Week 8 _ assignment – psychotherapy for clients with addictive

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Please review the complete instructions. Use the attached article to complete the assignment ( 7- to 10-slide PowerPoint presentation ) 

Assignment: Psychotherapy for Clients with Addictive Disorders

Addictive disorders can be particularly challenging for clients. Not only do these disorders typically interfere with a client’s ability to function in daily life, but they also often manifest as negative and sometimes criminal behaviors. Sometime clients with addictive disorders also suffer from other mental health issues, creating even greater struggles for them to overcome. In your role, you have the opportunity to help clients address their addictions and improve outcomes for both the clients and their families.


To prepare:

· Review the Learning Resources and consider the insights they provide about diagnosing and treating addictive disorders. As you watch the 187 Models of Treatment for Addiction video – consider what treatment model you may use the most with clients presenting with addiction.

Link – https://www.youtube.com/watch?v=eQkA0mIWx8A

· Use the attached article from the Walden Library database to complete the assignment – “Effectiveness of an app-based intervention to reduce substance use, gambling, and digital media use in vocational school students: study protocol for a randomized controlled trial”


The Assignment – instructions


In a 7- to 10-slide PowerPoint presentation, address the following. Your title and references slides do not count toward the 5- to 10-slide limit.

 

· Provide an overview of the article.

· What population (individual, group, or family) is under consideration?

· What was the specific intervention that was used? Is this a new intervention or one that was already studied?

· What were the author’s claims?

· Explain the findings/outcomes of the study in the article. Include whether this will translate into practice with your own clients. If so, how? If not, why?

· Explain whether the limitations of the study might impact your ability to use the findings/outcomes presented in the article. 

· Use the Notes function of PowerPoint to craft presenter notes to expand upon the content of your slides.

 

· Support your response with at least three other peer-reviewed, evidence-based sources. Explain why each of your supporting sources is considered scholarly. Provide references to your sources on your last slide. Be sure to include the article you used as the basis for this Assignment ( see below).


Reference article:

Effectiveness of an app-based intervention to reduce substance use, gambling, and digital media use in vocational school students: study protocol for a randomized controlled trial.

·

APA 7th Edition

(American Psychological Assoc.)

References

Arnaud, N., Weymann, J., Lochbühler, K., Pietsch, B., Rossa, M., Kraus, L., Thomasius, R., Hanewinkel, R., & Morgenstern, M. (2022). Effectiveness of an app-based intervention to reduce substance use, gambling, and digital media use in vocational school students: study protocol for a randomized controlled trial. Trials23(1), 1–10. https://doi.org/10.1186/s13063-022-06231-x

STUDY PROTOCOL Open Access

Effectiveness of an app-based intervention
to reduce substance use, gambling, and
digital media use in vocational school
students: study protocol for a randomized
controlled trial
Nicolas Arnaud1* , Johanna Weymann1, Kirsten Lochbühler2, Benjamin Pietsch3, Monika Rossa2, Ludwig Kraus2,
Rainer Thomasius1, Reiner Hanewinkel3 and Matthis Morgenstern3

Abstract

Background: Substance-related and addictive disorders are among the most common mental disorders in
adolescence and young adulthood. Vocational school students are a risk group for problematic substance use and
addictive behavior. However, the availability of evidence-based prevention concepts and programs is
underdeveloped in the vocational school setting.

Methods/design: A two-arm cluster randomized waitlist-controlled trial will be conducted to evaluate the
effectiveness of an app-based intervention to decrease substance use, gambling, and digital media use in
vocational school students in Germany. Vocational students will participate in an app-based intervention that is
designed to support voluntary commitment to abstain from or reduce substance or digital media use over a period
of 2 weeks. The “education-as-usual” control arm will have access to the intervention after data collection is
completed. One of the primary outcome measures will be the use of alcohol, nicotine, and digital media 30 days
after the intervention. Several secondary outcome measures will also be included, such as cannabis consumption,
gambling, symptoms of stress, physical activity, mindfulness, well-being, impulsivity and sensation seeking, and
readiness to change. A total of 4500 vocational students from 225 classes will be recruited and randomized across
three German federal states.

Discussion: This study protocol describes the design of an RCT testing the effectiveness of an app-based
intervention to reduce addictive behaviors in vocational school students. It is expected that this approach will be
feasible for and effective in the vocational school setting and that the study provides comprehensive information
on the key factors involved in temporary abstaining or reducing substance or digital media use.

Trial registration: German Clinical Trials Register DRKS00023788. Registered on 20 January 2021

Keywords: Prevention, Vocational students, Voluntary commitment, Abstinence, Substance use, Internet-related
problems, Cluster-randomized controlled trial

© The Author(s). 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
changes were made. The images or other third party material in this article are included in the article’s Creative Commons
licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons
licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated in a credit line to the data.

* Correspondence: [email protected]
1German Centre for Addiction Research in Childhood and Adolescence,
University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
Full list of author information is available at the end of the article

Arnaud et al. Trials (2022) 23:277
https://doi.org/10.1186/s13063-022-06231-x

Administrative information
Note: The numbers in curly brackets in this protocol
refer to SPIRIT checklist item numbers. The order of
the items has been modified to group similar items (see
http://www.equator-network.org/reporting-guidelines/
spirit-2013-statement-defining-standard-protocol-items-
for-clinical-trials/).

Title {1} Effectiveness of an app-based interven-
tion to reduce substance use, gam-
bling, and digital media use in
vocational school students: study proto-
col for a randomized controlled trial

Trial registration {2a and 2b}. Trial registration number
DRKS00023788. Registered on 20
January 2021.

Protocol version {3} The current protocol version is version
1.0, dated from 02 December 2021.

Funding {4} The trial is funded by the Federal
Ministry of Health Germany (BMG, grant
number: ZMVI1-2519DSM216). The
funding period is from 01 August 2019
to 31 December 2022. The funding
source has no role in the design of this
study and will not have any role in its
execution, analyses, interpretation of
the data, or decision to submit results.

Author details {5a} NA, JW, RT: German Centre for
Addiction Research in Childhood and
Adolescence at University Medical
Centre Hamburg-Eppendorf, Hamburg,
Germany; KL, MR, LK: IFT Institut für
Therapieforschung München, Germany;
MM, BP, RH: Institute for Therapy and
Health Research, IFT-Nord.

Name and contact information
for the trial sponsor {5b}

Institute for Therapy and Health
Research, IFT-Nord, Kiel, GermanyTrial’s
principal investigator: Reiner Hanewin-
kel, [email protected]; scientific
coordinator: Matthis Morgenstern,
[email protected]

Role of sponsor {5c} The sponsor is non-commercial. The
sponsor ensures quality management,
qualified and trained personnel, study
protocol compliance, and submission
of relevant study documents to the
ethics committee and regulatory au-
thorities. He supports the study with
trial unit facilities and study personnel.

Introduction
Background and rationale {6a}
Substance-related and addictive disorders typically have
their onset in early adolescence and belong to the most
common psychological disorders among emerging adults
[1, 2]. In Germany, the group of 18- to 20-year-olds has
the highest risk of addiction diagnoses regarding alcohol
(6.4%), cannabis (1.5%), amphetamines (0.4%), and co-
caine (0.3%) according to population-based survey data
[3]. Research has consistently shown that the period of
emerging adulthood [4] is not only associated with a

readiness to engage in risky and unhealthy behavior such
as substance abuse but also with limited capacities for
self-regulation and (substance use-related) habit forma-
tion [5].
The proportion of young people affected by addictive

behaviors increases if non-substance-related or “behav-
ioral” addictions, particularly Internet-related disorders,
are also taken into account [6]. Gambling disorder and
(screen-related) gaming disorder seem to be similar to
substance-related addictive disorders regarding their
clinical appearance, etiology, comorbidity, and thera-
peutic responsiveness [7, 8]. Moreover, they are of in-
creasing epidemiological relevance (even more so during
the current COVID-19 pandemic conditions, see [9])
and have therefore recently been included in the revised
classification of Substance-Related and Addictive Disor-
ders in the 11th edition of the International Classifica-
tion of Diseases (ICD-11) of the World Health
Organization (WHO) (see [10]).
The school setting is particularly relevant for

prevention efforts as it represents a central
developmental context where a large number of
individuals can be reached with comparatively little
effort [11]. The majority of evaluated school-based pre-
ventive intervention programs apply only to regular
schools, while there has been a lack of comparable pro-
grams for vocational schools [12]. However, in Germany,
a substantial proportion of young people leaves the regu-
lar school system during adolescence and starts a voca-
tional education, typically from the age of 16 [13, 14].
Vocational education in Germany largely takes place in
the “dual system,” in which trainees are employed in a
company and complete the practical part of their train-
ing there, while also attending vocational school, where
the theoretical part of the training takes place.
Recent studies suggest that vocational students

represent an important target group for prevention
efforts and health promotion. In a survey including 5688
German vocational students, 40.5% of the participants
reported a positive screening result for problematic
alcohol use and 3.6% reported a level of cannabis use
that puts them at serious risk for addiction [15]. The
percentage of vocational students that reported daily
smoking (41%) was 2.4 times greater than their age-
matched peers in the general population. With regard to
addictive behaviors such as online and offline gambling
and digital media use, there are currently no data avail-
able that estimate the specific risks of vocational stu-
dents. However, surveys indicate that media-related
problems are particularly widespread among adolescents
and young adults of typical vocational school age [6, 16].
A promising school-based prevention approach is a

voluntary commitment to abstain from or reduce habit-
ual behaviors like substance use. For example, one of the

Arnaud et al. Trials (2022) 23:277 Page 2 of 10

most widespread programs for the prevention of smok-
ing in secondary schools in Germany is the smoke-free
class competition “Be smart – don’t start.” At the core
of the program is a joint voluntary commitment of the
school class to not smoke for a period of 6 months. It
focuses on influencing social norms, promoting self-
regulation, and addressing social influences by deploying
cognitive-behavioral intervention techniques [17]. Over-
all, the evidence based on process and rigorous outcome
evaluations, long-term and iatrogenic effects, and cost-
benefit efficiency are convincing, even in comparison
with other programs (see [18]). An adaptation of this ap-
proach has also been shown to be effective in the pre-
vention of binge drinking among older adolescents in
the regular school setting in a randomized study [19].
Furthermore, the results of a recent controlled study in
Germany [20] suggested that a 20-min reduction of daily
social media use over a period of 2 weeks is positively
associated with well-being and a healthier lifestyle
among students. Specifically, the reduction in social
media use not only reduced social media use intensity
and the level of addictive symptoms but also the amount
of daily smoked cigarettes over a period of 3 months.

Objectives {7}
The present study aims to transfer the approach of
voluntary abstinence to the vocational school setting and
to evaluate the feasibility and effectiveness of this

approach using a randomized design. It is expected that
the intervention will increase awareness of habitual
behaviors (e.g., substance and digital media use) and
lead to a measurable reduction of these behaviors even
after the end of the abstinence or reduction period.

Trial design {8}
The current study uses a cluster-randomized controlled ex-
ploratory trial with two arms, an intervention group (IG),
and a waitlist control group (CG) with pre-post assess-
ments. All study participants will be randomly assigned to
one of the two groups on the class level (Fig. 1).

Methods: participants, interventions, and
outcomes
Study setting {9}
The study will be conducted in vocational schools in the
three German federal states of Schleswig-Holstein, Bav-
aria, and Hamburg. Schools were not systematically se-
lected to represent the complexity of the vocational
school system in Germany [14]; therefore, they vary in
size, regional area, urbanicity (rural vs. urban), and voca-
tional areas (e.g., business administration, industrial-
technical professions, personal services).

Eligibility criteria {10}
All vocational students will be eligible to participate in
the study if they or one of their legal guardians (if the

Fig. 1 Consolidated Standards for Reporting Trials (CONSORT) diagram: study design and participant flow

Arnaud et al. Trials (2022) 23:277 Page 3 of 10

student is under the age of 16) provide written informed
consent.
The age range of students attending vocational schools

in Germany is broad. The mean age of students when
starting vocational training is 19.7 years; approximately
11% of the students are aged 16 years or younger or 24
years or older [14].

Who will take informed consent? {26a}
Trial participants and, if under the age of 16, their
legal guardians will be provided with sufficient verbal
and written information about the study’s purpose
and procedures, information on confidentiality and
data protection procedures, possible advantages and
disadvantages of participation, and the option to
withdraw from the study at any time and without any
given reason. They are informed that participation in
the study is completely voluntary. Written informed
consent will be provided to and obtained from all
participants prior to study enrollment by members of
the study team.

Additional consent provisions for collection and use of
participant data and biological specimens {26b}
The consent includes the participant’s agreement to the
collected data being used and published in an
anonymized form for research purposes. This trial does
not involve collecting biological specimens for storage.

Interventions
Explanation for the choice of comparators {6b}
The comparator is an education-as-usual waitlist control
group. All participants will be randomly assigned to ei-
ther the app-based intervention group or the control
group. The participants of the control group will con-
tinue routine activities during the (approximately) 6-
week waiting period. This time frame was chosen be-
cause the intervention (use of the Mzo app) lasts 2
weeks and the primary trial outcomes concern past-
month substance and media use. After post-assessment,
participants of the control group will receive full access
to the intervention app. Crossover and influence from
peers in the experimental group can be considered low
due to class-wise randomization and the nature of the
vocational school setting (e.g., presence at school varies
for each vocational area, and students are not present at
school on a daily basis).

Intervention description {11a}
“Meine Zeit ohne” [my time without] (MZo) is an app-
based intervention that aims to encourage users to vol-
untarily abstain from an individually relevant habitual
behavior or to reduce it to a degree that is subjectively
considered significant or a “challenge” for a period of 2

weeks. After downloading the app (downloadable for de-
vices running on iOS 11.0 or higher/Android 6 or
higher) and log in with a password, students can set
their individual challenges. For the next 2 weeks, partici-
pants receive push notifications on a daily basis and are
asked for feedback about whether they have reached
their goal of the preceding day. MZo primarily targets
consumption behavior (both substance-related and non-
substance-related behavior, i.e., digital/screen-based
media-related behavior such as gaming and/or social
media use).

Criteria for discontinuing or modifying allocated
interventions {11b}
Participants in the intervention group can discontinue
the use of the intervention app at any time by deleting
the app from their mobile devices. The intervention, i.e.,
the use of the app, does not require any contact with the
study team.

Strategies to improve adherence to interventions {11c}
The implementation of the MZo challenge is entirely
app-based. The effort required to use the app can be
considered minimal. Adherence to the intervention is fa-
cilitated by an easy-access procedure (log-in and user
authentication are only required once after the download
of the app) and daily push notifications. The app pro-
vides the opportunity to choose individual behavior
change goals from a broad spectrum including an un-
defined goal category which can be specified by the indi-
vidual user.

Relevant concomitant care permitted or prohibited during
the trial {11d}
Participation in the current trial has no impact on
possible concomitant care during the time of the trial.

Provisions for post-trial care {30}
All participating schools are provided with contact
information of the study sites and can access evidence-
based information material on substance use and sub-
stance use prevention via the project website.

Outcomes {12}
Primary outcomes
Outcome measures at each time point are shown in Fig. 2.
One of the primary outcomes is self-reported use of alco-
hol, nicotine (cigarettes and/or electronic cigarettes), and
digital media (gaming and social media) in the past
month. Measures for alcohol use are based on [21] and in-
clude frequency of drinking (1 = “never” to 5 = “four times
a week or more”), quantity of alcoholic drinks on a typical
drinking day (1 = “1 or 2 alcoholic drinks” to 5 = “10 or
more alcoholic drinks”), and frequency of binge drinking

Arnaud et al. Trials (2022) 23:277 Page 4 of 10

(more than 6 alcoholic drinks on one occasion; 0 =
“never” to 4 = “daily or almost daily”). Nicotine use is
assessed based on students’ reports on the number of
days using cigarettes and/or electronic cigarettes and
their quantity per day. Problematic Internet gaming is
assessed using the Internet Gaming Disorder Scale-
Short-Form (IGDS-SF [22];), German version ([23]; 9-
items: e.g., “Have you continued your gaming activity
despite knowing it was causing problems between you
and other people?”; 1 = “never” to 5 = “very often”).
Problematic social media use was assessed using an
adapted version of the brief version of the Bergen Face-
book Addiction Scale (BFAS [24];; German version:
[25]). The scale consists of 6 items (e.g., “Felt an urge
to use social media more and more”; 1 = “very rarely”
to 5 = “very often”). All primary outcome measures (in
their German versions) have been used in previous
studies and can be considered psychometrically valid.

Secondary outcomes
A number of individual-level secondary outcome mea-
sures were selected based on their health-related rele-
vance and associability with the conceptual intervention
approach. These outcomes are as follows:

– Problematic cannabis use (Severity of Dependence
Scale (SDS), 5 items [26]; German version: [27])

– Problematic gambling (Brief Biosocial Gambling
Screen (BBGS), 3 items [28])

– Psychological stress (Depression Anxiety Stress
Scales 21 (DASS-21), subscale stress, 7 items [29];
German version: [30])

– Impulsivity and sensation seeking (Substance Use
Risk Profile Scale (SURPS), subscales impulsivity and
sensation seeking, 2 items each [31])

– Mindfulness skills (Child and Adolescent
Mindfulness Measure (CAMM), 10 items [32])

Fig. 2 Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) diagram detailing the trial activities and measures and
their timing

Arnaud et al. Trials (2022) 23:277 Page 5 of 10

– Physical activity (past month frequency of physical
activity/sports, single item, self-constructed)

– Positive mental health (Positive Mental Health Scale
(PMH), 9 items [33])

– Life satisfaction (L1, General Life Satisfaction Short
Scale, single item [34], German version [35])

– General self-efficacy (Short Scale for Measuring
General Self-efficacy Beliefs (ASKU), 3 items [36])

– Readiness and confidence to quit or reduce the use
of alcohol, nicotine, cannabis, gaming, social media,
and gambling (readiness/confidence ruler (10 = “not
at all ready/difficult to change” to 100 = “very ready/
difficult to change”) assessing readiness and
confidence in quitting or reducing each behavioral
outcome; based on [37])

For a list of included secondary outcomes, see Fig. 2.
Additionally, we assess socio-demographic data (age,
gender, migration background, socio-economic status),
progress of vocational education, educational sector, and
frequency of in-school education.

Participant timeline {13}
In Fig. 1, trial procedures from enrollment to the end of
the trial are illustrated.

Sample size {14}
The sample size is calculated to detect a minimum
relative difference of 20% between both groups at post-
assessment. This effect was based on previous studies on
the effectiveness of substance use prevention programs
[11, 19] and takes a clustered data structure and an
intra-class correlation (ICC) of 0.032 as well as a drop-
out rate of 30% on the student level into account (based
on [15]). The required sample size for 80% power to de-
tect between-group differences at the 0.05 level is 4500
students (2250 students per condition) from 225 classes.

Recruitment {15}
The three study sites cooperate with local school
supervisory authorities, which support the project and
allow the recruitment of a convenient sample of
vocational schools. Class teachers and other school staff
(such as school social workers) at those schools are
informed about the study in teacher conferences. This
information includes access to the project website which
features explanation videos about the MZo app and the
implementation of the study. Teachers will be provided
a login code to test the MZo app prior to
implementation in their class. If teachers decide to
participate in the study, two appointments for data
collection and for the introduction of the intervention
will be scheduled. Consent to participate in the study on

the student level has to be provided prior to baseline
assessment.

Assignment of interventions: allocation
Sequence generation {16a}
Randomization will be performed at the class level. The
randomization sequence has been created [38] using the
program “Randomization in Treatment Arms” (https://
www.evidat.com/rita). Classes of vocational schools will
be stratified by class characteristics and paired into
dyads of similar classes. The first member of a dyad will
have a 50% chance to be assigned to the intervention
group, and the remaining class will automatically be
assigned to the other trial arm.

Concealment mechanism {16b}
In the temporal order of study inclusion, allocation of
classes will be made according to the randomization
plan to either the MZo intervention or the control
group. Participants, teachers, and schools will have no
influence on the allocation process and assignment of
classes to either group, but they will not be blind to
randomization.

Implementation {16c}
Random allocation of classes within schools to either the
MZo intervention or the control group using the
randomization plan takes place at each study site under
the responsibility of the local study team. All students
who give their written consent (electronically) to
participate in the study will be enrolled. Unique
identifiers are generated using an ID-generator software
and will provide access to the electronic assessment por-
tal. The flow diagram of the study design is depicted in
Fig. 1.

Assignment of interventions: blinding
Who will be blinded {17a}
All participants, teachers, and schools will be blinded to
the randomization and allocation process. However, they
will not be blind to the MZo intervention, as
participants of the control group will be informed that
they will receive access to the MZo app after post-
assessment. Data analysts will be blinded.

Procedure for unblinding if needed {17b}
The design is open-label with only data analysts being
blinded so unblinding will not occur.

Data collection and management
Plans for assessment and collection of outcomes {18a}
Data will be collected class-wise in schools. The baseline
assessments will take place directly before the interven-
tion and the post-assessments at least 30 days after the

Arnaud et al. Trials (2022) 23:277 Page 6 of 10

end of the intervention. All measures are assessed via
the online system “SoSci Survey,” program version 3.2.12
(15.02.2021). All collected data is entered using partici-
pants’ personal smartphones. If individual smartphones
are unavailable or not functioning due to technical prob-
lems, the study teams will provide tablets to ensure data
collection. To guarantee a smooth online data assess-
ment, the study teams will also provide a portable LTE
router for a stable Internet connection in the classroom
if necessary. As for the MZo app and the online assess-
ment portal, compatibility with current Android and iOS
devices is given.

Plans to promote participant retention and complete
follow-up {18b}
According to their allocation, study participants will
complete the online questionnaires in class. Unique
identifiers are distributed by the study team and can be
used to access the questionnaire for pre- and post-
assessments. The same identifier can also be used to log
in to the MZo app. To maintain high retention rates be-
tween pre- and post-assessments, participants are en-
couraged to take a smartphone picture of their unique
identifier. To maximize data completeness, vocational
students who are absent from school on the day(s) of
the assessment will be contacted in a coordinated ap-
proach by their teachers.

Data management {19}
Online assessment data will automatically be transferred
to a local server at the study site in Kiel (SH),
minimizing errors of data entry. All participant data is
handled in accordance with the General Data Protection
Regulation (GDPR). All data will be maintained
confidentially before, during, and after the trial and is
stored securely at the study site in Kiel with access only
by dedicated study team members.

Confidentiality {27}
All data is collected using 6-digit unique identifiers to
access the online questionnaires. The first two digits of
this code identify the specific school, the next two digits
identify a particular class, and the last two digits that
identify an individual participant are randomly distrib-
uted. Single individuals cannot be identified.

Plans for collection, laboratory evaluation, and storage of
biological specimens for genetic or molecular analysis in
this trial/future use {33}
No biological specimens will be collected.

Statistical methods
Statistical methods for primary and secondary outcomes
{20a}
Analyses will account for the clustering of individuals in
school classes and will be reported following CONSORT
standards. Trial variables will be analyzed by the
intervention arm, into which participants were randomly
assigned. Continuous outcomes will be reported for each
trial arm using means and standard deviations, and
binary outcomes will be reported for each trial arm
using numbers and percentages. The main intervention
effects will be tested by means of logistic or linear multi-
level/random effects regression models with the levels
“classes” and “individuals,” whereby group and time vari-
ables as well as the interaction term group × time are
used. Primary between-group analyses will be adjusted
for baseline scores of the outcome variable, relevant co-
variates (baseline prognostic factors that are theoretically
associated with outcomes, including, but not limited to
age, gender, and migration background as well as the
personality traits sensation seeking and impulsiveness),
and those variables used to stratify randomization.

Interim analyses {21b}
No interim analysis will be performed.

Methods for additional analyses (e.g., subgroup analyses)
{20b}
For sensitivity analysis, unadjusted and complete case
(without imputation of missing data) analyses will
additionally be carried out for primary and secondary
outcomes. Potential moderators, such as individual
differences in socio-demographic factors (age, sex, etc.)
or vocational school-level factors (i.e., vocational sector,
etc.), and potential mediators (mechanisms of action)
such as self-efficacy or abstinence/reduction-related con-
trol beliefs will be explored in interaction analyses.

Methods in analysis to handle protocol non-adherence
and any statistical methods to handle missing data {20c}
Primary analyses will be based on the intention-to-treat
population, thus including data from all participants
who provide baseline data within a school class that was
previously randomly assigned to one of the two trial
conditions. Multiple imputation methods will be used to
estimate missing data.

Plans to give access to the full protocol, participant-level
data and statistical code {31c}
Anonymized study data and statistical codes will be
made available upon request given that data protection
according to GDPR and ethics according to ethical
approval are ensured.

Arnaud et al. Trials (2022) 23:277 Page 7 of 10

Oversight and monitoring
Composition of the coordinating center and trial steering
committee {5d}
The coordinating center is the primary sponsor of this
trial and is responsible for study supervision. The
coordinating investigators at the three study sites form a
steering committee for the study. They meet regularly
and are responsible for the critical review of the study
design, the study protocol, the data management, and all
the study-related documents. The coordinating investi-
gators provide oversight on the trial and support the
study team members who conduct and provide day-to-
day organizational support for the trial at each site. Fur-
thermore, the coordinating investigators are responsible
for the trial registration, revisions of the study protocol
and application/amendments to the ethics committee,
and scheduling of regular team meetings. All involved
investigators and team members ensure compliance with
the study protocol.

Composition of the data monitoring committee, its role,
and reporting structure {21a}
A Data Monitoring Committee is not considered
necessary as this is a low-risk intervention.

Adverse event reporting and harms {22}
Information on the occurrence of adverse events will be
documented. Adverse events related to the assessment
or use of the MZo app during the 2-week intervention
period will be recorded by the coordinating investigator.

Frequency and plans for auditing trial conduct {23}
The Project Group meets at least bi-weekly to review
the trial conduct throughout the trial period. There will
be no external auditing during the trial.

Plans for communicating important protocol amendments
to relevant parties (e.g., trial participants, ethical
committees) {25}
All protocol deviations or modifications will be
documented; all substantial protocol amendments will
be communicated to the ethics committee of the Center
for Psychosocial Medicine at the University Medical
Center Hamburg-Eppendorf, the responsible school au-
thorities at each study site (Center for Education Moni-
toring and Quality Development at schools in Hamburg,
IfBQ; the Center for Prevention at the Institute for Qual-
ity Development at Schools in Schleswig-Holstein,
IQ.SH; and the Bavarian State Ministry for Education
and Cultural Affairs), and the German Clinical Trials
Register, DRKS (DRKS00023788).

Dissemination plans {31a}
The study results will be presented at conferences and
symposia and will be submitted for publication in
relevant journals.

Discussion
The present study aims to transfer the voluntary abstinence
approach that has been established in regular schools to the
vocational school setting and extends it to digital media-
related addictive behaviors. This will be the first time that a
prevention program for vocational schools will be developed
and rigorously evaluated in a randomized study in Germany.
Moreover, the scientific evaluation of a fully app-based inter-
vention of this approach extends the literature on prevention
measures based on the voluntary commitment which up to
now has been mainly established in the form of the class
competition “Be smart – don’t start” [17].
If the trial results suggest that the approach is feasible

and effective, this could provide a much needed evidence-
based, relatively low-cost, and scalable program to reduce
substance use and Internet-related problems at vocational
schools in Germany. All MZo materials (explanation
video, app, MZo website) is designed to require minimal
effort and resources for schools/teachers. The “core inter-
vention material” is the MZo app which can be considered
credible for the target group since vocational students par-
ticipated in the process of conceptual development to
pilot testing for usability and acceptability.
To facilitate recruitment of vocational schools, the cluster

RCT design is limited to a convenience sample of vocational
schools willing to participate and a pre-post design. While
this approach may result in selection bias and limit conclu-
sions regarding long-term effectiveness, we consider this ap-
proach acceptable given that the study evaluates the
effectiveness of a newly developed intervention. Although the
recruited sample cannot be considered representative of vo-
cational schools in Germany, the generalizability of the re-
sults is facilitated by the inclusion of a broad range of
vocational sectors (i.e., service industries, business and ad-
ministrative professions as well as industrial-technical profes-
sions) within schools from three different states across
Germany. Moreover, implications for practice will be gained.
The study will contribute to the knowledge on how to effect-
ively implement the MZo intervention in (vocational)
schools. Finally, the inclusion of a range of potentially rele-
vant secondary outcomes, covariates, moderators, and medi-
ators in a reasonably large sample is expected to add to a
differential understanding of the trial results.

Trial status
Ongoing trial. Recruitment of participants started in
March 2021 and is expected to be completed in April
2022. Protocol version #1; protocol version date 1 April,
2022.

Arnaud et al. Trials (2022) 23:277 Page 8 of 10

Abbreviations
ASKU: Short Scale for Measuring General Self-efficacy Beliefs; AUDIT –
C: Alcohol Use Disorders Identification Test; BBGS: Brief Biosocial Gambling
Screen; BFAS: Bergen Facebook Addiction Scale; BMG: Federal Ministry of
Health Germany; CAMM: Child and Adolescent Mindfulness Measure;
CG: Control condition (group); CONSORT: Consolidated Standards for
Reporting Trials; DASS-21: Depression Anxiety Stress Scales 21; DRKS: German
Clinical Trials Register; GDPR: General Data Protection Regulation; ICC: Intra-
class correlation; ICD-11: International Classification of Diseases; IfBQ: Center
for Education Monitoring and Quality Development at schools in Hamburg;
IG: Intervention group; IGDS-SF: Internet Gaming Disorder Scale-Short-Form;
IQ.SH: Center for Prevention at the Institute for Quality Development at
Schools in Schleswig-Holstein; L1: General Life Satisfaction Short Scale;
MZo: “Meine Zeit ohne” [my time without]; PMH: Positive Mental Health
Scale; RCT: Randomized controlled trial; SDS: Severity of Dependence Scale;
SPIRIT: Standard Protocol Items: Recommendations for Interventional Trials;
SURPS: Substance Use Risk Profile Scale; WHO: World Health Organization

Acknowledgements
We would like to acknowledge Simone Leuckfeld, Freia Biedenweg, Laura
Borwieck, and Kristin Grahlher for their contributions to the study. We also
thank Regina Henkis, Gisela Mohr, Bernd Stüben, Armin Grzybek, and all
other persons involved in supporting the present study.

Authors’ contributions {31b}
MM, RH, NA, RT, KL, and LK conceived the study, initiated the study design,
and obtained funding. MM and BP are responsible for the data
management. MM, NA, KL, LK, JW, MR, and BP developed the methodology
for the intervention app and all study materials. NA and JW drafted the
manuscript. All authors commented on the drafts of the manuscript and
read and approved the final manuscript.

Funding {4}
Open Access funding enabled and organized by Projekt DEAL. The trial is
funded by the Federal Ministry of Health Germany (BMG, grant number:
ZMVI1-2519DSM216). The funding period is from 01 August 2019 to 31 De-
cember 2022. The funding source has no role in the design of this study and
will not have any role during its execution, analyses, interpretation of the
data, or decision to submit results.

Availability of data and materials {29}
The study material (information sheets) is available to the public and can be
found on the following website http://www.meine-zeit-ohne.de and by
request. The MZo application is suitable for iOS (iOS 11.0 or newer) and
Android (version 6 or newer) and is available in the app store for iOS devices
and Play Store for Android devices. Anonymized study data and statistical
codes for the analyses may be made available on request following study
closure.

Declarations

Ethics approval and consent to participate {24}
Approval for the study was obtained from the ethics committee of the
Center for Psychosocial Medicine at the University Medical Center Hamburg-
Eppendorf and the responsible school authorities at each study site (Center
for Education Monitoring and Quality Development at schools in Hamburg,
IfBQ; the Center for Prevention at the Institute for Quality Development at
Schools in Schleswig-Holstein, IQ.SH; and the Bavarian State Ministry for Edu-
cation and Cultural Affairs) prior to data collection. The study is conducted in
accordance with the CONSORT guidelines and complies with the principles
laid down in the Declaration of Helsinki [39]. It is registered in the DRKS pub-
lic database (trial registration number DRKS00023788). Written informed con-
sent will be obtained from all participants prior to study enrollment. All
substantial protocol deviations or modifications will be communicated to
the Ethics Committee and DRKS register.

Consent for publication {32}
Model consent forms will be provided on request.

Competing interests {28}
The authors declare that they have no competing interests.

Author details
1German Centre for Addiction Research in Childhood and Adolescence,
University Medical Centre Hamburg-Eppendorf, Hamburg, Germany. 2IFT
Institut für Therapieforschung, Munich, Germany. 3IFT-Nord Institute for
Therapy and Health Research, Kiel, Germany.

Received: 31 January 2022 Accepted: 27 March 2022

References
1. Stockings E, Hall WD, Lynskey M, Morley KI, Reavley N, Strang J, et al.

Prevention, early intervention, harm reduction, and treatment of substance
use in young people. Lancet Psychiatry. 2016;3(3):280–96. https://doi.org/1
0.1016/S2215-0366(16)00002-X.

2. Mokdad AH, Forouzanfar MH, Daoud F, Mokdad AA, el Bcheraoui C, Moradi-
Lakeh M, et al. Global burden of diseases, injuries, and risk factors for young
people’s health during 1990–2013: a systematic analysis for the Global
Burden of Disease Study 2013. Lancet. 2016;387(10036):2383–401. https://
doi.org/10.1016/S0140-6736(16)00648-6.

3. Pabst A, Kraus L, de Matos EG, et al. Substanzkonsum und
substanzbezogene Störungen in Deutschland im Jahr 2012. Sucht. 2013;
59(6):321–31. https://doi.org/10.1024/0939-5911.a000275.

4. Arnett JJ. Adolescent storm and stress, reconsidered. Am Psychol. 1999;
54(5):317–26. https://doi.org/10.1037/0003-066X.54.5.317.

5. Jordan CJ, Andersen SL. Sensitive periods of substance abuse: early risk for
the transition to dependence. Dev Cogn Neurosci. 2017;25:29–44. https://
doi.org/10.1016/j.dcn.2016.10.004.

6. Wartberg L, Kriston L, Thomasius R. The prevalence and psychosocial
correlates of Internet gaming disorder. Dtsch Arztebl Int. 2017;114(25):419–
24. https://doi.org/10.3238/arztebl.2017.0419.

7. Mann K, Fauth-Bühler M, Higuchi S, Potenza MN, Saunders JB. Pathological
gambling: a behavioral addiction. World Psychiatry. 2016;15(3):297–8.
https://doi.org/10.1002/wps.20373.

8. Brand M, Wegmann E, Stark R, Müller A, Wölfling K, Robbins TW, et al. The
Interaction of Person-Affect-Cognition-Execution (I-PACE) model for
addictive behaviors: update, generalization to addictive behaviors beyond
internet-use disorders, and specification of the process character of
addictive behaviors. Neurosci Biobehav Rev. 2019;104:1–10. https://doi.org/1
0.1016/j.neubiorev.2019.06.032.

9. Dong H, Yang F, Lu X, Hao W. Internet addiction and related psychological
factors among children and adolescents in China during the coronavirus
disease 2019 (COVID-19) epidemic. Front Psychiatry. 2020;11:751. https://doi.
org/10.3389/fpsyt.2020.00751.

10. Arnaud N, Thomasius R. Disorders due to substance use or addictive
behaviours in the ICD-11 [Störungen durch Substanzgebrauch und
abhängige Verhaltensweisen in der ICD-11]. Z Kinder Jugendpsychiatr
Psychother. 2020;49(6):486–93. https://doi.org/10.1024/1422-4917/a000748.

11. Onrust SA, Otten R, Lammers J, Smit F. School-based programmes to
reduce and prevent substance use in different age groups: what works for
whom? Systematic review and meta-regression analysis. Clin Psychol Rev.
2016;44:45–59. https://doi.org/10.1016/j.cpr.2015.11.002.

12. Morgenstern M, Seidel A-K, Hanewinkel R. Suchtprävention an beruflichen
Schulen. Bildung und Beruf. 2019;2:50–7.

13. Bray JW, Galvin DM, Cluff LA. Young adults in the workplace: a multisite
initiative of substance use prevention programs. Res Triangle Parc: NC. 2011.

14. Uhly A. A5 Ausbildung im dualen Ausbildungssystem – Analysen auf Basis
der Berufsbildungsstatistik. Bundesinstitut für Berufsbildung: Datenreport;
2017. https://www.bibb.de/datenreport/de/2017/63477.php. Accessed 13
Dec 2021

15. Montag J, Hanewinkel R, Morgenstern M. Prevalence and correlates of
substance use in 5 688 vocational school students [Verbreitung und
Korrelate des Substanzkonsums unter 5 688 Auszubildenden an beruflichen
Schulen]. Das Gesundheitswesen. 2015;77(6):411–7. https://doi.org/10.1055/
s-0034-1382043.

16. Kaess M, Parzer P, Brunner R, Koenig J, Durkee T, Carli V, et al. Pathological
Internet use is on the rise among European adolescents. J Adolesc Health.
2016;59(2):236–9. https://doi.org/10.1016/j.jadohealth.2016.04.009.

17. Hanewinkel R, Wiborg G, Abdennbi K, Ariza C, Bollars C, Bowker S, et al.
European smokefree class competition: a measure to decrease smoking in
youth. J Epidemiol Community Health. 2007;61(8):750–750; author reply 751.
https://doi.org/10.1136/jech.2006.057224.

Arnaud et al. Trials (2022) 23:277 Page 9 of 10

18. Isensee B, Hanewinkel R. Tabakprävention im Setting Schule am Beispiel
von “Be smart–don’t start”. Bundesgesundheitsblatt-Gesundheitsforschung-
Gesundheitsschutz. 2018;61(11):1446–52. https://doi.org/10.1007/s00103-01
8-2825-9.

19. Kalke J, Raschke P, Buth S. Initiierte Abstinenz. Prävention und
Gesundheitsförderung. 2006;1(4):219–26. https://doi.org/10.1007/s11553-006-
0034-0.

20. Brailovskaia J, Ströse F, Schillack H, Margraf J. Less Facebook use–more
well-being and a healthier lifestyle? An experimental intervention study.
Comput Hum Behav. 2020;108:106332. https://doi.org/10.1016/j.chb.202
0.106332.

21. Wohlert RH-J, T, Freyer-Adam J, Grothues J, Bischof G. Screening
questionnaires for problem drinking in adolescents: performance of AUDIT,
AUDIT-C, CRAFFT and POSIT. Eur Addict Res. 2013;19(3):121–7. https://doi.
org/10.1159/000342331.

22. Pontes HM, Griffiths MD. Measuring DSM-5 Internet gaming disorder:
development and validation of a short psychometric scale. Comput Hum
Behav. 2015;45:137–43. https://doi.org/10.1016/j.chb.2014.12.006.

23. Montag C, Schivinski B, Sariyska R, Kannen C, Demetrovics Z, Pontes HM.
Psychopathological symptoms and gaming motives in disordered
gaming—a psychometric comparison between the WHO and APA
diagnostic frameworks. J Clin Med. 2019;8(10):1691. https://doi.org/10.3390/
jcm8101691.

24. Andreassen CS, Torsheim T, Brunborg GS, Pallesen S. Development of a
Facebook addiction scale. Psychol Rep. 2012;110(2):501–17. https://doi.org/1
0.2466/02.09.18.PR0.110.2.501-517.

25. Brailovskaia J, Margraf J. Facebook addiction disorder (FAD) among German
students—a longitudinal approach. PLoS One. 2017;12(12):e0189719.
https://doi.org/10.1371/journal.pone.0189719.

26. Martin G, Copeland J, Gates P, Gilmour S. The Severity of Dependence Scale
(SDS) in an adolescent population of cannabis users: reliability, validity and
diagnostic cut-off. Drug Alcohol Depend. 2006;83(1):90–3. https://doi.org/1
0.1016/j.drugalcdep.2005.10.014.

27. Steiner S, Baumeister SE, Kraus L. Severity of dependence scale: establishing
a cut-off point for cannabis dependence in the German adult population.
SUCHT. 2008;54(7):57–63. https://doi.org/10.1024/2008.07.07.

28. Gebauer L, LaBrie R, Shaffer HJ. Optimizing DSM-IV-TR classification accuracy:
a brief biosocial screen for detecting current gambling disorders among
gamblers in the general household population. Can J Psychiatr. 2010;55(2):
82–90. https://doi.org/10.1177/070674371005500204.

29. Lovibond PF, Lovibond SH. The structure of negative emotional states:
comparison of the Depression Anxiety Stress Scales (DASS) with the Beck
Depression and Anxiety Inventories. Behav Res Ther. 1995;33(3):335–43.
https://doi.org/10.1016/0005-7967(94)00075-U.

30. Nilges P, Essau C. Die Depressions-Angst-Stress-Skalen: Der DASS – ein
Screeningverfahren nicht nur für Schmerzpatienten. Schmerz. 2015;29(6):
649–57. https://doi.org/10.1007/s00482-015-0019-z.

31. Woicik PA, Stewart SH, Pihl RO, Conrod PJ. The substance use risk profile
scale: a scale measuring traits linked to reinforcement-specific substance
use profiles. Addict Behav. 2009;34(12):1042–55. https://doi.org/10.1016/j.a
ddbeh.2009.07.001.

32. Greco LA, Baer RA, Smith GT. Assessing mindfulness in children and
adolescents: development and validation of the Child and Adolescent
Mindfulness Measure (CAMM). Psychol Assess. 2011;23(3):606–14. https://doi.
org/10.1037/a0022819.

33. Lukat J, Margraf J, Lutz R, van der Veld WM, Becker ES. Psychometric
properties of the Positive Mental Health Scale (PMH-scale). BMC Psychol.
2016;4(1):1–14. https://doi.org/10.1186/s40359-016-0111-x.

34. Cheung F, Lucas RE. Assessing the validity of single-item life satisfaction
measures: results from three large samples. Qual Life Res. 2014;23(10):2809–
18. https://doi.org/10.1007/s11136-014-0726-4.

35. Beierlein C, Kovaleva A, László Z, Kemper CJ, Rammstedt B. Kurzskala zur
Erfassung der Allgemeinen Lebenszufriedenheit (L-1). Zusammenstellung
sozialwissenschaftlicher Items und Skalen (ZIS). 2015. https://doi.org/10.61
02/zis229 Accessed 21 Dec 2021.

36. Beierlein C, Kovaleva A, Kemper C, Rammstedt B. Allgemeine
Selbstwirksamkeit Kurzskala (ASKU). Zusammenstellung
sozialwissenschaftlicher Items und Skalen (ZIS). 2014. https://doi.org/10.61
02/zis35 Accessed 21 Dec 2021.

37. Miller WR, Rollnick S. Motivational interviewing: helping people change. 3rd
ed. New York: Guilford Press; 2013.

38. Pahlke F, König IR, Ziegler A. Randomization in treatment arms (RITA): Ein
Randomisierungs-Programm für klinische Studien. Inform Biom Epidemiol
Med Biol. 2004;35:1–22.

39. World Medical Association Declaration of Helsinki: ethical principles for
medical research involving human subjects. JAMA 2013; 310: 2191-2194, 20,
https://doi.org/10.1001/jama.2013.281053.

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