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ORIGINAL RESEARCH
published: 22 March 2022
doi: 10.3389/fpsyt.2022.846834
Edited by:
Nicolas Franchitto,
Université Toulouse III Paul Sabatier,
France
Reviewed by:
Fikret Erdemir,
Gaziosmanpa ¸sa University, Turkey
Sakineh Hajebrahimi,
Tabriz University of Medical Sciences,
Iran
*Correspondence:
Maximilian Meyer
maximilian.meyer@upk.ch
†These authors have contributed
equally to this work and share first
authorship
Specialty section:
This article was submitted to
Addictive Disorders,
a section of the journal
Frontiers in Psychiatry
Received: 31 December 2021
Accepted: 25 February 2022
Published: 22 March 2022
Citation:
Meyer M, Brunner P,
Geissmann L, Gürtler M, Schwager F,
Waldis R, Vogel M, Wiesbeck GA and
Dürsteler KM (2022) Sexual
Dysfunctions in Patients Receiving
Opioid Agonist Treatment
and Heroin-Assisted Treatment
Compared to Patients in Private
Practice—Identifying Group
Differences and Predictors.
Front. Psychiatry 13:846834.
doi: 10.3389/fpsyt.2022.846834
Sexual Dysfunctions in Patients
Receiving Opioid Agonist Treatment
and Heroin-Assisted Treatment
Compared to Patients in Private
Practice—Identifying Group
Differences and Predictors
Maximilian Meyer1*†, Patrick Brunner1†, Leonie Geissmann2, Martin Gürtler3,
Fabienne Schwager1, Rowena Waldis1, Marc Vogel1, Gerhard A. Wiesbeck4and
Kenneth M. Dürsteler1,5
1Clinic for Adult Psychiatry, University Psychiatric Clinics, University of Basel, Basel, Switzerland, 2Division of Cognitive
Neuroscience, Department of Psychology, University of Basel, Basel, Switzerland, 3Health Center Allschwil
(Gesundheitszentrum Allschwil AG), Allschwil, Switzerland, 4Department of Clinical Research, University of Basel, Basel,
Switzerland, 5Department for Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich,
Zurich, Switzerland
Background and Aims: Sexual dysfunctions (SDs) show a marked impact on a
person’s general wellbeing. Several risk-factors like physical and mental illnesses as well
as alcohol and tobacco use have to date been identified to contribute to the occurrence
of SDs. The impact of opioid-agonist treatment (OAT) on SDs remains unclear, with
some studies demonstrating an improvement after methadone maintenance treatment
(MMT) initiation. However, no studies on the prevalence and predictors of SDs in
heroin-assisted treatment (HAT) exist to date.
Methods: A cross-sectional study was conducted with patients from a MMT center
(n= 57) and a center specializing in HAT (n= 47). A control group of patients with
mild transient illnesses (n= 67) was recruited from a general practitioner (GP). The
International Index of Erectile Function, the Female Sexual Function Index, as well
as measurements for psychological distress, depressive state, nicotine dependence,
and high-risk alcohol use were employed. Patients also completed a self-designed
questionnaire on help-seeking behavior regarding sexual health. Mann-Whitney-U tests
and chi-square tests were performed for group comparisons and binary logistic
regression models were calculated.
Results: Twenty-five percent of the GP sample (n= 17), 70.2% (n= 40) of the MMT
sample, and 57.4% (n= 27) of the HAT sample suffered from SDs at the time of study
conduction. OAT patients differed significantly from GP patients in depressive state,
high-risk alcohol use, nicotine dependence, and psychological distress. Age, depressive
state, and opioid dependence predicted the occurrence of SDs in the total sample. No
differences between OAT and GP patients were found regarding help-seeking behavior.
Discussion: Age, depressive state, and opioid dependence predicted the occurrence
of SDs in the total sample. It remains unclear whether SDs are caused by opioid intake
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Meyer et al. SDs in OAT
itself or result from other substance-use related lifestyle factors, that were not controlled
for in this study. A lack of help-seeking behavior was observed in our sample, underlining
the importance of clinicians proactively inquiring about the sexual health of their patients.
Conclusion: The high prevalence of SDs observed in MMT does not differ from the
prevalence in HAT. Clinicians should actively inquire about their patients’ sexual health
in GP and OAT centers alike.
Keywords: opioid use disorder, sexual dysfunction, erectile dysfunction, opioid dependence, heroin dependence
INTRODUCTION
Sexual dysfunctions (SDs) have a marked impact on the
psychosocial wellbeing of affected individuals and are associated
with anxiety and depression (1), poorer quality of life (2),
diminished confidence, and low self-esteem (3). SDs also have
detrimental effects on the relationship quality and the partners
wellbeing (4). In women, SDs can be subsumed to difficulties in
sexual desire, arousal, and pain (5). In men, the most common
SDs include erectile dysfunction (ED) and premature ejaculation
(6). Reported prevalence rates of SDs in the general population
are inconsistent and vary with assessment technique, definition
being used, underlying comorbidities and age (7,8). Scholars
have found the prevalence of male SDs to be lower than female
SDs, stating estimations between 10 and 52% for men and
between 12 and 80% for women (9,10). In premenopausal
women, recent estimations range from 41% (11) to 51% (12). The
prevalence of ED is estimated at 16% across the age of 20–75 years
(13), whereas the prevalence of premature ejaculation varies from
8 to 30% for all age groups (6).
Notably, prevalence estimates show a great variance and are
further complicated by the fact that in the health care system SDs
are commonly not inquired for Brookmeyer et al. (14). In primary
care, only 10–16% of general practitioners actively ask for sexual
concerns (15) and the rate of sexual history taking in urologists
and gynecologists was found to be 23 and 8%, respectively (16,
17). Additionally, only a small fracture of individuals affected by
SDs seek professional help for sexual concerns (18).
Several risk factors for SDs have been identified. Somatic
illnesses and psychiatric disorders have been found to negatively
impact sexual functioning, whereas findings on lifestyle factors
such as alcohol consumption and tobacco smoking remain
partly inconclusive for male and female SDs alike (19). The
use of opioids and opioid use disorders are also associated
with impaired sexual functioning (20). Due to a substance-using
lifestyle, chronic heroin users usually exhibit a multitude of risk
factors for sexual dysfunctions (e.g., poor nutrition, smoking,
alcohol use, mental comorbidity). The clinical gold standard in
treatment of these patients is opioid agonist treatment (OAT), in
which an alternative opioid, such as methadone, buprenorphine,
slow-release oral morphine, or pharmaceutical diacetylmorphine
(heroin, DAM) is prescribed. In many countries, methadone
maintenance treatment (MMT) is currently the most common
form of OAT (21) and only few countries have permitted
and introduced heroin-assisted treatment (HAT) (22). As in
the general population, reported prevalence rates of SDs in
individuals on MMT vary with some scholars reporting rates as
low as 14% (23) up to 93% for men (24) and 56.6% for women
(25). However, the lack of help-seeking behavior in regard to SDs
is present in MMT as well, making precise prevalence estimates
difficult: one study reported that in their sample only 8% of
men with ED consulted a physician (26). To our knowledge, no
prevalence rates for SDs in individuals receiving HAT or non-
treatment-seeking illicit heroin users exist, although data from
one retrospective study indicates improvement of SD after MMT
initiation (27).
Indeed, evidence suggests that OAT may have a positive
impact on hormonal levels and sexual functioning. It is well-
known that heroin exposure can impair hypothalamic-pituitary-
gonadal function, resulting in irregular menses and secondary
amenorrhea (28). Early studies found prevalence rates of
menstrual disorders among heroin-dependent women of 85–
90% (29,30). Cycle-length irregularity and amenorrhea were
also common among 133 women in MMT, but each additional
week on MMT was associated with decreased risk of both
short and long cycles, and 16 of the 27 women who were
amenorrhoeic at study entry restarted menses in that study
(31). In men, it has been reported that MMT improves SDs
after 6 months of treatment (32). However, this was recently
contradicted by a study that found similar rates of hypogonadism
in MMT and heavy heroin use (33). Additionally, differences
on the extent to which OAT affects sexual functioning have
been found. It has been repeatedly demonstrated that SDs occur
less frequently in OAT with buprenorphine compared to MMT
(34–36).
In summary, the impact of OAT on sexual functioning
remains controversial, with a noticeable lack of literature on
SDs in HAT. Studies found high prevalence rates of SDs in
individuals receiving OAT without it being certain whether the
opioid intake itself causes these symptoms. To this day, the extent
to which comorbidities and other factors associated with drug-
related lifestyle contribute to the occurrence of SDs is unclear.
Also, there are no studies available on prevalence rates for SDs in
individuals receiving HAT and contributing factors have to date
not been identified.
Aim
The aim of the present study was to assess sexual functioning
in opioid-dependent patients on OAT with either MMT or HAT
(injectable diacetylmorphine) as compared to a control sample of
general practitioner patients with mild transient illnesses. Three
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Meyer et al. SDs in OAT
research questions were formulated in line with this aim: 1. Do
patients receiving OAT differ from general practitioner patients
with mild transient illnesses with respect to help seeking behavior,
the prevalence, and the extent of sexual dysfunctions? 2. Do
patients receiving MMT differ from patients receiving HAT in
this regard? 3. What factors do contribute to the occurrence of
sexual dysfunctions?
MATERIALS AND METHODS
Study Design and Setting
The study was conducted in a cross-sectional design at a general
practitioner (GP, private practice) and at two opioid maintenance
centers of the Psychiatric University Clinics of Basel, Switzerland
from March 18 to 31, 2012. One center provided MMT
(mostly methadone and slow-release oral morphine). The other
center specialized in HAT (injectable diacetylmorphine alone
or in combination with other opioid-agonists including oral
diacetylmorphine). In both centers, opioid medications were
tailored to the needs and the substance-use history of the
individual patient and were provided as part of a comprehensive
treatment program covering a broad range of therapeutic
elements and supportive services.
Study Sample
Eligible for participation were either patients who had an
appointment with their GP due to a mild transient illness and all
patients receiving either MMT or HAT in the above-mentioned
centers and who did not show evidence of intoxication during
recruitment. OAT patients were recruited face-to-face at each
clinic while waiting in line for dispensing and GP patients were
recruited during their visit at the private practice.
Inclusion criteria for opioid-dependent patients were age
between 18 and 65 years, presence of sexual activity (including
masturbation) and a sexual relationship (including contacts
with sex workers) within the past 4 weeks, and ability
to understand and communicate in German to complete
the study measurements. Exclusion criteria were current
treatment with antiviral medication for viral hepatitis or HIV,
androgen replacement therapy, or phosphodiesterase type 5
inhibitors, medication or other medical conditions associated
with impaired sexual functioning, and participation in OAT for
less than 4 weeks.
Inclusion criteria for GP-patients were age of 18 years or
older and ability to understand and communicate in German
to complete the study measurements. Exclusion criteria were
the presence of a somatic illness, medication or other medical
condition that is associated with impaired sexual functioning as
well as age over 65 years. A separate study on the GP sample alone
has been published previously by the study team (37).
In total, 171 patients participated in the study, 67 of whom
were recruited in private practice. Fifty-seven were recruited from
the MMT center and 47 patients from the HAT center. The
sample size was derived from comparable studies in the field (21,
38). All patients and healthy controls were of Caucasian ancestry.
Measures and Data Collection
Demographic data concerning age, sex, nationality, highest
education level achieved, employment/social support status, civil
status, and housing situation were reported by each participant.
Participant-Rated Measurements
All patients completed a battery of standardized self-report
instruments in paper-pencil form. While completing the
questionnaires participants had the opportunity to ask the
investigator assessing the data if they had any further queries.
International Index of Erectile Function (IIEF): The IIEF
(39) is a validated 15-item self-administered questionnaire
assessing different domains of sexual functioning in men (erectile
function, orgasmic function, sexual desire, intercourse and
overall satisfaction). The optimal cut-off for the total score
has been found to be 53 (40). It has also been validated in
German (40), and the original five-factor structure could be
confirmed (41).
Female Sexual Function Index (FSFI): The FSFI (42) is a
19-item validated self-report questionnaire assessing the key
dimensions of sexual functioning in women over the past
4 weeks (desire, arousal, lubrication, orgasm, satisfaction, and
pain). A cut-off score of 26.55 has been found to show the
best sensitivity (0.733) und specificity (0.889) for differentiating
women with and without SD, with higher scores indicating better
sexual functioning (43).
Center of Epidemiologic Studies—Depression Scale
(CES-D): Depressive symptoms were assessed with the
German adaption of the CES-Depression Scale (Allgemeine
Depressionsskala-Lang, ADS-L) (44,45). The ADS-L
is a 20 item self-report measure of depressive mood.
Respondents rate items on a 4-point Likert-type scale from
0 (never/very rarely) to 4 (always/nearly all the time). The
scale is widely used and reliability and validity data have
been documented for the use within general and clinical
populations (46).
Symptom Checklist-27 (SCL-27): The SCL-27 (47) is a
modification of the German Symptom Checklist-90-R (48) and
evaluates psychological distress caused by physical disorders or
complaints on six subscales. Each subscale consists of 4–6 items
and each item is rated on a 5-point Likert scale. The Global
Severity Index (GSI) is calculated from the SCL and provides a
global composite score. The positive predictive value was 0.91
at the cut-off score of 0.5 for discriminating psychiatric patients
from a reference sample (49).
Alcohol Use Disorders Identification Test-Consumption
(AUDIT-C): This 3-item screening questionnaire developed
by the World Health Organisation to identify harmful or
hazardous alcohol consumption. Its utility as a screening
instrument for hazardous drinking has also been shown
in substance-dependent patients, with a sensitivity of 0.97,
a specificity of 0.69 and a positive predictive value of
0.65 (50,51). AUDIT-C items are scored on a scale of
0–12 and responses to each of the 3 items are assigned
0–4 points. The recommended AUDIT-C threshold for
unhealthy alcohol use differs between men (≥4) and women
(≥3) (52).
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TABLE 1 | Sample characteristics.
GP (n= 67) MMT (n= 57) HAT (n= 47) Total sample (n= 171)
Age M= 49.8 (SD = 12.0) M= 40.8 (SD = 8.9) M= 43.7 (SD = 6.5) M= 41.6 (SD = 9.8)
Sex Male n= 37 (55.2%) n= 36 (63.2%) n= 29 (61.7%) n= 102 (59.6%)
Female n= 30 (44.8%) n= 21 (36.8%) n= 18 (38.3%) n= 69 (40.4%)
Professional degree n= 62 (92.5%) n= 39 (68.4%) n= 28 (59.6%) n= 129 (75.4%)
Housing situation Alone n= 14 (20.9%) n= 35 (61.4%) n= 28 (59.6%) n= 77 (45%)
With partner n= 48 (71.6%) n= 9 (15.8%) n= 6 (12.8%) n= 63 (36.8%)
With parents n= 4 (6.0%) n= 5 (8.8%) n= 5 (10.6%) n= 14 (8.2%)
Assisted living - n= 4 (7.0%) n= 4 (8.5%) n= 8 (4.7%)
Shared apartment n= 1 (1.5%) n= 3 (5.3%) n= 2 (4.3%) n= 6 (3.5%)
Not specified (missing) - n= 1 (1.8%) n= 2 (4.3%) n= 3 (1.8%)
Civil status Unmarried n= 25 (37.3%) n= 47 (82.5%) n= 36 (76.6%) n= 108 (63.2%)
Married n= 36 (53.7%) n= 2 (3.5%) - n= 38 (22.2%)
Divorced n= 5 (7.5%) n= 5 (8.8%) n= 8 (17.0%) n= 18 (10.5%)
Separated n= 1 (1.5%) n= 1 (1.8%) n= 1 (2.1%) n= 3 (1.8%)
Widowed - n= 1 (1.8%) - n= 1 (0.6%)
Not specified (missing) - n= 1 (1.8%) n= 2 (4.3%) n= 3 (1.8%)
One or more children n= 34 (50.7%) n= 23 (40.4%) n= 14 (29.8%) n= 71 (41.5%)
Alcohol use disorder in family n= 12 (17.9%) n= 20 (35.1%) n= 12 (25.5%) n= 44 (25.7%)
Any other SUD in family n= 6 (9.0%) n= 7 (12.3%) n= 8 (17.0%) n= 21 (12.3%)
GP, general practitioner; MMT, methadone maintenance treatment; HAT, heroin-assisted treatment; SUD, substance use disorder.
Fagerström-Test for Nicotine Dependence (FTND-G): The
FTND (53) was designed to provide an ordinal measure of
nicotine dependence related to cigarette smoking. It contains six
items that evaluate the quantity of cigarette consumption, the
compulsion to use, and dependence. Yes/no items are scored
from 0 to 1 and multiple-choice items are scored from 0 to 3. The
items are summed to yield a total score of 0 to 10. The internal
consistency of FTND is moderate (Cronbach’s alpha = 0.56) (54).
A self-designed questionnaire was employed to inquire about
the role of sexual health during patients’ contact with health care
providers to assess help-seeking behavior. Items were rated on a
5-point Likert scale or in “yes”/”no”-form.
Statistical Analysis
Statistical analysis was conducted with SPSS version 28 (IBM). As
the data were not normally distributed Mann-Whitney-U tests
were performed to calculate differences in scale scores between
groups. Chi-square tests were used to determine differences
in prevalence rates and help-seeking behavior. Binary logistic
regression models were calculated to identify variables predictive
of SD. Included variables were tested for multicollinearity by
calculating the variance inflation factor. Level of significance was
set at p<0.05 for all calculations. Missing data was replaced by
the median of the respective variable when it became necessary.
Ethics
All participants gave written informed consent after being
informed about the aims and procedures of the study in detail.
Participants did not receive any compensation for participation
in the study. The study protocol was approved by the local ethics
committee (Ref. Nr. EK 31/11) and was conducted in accordance
with the Declaration of Helsinki.
RESULTS
Table 1 provides the sociodemographic
characteristics of the sample.
Prevalence of Sexual Dysfunction in the
Sample
Occurrence of sexual dysfunction was defined as IIEF score
lower than 53 for males (40) and an FSFI score lower than
26.55 for females (43). Prevalence of SDs in GP patients
25.4% (n= 17) differed significantly from the prevalence
found in OAT patients 64.4% (n= 67) as determined by
the chi-square test [χ2(1, n= 171) = 24.9, p<0.001].
No statistically significant difference was found between
prevalence in HAT patients (57.4%, n= 27) and prevalence
in MMT patients (70.2%, n= 40) [χ2(1, n= 104) = 1.8,
p= 0.18].
When comparing male to female patients, no differences were
found in the total sample [χ2(1, n= 171) = 1.6, p= 0.20], the GP
patients [χ2(1, n= 67) = 0.6, p= 0.43], all OAT patients [χ2(1,
n= 104) = 2.7, p= 0.10], and the HAT patients [χ2(1, n= 47) = 0.0,
p= 0.84]. In MMT patients, SDs occurred significantly more
often in male patients [χ2(1, n= 57) = 6.5, p= 0.01].
Differences in the Extent of Sexual
Dysfunction Between Patients Receiving
Opioid-Agonist Treatment and General
Practitioner Patients With Mild Transient
Illnesses
Descriptive statistics and differences as determined by the Mann-
Whitney-U test of FSFI and IIEF scores and their subdomains
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TABLE 2 | Sexual functioning in GP and OAT patients.
GP (n= 30) OAT (n= 39) p
FSFI full scale score M= 28.27 (SD = 6.72) M= 15.28 (SD = 9.95) <0.001
FSFI domains Desire M= 3.68 (SD = 1.14) M= 2.55 (SD = 1.44) <0.001
Arousal M= 4.52 (SD = 1.38) M= 2.39 (SD = 2.03) <0.001
Lubrication M= 5.02 (SD = 1.57) M= 2.46 (SD = 2.23) <0.001
Orgasm M= 5.05 (SD = 1.40) M= 2.06 (SD = 2.01) <0.001
Satisfaction M= 5.07 (SD = 1.04) M= 2.90 (SD = 1.55) <0.001
Pain M= 4.93 (SD = 1.60) M= 2.90 (SD = 2.57) <0.001
GP (n= 37) OAT (n= 65)
IIEF full scale score M= 57.73 (SD = 17.20) M= 40.80 (SD = 22.51) <0.001
IIEF domains Erectile function M= 24.70 (SD = 8.15) M= 16.51 (SD = 11.14) <0.001
Orgasmic function M= 8.89 (SD = 2.95) M= 5.68 (SD = 4.43) <0.001
Sexual desire M= 6.95 (SD = 1.61) M= 6.25 (SD = 2.35) 0.192
Intercourse satisfaction M= 9.49 (SD = 5.01) M= 5.02 (SD = 5.78) <0.001
Overall satisfaction M= 7.70 (SD = 2.26) M= 7.35 (SD = 2.18) 0.355
Mann-Whitney-U tests were performed to compare groups.
FSFI, Female Sexual Function Index; IIEF, International Index of Erectile Function; GP, general practitioner (sample); OAT, opioid-agonist treatment (sample); M, mean; SD,
standard deviation.
are provided in Table 2. There was a significant difference in the
total IIEF (U= 665.0, p<0.001, r= 0.37) and FSFI (U= 155.5,
p<0.001, r= 0.63) scores between the GP patients and OAT
patients, with GP patients showing significantly higher IIEF
and FSFI scores.
In a next step, only patients who met the respective IIEF-
and FSFI-cut-offs were included in the calculation of the
Mann-Whitney-U test to examine whether patients differed
in the severity of SD. No differences were found between
GP and OAT patients with SD in IIEF total and subdomain
scores. In female patients, we found the total FSFI score
as well as the orgasm and satisfaction-domain scores to be
significantly lower in OAT patients (p= 0.007, p= 0.007, and
p<0.001, respectively).
Groups also differed significantly in risk drinking behavior
as determined by the AUDIT-C, psychological distress as
determined by the SCL-27, severity of nicotine dependence
as determined by the FTND, and depressive symptoms as
determined by the ADS-L (Table 3).
Help-Seeking Behavior Regarding Sexual
Dysfunctions
Patients were asked whether they had ever talked about their
sexual health with their treating physician. About one third
of OAT patients [29.1% (n= 30)] and GP patients [32.8%
(n= 22)] answered to have done so. No significant difference
was found between groups as determined by a chi-square test
[χ2(1, n= 170) = 0.3, p= 0.61]. When asked whether their
treating physician had ever inquired about their sexual health,
23.3% (n= 24) of OAT patients and 17.9% (n= 12) of GP patients
responded “yes.” Again, there was no significant difference
between groups [χ2(1, n= 170) = 0.7, p= 0.40]. The question
whether patients ever wanted to receive counseling regarding
their sexual health from their treating physician was also asked
and responses are shown in Figure 1.
Differences in the Extent of Sexual
Dysfunction Between Patients Receiving
Methadone Maintenance Treatment and
Patients Receiving Heroin-Assisted
Treatment
No significant difference in IIEF (U= 505.5, p= 0.828) and
FSFI (U= 164, p= 0.481) total scores was found when
comparing MMT to HAT patients. Additionally, there was no
significant difference between groups in IIEF or FSFI subscales.
Comparisons remained non-significant for total scores and
subdomain scores after including only MMT and HAT patients
who met the cut-offs of the IIEF and FSFI.
Factors Contributing to the Occurrence
of Sexual Dysfunction
Explorative binary logistic regression was performed to identify
predictors of SD in our study population. Occurrence of sexual
dysfunction was again defined as IIEF score lower than 53 or FSFI
score lower than 26.55. Variables included were age, sex, whether
patients suffered from opioid dependence (i.e., patients from the
MMT and HAT center), depressive state as determined by the
TABLE 3 | Descriptive statistics and differences in total scale scores as
determined by Mann-Whitney-U tests.
Scale GP (n= 67) OAT (n= 104) p
AUDIT-C M= 3.04 (SD = 1.55) M= 2.99 (SD = 3.26) 0.049
GSI M= 0.29 (SD = 0.32) M= 0.97 (SD = 0.81) <0.001
FTND M= 0.54 (SD = 1.46) M= 4.92 (SD = 2.69) <0.001
ADS-L M= 10.75 (SD = 8.83) M= 19.08 (SD = 9.85) <0.001
AUDIT-C, Alcohol Use Disorders Identification Test-Consumption; GSI, Global
Severity Index; FTND, Fagerström-Test for Nicotine Dependence; ADS-L,
Allgemeine Depressionsskala-Lang; M, mean; SD, standard deviation.
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Meyer et al. SDs in OAT
FIGURE 1 | GP (n= 67) and OAT (n= 103) patients’ answers about whether they ever felt the need for counseling.
ADS-L, psychological distress as determined by the GSI, high-
risk alcohol use as determined by the AUDIT-C and severity of
nicotine dependence as determined by the FTND. The results are
provided in Table 4.
To find out, whether predictive variables differed in the MMT
and the HAT population, calculation was repeated for both
patient groups, respectively. The opioid dependence variable was
not included in these models. Whereas age remained significant
in the MMT population (B= 0.086, p= 0.033, OR = 1.090), no
variable was found to be predictive in the HAT sample.
DISCUSSION
This is the first study reporting on the prevalence of SDs and
its contributing factors in HAT. We found the prevalence of
SDs in our sample of GP, MMT and HAT patients to be 25,
70, and 57%, respectively. The prevalence of SDs observed in
our sample of MMT patients is in line with previously reported
findings (24,25). Importantly, we did not find a significant
difference in the respective MMT and HAT prevalence rates
and our results therefore indicate that SDs are equally common
in HAT patients. We also found that the severity of SDs
as measured by the IIEF and the FSFI in HAT and MMT
patients did not differ.
Unsurprisingly, we found SDs to be significantly more
frequent in OAT patients when compared to GP patients
TABLE 4 | Logistic regression on sexual dysfunction prevalence in the total
sample (n= 171).
Variables B p OR (CI 95%)
Age 0.044 0.019 1.045 (1.007–1.084)
Sex 0.381 0.316 1.475 (0.690–3.152)
Depressive state 0.054 0.032 1.055 (1.005–1.109)
Nicotine dependence –0.003 0.968 0.997 (0.853–1.165)
Psychological distress 0.146 0.701 1.158 (0.549–2.442)
High-risk alcohol use –0.012 0.856 0.988 (0.863–1.130)
Opioid dependence 1.288 0.010 3.625 (1.369–9.595)
Nagelkerkes R2= 0.291; Hosmer-Lemeshow-test: χ2= 2.211, p = 0.974.
OR, odds ratio; CI, confidence interval.
with mild and transient illnesses. However, only female
OAT patients experienced more severe SDs as indicated by
lower total scale scores. This difference was not observed
in male GP and OAT patients. GP patients also differed
significantly from OAT patients in psychological distress,
nicotine dependence, high-risk drinking behavior, and depressive
symptoms. However, in our regression analysis, only depressive
state emerged to be predictive for the occurrence of SDs
in the total sample. In addition to depressive state, age and
opioid dependence predicted SDs, which was also found in
previous studies with patients receiving either methadone or
buprenorphine (34).
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Importantly, no difference between GP and OAT
patients was observed regarding the lack of help-seeking
behavior. Due to the high prevalence of SDs in individuals
with opioid use disorder, clinicians should proactively
inquire about their occurrence in these patients. However,
in our sample, only 23% of OAT patients stated to
have previously been asked about their sexual health
by their treating physician. While the reasons for this
finding can only be speculated on, low rates of sexual
health examinations have previously been reported in the
literature (15–17), underlining the need to further raise
awareness of SDs in OAT.
No variable (including age) was found to predict SDs
in the regression model only including HAT patients. This
indicates that not all contributing factors were directly assessed
by our study. It also raises the question whether substance-
use related lifestyle factors or opioid agonists themselves
play a large role in the emergence of SDs in this patient
population. Regarding the latter, studies have repeatedly
demonstrated that male patients in MMT suffer from SDs
more often when compared to patients receiving treatment
with buprenorphine (35,36). This suggests that methadone
itself contributes partly to the occurrence of SDs in opioid-
dependent men. Since we found no difference in the prevalence
of SDs between HAT and MMT patients, this might also
hold true for DAM.
It remains unclear whether SDs are caused by opioid intake
itself or result from other substance-use related lifestyle factors,
that we did not control for. On a behavioral level, the substance-
use related lifestyle frequently found in opioid-dependent
patients has been suggested to affect various aspects of physical
and mental health (38), which makes it hard to distinguish direct
consequences of OAT from opioid-dependence-related factors.
However, some factors that may be related directly or indirectly to
opioid-dependence like tobacco smoking, psychological distress
and higher rates of depression did not contribute to the
occurrence of SDs in our sample. Other factors we did not
specifically account for in our analysis might include mental
comorbidities, disadvantageous health behaviors (e.g., illicit drug
use), somatic illnesses, co-medication, and low socioeconomic
status. In male MMT and buprenorphine patients, medical
status, psychiatric illness, other current substance use, and
civil status have previously been identified to be associated
with SDs (55).
Studies comparing methadone and buprenorphine with
regard to the occurrence of SDs in male and female patients
have to date shown mixed results. Ruíz Ruíz et al. found
the prevalence of SDs to be higher in the methadone
group (36), whereas other studies did not find beneficial
effects of buprenorphine (56). Therefore, the recommendation
of switching from methadone to buprenorphine in MMT
patients with SDs is not unequivocally supported by literature.
Additionally, HAT is provided for individuals who did previously
not respond to other forms of OAT, which most of the time
precludes a change in their treatment regimen. Nonetheless, our
data shows that just as in MMT, screening for SDs is equally
important in HAT.
Limitations
In addition to the above-mentioned shortcomings, the
present study shows several other limitations. The first
shortcomings concern the convenience sampling and the
moderate sample size, which limit the generalizability of
the present findings. Additionally, we did not control for
daily opioid dosages, for co-morbidities and for illicit
substance use, which may have a great impact on SDs.
Also, we did not assess biological markers such as sexual
hormone levels and the Body Mass Index. Finally, we
did not analyze variables of interest for female and male
patients individually.
CONCLUSION
Patients in OAT suffer from SDs more often than GP patients
with mild transient illness. Clinicians working in OAT centers
and GP alike need to actively inquire about the sexual
health of their patients. Depressive state, age, and opioid
dependence predicted the occurrence of SDs in our sample
of GP, MMT and HAT patients. No differences in frequency
and extent of SDs were observed when comparing patients
receiving HAT to MMT patients. Future studies are needed
to assess whether the intake of DAM itself contributes to the
occurrence of SDs.
DATA AVAILABILITY STATEMENT
The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Ethikkommission beider Basel (Ref. Nr. EK
31/11). The patients/participants provided their written informed
consent to participate in this study.
AUTHOR CONTRIBUTIONS
PB, GW, and KD designed the study and wrote the study
protocol. PB, MG, FS, MV, and KD were responsible for
data collection and data management. MM, LG, RW, and
KD conducted the data analyses and interpretation for the
manuscript. MM, LG, and KD drafted the manuscript. All
authors provided critical revision of the manuscript for
important intellectual content.
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Conflict of Interest: The authors declare that the research was conducted in the
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