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Feasibility and potential efficacy of a guided internet- and mobile-based CBT for adolescents and young adults with chronic medical conditions and comorbid depression or anxiety symptoms (youthCOACHCD): a randomized controlled pilot trial



Adolescents and young adults (AYA) with a chronic medical condition show an increased risk for developing mental comorbidities compared to their healthy peers. Internet- and mobile-based cognitive behavioral therapy (iCBT) might be a low-threshold treatment to support affected AYA. In this randomized controlled pilot trial, the feasibility and potential efficacy of youthCOACHCD, an iCBT targeting symptoms of anxiety and depression in AYA with chronic medical conditions, was evaluated.


A total of 30 AYA (Mage 16.13; SD= 2.34; 73% female), aged 12-21 years either suffering from cystic fibrosis, juvenile idiopathic arthritis or type 1 diabetes, were randomly assigned to either a guided version of the iCBT youthCOACHCD (IG, n=15) or to a waitlist control group (CG, n=15), receiving an unguided version of the iCBT six months post-randomization. Participants of the IG and the CG were assessed before (t0), twelve weeks after (t1) and six months after (t2) randomization. Primary outcome was the feasibility of the iCBT. Different parameters of feasibility e.g. acceptance, client satisfaction or potential side effects were evaluated. First indications of the possible efficacy with regard to the primary efficacy outcome, the Patient Health Questionnaire Anxiety and Depression Scale, and further outcome variables were evaluated using linear regression models, adjusting for baseline values.


Regarding feasibility, intervention completion was 60%; intervention satisfaction (M = 25.42, SD = 5.85) and perceived therapeutic alliance (M = 2.83, SD = 1.25) were moderate and comparable to other iCBTs. No patterns emerged regarding subjective and objective negative side effects due to participation in youthCOACHCD. Estimates of potential efficacy showed between group differences, with a potential medium-term benefit of youthCOACHCD (β = -0.55, 95%CI: -1.17; 0.07), but probably not short-term (β = 0.20, 95%CI: -0.47; 0.88).


Our results point to the feasibility of youthCOACHCD and the implementation of a future definitive randomized controlled trial addressing its effectiveness and cost-effectiveness. Due to the small sample size, conclusions are premature, however, further strategies to foster treatment adherence should be considered.

Trial registration

The trial was registered at the WHO International Clinical Trials Registry Platform via the German Clinical Trials Register (ID: DRKS00016714, 25/03/2019).

Peer Review reports


Worldwide, approximately 15-20% of adolescents and young adults (AYA) live with chronic medical conditions [1]. In recent decades the incidence rate increased [2]. Chronic conditions can impact the cognitive, physical, social and emotional development of afflicted AYA beyond the usual developmental challenges at this age [3]. In comparison to their healthy peers, young people with a chronic medical condition report elevated internalizing and externalizing behavior problems. Particularly, symptoms of anxiety and depression are increased in AYA with chronic conditions in comparison to their healthy peers [4, 5]. Comorbid mental health issues can have an important impact on AYAs’ quality of life, disease course, regime adherence and medical outcomes [6].

In adolescence, worsening in inborn or acquired disease state can be found. Therefore, research in clinical practice has been focused to improve clinical outcomes [7]. Nonetheless, the significant impact of mental comorbidities on clinical outcome parameters as well as quality of life highlights the need for a multidisciplinary approach [8]. Especially, as the prevalence of mental disorders generally increases in adolescence compared to childhood [9].

Treatment guidelines recommend cognitive behavioral therapy (CBT) as first line approach for AYA with mental health issues (e.g. [10]). There is a growing evidence base reporting on the effectiveness of CBT for the prevention and treatment of anxiety and depression symptoms in AYA [11, 12]. Studies also suggest the effectiveness of CBT when specifically targeting AYA with chronic conditions and comorbid symptoms of anxiety and depression [13]. However, access to psychological and behavioral interventions is limited for many patients. Only a small proportion of AYA with chronic conditions in need of mental health services actually receives professional support [6, 14, 15]. In a Dutch web-survey of AYA with type 1 diabetes (T1D) only 28% of participants with symptoms of depression received psychological care [15]. Unmet health care needs highly impact AYAs’ physical and mental health outcomes in adulthood [16]. Reasons for this mental health care gap might be a lack of financial and personnel resources, structural reasons, such as healthcare systems, availability of resources, as well as personal reasons such as lack of problem awareness, lack of time, living in rural areas, fear of stigmatization and distrust towards mental health care [15,16,17,18].

As an opportunity to overcome some of the challenges associated with traditional face-to-face mental health care, internet- and mobile-based interventions (IMI) have been suggested. In the general population of AYA, IMI, especially based on CBT (iCBT), have been shown to be efficacious in reducing symptoms of anxiety and depression [19]. The evidence for utilizing IMI on AYA with chronic conditions points to their feasibility and effectiveness [20]. However, only a few studies focus on the efficacy of IMI targeting AYA with a chronic condition and comorbid mental health disorders. Meta-analyses include only a small number of studies focusing exclusively on internalizing symptoms. These studies showed limited methodological quality and indicate limited efficacy [21, 22]. Therefore, we aimed to develop a user-centered iCBT for AYA with a chronic medical condition and comorbid symptoms of anxiety and depression and evaluate its potential efficacy in an appropriate study design in the framework of the COACH project (Chronic conditions in adolescents: implementation and evaluation of patient-centered collaborative healthcare). The iCBT, called youthCOACHCD (CD = Chronic conditions) is intended to provide an evidence-based low-threshold service for this target group. In addition to reducing symptoms of anxiety and depression, youthCOACHCD aims to support AYA in dealing with further potential symptoms of mental disorders that are highly important in adolescence and when living with a chronic medical condition: potential symptoms of post-traumatic stress disorder due to (treatment of) the chronic condition [23]; risk-taking behaviors such as excessive alcohol consumption, often associated with symptoms of anxiety and depression [24, 25]; coping with the chronic condition; self-efficacy [26].

The intervention development and evaluation are conducted within the framework of the multi-center interdisciplinary COACH project. COACH focusses on AYA with cystic fibrosis (CF), juvenile idiopathic arthritis (JIA) or T1D. The reason for selecting these chronic medical conditions is to cover a broad spectrum of diseases with different requirements and burdens for AYA. In order to develop a user-centered iCBT program and thus to increase the effectiveness of and engagement with youthCOACHCD, the intervention program is developed in three steps. In a first step, qualitative research is conducted to determine concerned AYA needs and preferences for the program [27]. Second, a feasibility trial is conducted to ensure the acceptance, feasibility and potential efficacy of youthCOACHCD. Third, a large scale randomized controlled trial is conducted to evaluate the (cost-) effectiveness of youthCOACHCD [28]. Here we report on the results of the second step, the feasibility trial. As recommended by the CONSORT statement, the primary aim of these studies is the assessment of the feasibility of conducting a future definitive trial [29]. Therefore, we focus on the following objectives:

  1. 1.

    Is youthCOACHCD feasible and accepted as measured by adherence and dropout rates, formative user feedback, potential side effects, interventions satisfaction, and therapeutic alliance?

  2. 2.

    Does youthCOACHCD potentially have a short- and medium-term efficacy in terms of improved symptoms of anxiety and depression, coping with the disease, health-related quality of life, self-efficacy, post-traumatic growth, reduced symptoms of post-traumatic stress disorder, less alcohol consumption, and perceived social support in comparison to a waiting list control group?


A randomized controlled feasibility trial was conducted comparing the guided iCBT youthCOACHCD (IG) with a waiting list control group (CG) receiving the unguided youthCOACHCD program six months post-randomization. The study is reported and was conducted in accordance with the CONSORT statement for feasibility trials [29], approved by the ethics committee of Ulm University (Number 292/18) and a-priori registered at the WHO International Clinical Trials Registry Platform via the German Clinical Trials Register (ID: DRKS00016714, 25/03/2019). Please note, we changed the primary study aim from potential efficacy (as described in the study registration) to feasibility in order to emphasize the explorative design of this trial.


AYA (1) aged between 12 and 21 years, (2) reporting to have CF, JIA or T1D (self-report) were eligible for participation in case of (3) available internet access and (4) providing informed consent for participation. We included AYA with a broad range of symptoms of anxiety and depression in order to generate knowledge regarding the accessibility, usefulness and feasibility of youthCOACHCD across the mental health strains spectrum. Therefore, there was no cut-off scores for the self-reported symptoms of depression and anxiety to be involved in the study. Additionally, having a score > 1 in the ninth item of the Beck Depression Inventory revision (BDI-II item = 0: “I’m not thinking of harming myself.”, BDI-II item = 1: “I have thoughts of killing myself, but I would not carry them out.”, BDI-II item = 2: “I would like to kill myself.”, BDI-II item = 3: “I would kill myself if I had the chance.”) at baseline measurement was an exclusion criterion [30]. Participants stating a BDI-II Item 9 = 1, received an online information letter with detailed information on available health services and the advice to use professional help, but were not excluded from the study. All inclusion criteria were based on the self-reports of the participants.

Recruitment of Participants

Between April 2019 and May 2020 an open recruitment strategy was applied to AYA living in Germany: social media posts in chronic condition related self-help groups, flyers in medical practices and clinics, or information to e-mail distribution lists of self-help groups. Interested AYA contacted the study team via e-mail. AYA eligible for inclusion had to return their informed consent, in case of AYA younger than 16 years, informed consent had to be provided by caregivers as well. Additionally, participants were asked to name a caregiver for others assessments about the AYA. Caregivers needed to be 18 years of age or older and provide written informed consent for inclusion as third person assessor of AYAs’ health.

Sample Size

A formal sample size calculation was not performed, given the feasibility character of this trial. The number of participants was estimated at around 10% of the calculated sample size required for the definitive RCT (n = 212) and we anticipated a high dropout rate of 50%, resulting in a sample size of n = 30 [31].


Randomization was performed at the individual level by a person not otherwise involved in the trial process applying a permuted block randomization with an allocation ratio of 1:1 and variable 4, 6 and 8-block sizes. Random allocation was computer-generated using the program Sealed Envelope [32]. Members of the study team who were concerned with outcome assessment, were blinded and did not receive any information about the participants’ group allocation.

Intervention Protocol

The intervention program youthCOACHCD was developed by the department of clinical psychology and psychotherapy at Ulm University. youthCOACHCD is CBT-based and consists of an introductory session and seven modules. A description of the specific module contents can be found elsewhere [28]. All intervention contents are presented in a youth-oriented and varied manner (i.e. video-, audio-, illustration- and text-based content presentation; writing-based or multiple-choice tasks and quizzes). Stories of three fictional AYA with a chronic condition and symptoms of depression and anxiety are implemented in every module in order to facilitate identification. Intervention content and design were informed by focus groups conducted with potential users of youthCOACHCD [27].

AYA were recommended to complete one module per week. AYA in the IG were allocated to one of two eCoaches who were graduates of a Master’s Degree in Psychology and were enrolled in a training program in CBT with children and adolescents. eCoaches were supervised by two licensed psychotherapists and provided semi-standardized, asynchronous feedback after each completed module, including positive reinforcement and motivation, based on principles of CBT [28]. Participants of the IG were asked to schedule an appointment for completing their next module and were reminded by their eCoach, if they did not stick to their appointment or managed to work on their modules for an extended period of time. First, three reminding messages of the eCoach were sent to the participant (2, 5 and 8 days after the scheduled appointment). In order to use an additional contact medium, the non-blinded members of the study team attempted to reach the participant by phone, three times over a period of two weeks. Participants were asked for potential reasons for not completing their modules (e.g. technical difficulties). If the contact attempt failed, these participants were regarded as dropouts.

In addition to the seven modules, AYA were advised to keep a daily mood diary, which is offered on a mobile app [33]. This was intended to support the transfer of the intervention contents into everyday life. Furthermore, the app provided daily motivational prompts.

youthCOACHCD was implemented via the secure online platform Minddistrict [33]. Participants of the CG were given access to the unguided version of youthCOACHCD six months after the randomization. Participants of both the CG and the IG could make use of any offers of additional routine care and were informed about these via flyer.


Participants of both the IG and the CG were invited to participate in self-report surveys at three time points: Baseline (t0), twelve weeks post-randomization (t1) and six months post-randomization (t2, follow-up measurement), regardless of the extent to which AYA of the IG have completed the intervention process. Surveys were implemented on the secure platform Unipark [34]. Participants were invited by e-mail. If they did not respond to the invitation, they were reminded by e-mail and phone calls. AYA received 10€ for each completed survey as compensation. Named caregivers also completed surveys at the same three measurement points. Table 1 presents an overview of all applied measurement instruments and assessment time points. A detailed description of the measurement instruments can be found elsewhere [28].

Table 1 Outcome assessment and assessment time point, if applicable

Statistical Analysis

To answer the main objective of this study – the feasibility of youthCOACHCD – the following measurements were analyzed: adherence and dropout rates, formative user feedback, potential side effects, intervention satisfaction, and therapeutic alliance. Adherence and dropout rates, participant scores in the assessment of intervention satisfaction, as well as therapeutic alliance were compared to the results reported in other clinical trials on IMI targeting AYA. Comparable results pointing to feasibility of the trial were discussed. Furthermore, potential side effects were measured by the INEP-On as well as the Internet Usage Expectancies Scale. If a pattern in the participants’ answers on the INEP-On had emerged, that would have been discussed as a side effect. Additionally, decreased internet usage would have be rated as another side effect.

Data was analyzed using R [55]. Participants’ characteristics and all outcome variables are described descriptively (mean, standard deviation, frequency, percentage). Potential group differences at post-randomization measurement points are investigated using linear regression models, adjusting for baseline values for continuous outcomes. All continuous variables were z-standardized, and dummy-coding was applied to dichotomous variables. Potential outliers, which bear the risk of biasing results, were identified using scatter plot and Cook`s distance [56,57,58]. Because the sample size in this feasibility trial has low statistical power, corresponding 95%-confidence intervals are reported for each outcome, but we refrained from reporting p-values [29, 59]. Furthermore, the standardized regression coefficient as well as Cohen’s d for between group differences and the corresponding 95%-confidence intervals are reported. Sensitivity analysis showed no crucial differences between data imputed by multivariate imputation by chained equations [60] with predictive mean matching method and observed data. Therefore, we decided to report on the observed data only. All efficacy analyses are based on an intention-to-treat (ITT). Furthermore, to get a comprehensive idea of the potential effectiveness, analysis based on per-protocol (PP) principle were conducted. PP was defined as participants completing 80% of the modules up to t1. In the forthcoming confirmative RCT, only AYA with clinically relevant symptoms of depression and/ or anxiety will be involved. In this feasibility trial we also included AYA without clinically relevant symptoms due to ethical reasons. Therefore, additional sub-group analyses for AYA with clinically relevant symptoms of depression and / or anxiety (PHQ-9 or GAD-7 score 7) [61, 62] were conducted. Because of this feasibility trial’s low sample size, a cost-analysis based on the CAMSHRI-DE is not applicable. Therefore, we only conducted descriptive analysis of service use according to the CAMSHRI-DE.

Regarding the CONSORT guidelines for feasibility trials, the analysis of mediating and moderating effects with a sample of n = 30 is not applicable [29]. Therefore, only changes in behavioral activation and automatic thoughts that might have a mediating effect, are reported.


Recruitment and Baseline Characteristics of Participants

Thirty-three AYA were assessed for eligibility and provided informed consent. Thirty AYA completed baseline measurements and were included for randomization. The mean age of randomized AYA was M = 16.13 (SD = 2.34). Of the participants, 73% were female. Furthermore, 13% of AYA reported having CF, 37% JIA, and 50% T1D. Average depression and anxiety symptom burden was M = 12.83 (SD = 7.48). Detailed information on baseline sample characteristics is provided in Table 2. Of participants (IG: n = 8; CG: n = 7), 50% showed symptoms of anxiety and/ or depression above a cut-off score of PHQ-9 or GAD-7 7.

Almost all participants reported having been treated by a general practitioner or paediatrician (24/30) and a disease-specific physician (29/30) during the 9-month reporting period. Several participants reported having used further medical/therapeutic care services: inpatient care (8/30), physiotherapy (13/30), psychotherapy (6/30) and ergotherapy (5/30). School-based services (especially additional support through the class teacher) and social services were only used by a small percentage of the participants (6/30 or 5/30, respectively). The median number of medications taken or medical devices used is 2.0 each (supplementary material Table A.2).

Table 2 Participant characteristics at baseline per group and overall

Feasibility Outcomes

Intervention adherence

Of the participants in the IG (n = 15), nine (60%) completed all seven modules; one completed three modules (7%); one completed the introductory module (7%) and four (27%) never began the intervention. Reasons for no uptake of the intervention were: no motivation, changes in life circumstances, too much time or effort required. AYA who completed all seven modules needed between five to 32 weeks. The participant who needed 32 weeks interrupted the intervention for personal reasons. The median for intervention duration was eleven weeks. 33% of AYA completing all modules completed questionnaires twelve weeks post-randomization before they had finished all modules.

Of the IG, six participants completed 80% of the modules up to t1 (a-priori defined as adherent; 40%). This subsample was included in per protocol analyses on efficacy outcomes.

AYA of the IG used the daily mood diary 0 to 46 times, with a median of 6 times. Including only adherent participants of the IG, median usage was 19 times (range: 1- 46).

Study dropout

Of the included 30 participants, 24 completed all questionnaires (80%; IG: 80%, CG%: 80%), pointing to a study dropout of 20% (Fig. 1).

Fig. 1
figure 1

CONSORT flow chart displaying participant flow through the study

Formative feedback

Seven participants of the IG provided feedbacks across the seven modules on time needed per module: 33% reported to spent 10-30 min, 54% 30-50 min, 7% 50-70 min, 3% 70-90 min and 3% 90-120 min. 87% perceived the length of the modules as appropriate, 5% as too long and 8% as too short. No AYA provided negative qualitative feedback. 17 positive qualitative feedbacks across modules were provided. These solely included individual tasks that were perceived to be particularly helpful.

Subjective side effects

Potential side effects of the participation in youthCOACHCD were assessed twelve weeks and six months post-randomization in the IG. Based on INEP-On, AYA of the IG reported overall 45 negative, 146 neutral, and 66 positive effects twelve weeks after randomization and 41 negative, 149 neutral, and 66 positive effects six months post-randomization. Eight AYA reported at least one negative effect attributed to the intervention. In detail, at twelve weeks and six months post-randomization AYA linked 22% (n = 10) and 32% (n = 13) of the negative effects, 24% (n = 35) and 24% (n = 36) of the neutral effects, and 67% (n = 44) and 73% (n = 48) of the positive effects to the intervention. The most often reported negative effects twelve weeks post-randomization were difficulties in making decisions alone (n = 5, 0% attributed to intervention), longer periods of feeling bad (n = 5, 0% attributed to intervention) and decreased motivation to start a psychotherapeutic treatment (n = 5, 80% attributed to intervention). The most reported negative effects six months post-randomization were: financial worries (n = 5, 20% attributed to intervention) and difficulties in making decisions alone (n = 5, 0% attributed to intervention). A detailed overview for both measurement time points can be found in the supplementary material (Table A.3 and Table A.4).

Suicidal ideation

Suicidal thoughts without intention to realize them, occurred twice at baseline measurement, once at t1, and twice at t2. The participants stated a BDI-II Item 9 = 1.

Satisfaction with intervention

Of the IG, twelve AYA reported mean satisfaction with youthCOACHCD of M = 25.42 (SD = 5.85) at twelve weeks post-randomization and of M = 26.50 (SD = 4.68) six months post-randomization (measured by the CSQ-I: potential sum score range 8-32). In addition, 58% would recommend the intervention to a friend, 17% would likely recommend it, 17% would partly recommend it, and 8% would not recommend youthCOACHCD to a friend.

Therapeutic alliance

In the IG, twelve participants rated the therapeutic alliance with the WAI-SR questionnaire (range per scale: 1-5) twelve weeks post-randomization on the scales bond (M = 2.77, SD = 1.26), task (M = 2.82, SD = 1.20) and goal (M = 2.91, SD = 1.35). The overall mean was M = 2.83 (SD = 1.25). The six months post-randomization bond was rated with M = 2.75 (SD = 1.13), task with M = 3.06 (SD = 1.06) and goal with M = 3.15 (SD = 0.97). Resulting in an overall mean of 2.99 (SD = 1.00) six months post-randomization.

Internet usage

The internet usage behavior (in hours per week) decreased in the IG (see Table 3). Additionally, changes in expectations of using the internet measured by the IUES are presented in Table 4.

Efficacy outcomes

Graphical illustration and Cook’s distance revealed two outliers regarding symptom change (PHQ-ADS) from baseline to twelve weeks post-randomization. Both outliers belonged to the IG. In ITT-analysis, there were non-significant changes in the primary efficacy outcome, symptoms of anxiety and depression, in the IG in comparison to the CG twelve weeks post-randomization (β = 0.20, 95%-CI: [-0.47; 0.88]) and six months post-randomization (β= -0.55, 95%-CI: [-1.17; 0.07]) when adjusting for baseline values. Table 3 presents all means and standard deviations for all outcomes in the CG and IG. Data on all efficacy outcomes are presented in Table 4.

Subsample analysis based on ITT-analysis, including n = 14 participants reporting symptoms of anxiety and/ or depression above a cut off score of PHQ-9 or GAD-7 7 at baseline measurement (IG: M = 21.41, SD = 16.71; CG: M = 16.71, SD = 4.53) revealed non-significantly higher symptom scores (PHQ-ADS) in the IG compared to the CG twelve weeks post-randomization (β = 0.27, 95%-CI: [-0.96; 1.51]) and non-significantly lower symptom scores (PHQ-ADS) six months post-randomization (β = -0.53, 95%-CI: [-1.84; 0.77]), adjusted for baseline scores. Data on all efficacy outcomes, based on participants with clinically relevant or no clinically relevant symptoms of anxiety and depression, are presented in the supplementary material (Table A.5 and Table A.6).

Additionally, per protocol analysis showed non-significant difference between the IG and the CG regarding PHQ-ADS score twelve weeks post-randomization (β = 0.07, 95%-CI: [-0.78; 0.91]) and six months post-randomization (β = -0.52, 95%-CI: [-1.33; 0.28]), adjusted for baseline scores. Detailed information on results of the per protocol analysis can be found in the supplementary material (Table A.7).

Table 3 Means and standard deviations for the intervention group and waiting list control group
Table 4 Results of linear regression models and Cohen’s d for efficacy outcomes at post-treatment (t1) and 6-month follow-up (t2) based on ITT analyses

Caregiver report

Baseline measurements were provided by twenty caregivers (IG: n = 10; CG: n = 10). Of these 19 (IG: n = 10; CG: n = 9) caregivers also provided measurements twelve weeks or six months post-randomization (95% female, Mage = 45.51, SDage = 5.15). Symptoms of anxiety (β = -0.30, 95%-CI: [-1.16; 0.57]) or depression (β = -0.18, 95%-CI: [-0.93; 0.58]) of AYA reported by caregivers have not significantly changed twelve weeks and six months (anxiety: β = -0.20, 95%-CI: [-1.14; 0.73]; depression: β = - 0.20, 95%-CI: [-0.84; 0.44]) post-randomization. Detailed information on mean and standard deviation on all caregiver reported outcomes as well as results of linear regression analyses of all other caregiver reported outcome changes can be found in the supplementary material (Table A.8 and Table A.9).


This randomized controlled pilot trial evaluated the feasibility and potential efficacy of an iCBT for AYA with a chronic medical condition and comorbid symptoms of anxiety and/ or depression. To our knowledge, this is the first iCBT intervention for this specific target group in Germany. Feasibility of youthCOACHCD was supported and no severe side effects were reported. Feasibility was operationalized by adherence and dropout rate, formative user feedback, potential side effects, interventions satisfaction, and therapeutic alliance.

We observed a study dropout rate of 20%. In comparison to reported treatment dropout rates from efficacy studies among children and adolescents in an outpatient mental health care setting [63] as well as to these reported from internet-based interventions for mental disorders in AYA [64, 65], this rate is above average. Hence, the applied close reminder procedure by e-mail and phone should be maintained.

The observed intervention adherence rate of 40% in the IG is restricted but comparable to common adherence rates reported in self-management IMIs targeting AYA [66]. It might be valuable to consider further strategies to increase intervention adherence. In addition to the aforementioned close reminder procedure by the study team or the eCoaches, strategies of the Persuasive System Design principle (PSD; [67]) could be valuable in order to prevent non-adherence during intervention completion. Principles of the PSD framework aim to optimize the human-machine interaction and therefore influence users’ attitudes and behaviors [68]. Implementing PSD in IMI showed positive effects on treatment adherence, effectiveness and user satisfaction before [66, 69]. Increasing the trustworthiness and competence of an intervention is one of the four PSD key principles (system credibility). Given that twelve weeks post-randomization 33% of participants reported concerns about data security (INEP-On), optimizing youthCOACHCD with regard to system credibility could be valuable. Additionally, improving the interaction between the user and intervention system is a further core feature of the PSD [67]. One potential strategy to realize this principle could be the implementation of further gamification approaches [70]. In the current version of youthCOACHCD, participants have the opportunity to download a certificate for every completed module. This reward procedure might be more effective if rewards would be presented in a more gamified manner, e.g. by collecting badges or trophies for every completed task [71, 72]. Furthermore, an avatar accompanying the AYA through the intervention could increase the social role and liking of the intervention and therefore might be valuable for users’ adherence [73]. Incorporating peer support is a further PSD principle. For example, consideration could be given to including a feature that allows participants to remind each other to complete the mood diary and thus collect rewards together. This could potentially increase the reported low engagement with the mood diary. However, further studies are required regarding the potential effectivity of such peer support features [69]. Participants of the focus groups which were conducted before the development of youthCOACHCD did not reach consent whether they would like such peer support features [27]. As an interesting additional finding, the unguided version of youthCOACHCD as provided to the wait list control group resulted in an intervention uptake rate of only 53% (uptake rate in IG: 73%) and a completer rate of 7% (completer rate in IG: 60%). Hence, human guidance seems to be a decisive factor regarding intervention uptake and adherence. This result is consistent with the literature indicating that guided IMI are superior to unguided versions [74, 75]. In the forthcoming RCT, the involvement of recruiting physicians could be valuable to further strengthen AYAs’ adherence [79]. Physicians might reinforce intervention uptake by using strategies such as motivational interviewing [76]. Furthermore, they could continually ask the AYA about completing the modules to reinforce a certain commitment of AYA. Another important aspect in regard to adherence might be parental involvement [77, 78]. In our focus groups study, AYA pointed out that they would prefer not to involve their parents [27]. However, youthCOACHCD targets a wide age range of AYA. Younger AYA might be supported by parental involvement in a different way than older AYA. The potential moderating effect of age on adherence and effectiveness will be part of the forthcoming confirmative RCT. The potential benefits of parental involvement should be assessed in future dismantling studies.

Intervention content was based on established methods of CBT and informed by focus groups preliminary to this study [27]. Intervention content should be perceived as personal relevant and supportive to increase intervention adherence and effectiveness of an IMI [79]. Formative user feedback showed that AYA completing intervention modules had no negative feedback about intervention content. Therefore, the intervention content seems to be perceived as appropriate for this target group. Furthermore, with 87% rating the length of modules to be adequate, no further modifications might be required.

Further results on the feasibility of youthCOACHCD are promising. The therapeutic alliance is comparable to those in other internet-based interventions [38, 80]. No pattern emerged regarding reported negative subjective side effects of the intervention attributed to youthCOACHCD and neither the internet usage nor the internet use expectancies changed importantly in the IG. However, the high standard deviations limit the interpretability of the results. Nevertheless, it is important to emphasize at this stage that there are no indications of a subjective and objective negative side effect due to participation in youthCOACHCD.

More female (73%) than male AYA participated. One possible explanation could be that females are more affected by internalizing disorders during adolescence [9]. Furthermore, more females are affected by JIA [81]. In addition, male adolescents with emotional burdens tend to show less help-seeking behavior than female adolescents [82, 83]. Some of the known barriers to help-seeking in AYA are self-reliance, lack of perceived confidentiality and trust in the potential source of help, or lack of knowledge about symptoms of mental disorders [84]. In order to increase intervention reach, these potential barriers should be addressed in the recruitment process, e.g., through personal information provided by a trusted physician or applying strategies of motivational interviewing [76, 85, 86].

Results on potential efficacy of youthCOACHCD should be interpreted with caution and in an explorative manner due to the small underpowered sample size and the overall explorative nature of this feasibility trial [59, 87]. The effect was not yet found twelve weeks post-randomization. The explorative interpretation of the study findings might suggest a temporary worsening of symptom. It is common that especially treatment of anxiety or post-traumatic stress disorder in AYA bears the risk of no improvement or symptom increase during or short-term after treatment [88]. This might be a necessary feature of effective psychotherapy [89]. However, follow-up measurements often reveal a positive long-term effect on symptom change as it is the case in this feasibility trial. The assumption of initially symptom worsening by confrontation with the mental disorders in this study, might be supported by the changes in potential mechanisms of change: e.g. automatic negative thoughts, measured by the ATQ-R, increased twelve weeks post-randomization, meaning, that maladaptive thought patterns seem to be more present short term after intervention and decrease to follow-up. Similar patterns can be seen in further potential mechanisms of change, i.e. coping with the disease and behavioral activation [90]. However, no final conclusion can be drawn until the results of the confirmatory trial.

Some limitations should be considered when interpreting the presented findings. The sample size is very small and no final conclusions on efficacy of youthCOACHCD can be drawn. Furthermore, due to the small sample size, we only report on the efficacy of youthCOACHCD across all three included chronic medical conditions. Efficacy of the iCBT and possible disease specific differences regarding efficacy could only be assessed in a larger sample or in disease specific studies. Stratified randomization is recommended in future similar trials to avoid unequal distribution of chronic medical conditions between study arms (e.g. 75% (3/4) of AYA with CF were in the IG in this study).


Due to the challenging nature of living with a chronic medical condition in adolescence, it is important to provide low-threshold psychological support to this currently underserved target group. The adherence and dropout rates, intervention satisfaction, and therapeutic alliance results found in this randomized controlled pilot trial are comparable to the results of other internet-based trials. Formative user feedback was positive and no patterns emerged relating to any potential side effects of the intervention. These results point to the feasibility of youthCOACHCD, an iCBT for AYA with chronic medical conditions targeting symptoms of depression and anxiety. The results suggest that the implementation of a definitive future RCT is indicated to evaluate the effectiveness of the intervention and identify possible moderating and mediating effects.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.



Automatic Thoughts Questionnaire-Revised


Alcohol Use Disorders Identification Test (consumption items)


Adolescents and young adults


Behavioral Activation for Depression Scale


Berliner Social Support Scale


Child and Adolescent Trauma Screen


Child and Adolescents Trauma Screen-Caregiver


Cognitive and Behavioral Therapy


Cystic fibrosis


Control group


Confidence Interval


Chronic conditions in adolescents: implementation and evaluation of patient-centered collaborative healthcare


Coping with a Disease

Cohen’s d:

Between-group effect size


General perceived Self-Efficacy scale


Juvenile idiopathic arthritis


Internet-based cognitive behavioral therapy


Intervention group


Internet- and mobile-based intervention


Intention to treat


Internet Use Expectancies Scale




Per Protocol


Patient Health Questionnaire Anxiety and Depression Scale


Persuasive System Design


Screen for Child Anxiety Related Emotional Disorders


Standard deviation


Short version of the Mood and Feeling Questionnaire


Stress-Related Growth Scale


Type 1 Diabetes


Visual Analogue Scale of the EuroQol Five-Dimensional Questionnaire- Youth

β :

Standardized regression coefficient


  1. Jin M, An Q, Wang L. Chronic conditions in adolescents. Exp Ther Med. 2017;14:478–82.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Patterson CC, Harjutsalo V, Rosenbauer J, Neu A, Cinek O, Skrivarhaug T, et al. Trends and cyclical variation in the incidence of childhood type 1 diabetes in 26 European centres in the 25 year period 1989-2013: a multicentre prospective registration study. Diabetologia. 2019;62:408–17.

    Article  PubMed  Google Scholar 

  3. Yeo M, Sawyer S. Chronic illness and disability. BMJ. 2005;330:721–3.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Pinquart M, Shen Y. Anxiety in children and adolescents with chronic physical illnesses: a meta-analysis. Acta Paediatr. 2011;100:1069–76.

    Article  PubMed  Google Scholar 

  5. Pinquart M, Shen Y. Depressive symptoms in children and adolescents with chronic physical illness: an updated meta-analysis. J Pediatr Psychol. 2011;36:375–84.

    Article  PubMed  Google Scholar 

  6. Delamater AM, Guzman A, Aparicio K. Mental health issues in children and adolescents with chronic illness. I’tnl Jrnl Human Rights Health. 2017;10:163–73.

    Article  Google Scholar 

  7. Miller KM, Beck RW, Foster NC, Maahs DM. HbA1c levels in Type 1 Diabetes from early childhood to older adults: a deeper dive into the influence of technology and socioeconomic status on HbA1c in the T1D Exchange Clinic Registry findings. Diabetes Technol Ther. 2020;22:645–50.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Sildorf SM, Breinegaard N, Lindkvist EB, Tolstrup JS, Boisen KA, Teilmann GK, et al. Poor metabolic control in children and adolescents with Type 1 Diabetes and psychiatric comorbidity. Diabetes Care. 2018;41:2289–96.

    Article  PubMed  Google Scholar 

  9. Thapar A, Collishaw S, Pine DS, Thapar AK. Depression in adolescence. The Lancet. 2012;379:1056–67.

    Article  Google Scholar 

  10. Quittner AL, Abbott J, Georgiopoulos AM, Goldbeck L, Smith B, Hempstead SE, et al. International Committee on Mental Health in Cystic Fibrosis: Cystic Fibrosis Foundation and European Cystic Fibrosis Society consensus statements for screening and treating depression and anxiety. Thorax. 2016;71:26–34.

    Article  PubMed  Google Scholar 

  11. Oud M, Winter L de, Vermeulen-Smit E, Bodden D, Nauta M, Stone L, et al. Effectiveness of CBT for children and adolescents with depression: a systematic review and meta-regression analysis. Eur Psychiatry. 2019;57:33–45.

    Article  PubMed  Google Scholar 

  12. James AC, James G, Cowdrey FA, Soler A, Choke A. Cognitive behavioural therapy for anxiety disorders in children and adolescents. Cochrane Database Syst Rev. 2013:CD004690.

  13. Morey A, Loades ME. Review: How has cognitive behaviour therapy been adapted for adolescents with comorbid depression and chronic illness? A scoping review. Child Adolesc Ment Health 2020.

    Article  PubMed  Google Scholar 

  14. Hintzpeter B, Klasen F, Schön G, Voss C, Hölling H, Ravens-Sieberer U. Mental health care use among children and adolescents in Germany: results of the longitudinal BELLA study. Eur Child Adolesc Psychiatry. 2015;24:705–13.

    Article  PubMed  Google Scholar 

  15. Wit M de, Snoek FJ. Depressive symptoms and unmet psychological needs of Dutch youth with type 1 diabetes: results of a web-survey. Pediatr Diabetes. 2011:172–6.

  16. Hargreaves DS, Elliott MN, Viner RM, Richmond TK, Schuster MA. Unmet health care need in US adolescents and adult health outcomes. Pediatrics. 2015;136:513–20.

    Article  PubMed  Google Scholar 

  17. Owens PL, Hoagwood K, Horwitz SM, Leaf PJ, Poduska JM, Kellam SG, Ialongo NS. Barriers to children’s mental health services. Journal of the American Academy of Child & Adolescent Psychiatry. 2002;41:731–8.

    Article  Google Scholar 

  18. Corrigan PW, Druss BG, Perlick DA. The impact of mental illness stigma on seeking and participating in mental health care. Psychol Sci Public Interest. 2014;15:37–70.

    Article  PubMed  Google Scholar 

  19. Domhardt M, Steubl L, Baumeister H. Internet- and mobile-based interventions for mental and somatic conditions in children and adolescents. Z Kinder Jugendpsychiatr Psychother. 2020;48:33–46.

    Article  PubMed  Google Scholar 

  20. Badawy SM, Barrera L, Sinno MG, Kaviany S, O’Dwyer LC, Kuhns LM. Text messaging and mobile phone apps as interventions to improve adherence in adolescents with chronic health conditions: a systematic review. JMIR Mhealth Uhealth. 2017;5:e66.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Domhardt M, Schröder A, Geirhos A, Steubl L, Baumeister H. Efficacy of digital health interventions in youth with chronic medical conditions: A meta-analysis. Internet Interventions 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Thabrew H, Stasiak K, Hetrick SE, Wong S, Huss JH, Merry SN. E-Health interventions for anxiety and depression in children and adolescents with long-term physical conditions. Cochrane Database Syst Rev. 2018;8:CD012489.

    Article  PubMed  Google Scholar 

  23. Pinquart M. Posttraumatic stress symptoms and disorders in children and adolescents with chronic physical illnesses: a meta-analysis. J Child Adolesc Trauma. 2020;13:1–10.

    Article  PubMed  Google Scholar 

  24. Maughan B, Collishaw S, Stringaris A. Depression in childhood and adolescence. Journal of the Canadian Academy of Child and Adolescent Psychiatry. 2013:35–40.

  25. Surís J-C, Michaud P-A, Akre C, Sawyer SM. Health risk behaviors in adolescents with chronic conditions. Pediatrics. 2008;122:e1113-8.

    Article  PubMed  Google Scholar 

  26. Iturralde E, Weissberg-Benchell J, Hood KK. Avoidant coping and diabetes-related distress: pathways to adolescents’ Type 1 Diabetes outcomes. Health Psychol. 2017;36:236–44.

    Article  PubMed  Google Scholar 

  27. Geirhos A, Lunkenheimer F, Holl R, Minden K, Schmitt A, Temming S, et al. Involving patients’ perspective in the development of an internet- and mobile-based CBT intervention for adolescents with chronic medical conditions: findings from a qualitative study. Internet Interventions 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lunkenheimer F, Domhardt M, Geirhos A, Kilian R, Mueller-Stierlin AS, Holl RW, et al. Effectiveness and cost-effectiveness of guided internet- and mobile-based CBT for adolescents and young adults with chronic somatic conditions and comorbid depression and anxiety symptoms (youthCOACHCD): study protocol for a multicentre randomized controlled trial. Trials. 2020;21:253.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Eldridge SM, Chan CL, Campbell MJ, Bond CM, Hopewell S, Thabane L, et al. CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ. 2016:i5239.

  30. Kühner C, Bürger C, Keller F, Hautzinger M. Reliabilität und Validität des revidierten Beck-Depressionsinventars (BDI-II). Befunde aus deutschsprachigen Stichproben. [Reliability and validity of the Revised Beck Depression Inventory (BDI-II). results from German samples]. Nervenarzt. 2007;78:651–6.

    Article  PubMed  Google Scholar 

  31. Cocks K, Torgerson DJ. Sample size calculations for pilot randomized trials: a confidence interval approach. J Clin Epidemiol. 2013;66:197–201.

    Article  PubMed  Google Scholar 

  32. sealed envelope. Accessed 19 May 2021.

  33. Minddistrict. Accessed 19 May 2021.

  34. Unipark. Accessed 19 May 2021.

  35. Ladwig I, Rief W, Nestoriuc Y. Welche Risiken und Nebenwirkungen hat Psychotherapie? - Entwicklung des Inventars zur Erfassung Negativer Effekte von Psychotherapie (INEP). Verhaltenstherapie. 2014;24:252–63.

    Article  Google Scholar 

  36. Brand M, Laier C, Young KS. Internet addiction: coping styles, expectancies, and treatment implications. Front Psychol. 2014;5:1256.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Wilmers F, Munder T, Leonhart R, Herzog T, Plassmann R, Barth J, Linster HW. Die deutschsprachige Version des Working Alliance Inventory – short revised (WAI-SR) – Ein schulenübergreifendes, ökonomisches und empirisch validiertes Instrument zur Erfassung der therapeutischen Allianz*. Klin. Diagnostik u. Evaluation. 2008;1:343–58.

    Google Scholar 

  38. Munder T, Wilmers F, Leonhart R, Linster HW, Barth J. Working Alliance Inventory-Short Revised (WAI-SR): psychometric properties in outpatients and inpatients. Clin Psychol Psychother. 2010;17:231–9.

    Article  PubMed  Google Scholar 

  39. Boß L, Lehr D, Reis D, Vis C, Riper H, Berking M, Ebert DD. Reliability and validity of assessing user satisfaction with web-based health interventions. J Med Internet Res. 2016;18:e234.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Kroenke K, Wu J, Yu Z, Bair MJ, Kean J, Stump T, Monahan PO. Patient Health Questionnaire Anxiety and Depression Scale: initial validation in three clinical trials. Psychosom Med. 2016;78:716–27.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Wille N, Badia X, Bonsel G, Burström K, Cavrini G, Devlin N, et al. Development of the EQ-5D-Y: a child-friendly version of the EQ-5D. Qual Life Res. 2010;19:875–86.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Ravens-Sieberer U, Wille N, Badia X, Bonsel G, Burström K, Cavrini G, et al. Feasibility, reliability, and validity of the EQ-5D-Y: results from a multinational study. Qual Life Res. 2010;19:887–97.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Petersen C, Schmidt S, Bullinger M. Brief report: Development and pilot testing of a coping questionnaire for children and adolescents with chronic health conditions. J Pediatr Psychol. 2004;29:635–40.

    Article  PubMed  Google Scholar 

  44. Hinz A, Schumacher J, Albani C, Schmid G, Brähler E. Bevölkerungsrepräsentative Normierung der Skala zur Allgemeinen Selbstwirksamkeitserwartung. Diagnostica. 2006;52:26–32.

    Article  Google Scholar 

  45. Sachser C, Berliner L, Holt T, Jensen TK, Jungbluth N, Risch E, et al. International development and psychometric properties of the Child and Adolescent Trauma Screen (CATS). J Affect Disord. 2017;210:189–95.

    Article  PubMed  Google Scholar 

  46. Park CL, Cohen LH, Murch RL. Assessment and prediction of stress-related growth. Journal of Personality. 1996;64:71–105.

    CAS  Article  PubMed  Google Scholar 

  47. Maercker A, Langer R. Persönliche Reifung (Personal Growth) durch Belastungen und Traumata: Validierung zweier deutschsprachiger Fragebogenversionen. Diagnostica. 2001;47:153–62.

    Article  Google Scholar 

  48. Schulz U, Schwarzer R. Soziale Unterstützung bei der Krankheitsbewältigung: Die Berliner Social Support Skalen (BSSS). Diagnostica. 2003;49:73–82.

    Article  Google Scholar 

  49. Bush K, Kivlahan DR, McDonell M, Fihn S, Bradley KA, for the Ambulatory Care Quality Improvement Project. The AUDIT Alcohol Consumption Questions (AUDIT-C) an effective brief screening test for problem drinking. Arch Intern Med. 1998;158:1789–95.

    CAS  Article  PubMed  Google Scholar 

  50. Chisholm D, Knapp, M.R.J., Knudsen HC, Amaddeo F, Gaite L. Client Socio-Demographic and Service Receipt Inventory - European Version: development of an instrument for international research. Br J Psychiatry. 2000;177:28–33.

    Article  Google Scholar 

  51. Teismann T, Ertle A, Furka N, Willutzki U, Hoyer J. The German version of the Behavioral Activation for Depression Scale (BADS): a psychometric and clinical investigation. Clin Psychol Psychother. 2016;23:217–25.

    Article  PubMed  Google Scholar 

  52. Kendall C, Howard BL, Hays RC. Self-referent speech and psychopathology: the balance of positive and negative thinking. Cognit Ther Res. 1989;13:583–98.

    Article  Google Scholar 

  53. Essau CA, Muris P, Ederer EM. Reliability and validity of the Spence Children’s Anxiety Scale and the Screen for Child Anxiety Related Emotional Disorders in German children. Journal of Behavior Therapy and Experimental Psychiatry. 2002;33:1–18.

    Article  PubMed  Google Scholar 

  54. Thabrew H, Stasiak K, Bavin L-M, Frampton C, Merry S. Validation of the Mood and Feelings Questionnaire (MFQ) and Short Mood and Feelings Questionnaire (SMFQ) in New Zealand help-seeking adolescents. Int J Methods Psychiatr Res. 2018;27:e1610.

    Article  PubMed  PubMed Central  Google Scholar 

  55. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical. 2020.

  56. Cohen J, Cohen P, West SG, Aiken LS. Applied multiple regression/correlation analysis for the behavioral sciences. 3rd ed. New York, London: Routledge; 2015.

    Google Scholar 

  57. Kannan KS, Manoj K. Outlier detection in multivariate data. ams. 2015;9:2317–24.

    Article  Google Scholar 

  58. Aguinis H, Gottfredson RK, Joo H. Best-practice recommendations for defining, identifying, and handling outliers. Organizational Research Methods. 2013;16:270–301.

    Article  Google Scholar 

  59. Christley RM. Power and error: increased risk of false positive results in underpowered studies. TOEPIJ. 2010;3:16–9.

    Article  Google Scholar 

  60. van Buuren S, Groothuis-Oudshoorn K. MICE: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software 2011.

    Article  Google Scholar 

  61. Cichoń E, Kiejna A, Kokoszka A, Gondek TM, Radzio R, Jastrzębski A, et al. People with diabetes need a lower cut-off than others for depression screening with PHQ-9. PLoS One. 2020;15:e0240209.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  62. Plummer F, Manea L, Trepel D, McMillan D. Screening for anxiety disorders with the GAD-7 and GAD-2: a systematic review and diagnostic metaanalysis. Gen Hosp Psychiatry. 2016;39:24–31.

    Article  PubMed  Google Scholar 

  63. Haan AM de, Boon AE, Jong JTVM de, Hoeve M, Vermeiren RRJM. A meta-analytic review on treatment dropout in child and adolescent outpatient mental health care. Clin Psychol Rev. 2013;33:698–711.

    Article  PubMed  Google Scholar 

  64. Melville KM, Casey LM, Kavanagh DJ. Dropout from internet-based treatment for psychological disorders. Br J Clin Psychol. 2010;49:455–71.

    Article  PubMed  Google Scholar 

  65. Clarke AM, Kuosmanen T, Barry MM. A systematic review of online youth mental health promotion and prevention interventions. Journal of Youth and Adolescence. 2015;44:90–113.

    Article  PubMed  Google Scholar 

  66. Kelders SM, Kok RN, Ossebaard HC, van Gemert-Pijnen JEWC. Persuasive system design does matter: a systematic review of adherence to web-based interventions. J Med Internet Res. 2012;14:e152.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Baumeister H, Kraft R, Baumel A, Pryss R, Messner EM. Persuasive e-health design for behavior change. In: H. Baumeister CM, editor. Digital phenotyping and mobile sensing. Cham: Springer Nature; 2019. p. 261–276.

    Chapter  Google Scholar 

  68. Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: key issues, process model, and system features. CAIS 2009.

    Article  Google Scholar 

  69. Wozney L, Huguet A, Bennett K, Radomski AD, Hartling L, Dyson M, et al. How do eHealth programs for adolescents with depression work? A realist review of Persuasive System Design components in internet-based psychological therapies. J Med Internet Res. 2017;19:e266.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Brown M, O’Neill N, van Woerden H, Eslambolchilar P, Jones M, John A. Gamification and adherence to web-based mental health interventions: a systematic review. JMIR Ment Health. 2016;3:e39.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Palermo TM, La Vega R de, Dudeney J, Murray C, Law E. Mobile health intervention for self-management of adolescent chronic pain (WebMAP mobile): Protocol for a hybrid effectiveness-implementation cluster randomized controlled trial. Contemp Clin Trials. 2018;74:55–60.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Palermo TM, La Vega R de, Murray C, Law E, Zhou C. A digital health psychological intervention (WebMAP Mobile) for children and adolescents with chronic pain: results of a hybrid effectiveness-implementation stepped-wedge cluster randomized trial. Pain. 2020;161:2763–74.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Christie GI, Shepherd M, Merry SN, Hopkins S, Knightly S, Stasiak K. Gamifying CBT to deliver emotional health treatment to young people on smartphones. Internet Interventions. 2019;18:100286.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Domhardt M, Geßlein H, Rezori RE von, Baumeister H. Internet- and mobile-based interventions for anxiety disorders: a meta-analytic review of intervention components. Depress Anxiety. 2019;36:213–24.

    Article  PubMed  Google Scholar 

  75. Baumeister H, Reichler L, Munzinger M, Lin J. The impact of guidance on internet-based mental health interventions — A systematic review. Internet Interventions. 2014;1:205–15.

    Article  Google Scholar 

  76. Reinauer C, Viermann R, Förtsch K, Linderskamp H, Warschburger P, Holl RW, et al. Motivational Interviewing as a tool to enhance access to mental health treatment in adolescents with chronic medical conditions and need for psychological support (COACH-MI): study protocol for a clusterrandomised controlled trial. Trials. 2018;19:629.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Rose T, Barker M, Maria Jacob C, Morrison L, Lawrence W, Strömmer S, et al. A Systematic Review of Digital Interventions for Improving the Diet and Physical Activity Behaviors of Adolescents. J Adolesc Health. 2017;61:669–77.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Domhardt M, Engler S, Nowak H, Lutsch A, Baumel A, Baumeister H. Mechanisms of Change in Digital Health Interventions for Mental Disorders in Youth: Systematic Review. J Med Internet Res. 2021;23:e29742.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Achilles MR, Anderson M, Li SH, Subotic-Kerry M, Parker B, O’Dea B. Adherence to e-mental health among youth: considerations for intervention development and research design. Digit Health. 2020;6:2055207620926064.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Jasper K, Weise C, Conrad I, Andersson G, Hiller W, Kleinstäuber M. The working alliance in a randomized controlled trial comparing internet-based self-help and face-to-face cognitive behavior therapy for chronic tinnitus. Internet Interventions. 2014;1:49–57.

    Article  Google Scholar 

  81. Thomschke S, Schulz M, Bätzing J. Epidemiologie der juvenilen idiopathischen Arthritis (JIA) in der ambulanten Versorgung – eine Analyse anhand bundesweiter vertragsärztlicher Abrechnungsdaten der Jahre 2009 bis 2015.

  82. Schonert-Reihl, K.A. & Muller, J.R. Correlates of help-seeking in adolescence. Journal of Youth and Adolescence. 1996:705–31.

  83. Ando S, Nishida A, Usami S, Koike S, Yamasaki S, Kanata S, et al. Help-seeking intention for depression in early adolescents: associated factors and sex differences. J Affect Disord. 2018;238:359–65.

    Article  PubMed  Google Scholar 

  84. Gulliver A, Griffiths KM, Christensen H. Perceived barriers and facilitators to mental health help-seeking in young people: a systematic review. BMC Psychiatry. 2010;10:113.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Schaefer MR, Kavookjian J. The impact of motivational interviewing on adherence and symptom severity in adolescents and young adults with chronic illness: a systematic review. Patient Educ Couns. 2017;100:2190–9.

    Article  PubMed  Google Scholar 

  86. van Voorhees BW, Hsiung RC, Marko-Holguin M, Houston TK, Fogel J, Lee R, Ford DE. Internal versus external motivation in referral of primary care patients with depression to an internet support group: randomized controlled trial. J Med Internet Res. 2013;15:e42.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Sim J. Should treatment effects be estimated in pilot and feasibility studies? Pilot Feasibility Stud. 2019;5:107.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Barlow DH. Anxiety and its disorders: The nature and treatment of anxiety and panic. 2nd ed. New York, NY: Guilford Press; 2002.

    Google Scholar 

  89. Lorenz TK. Predictors and impact of psychotherapy side effects in young adults. Couns Psychother Res. 2021;21:237–43.

    Article  Google Scholar 

  90. Domhardt M, Steubl L, Boettcher J, Buntrock C, Karyotaki E, Ebert DD, et al. Mediators and mechanisms of change in internet- and mobile-based interventions for depression: a systematic review. Clin Psychol Rev. 2021;83:101953.

    Article  PubMed  Google Scholar 

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We thank all student assistants for their support in participant recruitment and management, Ramona Ranz for the randomization and Yannik Terhorst for his advice on the statistical evaluation. Furthermore, we would like to thank the eCoaches of the participants and their supervisors. We would also like to express a big thank to all participants and to the self-help groups, clinics and practices that supported us in the recruitment process.


Open Access funding enabled and organized by Projekt DEAL. This study is realized as part of the project „Chronic Conditions in Adolescents: Implementation and Evaluation of Patient-centered Collaborative Healthcare (COACH)”, funded by the German Federal Ministry of Education and Research (Grant identification 01GL1740E).

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Authors and Affiliations



AG, MD, FL and HB conceptualized and developed the intervention and the study design. AG and FL carried out the study management. AG and AMS conducted the statistical analyses and AG interpreted the data. AG took the lead in writing the manuscript. MD, FL, RWH, ST, KM, PW, TM, AMS, HB provided critical feedback. All authors approved the final version.

Corresponding author

Correspondence to A. Geirhos.

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Ethics approval and consent to participate

The study was approved by the Ethics Committee of Ulm University (file number 292/18). Informed consent was obtained from parents/guardians of the participants whose age was below 16 and informed consent was obtained from the participants whose age was above 16. All methods were performed in accordance with the relevant guidelines and regulations (Declaration of Helsinki).

Consent for publication

Not applicable.

Competing interests

HB is a consultant for different insurance companies, health care associations, and psychotherapy chambers and gives talks and workshops and conducts a third party-funded project on iCBT and the dissemination and implementation of iCBT. The remaining authors declare that they have no competing interests.

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Geirhos, A., Domhardt, M., Lunkenheimer, F. et al. Feasibility and potential efficacy of a guided internet- and mobile-based CBT for adolescents and young adults with chronic medical conditions and comorbid depression or anxiety symptoms (youthCOACHCD): a randomized controlled pilot trial. BMC Pediatr 22, 69 (2022).

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  • Chronic medical condition
  • Depression
  • Anxiety
  • Internet- and mobile based intervention
  • Cognitive behavioral therapy
  • Randomized controlled pilot trial
  • Type 1 diabetes
  • Cystic fibrosis
  • Juvenile idiopathic arthritis