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Web-based self-help programs that reduce problematic substance use are able to reach hidden consumer groups in the general population. These programs are characterized by their low treatment threshold and nonrestrictive intervention settings. They are also cost effective, making them of interest to both low-income and high-income industrialized countries with ever-increasing health costs.
To test the feasibility and effectiveness of an anonymous, fully automated, Web-based self-help intervention as an alternative to outpatient treatment services for cocaine users.
A total of 196 cocaine-using participants were recruited through various online and offline media for a randomized controlled trial. Participants in the intervention group received interactive cognitive behavioral modules and a consumption diary to reduce cocaine use, whereas participants in the control group received online psychoeducative information modules. Web-based follow-up assessments were conducted after 4 weeks, 6 weeks, and 6 months. Treatment retention was examined and compared between the intervention and control groups. Severity of cocaine dependence was the main outcome measure. Secondary outcomes were cocaine craving, depression symptoms, and alcohol and other substance use.
This Web-based intervention attracted older and more educated participants than existing outpatient treatment programs for which cocaine is the primary substance of abuse. Participants in the intervention group showed greater treatment retention compared with the control group (
For cocaine users with low dependence severity, a fully automated Web-based cognitive behavioral self-help intervention is a feasible alternative with limited effectiveness in outpatient treatment services. However, this type of intervention may attract specific user groups that are rarely reached by existing outpatient treatment and may help them to control their cocaine consumption anonymously.
ISRCTN93702927; http://www.controlled-trials.com/ISRCTN93702927 (Archived by WebCite at http://www.webcitation.org/6CTMM10MR)
Data on the prevalence of problematic cocaine use and addiction are lacking in Switzerland and many other developed countries, but there is no doubt that cocaine use has increased in Switzerland in recent years [
Over the past 12 years, a number of interventions enhanced by information and communication technology (ICT) have aimed to optimize various aspects of mental health care, such as the treatment of eating disorders [
Snow Control, a 6-week Internet-based self-help intervention program for problematic cocaine users who intend to control, reduce, or stop their consumption of cocaine, was tested between March 2010 and December 2011 and compared with a control condition in a randomized controlled trial [
Snow Control is based on cognitive behavioral therapy (CBT) methods that have been tested on cocaine addicts [
The intervention is structured into 8 modules that are activated for week-by-week access in the first 3 weeks, with 4 additional voluntary modules that can be activated during weeks 4 to 6. A detailed description of the intervention can be viewed in the study protocol [
To assess the effectiveness of the Snow Control intervention, an appropriate psychoeducative online control condition was developed. Participants in the control condition received 8 psychoeducative information modules about risks, potential harm, and other important information about cocaine consumption followed by a quiz to evaluate their knowledge. The duration of the control condition was equal to the 6 weeks of the experimental intervention; however, the control condition did not include the whole consumption diary. Participants in the control condition were asked to specify the amount of cocaine consumed in the previous 7 days, but not the amount of cocaine they planned to consume in the next 7 days.
To avoid serious harm to the participants in the intervention and control condition during the study, a detailed consent procedure with thorough safety instructions was provided as well as a continuously accessible 24-hour emergency list (including the numbers of emergency help lines and contact information for the study team and the webmaster), regardless of whether participants withdrew or dropped out of the study. Moreover, during the 6-week intervention phase, the participants had the opportunity to contact a corresponding outpatient clinic in a nearby city by telephone (lists with opening hours, Web links, postal addresses, and telephone numbers were provided).
All outcome measures were assessed through online questionnaires. After providing informed consent, participants who met the study entry criteria created a personal and secure log-in name and password and received an automated email notification with their access information. They were then directed to a baseline assessment Web page with questions regarding sociodemographic characteristics and consumption patterns. The primary outcome measures of cocaine consumption were recorded as the number of days and quantity of cocaine used, in milligrams, as specified in the consumption diary and reflected by the Severity of Dependence Scale (SDS) [
Generalized estimating equation (GEE) analyses were carried out to investigate the effectiveness of the intervention on different variables assessed at baseline and various follow-up points over the study period of 6 months. The GEE is a repeated-measures regression model that takes into account the correlation between the repeated measures of each person [
History data were analyzed with descriptive statistics and general linear models for repeated measures using group membership as a between-subject factor. Because retention was crucial in this study, we explored the baseline predictors of 6-week retention, defined as completion of the consumption diary, using binary logistic regression analyses. First, all potential predictor variables were entered into a preliminary regression model. Next, variables that were not significant (
The study participants were recruited between March 2010 and October 2011 through the Snow Control website; websites of outpatient treatment centers in the Canton of Zurich, Switzerland; websites of national organizations for alcohol and drug prevention in nightlife settings; and tailored advertisements on national social media platforms. In addition, advertisements were placed on national Internet forums, newspapers, and on 2 television reports that were broadcasted on Swiss Television. People interested in participating received more information on the Snow Control website. The website explained the rationale of the study, the different assessments, assessment schedules, and the assessment duration. The participants were informed about (1) study inclusion and exclusion criteria, (2) the potential risks of participation, (3) safety arrangements during and after the study phase, (4) the inability of Snow Control to replace face-to-face therapy for problematic cocaine use/abuse, and (5) the circumstances under which they should contact their general practitioner or a professional from the medical advisory and emergency list that was made accessible at all times and how to make this contact. The participants were also informed that the study was reviewed by the ethics committee of the Canton of Zurich and given their declaration of no objection (
The study inclusion criteria were a minimal age of 18 years and cocaine use on at least 3 occasions in the past 30 days. The exclusion criteria consisted of participation in other psychosocial or pharmacological treatments for the moderation or cessation of cocaine use, reports of opioid use in the past 30 days (with the exception of substitution maintenance treatment for opioid dependence without street heroin use in the last 30 days), and previous treatment for cardiovascular problems or apoplexy. The exclusion criterion of a BDI score > 55 was omitted because the average BDI depression characteristics were above the 55-point score.
The flow of study participants is depicted in
Flowchart of study participants.
There were no differences between the Snow Control intervention group and the control group in the examined baseline variables (
Baseline characteristics of the participants in the Snow Control (intervention) group and control group.
Characteristics | Snow Control | Control group | Total | Chi-squarea | ||
(n = 96) | (n = 100) | (N = 196) | ( |
(χ21) | ||
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Female | 22 (22.9) | 21 (21.0) | 43 (21.9) |
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0.3 |
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Male | 74 (77.1) | 79 (79.0) | 153 (78.1) |
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Age, mean (SD) | 34.9 (9.1) | 33.4 (8.5) | 34.2 (8.8) | 1.150 |
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Obligatory school | 7 (7.3) | 11 (11.0) | 18 (9.2) |
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0.5 |
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Apprenticeship, vocational school | 39 (40.6) | 39 (39.0) | 78 (39.8) |
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High school degree | 15 (15.6) | 16 (16.0) | 31 (15.8) |
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Higher professional education degree | 24 (25.0) | 22 (22.0) | 46 (23.5) |
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University degree | 11 (11.5) | 12 (12.0) | 23 (11.7) |
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Severity of Dependence Scale (SDS) | 7.8 (3.3) | 8.2 (3.0) | 8.0 (3.1) | 1.006 |
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Cocaine Craving Questionnaire-Brief (CCQ-Brief) | 44.3 (9.8) | 43.9 (10.6) | 44.1 (10.3) | 0.095 |
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Beck Depression Inventory (BDI) | 55.5 (12.6) | 57.7 (14.9) | 56.6 (13.9) | 1.309 |
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Years of cocaine consumption, mean (SD) | 6.2 (6.2) | 7.2 (7.5) | 6.7 (6.9) | 0.992 |
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Nasal | 86 (89.6) | 96 (96.0) | 182 (92.9) |
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0.1 |
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Smoked | 14 (14.6) | 12 (12.0) | 26 (13.3) |
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1.7 |
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Oral | 11 (11.5) | 12 (12.0) | 23 (11.7) |
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0.5 |
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Injected (nonintravenous) | 1 (1.0) | 4 (4.0) | 5 (2.6) |
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1.3 |
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Injected (intravenous) | 3 (3.1) | 2 (2.0) | 5 (2.6) |
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0.6 |
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Amphetamines, ecstasy | 20 (20.8) | 27 (27.0) | 47 (24.0) |
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1.1 |
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Cannabis | 53 (55.2) | 59 (59.0) | 112 (57.1) |
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0.8 |
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Benzodiazepines, barbiturates | 11 (11.5) | 7 (7.0) | 18 (9.2) |
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1.1 |
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Heroin | 4 (4.2) | 4 (4.0) | 8 (4.1) |
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0.1 |
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Methadone | 3 (3.1) | 1 (1.0) | 4 (2.0) |
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1.0 |
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19 (19.8) | 21 (21.0) | 40 (20.4) |
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0.0 | |
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Amphetamines, ecstasy | 18 (18.7) | 19 (19.0) | 27 (18.9) |
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0.0 |
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Cannabis | 37 (38.5) | 49 (49.0) | 86 (43.9) |
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1.8 |
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Benzodiazepines, barbiturates | 14 (14.6) | 8 (8.0) | 22 (11.2) |
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1.4 |
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Heroin | 0 (0) | 0 (0) | 0 (0) |
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— |
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Methadone | 2 (2.1) | 2 (2.0) | 4 (2.0) |
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1.0 |
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Alcohol use | 82 (85.4) | 86 (86.0) | 168 (85.7) |
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0.6 |
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Binge alcohol use | 40 (41.7) | 36 (36.0) | 80 (40.8) |
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0.6 |
a None of the comparisons was significant (
The participants in this study reported an average of 6.7 years (SD 6.9) of cocaine use and their most frequent method of use was snorting cocaine (182/196, 92.9%). Most of the participants had not used heroin (188/196, 95.9%) or methadone (192/196, 98.0%) in their lifetimes. The use of amphetamines or ecstasy, substances typically consumed during local nightlife activities [
Participants in the Snow Control intervention group completed more modules (mean 2.60, SD 2.04) than those in the control group (mean 1.80, SD 1.60;
According to the consumption diary data, retention in the intervention group (see
Logistic regression of baseline variables for retention at Week 6.
Variables | Odds ratio (95% CI) |
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Condition (0 = control group, 1 = intervention group) | 2.65 (1.04-6.77) | .04 |
Age (range 18-56) | 1.05 (1.01-1.10) | .047 |
Severity of dependence (SDS, range 1-10) | 0.76 (0.64-0.92) | .004 |
Depressive symptoms (BDI, range 20-91) | 1.06 (1.02-1.11) | .005 |
Retention in the Snow Control online self-help intervention (n = 96) and the control condition (n = 100).
As seen in
Descriptive statistics of the continuous outcome variables from the imputed dataset.
Continuous outcome variables | Baseline | 4 weeks | 6 weeks | 6 months | |||
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Intervention group | 7.8 (3.3) | 7.3 (5.2) | 5.2 (3.4) | 3.8 (2.1) | ||
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Control group | 8.2 (3.0) | 7.1 (5.3) | 5.4 (3.4) | 4.0 (2.2) | ||
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Intervention group | 44.3 (9.8) | 46.3 (12.1) | 48.5 (11.2) | 47.4 (7.2) | ||
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Control group | 43.9 (10.6) | 45.1 (14.1) | 47.8 (11.4) | 46.6 (7.6) | ||
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Intervention group | 55.5 (12.6) | — | 51.8 (16.3) | 45.0 (10.5) | ||
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Control group | 57.7 (14.9) | — | 54.3 (16.9) | 45.6 (10.6) |
Results from linear generalized estimating equation (GEE) models examining the effect of study group (control group vs Snow Control intervention), time, and study group × time interaction terms on cocaine dependence, cocaine craving, and depression.
Continuous outcome variables | Beta | Standard error |
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Study group (control vs intervention) | –0.36 | 0.74 | –0.49 | .63 |
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Time | –1.45 | 0.23 | –6.25 | .000 |
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Study group × time | 0.07 | 0.22 | 0.33 | .75 |
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Study group (control vs intervention) | 0.67 | 1.92 | 0.35 | .73 |
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Time | 1.07 | 0.78 | 1.37 | .21 |
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Study group × time | 0.07 | 0.60 | 0.12 | .90 |
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Study group (control vs intervention) | –2.86 | 2.69 | –1.06 | .29 |
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Time | –4.45 | 1.09 | –4.08 | .006 |
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Study group × time | 0.43 | 0.76 | 0.57 | .57 |
a Variable was assessed at baseline, and at 4-week, 6-week, and 6-month follow-ups.
b Variable was assessed at baseline, and at 6-week and 6-month follow-ups.
Descriptive statistics of the binary outcome variables from the imputed dataset.
Binary outcome variables | Baseline | 4 weeks | 6 weeks | 6 months | |
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Intervention group | 38.5 | 57.1 | 66.7 | 84.0 |
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Control group | 48.6 | 60.2 | 69.4 | 89.2 |
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Intervention group | 100 | 75.8 | 71.2 | 66.9 |
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Control group | 100 | 76.6 | 76.4 | 62.4 |
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Intervention group | 85.4 | 73.5 | 76.9 | 100 |
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Control group | 86.0 | 74.4 | 77.2 | 100 |
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Intervention group | 41.7 | 60.2 | 52.5 | 74.2 |
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Control group | 36.0 | 62.8 | 59.6 | 71.4 |
Results from logistic generalized estimating equation (GEE) models examining the effect of the study group (control group vs Snow Control intervention), time, and the study group × time interaction terms on the consumption of different substances.
Binary outcome variablesa | OR (95% CI)b | Standard error |
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Cannabis consumption within previous month (df = 9.4) |
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Study group (control vs intervention) | 0.73 (0.30 - 1.79) | 0.33 | –0.69 | .49 |
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Time | 1.92 (1.32 - 2.79) | 0.32 | 3.93 | .003 |
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Study group × time | 1.03 (0.72 - 1.47) | 0.18 | 0.18 | .86 |
Cocaine consumption within previous month (df = 4.0) |
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Study group (control vs intervention) | 0.78 (0.17 - 3.55) | 0.22 | –0.07 | .95 |
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Time | 0.42 (0.07 - 2.50) | 0.45 | –0.58 | .59 |
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Study group × time | 1.08 (0.70 - 1.67) | 0.24 | 0.36 | .72 |
Alcohol consumption within previous month (df = 10.0) |
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Study group (control vs intervention) | 0.95 (0.42 - 2.15) | 0.39 | –0.13 | .89 |
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Time | 1.42 (1.06 - 1.90) | 0.19 | 2.61 | .02 |
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Study group × time | 1.01 (0.74 - 1.37) | 0.15 | 0.07 | .95 |
Binge drinking within previous month (df = 5.0) |
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Study group (control vs intervention) | 1.13 (0.45 - 2.84) | 0.52 | 0.28 | .78 |
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Time | 1.57 (0.77 - 3.21) | 0.44 | 1.64 | .16 |
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Study group × time | 0.94 (0.66 - 1.34) | 0.16 | –0.35 | .73 |
a Variables were assessed at baseline, and at 4-week, 6-week, and 6-month follow-ups.
b OR: odds ratio.
According to the consumption diaries (see
Mean weekly cocaine-free days for weeks 1 to 6.
Mean weekly milligrams of cocaine for weeks 1 to 6.
During the study, 13 participants (6 in Snow Control intervention and 7 in control group) contacted outpatient treatment services for additional help as indicated on the website. Of these participants, 5 received medical advice by telephone (3 in Snow Control intervention and 2 in control group), and 8 (3 in Snow Control intervention and 5 in control group) entered an outpatient treatment service because they found the help received through the website to be insufficient. Most of these participants reported impulsive cocaine use and/or severe psychiatric comorbidity.
According to the results of our study, the implementation of a fully automated cognitive behavioral online self-help intervention for the reduction of cocaine use is feasible, but of limited effectiveness when compared with a psychoeducative active control condition in a sample of relatively treatment-naive cocaine users. There was not a greater improvement in the severity of cocaine dependence in the Snow Control intervention group than in the control group. Participants in the intervention group who remained in treatment reduced their average weekly use of cocaine (in milligrams) to a similar level as that observed in the control group; the average weekly cocaine-free days were somewhat higher in the control group, but did not change substantially in either group. Cocaine craving, alcohol use, binge drinking, use of illicit substances other than cocaine, and depression characteristics also did not improve compared with controls. Study retention and intervention participation were higher in the Snow Control intervention group, suggesting that this type of intervention was more attractive to participants than the alternative psychoeducative information, corresponding quiz, and limited consumption diary that was presented to the control group.
One reason that only very small differences were observed between the intervention and control group might lie in the comparable durations for each module and the similar stepwise weekly access to the modules. Sessions for both groups were designed to demand similar time from their users [
One obvious reason why we did not find a greater reduction in the frequency of cocaine use or in the severity of cocaine dependence was the fact that the majority of participants chose to reduce the quantity of cocaine consumed, but did not choose to increase the number of cocaine-free days. This finding was the case although we communicated that this intervention was intended to help participants control or reduce cocaine use or to achieve cocaine abstinence [
Although the number of questionnaires was limited, the participants demonstrated a clear aversion to completing the questionnaires. This aversion was the primary flaw in the study design. Many participants filled out the consumption diary and used the designed modules or read the psychoeducative texts, but they simply closed their Internet browsers when the questionnaires began. The implementation of telephone contact to increase study retention, as performed in similar studies for the reduction of alcohol [
The dropout rates for completion of the consumption diary (81.2% in the intervention and 92% in the control group) were higher than we expected (70%) when we designed the study as a randomized controlled trial. In addition to inclusion in the intervention group, factors that contributed to the retention of participants in treatment until week 6 included the low severity of symptoms of cocaine dependence, age, and depression symptoms, suggesting that the online self-help format is difficult to follow for more severely cocaine-dependent participants and has better retention for depressed and older cocaine users.
Future variations of the intervention will attempt to increase retention by implementing personal, but anonymous, chat contacts similar to those implemented in an online self-help intervention for cannabis users [
We strongly recommend the development of a consumption diary as the primary outcome measure for Internet-based studies aimed at the reduction of illicit substance use. Additionally, if feasible, contingency management (compensation for online-intervention attendance) might increase treatment retention. Unfortunately, in addition to the financial limitations of this study, this contingency management strategy was not feasible in this study in Switzerland due to the structure of the treatment supply center and the probable strong rejection from health authorities and politics.
We conclude that a fully automated Web-based cognitive behavioral self-help intervention is feasible, but of limited effectiveness compared with a psychoeducative control group for cocaine users with low dependence severity. This type of intervention may attract older and more educated participants than existing outpatient treatments for which cocaine is the primary substance of abuse and might help to control participants’ cocaine consumption. Future studies should attempt to improve treatment retention through additional Web-based approaches, such as anonymous chat sessions, and investigate the program’s effectiveness in more detail.
CONSORT Ehealth Checklist V1.6 [
Beck Depression Inventory
cognitive behavioral therapy
Chi-square test
brief version of the Cocaine Craving Questionnaire
Cohen’s d
Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition)
European version of the Addiction Severity Index
generalized estimating equation
International Classification of Diseases, Tenth Revision
imputation by chained equations
information and communication technology
odds ratio
Severity of Dependence Scale
t test
Cohen’s effect size w
Funding for this study was provided by the Swiss Office for the Coordination of Addiction Facilities Infodrog (Grant No 4962/09/ZHZ/WSOK) and the Association for Drug-Related Work in the city of Basel, Switzerland. The sponsors had no role in the design or conduct of the study, the collection, management, analysis, or interpretation of the data, or the preparation, review, or approval of the manuscript. Particular appreciation goes to the staff of the Working Group for the Low-Risk Use of Drugs in Zurich, Switzerland, and their patients, who voluntarily participated in the pilot testing of the Snow Control intervention and the control intervention. We also want to thank all of the outpatient treatment institutions and nightlife prevention services that helped to recruit participants by placing a link on their websites.
None declared.