related immediate post-injection reaction or injection site pruritus, somnolence,serious adverse events and opioid overdoses that re-quired the use of naloxone. In the DAM arm, womenhad a lower dose than men. None of the potentialexplanatory factors tested were significant, nor providedexplanation for the difference between men and womenin psychological health (i.e. differences persisted evenafter adjusting for baseline values, dose, and treatmentarm, and exploring adverse events by gender).There were no significant differences between menand women in prior month income from non-legal,legal, or total sources at baseline nor at six-months(Table 3). Among both men and women, over 70% oflegal income at baseline and at six-months came fromincome assistance. Days of involvement in sex work,drug dealing and property theft are presented in Table 4.There were a higher proportion of men involved in drugdealing compared to women, both at baseline and at six-months. At baseline, 90.00% of women and 87.50% ofmen that engaged in drug dealing, did so to supporttheir own use, rather than for income. The proportion ofmen and women engaged in property theft were 15.71%and 17.74% respectively at baseline and 5.71% and 4.84%at six months. The proportion of participants involvedin sex work was significantly different between men andwomen at baseline (0% vs. 30.65%) and six months(1.43% vs. 20.97%).Of the 202 participants, 191 participants (132 men,and 59 women) gave a response as to why they thoughtthe treatment was or was not effective (yes, no, orunsure). Among the 11 missing respondents, 4 did notcomplete the 6-month interview, and 7 did not completethis question. Among those seven participants that didnot complete this question, three were women and fourwere men. In response to the question of whether thetreatment was effective these participants responded; yes(n = 4); unsure (n = 1); missing (n = 2).Table 1 Baseline socio-demographic, health, drug use and treatment profile of SALOME participants by genderTotalN = 202WomenN = 62MenN = 140Socio-demographicsAge* 44.33 ± 9.63 40.66 ± 9.34 45.95 ± 9.34Currently has an intimate partner* 74 (36.63) 32 (51.61) 42 (30.00)Self- identify as Indigenousa* 62 (30.69) 29 (46.77) 33 (23.57)High school certificate or higher 108 (53.47) 31 (50.00) 77 (55.00)Any non-stable housing in prior 3 yearsb 141 (69.80) 38 (61.29) 103 (73.57)Paid in exchange for sex in the prior month 20(9.90) 19 (30.65) 0(0)Ever paid in exchange for sex* 83 (41.09) 52 (83.87) 31 (22.14)Months ever incarcerated*c 10 [1–36] 2 [0–6] 18 [3–60]Days of non-legal activities in prior monthd 14.15 ± 13.71 14.98 ± 13.59 13.79 ± 13.79HealthHIV Positive* 30 (14.85) 14 (22.58) 16 (11.43)MAP Physical Health Scoree* 12.17 ± 8.01 14.92 ± 9.12 10.92 ± 7.15MAP Psychological Health Scoree* 9.40 ± 8.97 12.35 ± 10.56 8.05 ± 7.83Drug Use and TreatmentDays using any illicit opioids 27.95 ± 4.19 28.15 ± 4.48 27.86 ± 4.07Heroin, injection 25.38 ± 7.99 25.84 ± 7.69 25.18 ± 8.14Times of heroin use on a typical day 3.40 ± 2.59 3.73 ± 2.50 3.26 ± 2.62Crack cocaine, smoked* 10.32 ± 12.72 14.71 ± 13.62 8.38 ± 11.83Times attempted MMT in prior 5 yearsf 2.81 ± 2.09 3.06 ± 2.10 2.69 ± 2.09*Indicates significance below p < 0.05Plus minus values (±) indicate mean and standard deviation; Values in parentheses indicate number (n) and percentage (%); Values in brackets represent medianand interquartile range (Q1–Q3). Statistics are p values for a t-test or chi-square test:SD Standard Deviation, MAP Maudsley Addiction Profile, HIV Human Immunodeficiency Virus, MMT Methadone Maintenance TreatmentaIndigenous Ancestry refers to the self-report of any Inuit, Metis or, First Nations AncestrybNon-stable housing refers to living in single resident occupancy hotel rooms with restrictions, couch surfing, outdoors, vehicles, or in public placescData are zero saturated and heavily skewed. As such, median and interquartile ranges are presenteddDays of non-legal activities is a measured as a sum of the number of days in the prior month engaged in any of: dealing of drugs, property theft, violence, dis-orderly conduct, sex work, major driving violations, and broken conditions imposed by the legal systemeMAP scores range from 0 to 40; higher scores indicate poorer physical or psychological healthfData come from PhamaNet, British Columbia’s Provincial pharmacy dispensation databasePalis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 5 of 12Table 2 Treatment outcomes by gender at six monthsOutcomes at six months WomenN = 62MenN = 140Women vs. MenN = 202Street opioid useDays illicit heroin usea 3.69 (2.08, 5.52) 3.84 (2.54, 5.27) −0.15 (−2.16, 1.98)Days illicit opioid usea 5.28 (3.18, 7.59) 4.84 (3.43, 6.26) 0.44 (−1.93, 3.17)Proportion of urine positive for street heroin markersc 0.27 (0.18, 0.40) 0.25 (0.16, 0.35) OR1.16 (0.53, 2.51)Retention in treatmentProportion of participants receiving treatment ≥28 daysc 0.83 (0.72, 0.91) 0.79 (0.71, 0.85) OR1.34 (0.62, 2.87)MAP health symptom scoresPhysical healthb 12.29 (10.43, 14.15) 11.37 (10.07, 12.67) 0.92 (−1.38, 3.23)Psychological health*b 6.95 (5.01, 8.90) 9.35 (8.01, 10.69) −2.39 (−4.72, −0.07)Other outcomesDays of non-legal activitya 3.61 (1.61, 5.90) 3.14 (1.86, 4.53) 0.47 (−1.82, 3.14)Days of crack cocaine usea 7.10 (4.70, 9.76) 5.16 (3.26, 7.62) 1.95 (−0.08, 4.28)*Indicates significance below p < 0.05Differences in proportions (urine positive and retention) are presented as odds ratios (OR). For all other variables mean difference in days or scores are presented.Both proportions and means are presented with 95% confidence intervals in bracketsAll models were adjusted for treatment arm and the average daily dose. Models were also adjusted for baseline values using analysis of covariance (ANCOVA) toaccount for gender difference at baseline. This is with the exception of the retention variable, and urine positive for street heroin markers (there is no baselinevalue for retention, and as per inclusion criteria all patients had urine positive for street opioids at baseline)aContinuous outcomes with an excess of zero counts: Zero-inflated Poisson regression was used. Adjusted mean difference between the two gender groups andconfidence intervals were estimated by the Bootstrap methodbContinuous outcomes: Linear regression models were used to estimate the mean difference and 95% CIcBinary outcomes: Logistic regression was used to estimate odds ratios and 95% CIs to compare the proportions between groupsTable 3 Prior Month Income from Legal, Non-Legal, and Total Sources by genderSource of income WomenN = 62MenN = 140N(%) Median (IQR) N(%) Median (IQR)BaselineNon-legal 45 (72.58) 2000.00(800.00, 4600.00)86 (61.43) 1750.00(500.00, 4000.00)Legal 61 (98.39) 1111.00(850.00, 1400.00)140 (100.00) 1150.00(900.00, 1587.50)Total 62 (100.00) 2282.50(1400.00, 4200.00)140 (100.00) 2115.50(1487.50, 4022.00)Six-monthsNon-legal 23 (37.10) 1000.00(500.00, 1500.00)38 (27.94) 1500.00(250.00, 3000.00)Legal 60 (96.77) 1080.00(836.00, 1300.00)135 (96.43) 1100.00(906.00, 1330.00)Total 62 (100.00) 1300.00(960.00, 2120.00)136 (100.00) 1200.00(957.50, 1955.00)Medians are in Canadian Dollars. IQR = Interquartile Range. Medians and IQR data is presented for women and men reporting at least one dollar of income ineach sourceLegal Sources: Employment, Income Assistance, Pension, Disability, Money from partner, family or friendsNon-legal Sources: Drug dealing, property theft, and sex workThere were no significant differences found between men and women in regards to baseline or six-month non-legal, legal, or total incomePalis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 6 of 12Among all 191 respondents, 175 (91.62%) thought thetreatment was effective, 10 (5.23%) thought the treat-ment was not effective, and 6 (3.14%) were unsure. Atotal of 436 references were coded among 191 partici-pants. Each of the participants that thought the treat-ment was not effective (n = 10) gave one of thefollowing reasons: negative side effects, withdrawalsymptoms, or craving. Each of the participants that wereunsure gave statements about both negative (e.g. sideeffects) and positive aspects (e.g. reduced street use) ofthe treatment (n = 6).Seven themes emerged for reasons participants perceivedthe treatment to be effective (Table 5). The most com-monly referenced themes were improved health andimproved quality of life, followed by stopped or reducedstreet drug use and stopped or reduced non-legal activities.Participants also discussed reduced craving or withdrawal,spending money on things other than drugs, and aspectsof the model of care in which the treatments are delivered.Many participants made statements about the mul-tiple components of their health and quality of life thatwere bettered by the treatment. Men gave more generalstatements such as “My health is better”, while womengenerally explained in more depth what better healthmeant for them:“Everything in my life has changed, I have housing now,I eat every day, I'm sleeping better, I am way healthier,less stressed. I have a cat now that I spayed andvaccinated and take care of - I haven't had a pet in 10years because I was too all over the place mentally. Ialso have regained my relationship with my mom, mysiblings, my kids, my partner. I was so wrapped up inaddiction that I became a non-person. Now I'm wokenup. I'm back.” (Participant 6089, Gender: Woman)Men and women similarly referenced general improve-ments in lifestyle and social life as components of qualityof life. Men however were more likely to reference nothaving to “hustle” (“Nice not to have to get up and runthe race every day”) and women were more likely to ref-erence not having to do sex work (“Before, I worked (sexwork)… now I don't have to do it anymore”). Many of thestatements made touched on multiple components ofhealth and lifestyle:“I am very content with what I'm getting and thewhole program. It's given me time to reflect on things Iwas too busy to reflect on before. Being wired is a fullTable 4 Self-reported involvement in non-legal activities by gender at baseline and six-monthsWomenN = 62MenN = 140Type of Activity N(%)a Days in prior 30b N(%)a Days in prior 30bBaselineDrug Dealing 23 (37.10) 22.04 ± 10.42 67 (47.86) 21.10 ± 11.10Property Theft 11 (17.74) 15.27 ± 13.09 22 (15.71) 18.64 ± 12.30Sex Work 19 (30.65)* 14.21 ± 10.13 0 (0) 0Six-monthsDrug Dealing 10 (16.13) 15.00 ± 11.68 27 (19.29) 17.04 ± 11.64Property Theft 3 (4.84) 14.67 ± 6.11 8 (5.71) 7.75 ± 9.56Sex Work 13 (20.97)* 11.46 ± 10.49 2 (1.43) 11.00 ± 1.41*Indicates significance below p < 0.05 Plus minus values (±) indicate mean and standard deviation; Values in parentheses indicate number (n) and percentage (%);Column presents the proportion of women or men reporting one or more days in the prior 30 days engaging in each of the corresponding listed activitiesaColumn presents the average number of days in the prior 30 days engaged in each of the corresponding listed activities, among those reporting at least 1 day incolumn (a)bColumn presents the proportion of men and proportion of women reporting one or more days in the prior 30 days engaging in each of the correspondinglisted activitiesTable 5 Participant reasons for Treatment EffectivenessThemes TotalN = 191N (%)WomenN = 59N (%)MenN = 132N (%)Improved Health 79 (41.36) 23 (38.98) 56 (42.42)Improved Quality of Life 64 (33.5) 19 (32.20) 45 (34.09)Stopped or reduced street use 57 (29.84) 16 (27.12) 41 (31.06)Stopped or reduced non-legal activity 41 (21.47) 8 (13.56) 33 (25.00)Reduced craving or withdrawal 39 (20.42) 14 (23.73) 25 (18.94)Spending money on things otherthan drugs24 (12.57) 7 (11.86) 17 (12.88)Model of Care 24 (11.88) 5 (8.47) 19 (14.39)Responses arise from an open-ended questions asked of participants after6 months of treatmentThemes are listed in order of frequencyResponses are in reference to the treatment participants thought they werereceiving after the first 6 months of treatment (treatment was blinded)Columns refer to the number of participants (total, women, men) that made areference at a given theme and the percent referencing a given theme out ofall participants (total, women, men) that provided a response. (e.g. forImproved Health: Total = 79/191 = 41.36%;Women = 23/59 = 39.98%; Men = 56/132 = 42.42%)Palis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 7 of 12time job. Getting the coin, scoring, enjoying the high:it consumes a big part of your day. Now, I have moretime, and I'm finding more things to do that I like,like cycling. I'm helping one of the other participantsbecome a better reader. Hanging out with friends,playing pool.” (Participant 6125, Gender: Man)Men’s descriptions tended to include statements aboutreducing or stopping criminal involvement. Men speci-fied reduced theft, dealing, and worries of going to jail,while only two women made such specific references.Women and men similarly referenced stopping or redu-cing street drug use, mostly referring to opioid use.“I'm taking care of business now, getting my life ontrack, of course my money situation has improved,healthier now, I was doing crime before, and nowthere's no need for money, for doing whatever to getmoney, I have a choice now, and I choose to do hardlyany crime”. (Participant 6201, Gender: Man)“I am not needing to score as often as I used to… I amless desperate.” (Participant 6046, Gender:Transgender Woman)“I had no craving, no desire to go out and use, I havea chance at a normal life. Salome is crazy good! Itworks.” (Participant 6020, Gender: Woman)“It is the first time I have been totally clean of streetheroin. It really feels like the difference between lifeand death.”(Participant 6065, Gender: Man)Both women and men referenced the fact that themedication reduces cravings and symptoms of with-drawal as a reason for treatment effectiveness. Whilemen and women referenced improved financial situ-ation, men tended to make more comments on spendingmoney on things other than drugs as compared towomen. Comments made included statements like: “Istill have money at the end of the month”, or “I ownthings again, I am not spending it all on dope.” and“Hardly spend money on drugs, spend it all on food”.Men and women had similar descriptions surroundingthe model of care as a reason for treatment effectiveness.These comments reflect that the model allowed for indi-vidualized care, that it provided structure and security,and it is less stigmatizing than other models.“I haven't used street heroin since study started; I amon injectable and that's a big part of the addiction.[The program] offers a routine, a security blanket,don't need to worry anymore. It's changed my wholethinking” (Participant 6028, Gender: Man).DiscussionFindings of the present study were consistent with theexisting literature on treatment outcomes among menand women receiving injectable opioid assisted treatmentsfor severe opioid use disorder [8, 9]. Overall, no significantdifferences were found by gender in the tested efficacyoutcomes. This finding is particularly relevant consideringwomen presented to treatment with vulnerabilities notfaced to the same extent by men. The supervised model ofcare with medically-prescribed injectable opioids aims toreach and treat individuals that, despite other options be-ing available, continue injecting opioids in the street. Thestudy participants presented to treatment after many yearsof injecting street opioids, with more than half of themreporting having a chronic condition that interferes withtheir daily lives, as well as histories of incarceration, sexwork, and homelessness [31]. While SALOME partici-pants represent the most vulnerable population of long-term street opioid-injection users, women face particularvulnerabilities and as such, it is important to determinewhether this treatment engages and retains them intotreatment as well as men.After six months of treatment, no significant differencesbetween men and women were found in days of illicit her-oin use, illicit opioid use, nor proportion of urine positivefor street heroin markers. A similar proportion of menand women were retained at six-months (approximately80% had received treatment at least 28 days in the prior30). Men and women reported a similar number of daysusing crack cocaine and involved in non-legal activity.While there were no significant differences in physicalhealth scores, women’s psychological health scores weresignificantly better than men’s, after adjusting for baselinevalues, dose, and treatment arm. This is similar to findingsin the NAOMI trial, where women in the DAM arm hadsignificantly better psychological health scores thanwomen in the methadone maintenance treatment arm, yetthis difference was not seen in men [17].While men and women did not differ in terms of daysof overall involvement in non-legal activities, there weregender differences when looking into the specific typesof activities. For example, at both baseline and six-months significantly more women were involved in sexwork as compared to men. Interestingly, the proportionof women engaged in sex work was not reduced signifi-cantly from baseline to six-months. While we are limitedin our analysis and conclusions due to the small samplesize, continued involvement in sex work presents aparticular vulnerability, with potential implications forpatterns of street drug use and health outcomes. In aprior clinical trial with a similar population, women en-gaged in sex work were more likely to continue injectingin the street and using cocaine. Also, women who wereretained were less likely to be involved in sex work [41].Palis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 8 of 12With such a high retention rate at six months forwomen receiving injectable treatment in SALOME(83%), there is a compelling case to make to offer thistreatment to women that continue injecting in the streetdespite other treatment options being available. Accessto injectable medications can provide a starting point toreconnect with the health care system, and work withpatients to meet their individual needs. The supervisedmodel of care is a bundle, meaning that every participantis offered all services available at the clinic. Participantsare connected with services inside and outside of theclinic, based on their needs and willingness. Engagingwith the clinic services up to three times a day for themedication provides nurses and health care allies oppor-tunities to engage with the patients, to meet them wherethey are at, and to respond to particular vulnerabilitiesfaced by patients in a timely manner.This study also investigated participants’ reasons fortreatment effectiveness. Prior studies suggest that distinctperceptions of treatment outcomes and effectiveness canbe determined with gender-specific analyses. For example,a study of treatment outcomes among offenders in a resi-dential substance use treatment program showed thatmen and women had differing perceptions of treatment,and emphasized the importance of considering percep-tions of outcomes to best understand treatment needs[42]. Further, among a sample of long-term opioiddependent men and women in Vancouver, Canada, it wasfound that despite reporting similar treatment satisfactionscores, men and women had distinct perceptions of thepositive aspects of treatment [43]. This evidence supportsthe added value of including open-ended questions tocomplement quantitative outcomes in studies of treatmenteffectiveness.Our study found seven major themes. A similar pro-portion of men and women made references to each ofthese themes. There were however, particular nuances inthe way in which men and women spoke about each ofthe themes. For example, women’s comments surround-ing improvements in health and quality of life weremuch more descriptive than men’s. Women’s commentsranged from references to personal growth and stability,to physical well-being and improvements in their sociallives. Better health for women meant rebuilding relation-ships with family members, stronger self-connection,and better self-care in ways in which they saw tangibleimprovements (e.g. better nutrition leading to weightgain). These descriptions suggest that this treatment isparticularly impactful for women’s health.Men made comments about reducing or stopping non-legal activities while receiving the treatment. A significantreduction in non-legal activities is a consistent outcomeamong studies of injectable opioid assisted treatment [29,44, 45]. This positive outcome is evident in the men’scomments surrounding reductions in crime, describing re-duced worry about arrest, no longer having the diffi-culty of engaging in the daily “hustle” to attain drugs,and freeing time in their day to engage in othermeaningful activities. Although men and women hadno differences in the reduction in the number of daysengaged in non-legal activities, this study shows thisoutcome to be particularly relevant for men, accord-ing to their comments.Before starting treatment with injectable opioids, it ispossible that the medication itself (i.e. pharmaceuticalgrade heroin) is the most attractive component of carefor the participant [46]. In a prior clinical trial it wasfound that many participants were drawn to the treat-ment just because of the possibility of receiving pharma-ceutical grade heroin [47]. However, in the presentstudy, when participants were asked why the treatmentwas effective for them, there was not a strong emphasis onthe medication itself as a reason for treatment effectiveness.When participants made comments about the medicationthey were general (e.g. “I am not dope sick” or “no with-drawal”). Instead, statements surrounding treatment effect-iveness were primarily derived from comments aboutimprovements made in various aspects of the participants’lives that have been positively impacted by the treatmentand services they had received. These descriptions wereabout health and quality of life, areas that participants wereable to focus on given access to an effective medication.These findings are consistent with those of The Experi-mental Narcotics Prescription Programme in Andalusia(PEPSA), a clinical trial of heroin-assisted treatment inSpain. This study found that when heroin, a substancetypically obtained non-legally was medically prescribedthere was a shift in the significance given to the substanceitself [48]. Once the program took care of the injectablemedication, many other needs beyond the medicationbecame evident [49] allowing for participants to focus onimprovements in physical and mental health, familyrelations, and employment.In the present study, the men’s and women’s accounts ofreasons for treatment effectiveness are in line with the ideathat once participants were provided with access to themedication they were dependent on (i.e. physical treatmentneeds were met), they regained meaningful space and timeto focus on other aspects of their lives. The recognition thatpatients’ needs may broaden throughout the course oftreatment suggests that the treatment system must be pre-pared to respond to these needs, in a way that is flexibleand reactive to the patient and their progress. Prior studieson patients receiving injectable opioids under supervisionsuggest that engaging patients in research regarding theirperceptions of treatment (e.g. treatment expectations, treat-ment effectiveness) can provide a comprehensive assess-ment of treatment challenges and treatment needs in orderPalis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 9 of 12to optimize the treatment received as they progress throughtreatment [50, 51].In the present study, participants were asked to share theirperceptions of treatment effectiveness. Evidence suggeststhat providing patients with the opportunity to discuss andshare their perceptions of their treatment outcomes and ef-fectiveness can serve as a source of empowerment [52, 53].This is particularly relevant to shifting away from traditionalpaternalistic approaches to the provision of health careservices, to a system more focused on patient autonomy,shared decision making and patient satisfaction [54]. Involv-ing patients in the stages of outcomes research can work toenrich the scope with which researchers assess outcomes,can promote patient knowledge, and can contribute to aninformed dialogue between patients and their health careproviders [54]. Future clinical trials should consider the inte-gration of similar open-ended questions on patient percep-tions of treatment effectiveness to achieve these benefits.There are several limitations that must be recognized.Given the nature of the study design, we are limited in ourability to observe more gender specific aspects of treatmentbeyond that of efficacy. Although we found that women inthe DAM arm used a daily and average dose significantlylower than men, none of the potential explanatory factorstested were significant, nor provided explanation for thisdifference. It is important to note that doses were individu-ally titrated, that overall there were no gender differences intreatment outcomes and that women were not more likelythan men to correctly guess the treatment assignment [34].As such, it is possible that there is some unobserved vari-able driving this difference in dose, or that the sample sizeis too small to detect an effect. Data on participant percep-tions of treatment effectiveness were collected while partici-pants continued to receive blinded medication. This limitedthe depth of qualitative data that could be collected on per-ceptions of treatment effectiveness, as the collection of pri-mary outcome data and protection of the blinding had tobe prioritized. Finally, three participants self-identified astransgender women, and were included in the analysis aswomen. We recognize that transgender people face uniquestructural vulnerabilities, however with such a small samplewe were not able to conduct separate meaningful analysis.The present study is a secondary analysis of data from theSALOME clinical trial. No a priori power calculations wereconducted before performing the analyses reported herein.Hence, the analyses presented may be statistically underpowered to detect clinically meaningful differences.ConclusionsThe supervised model of care with injectable medica-tions provides a particularly suitable framework forproviding care to opioid-dependent men and women notattracted or retained by other treatments. Regardless ofpresenting to treatment with particular vulnerabilities notreported to the same extent by men, women achievedsimilar outcomes. As such, there is an important case tobe made to make this treatment available to women. Inthe present clinical trial treatment effectiveness was mean-ingfully explained when participant perceptions wereaccounted for. Descriptions were centered on health andquality of life, areas that participants were able to focus ongiven access to a reliable and stable effective medication.Building on prior findings, this study adds evidence tosupport the provision of supervised injectable diacetyl-morphine or hydromorphone to the most vulnerable menand women that inject street opiates and are not attractedor reached by other treatments.AbbreviationsDAM: Diacetylmorphine; HDM: Hydromorphone; HIV: Humanimmunodeficiency virus; MAP: Maudsley addiction profile; MMT: Methadonemaintenance therapy; SALOME: Study to assess longer term opioidmedication effectiveness; SD: Standard deviationAcknowledgementsFirst and foremost, we would like to acknowledge the contribution andcommitment of the study participants who made it possible to continueadvancing this research while overcoming its many challenges. Also, atProvidence Health Care, Justin Karasik and the communications team; JulieForeman and the clinical team at Providence Crosstown Clinic; AminJanmohamed and the pharmaceutical team at Providence Crosstown Clinic.Finally, we wish to acknowledge all members of the Community AdvisoryBoard and Data Safety Monitoring Board, staff of the Centre for HealthEvaluation and Outcome Sciences and Salima Jutha, the SALOMEinvestigators and research team.FundingThe SALOME trial was funded through an operating grant from theCanadian Institutes of Health Research (MCT - 103,817) in partnership withProvidence Health Care with additional financial support from theInnerChange Foundation, Providence Health Care Research Institute, St.Paul’s Hospital Foundation and Vancouver Coastal Health. Further financialsupport was provided by the Michael Smith Foundation for Health ResearchCareer Award and the Canada Institutes of Health Research New InvestigatorAward (EOJ) and the Canada Research Chairs Program (MTS). The fundingsources had no role in the design and conduct of the study; collection,management, analysis and interpretation of the data; and preparation,review or approval of the manuscript.Availability of data and materialsThe datasets used and/or analysed during the current study are availablefrom the corresponding author on reasonable request.Authors’ contributionsEOJ, MTS, SB, DM, AHA, and MK contributed to the design of the SALOMEstudy. KM, KL, SM, and SH contributed to patient recruitment, engagementand data collection. Senior Biostatistician DG led all statistical analyses. EOJ,HP wrote the first version of the manuscript. All authors have approved thefinal manuscript.Competing interestsThe authors declare that they have no competing interests.Consent for publicationNot applicable.Ethics approval and consent to participateThe study received ethical approval from the Providence Health Care/University of British Columbia Research Ethics boards and was conductedbetween December 2011 and September 2014.Palis et al. Substance Abuse Treatment, Prevention, and Policy  (2017) 12:25 Page 10 of 12Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Author details1Centre for Health Evaluation & Outcome Sciences, Providence Health Care,St. Paul’s Hospital, 575- 1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada.2School of Population and Public Health, University of British Columbia, 2206East Mall, Vancouver, BC V6T 1Z3, Canada. 3Centre de Recherche du CentreHospitalier de l’Université de Montréal (CRCHUM), Hôpital Saint-Luc,Montréal, QC H2X 3J4, Canada. 4 Providence Crosstown Clinic, ProvidenceHealth Care, 84 West Hastings Street, Vancouver, BC V6B 1G6, Canada.5Department of Psychiatry, Faculty of Medicine, Detwiller Pavilion 2255Wesbrook Mall, Vancouver, BC V6T 2A1, Canada. 6Northern Ontario School ofMedicine, 935 Ramsey Lake Road, Sudbury, ON P3E 2C6, Canada.Received: 8 March 2017 Accepted: 12 May 2017References1. 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