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Abstract Background The risk of breast cancer patients for long-term side effects of therapy such as neurotoxicity and cardiotoxicity as well as late effects regarding comorbidities varies from individual to individual. Personalised follow-up care concepts that are tailored to individual needs and the risk of recurrences, side effects and late effects are lacking in routine care in Germany. Methods We describe the methodology of BETTER-CARE, a parallel-arm cluster-randomised controlled trial conducted at 15 intervention and 15 control centres, aiming to recruit 1140 patients, and the results of the pilot phase. The needs- and risk-adapted complex intervention, based on existing development frameworks, includes a multidisciplinary network and digital platforms for symptom and need documentation and just-in-time adaptive interventions. The control group comprises usual care according to clinical guidelines. The primary outcome is health-related quality of life (EORTC QLQ-C30 global health), and secondary outcomes include treatment adherence. Results The 2-month pilot phase comprising 16 patients in one intervention and one control pilot centre demonstrated the feasibility of the BETTER-CARE approach. Discussion BETTER-CARE is a feasible intervention and study concept, investigating individualised needs- and risk-adapted breast cancer follow-up care in Germany. If successful, the approach could be implemented in German routine care. Trial registration German Clinical Trial Register DRKS00028840. Registered on April 2022.

Abstract The challenge of sustaining user engagement in eHealth interventions is a pressing issue with significant implications for the effectiveness of these digital health tools. This study investigates user engagement in a cognitive-behavioral therapy-based eHealth intervention for procrastination, using a dataset from a randomized controlled trial of 233 university students. Various machine learning models, including Decision Tree, Gradient Boosting, Logistic Regression, Random Forest, and Support Vector Machines, were employed to predict patterns of user engagement. The study adopted a two-phase analytical approach. In the first phase, all features of the dataset were included, revealing ‘total_minutes’—the total time participants spent on the intervention and the eHealth platform—as the most significant predictor of engagement. This finding emphasizes the intuitive notion that early time spent on the platform and the intervention is a strong indicator of later user engagement. However, to gain a deeper understanding of engagement beyond this predominant metric, the second phase of the analysis excluded ‘total_minutes’. This approach allowed for the exploration of the roles and interdependencies of other engagement indicators, such as ‘number_intervention_answersheets’—the number of completed lessons, ‘logins_first_4_weeks’—login frequency, and ‘number_diary_answersheets’—the number of completed diaries. The results from this phase highlighted the multifaceted nature of engagement, showing that while ‘total_minutes’ is strongly correlated with engagement, indicating that more engaged participants tend to spend more time on the intervention, the comprehensive engagement profile also depends on additional aspects like lesson completions and frequency of platform interactions.

Objective This systematic review and meta-analysis evaluates the available evidence on efficacy of social support strategies, as defined by the persuasive system design framework, in internet-based and mobile-based interventions (IMI) targeting mental health.Design Systematic review and meta-analysis.Data sources PubMed, Embase, PsycINFO and the Cochrane Central Register of Controlled Trials.Eligibility criteria for selecting studies Randomised controlled trials comparing IMI implementing a social support strategy for mental health symptoms to various control conditions. Publications up to June 2023 (date of search 6 June 2023) were considered.Data extraction and synthesis Two independent reviewers screened and extracted data in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed with the Risk of Bias Tool V.2.0. Data were pooled based on a random-effects model.Results After screening 6484 records, a total of 45 studies met our inclusion criteria. At 96%, social support was predominantly implemented through the strategy of social facilitation, by which users recognising others using the intervention (eg, discussion forum). IMI implementing social support strategies showed moderate effect sizes of Hedges’ g=−0.34 (95% CI −0.47 to −0.21, p

BackgroundThe objective, unobtrusively collected GPS features (eg, homestay and distance) from everyday devices like smartphones may offer a promising augmentation to current assessment tools for depression. However, to date, there is no systematic and meta-analytical evidence on the associations between GPS features and depression. ObjectiveThis study aimed to investigate the between-person and within-person correlations between GPS mobility and activity features and depressive symptoms, and to critically review the quality and potential publication bias in the field. MethodsWe searched MEDLINE, PsycINFO, Embase, CENTRAL, ACM, IEEE Xplore, PubMed, and Web of Science to identify eligible articles focusing on the correlations between GPS features and depression from December 6, 2022, to March 24, 2023. Inclusion and exclusion criteria were applied in a 2-stage inclusion process conducted by 2 independent reviewers (YT and JK). To be eligible, studies needed to report correlations between wearable-based GPS variables (eg, total distance) and depression symptoms measured with a validated questionnaire. Studies with underage persons and other mental health disorders were excluded. Between- and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE (Strengthening the Reporting of Observational studies in Epidemiology) guidelines. Publication bias was investigated using Egger test and funnel plots. ResultsA total of k=19 studies involving N=2930 participants were included in the analysis. The mean age was 38.42 (SD 18.96) years with 59.64% (SD 22.99%) of participants being female. Significant between-person correlations between GPS features and depression were identified: distance (r=–0.25, 95% CI –0.29 to –0.21), normalized entropy (r–0.17, 95% CI –0.29 to –0.04), location variance (r–0.17, 95% CI –0.26 to –0.04), entropy (r=–0.13, 95% CI –0.23 to –0.04), number of clusters (r=–0.11, 95% CI –0.18 to –0.03), and homestay (r=0.10, 95% CI 0.00 to 0.19). Studies reporting within-correlations (k=3) were too heterogeneous to conduct meta-analysis. A deficiency in study quality and research standards was identified: all studies followed exploratory observational designs, but no study referenced or fully adhered to the international guidelines for reporting observational studies (STROBE). A total of 79% (k=15) of the studies were underpowered to detect a small correlation (r=.20). Results showed evidence for potential publication bias. ConclusionsOur results provide meta-analytical evidence for between-person correlations of GPS mobility and activity features and depression. Hence, depression diagnostics may benefit from adding GPS mobility and activity features as an integral part of future assessment and expert tools. However, confirmatory studies for between-person correlations and further research on within-person correlations are needed. In addition, the methodological quality of the evidence needs to improve. Trial RegistrationOSF Registeries cwder; https://osf.io/cwder

BackgroundSpecialized studies have shown that smartphone-based social interaction data are predictors of depressive and anxiety symptoms. Moreover, at times during the COVID-19 pandemic, social interaction took place primarily remotely. To appropriately test these objective data for their added value for epidemiological research during the pandemic, it is necessary to include established predictors. ObjectiveUsing a comprehensive model, we investigated the extent to which smartphone-based social interaction data contribute to the prediction of depressive and anxiety symptoms, while also taking into account well-established predictors and relevant pandemic-specific factors. MethodsWe developed the Corona Health App and obtained participation from 490 Android smartphone users who agreed to allow us to collect smartphone-based social interaction data between July 2020 and February 2021. Using a cross-sectional design, we automatically collected data concerning average app use in terms of the categories video calls and telephony, messenger use, social media use, and SMS text messaging use, as well as pandemic-specific predictors and sociodemographic covariates. We statistically predicted depressive and anxiety symptoms using elastic net regression. To exclude overfitting, we used 10-fold cross-validation. ResultsThe amount of variance explained (R2) was 0.61 for the prediction of depressive symptoms and 0.57 for the prediction of anxiety symptoms. Of the smartphone-based social interaction data included, only messenger use proved to be a significant negative predictor of depressive and anxiety symptoms. Video calls were negative predictors only for depressive symptoms, and SMS text messaging use was a negative predictor only for anxiety symptoms. ConclusionsThe results show the relevance of smartphone-based social interaction data in predicting depressive and anxiety symptoms. However, even taken together in the context of a comprehensive model with well-established predictors, the data only add a small amount of value.

This systematic review aimed to synthesize evidence on predictors and moderators of treatment outcomes in internet- and mobile-based interventions (IMIs) for depression, informing personalized care. A systematic search across PubMed, PsycInfo, and Cochrane yielded 33,002 results. Two reviewers independently performed screening, data extraction, risk of bias assessment, and methodological quality evaluation. Fifty-eight single studies (m = 466 analyses) focusing on baseline-predictors (59.7 %, m = 278), process-predictors (16.5 %, m = 77), and moderators (21.9 %, m = 102), and six individual patient data meta-analyses (m = 93) were included. Only 24.0 % (m = 112/466) of analyses in single studies and 15.1 % (m = 14/93) in individual patient data meta-analyses were significant. Evidence from single studies was rated as insufficient for all variable categories with only 2 out of 40 categories showing >50 % significant results. Baseline depression severity had the strongest predictive value with higher scores linked to better outcomes followed by variables indicative for the course-of-change. Other frequently analyzed and potentially relevant variables with significant results were adherence, age, educational level, ethnicity, relationship status, treatment history, and behavioral variables. More high quality quantitative studies with sufficient power are essential to validate and expand findings, identifying predictors and moderators specifically relevant in IMIs to explain differential treatment effects.

Abstract Background Counselling adolescents with chronic medical conditions (CMCs) can be challenging regarding suitable interviewing skills and clinicians’ attitudes toward the patient. Successful communication can be a key element of treatment. Motivational Interviewing (MI) is broadly applicable in managing behavioural problems and diseases by increasing patient motivation for lifestyle changes. However, data concerning the applicability, feasibility and implementation of MI sessions in everyday practice are missing from the physicians’ point of view. Method The present study was conducted as a mixed methods design. Twenty paediatricians were randomized to a 2-day MI course followed by MI consultations. Data were collected through a questionnaire one year after MI training. Factors for effective training and possible barriers to successful use of MI were examined. Results Completed questionnaires were returned by 19 of 20 paediatricians. The paediatricians’ experiences with MI demonstrate that MI is regarded as a valuable tool when working with adolescents with CMCs. 95% of all respondents reported that they found MI education necessary for their clinical work and were using it also outside the COACH-MI study context. 73.7% percent saw potential to strengthen the connection to their patients by using MI. The doctors were already using more MI conversation techniques after a 2-day MI course. Obstacles were seen in the short training, the lack of time and missing undisturbed environment (interruptions by telephone, staff, etc.) during clinical flow. Conclusions MI techniques are not yet a regular part of medical training. However, a 2-day MI course was rated effective and provided a lasting impact by physicians caring for children and adolescents with chronic medical conditions (CMCs), although booster sessions should be offered regularly. Trial registration The study was registered in the German Clinical Trials Register (DRKS00014043) on 26/04/2018.

Abstract Background Previous studies have shown that growing up with rheumatic conditions can fuel dissatisfaction and psychological distress, which in turn affects disease self-management and treatment adherence. Primary objective of this study was to estimate the prevalence of anxiety and depression symptoms in adolescents and young adults (AYA) with juvenile idiopathic arthritis (JIA) and to identify correlates of conspicuous screening results. Methods Initiated as part of the COACH multicenter observational study, outpatients aged 12 to 21 years participating in the National Pediatric Rheumatological Database (NPRD) were prospectively screened for mental health using the Patient Health Questionnaire-9 (PHQ-9) and the Generalised Anxiety Disorder Scale-7 (GAD-7). Results Data from 1,150 adolescents with JIA (mean age 15.6 ± 2.2 years; mean disease duration 7.2 ± 4.9 years, 69% female, 43% oligoarthritis, 26% polyarthritis) were analysed. Overall, 32.7% (n = 316) of AYA showed conspicuous screening results, of whom 30.4% reported clinically relevant suicidal or self-harm thoughts. About 19% of screened patients showed moderate to severe depressive or anxious symptoms. AYA with conspicuous screening results were older (15.8 vs. 15.2 years; p

Abstract Background Studying at university is a stressful time for many, which might result in the development of mental health problems. In the first wave of Covid-19, university students in Turkey reported suffering from an elevated level of stress compared to their peers in other countries. Mindfulness-based interventions could provide the means of successfully decreasing the stress level of university students. Moreover, offering interventions via the Internet could be a scalable option to prevent and treat mental health problems, while offering time/place flexibility, anonymity, and cost-effectiveness. Method In a randomized controlled trial of parallel design, the feasibility of a culturally adapted internet- and mobile-based intervention (IMI) (StudiCareM-TR) to promote mindfulness among Turkish-speaking university students was tested. Participants (N = 58) of a public university in Istanbul were randomized into an intervention (IG) vs. waitlist control group (WL). Measurements took place at baseline (t0) and 10 weeks post-randomization (t1). Intervention adherence, acceptance, and potential negative effects were feasibility outcomes. Levels of mindfulness, perceived stress, depression, anxiety, and wellbeing were analyzed in linear regression models to assess the potential efficacy of StudiCareM-TR. All analyses were conducted with the intention-to-treat sample, adjusting for baseline values. Results Based on participants’ feedback, StudiCareM-TR was perceived as acceptable, resulted in few negative effects (n = 7), and yielded improvements in mindfulness (β = 0.70) and presenteeism (β = − 0.61) compared to WL. Secondary outcomes of depression, anxiety, stress, and wellbeing did not show significant improvements. Assessment dropout was 31% (IG: 50%: WL: 89%), and intervention dropout was 45%. Conclusions StudiCareM-TR is feasible and acceptable to use among university students in Turkey and has the potential to improve their mindfulness levels. The intervention should be further developed with a focus on engagement-facilitating features in order to reduce intervention dropouts. Trial registration ID DRKS00024557.

Abstract Background The experience of benefit-finding and growth (BFG), defined as perceiving positive life changes resulting from adversity, is increasingly studied among youths with chronic health conditions (CCs). However, empirical evidence is scarce for explaining individual differences in BFG. The study aimed to test a model of BFG, including an interplay of personal and environmental factors and coping processes. Methods A sample of N = 498 youths (12–21 years) recruited from three German patient registries for CCs (type 1 diabetes: n = 388, juvenile idiopathic arthritis: n = 82, cystic fibrosis: n = 28) completed a questionnaire including self-reported optimism, social support from parents and peers, coping strategies, and BFG. The model was created to reflect the theoretical assumptions of the Life Crisis and Personal Growth model and current empirical evidence. Structural equation modeling was conducted to evaluate the incremental explanatory power of optimism, peer group integration, parental support, acceptance, cognitive reappraisal, and seeking social support over and above sociodemographic and disease-related characteristics. Results The model (CFI = 0.93; RMSEA = 0.04; SRMR = 0.05) explained 32% of the variance in BFG. Controlling for sociodemographic and disease-related characteristics, acceptance, cognitive reappraisal, and seeking social support were directly and positively linked to BFG. All tested coping strategies significantly mediated the association between optimism and BFG, whereas seeking social support significantly mediated the relation between peer group integration and BFG. Discussion The study stresses the prominent role of emotion-focused coping strategies and peer group integration in enhancing BFG in youths with CCs. Trial registration German Clinical Trials Register (DRKS), no. DRKS00025125. Registered on May 17, 2021.

BackgroundMental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI).MethodsA total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests.ResultsThe acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p

This review investigates persuasive design frameworks within eHealth, concentrating on methodologies, their prevalence in mental and behavioral health applications, and identifying current research gaps. An extensive search was conducted across 8 databases, focusing on English publications with full text available. The search prioritized primary research articles, post-2011 applications, and eHealth platforms emphasizing treatment or support. The inclusion process was iterative, involving multiple authors, and relied on detailed criteria to ensure the relevance and contemporaneity of selected works. The final review set comprised 161 articles, providing an overview of persuasive design frameworks in eHealth. The review highlights the state of the art in the domain, emphasizing the utilization and effectiveness of these frameworks in eHealth platforms. This review details the restricted adoption of persuasive design frameworks within the field of eHealth, particularly in the mental and behavioral sectors. Predominant gaps include the scarcity of comparative evaluations, the underrepresentation of tailored interventions, and the unclear influence of persuasive components on user experience. There is a notable requirement for further scrutiny and refinement of persuasive design frameworks. Addressing these concerns promises a more substantial foundation for persuasive design in eHealth, potentially enhancing user commitment and platform efficiency.

BackgroundMental health (MH) problems in youth are prevalent, burdening, and frequently persistent. Despite the existence of effective treatment, the uptake of professional help is low, particularly due to attitudinal barriers. ObjectiveThis study evaluated the effectiveness and acceptability of 2 video-based microinterventions aimed at reducing barriers to MH treatment and increasing the likelihood of seeking professional help in young people. MethodsThis study was entirely web based and open access. The interventions addressed 5 MH problems: generalized anxiety disorder, depression, bulimia, nonsuicidal self-injury, and problematic alcohol use. Intervention 1 aimed to destigmatize and improve MH literacy, whereas intervention 2 aimed to induce positive outcome expectancies regarding professional help seeking. Of the 2435 participants who commenced the study, a final sample of 1394 (57.25%) participants aged 14 to 29 years with complete data and sufficient durations of stay on the video pages were randomized in a fully automated manner to 1 of the 5 MH problems and 1 of 3 conditions (control, intervention 1, and intervention 2) in a permuted block design. After the presentation of a video vignette, no further videos were shown to the control group, whereas a second, short intervention video was presented to the intervention 1 and 2 groups. Intervention effects on self-reported potential professional help seeking (primary outcome), stigma, and attitudes toward help seeking were examined using analyses of covariance across and within the 5 MH problems. Furthermore, we assessed video acceptability. ResultsNo significant group effects on potential professional help seeking were found in the total sample (F2,1385=0.99; P=.37). However, the groups differed significantly with regard to stigma outcomes and the likelihood of seeking informal help (F2,1385=3.75; P=.02). Furthermore, separate analyses indicated substantial differences in intervention effects among the 5 MH problems. ConclusionsInterventions to promote help seeking for MH problems may require disorder-specific approaches. The study results can inform future research and public health campaigns addressing adolescents and young adults. Trial RegistrationGerman Clinical Trials Register DRKS00023110; https://drks.de/search/de/trial/DRKS00023110

ObjectiveSmart sensing has the potential to make psychotherapeutic treatments more effective. It involves the passive analysis and collection of data generated by digital devices. However, acceptance of smart sensing among psychotherapy patients remains unclear. Based on the unified theory of acceptance and use of technology (UTAUT), this study investigated (1) the acceptance toward smart sensing in a sample of psychotherapy patients (2) the effectiveness of an acceptance facilitating intervention (AFI) and (3) the determinants of acceptance.MethodsPatients (N = 116) were randomly assigned to a control group (CG) or intervention group (IG). The IG received a video AFI on smart sensing, and the CG a control video. An online questionnaire was used to assess acceptance of smart sensing, performance expectancy, effort expectancy, facilitating conditions and social influence. The intervention effects of the AFI on acceptance were investigated. The determinants of acceptance were analyzed with structural equation modeling (SEM).ResultsThe IG showed a moderate level of acceptance (M = 3.16, SD = 0.97), while the CG showed a low level (M = 2.76, SD = 1.0). The increase in acceptance showed a moderate effect in the intervention group (p

Background: Despite severely burdened individuals, often being excluded from research studies on internet- and mobile-based interventions (IMIs), negative events (NEs) including suicidal thoughts and behaviors (STBs) can still occur during a trial. NEs require monitoring and adequate safety measures. However, study protocols frequently lack comprehensive descriptions of procedures for managing NEs. Aims: This study aimed to illustrate the assessment, monitoring, and procedures for addressing NEs in two studies on IMIs in adults and youth using case reports, to identify strengths and weaknesses of the NE management approaches, and to derive key learnings and recommendations. Methods: Two case reports were drawn from two distinct IMI studies. The first study, PSYCHOnlineTHERAPY, evaluates the combination of an IMI with on-site psychotherapy for anxiety and depressive disorders in adults (adult blended study). The second study evaluates a standalone, therapist-guided IMI for post-traumatic stress disorder (PTSD) in youth (youth standalone study). Potential NEs were predefined depending on the study sample. The case studies thoroughly document the systematic recording and ongoing monitoring of NEs through self-report and observer-based assessments during the interventions. The cases illustrate a variety of NE management strategies, including automated and personalized approaches, adapted to the specific nature and severity of the NEs. The NE management approaches are visualized using decision trees. Results: In the adult blended case study, online questionnaires detected STBs and triggered automated support information. As on-site therapy had already ended, a telephone consultation session allowed for the identification and discussion of the heightened intensity of suicidal thoughts, along with the development of specific additional help options. In the youth standalone case study, heightened tension in an adolescent with PTSD during trauma processing could be addressed in a telephone therapeutic session focusing on resource activation and emotion regulation. The referral to on-site treatment was supported. Overall, advantages of the NE management included automated procedures, multimodal assessment of a wide range of NEs, and standardized procedures tailored to different severity levels. Weaknesses included the use of single-item assessments for STBs and lack of procedures in case of deterioration or nonresponse to treatment. Conclusion: This study provides practical insights and derives key learnings and recommendations regarding the management of NEs in different IMI contexts for both adults and youth.

Background: It is uncertain whether app-based interventions add value to existing mental health care. Objective: To examine the incremental effects of app-based interventions when used as adjunct to mental health interventions. Methods: We searched PubMed, PsycINFO, Scopus, Web of Science, and Cochrane Library databases on September 15th, 2023, for randomised controlled trials (RCTs) on mental health interventions with an adjunct app-based intervention compared to the same intervention-only arm for adults with mental disorders or respective clinically relevant symptomatology. We conducted meta-analyses on symptoms of different mental disorders at postintervention. PROSPERO, CRD42018098545. Results: We identified 46 RCTs (4869 participants). Thirty-two adjunctive app-based interventions passively or actively monitored symptoms and behaviour, and in 13 interventions, the monitored data were sent to a therapist. We found additive effects on symptoms of depression (g = 0.17; 95 % CI 0.02 to 0.33; k = 7 comparisons), anxiety (g = 0.80; 95 % CI 0.06 to 1.54; k = 3), mania (g = 0.2; 95 % CI 0.02 to 0.38; k = 4), smoking cessation (g = 0.43; 95 % CI 0.29 to 0.58; k = 10), and alcohol use (g = 0.23; 95 % CI 0.08 to 0.39; k = 7). No significant effects were found on symptoms of depression within a bipolar disorder (g = -0.07; 95 % CI -0.37 to 0.23, k = 4) and eating disorders (g = -0.02; 95 % CI -0.44 to 0.4, k = 3). Studies on depression, mania, smoking, and alcohol use had a low heterogeneity between the trials. For other mental disorders, only single studies were identified. Only ten studies had a low risk of bias, and 25 studies reported insufficient statistical power. Discussion: App-based interventions may be used to enhance mental health interventions to further reduce symptoms of depression, anxiety, mania, smoking, and alcohol use. However, the effects were small, except for anxiety, and limited due to study quality. Further high-quality research with larger sample sizes is warranted to better understand how app-based interventions can be most effectively combined with established interventions to improve outcomes.

IntroductionMost university students with mental disorders remain untreated. Evaluating the acceptance of intervention targets in mental health treatment, promotion, and prevention, as well as mental health service delivery modes is crucial for reducing potential barriers, increasing healthcare utilization, and efficiently allocating resources in healthcare services.AimThe study aimed to evaluate the acceptance of various intervention targets and delivery modes of mental health care services in German first-year university students.MethodsIn total, 1,376 first-year students from two German universities from the 2017–2018 multi-center cross-sectional cohort of the StudiCare project, the German arm of the World Mental Health International College Student Survey initiative, completed a web-based survey assessing their mental health. Mental disorder status was based on self-reported data fulfilling the DSM-IV criteria. We report frequencies of accepted delivery modes [categories: group or in-person therapy with on or off campus services, self-help internet- or mobile-based intervention (IMI) with or without coaching, or a combination of a in-person and IMI (blended)]. In a multinomial logistic regression, we estimate correlates of the preference for in-person vs. IMI vs. a combination of both modes (blended) modalities. Additionally, we report frequencies of intervention targets (disorder specific: e.g., social phobia, depressive mood; study-related: test anxiety, procrastination; general well-being: sleep quality, resilience) their association with mental disorders and sex, and optimal combinations of treatment targets for each mental illness.ResultsGerman university students' acceptance is high for in-person (71%–76%), moderate for internet- and mobile-based (45%–55%), and low for group delivery modes (31%–36%). In-person treatment (72%) was preferred over IMI (19%) and blended modalities (9%). Having a mental disorder [odds ratio (OR): 1.56], believing that digital treatments are effective (OR: 3.2), and showing no intention to use services (OR: 2.8) were associated with a preference for IMI compared to in-person modes. Students with prior treatment experience preferred in-person modes (OR: 0.46). In general, treatment targets acceptance was higher among female students and students with mental disorders. However, this was not true for targets with the highest (i.e., procrastination) and the lowest (i.e., substance-use disorder) acceptance. If only two intervention targets were offered, a combination of study-related targets (i.e., procrastination, stress, time management) would reach 85%–88% of the students.ConclusionIn-person services are preferred, yet half of the students consider using IMI, preferably aiming for a combination of at least two study-related intervention targets. Student mental health care services should offer a combination of accepted targets in different delivery modes to maximize service utilization.