Background: The therapeutic alliance (TA) is a robust predictor of outcome in psychotherapy. Blended care (BC), combining face-to-face (F2F) with digital components, is gaining momentum in mental health care, yet the role of the TA remains poorly understood. Objectives: This preregistered systematic review and meta-analysis examined (1) levels of TA across BC studies, (2) the association between TA and outcome in BC, and (3) differences in TA ratings between BC and control conditions. Methods: The search identified 48 studies reporting TA in BC (N = 3210 participants who received BC). Multilevel meta-analyses estimated the alliance-outcome correlation and standardized mean differences in TA between BC and control groups, including F2F psychotherapy and treatment as usual. Moderator analyses examined patient-, therapist-, and treatment-level variables. Results: Alliance ratings were high across BC groups (average percent of maximum possible score across measures rated by patients: 74.1 ± 12.0). The association between TA and outcome in BC was small to moderate (r = .24, 95% CI [.16, .31], p < .001). Patient-rated TA in BC did not differ significantly from patient-rated TA in control groups (g = 0.07, 95% CI [-0.07, 0.21], p = 0.339). Conclusions: The combination of digital and F2F elements to treat mental health problems does not compromise the TA. Alliance remains a meaningful predictor of outcome in this context and alliance levels in BC are comparable to those in F2F controls. Findings highlight the need for BC-specific measures of the TA, and standardized reporting of BC characteristics for granular synthesis.

Abstract Background Expectations are considered an important mechanism of change in psychotherapeutic interventions, including internet- and mobile-based interventions (IMI). This study aims to investigate whether two expectation-focused microinterventions can enhance the effects of an IMI for participants with elevated depression. Methods All participants will receive an established IMI consisting of six evidence-based cognitive behavioral modules. In this 2×3 factorial design, 720 adult participants will be randomized to receive (1) either the IMI in standard or personalized framing (first randomization factor), in combination with (2) an expectation-focused telephone call mid-treatment, a supportive phone call or no phone call (second randomization factor). The primary outcome is depression at mid- and post-treatment (BDI-II). Secondary measures include expectations, adherence, state and trait anxiety and depression, disability, negative effects, and satisfaction with treatment. Discussion This study will increase knowledge about applying micro-interventions to modify expectations and improve the effects of IMI in the treatment of depressive symptoms. Scalable IMI has the potential to improve healthcare but ways to further improve their effects and adherence need to be explored. Trial registration The trial was prospectively registered under DRKS00032982. Registered on July 11, 2023.

Common factors and facilitative interpersonal skills are central to mental health treatment outcomes, yet existing assessments remain fragmented across constructs, modalities, and rater perspectives. We developed and validated the Cross-Modal Inventory for Common Factors and Facilitative Interpersonal Skills (CMICF), a brief patient-reported measure for psychotherapeutic and psychiatric settings. Data came from two clinical samples receiving mental health treatment (construction: N = 707; validation: N = 1,230; øage = 36.7[18-79], 78.7% female). An initial 101-item pool covering 14 evidence-based relational and interpersonal skill domains was reduced using ant colony optimization and expert-guided scale merging. The final 33-item instrument comprised nine factors: alliance bond capacity, goals/collaboration, congruence, emotional expression, hope/positive expectations, treatment credibility, managing countertransference, rupture-repair responsiveness, and verbal fluency. Confirmatory factor analyses showed excellent model fit in the construction sample (CFI = .974, RMSEA = .036, SRMR = .029) and validation sample (CFI = .959, RMSEA = .045, SRMR = .036). Internal consistency was good to excellent for most subscales (ω = .73–.91), except congruence (ω = .58). Configural, metric, scalar, and strict invariance were supported across treatment settings and personality dysfunction severity. Convergent validity was demonstrated through theoretically consistent associations with established measures of alliance and related relational constructs. Discriminant validity was supported by small negative associations with psychopathology (all |r| < .30). Alliance bond capacity showed partly strong intercorrelations, indicating that specific relational processes may be anchored in the overall therapeutic bond. The CMICF provides a psychometrically robust, cross-modal assessment of relational common factors and facilitative interpersonal skills from the patient perspective in psychotherapy and psychiatric care.

OBJECTIVE:Blended Care (BC) has emerged as a promising approach to address the growing demand for mental health treatment, but little is known about its change mechanisms and how they compare to traditional psychotherapy (PT). This study investigates therapeutic alliance, general and mental health self-efficacy, and therapeutic agency function as mechanisms of change. METHODS:We conducted a secondary analysis of a randomized controlled trial (N = 1,159 patients) comparing BC to PT in routine outpatient care. Mechanism and outcome variables (mental distress, satisfaction with life) were assessed at four time points over six months. We used random-intercept cross-lagged panel models (RI-CLPM) to differentiate between- from within-person effects. RESULTS:All constructs were associated with better outcomes. Temporal effects showed that mental health self-efficacy predicted subsequent increases in satisfaction with life, and therapeutic alliance predicted lower mental distress at specific time points. General self-efficacy showed inconsistent effects, with counterintuitive findings in the BC group, where higher self-efficacy predicted increased mental distress. Agency was mainly related to satisfaction with life. Outcomes also predicted changes in mechanisms. Differences between BC and PT were only significant for general self-efficacy. CONCLUSION:Our findings suggest that therapeutic change is dynamic and reciprocal. The unexpected associations in the BC group need replication.

Blended care (BC), combining face-to-face therapy with digital components, is gaining momentum in the field of mental health, yet lacks conceptual clarity. This perspective paper outlines a dimensional conceptualization of BC and introduces the B-FIT (Blend-Focus-Integration-Timing) framework. We highlight the need to refine the theoretical foundations of BC, strengthen the evidence base for its effectiveness, and integrate stakeholder perspectives to inform future research and support the successful implementation of BC.

Patients' expectations about treatment benefits are robust predictors of clinical outcomes across medical and psychological contexts. Recent evidence suggests that expectancy effects in digital mental health interventions (DMHIs) are comparable in magnitude to those observed in face-to-face treatments. Despite their relevance, systematic guidance on how expectations can be shaped and optimized within DMHIs is limited. This narrative review summarizes theoretical and empirical work on expectations, including placebo and nocebo mechanisms, and digital intervention design to outline how expectation principles may be integrated into DMHIs. We describe three overarching principles - proactive expectation management, warmth and competence, and observational learning - and discuss how these mechanisms can be translated into practice across different stages and components of DMHI, including recruitment and onboarding, content, guidance, and interface design. We further highlight opportunities for expectation monitoring, automated feedback, and just-in-time adaptive interventions to support expectations. While modifications to single components may yield limited effects, coordinated, expectation-informed optimization across multiple DMHI components may have the potential to meaningfully enhance engagement and clinical outcomes. We conclude by discussing conceptual and methodological considerations and outline promising future directions for integrating the expectation lens within digital mental health.

ObjectiveTherapists differ in their effectiveness, yet precision mental health has primarily focused on matching patients to treatments rather than to the person delivering it. We investigated whether machine-learning (ML) models trained on comprehensive patient and therapist data can predict early psychotherapy outcomes and generate patient-specific therapist recommendations. MethodsOur sample included 1,159 patients nested within 189 therapists in routine outpatient psychotherapy in Germany. The outcome was mental distress (PHQ-8 and GAD-7 composite) at week 6 of therapy. Predictors comprised (A) therapist demographics, professional information, and personality, and (B) patient demographics, personality, and clinical features. We trained and compared three explainable ML models with strength in modeling interactions, i.e., Factorization Machines, CatBoost, and Explainable Boosting Machines, against reasonable benchmarks (i.e., patient-only). We evaluated recommendation validity by regressing week-6 distress on the predicted rank of the factual therapist. ResultsA total of 957 patients nested within 174 therapists were available for analysis (5±4 patients per therapist). CatBoost outperformed other ML architectures in predicting mental distress (RMSE = 6.05 ± 0.11) but performed similarly to the patient-only benchmark (RMSE = 6.09 ± 0.12, p = .09). Week-6 distress tended to be higher when the factual therapist received a worse rank, but this association was small and not statistically significant (b = 0.0089, SE = 0.0060, 95% CI [-0.0028, 0.0207], p = .136). ConclusionsTherapist features added little predictive value beyond patient features, and we found no robust evidence that model-based therapist rankings translated into better outcomes. Datasets with higher therapist caseloads are needed to evaluate therapist recommender systems more conclusively.

Background: While growing research confirms the efficacy of transdiagnostic cognitive behavioral psychotherapy (TD-CBT) by examining group-level changes from pre to post-treatment, less is known about inter-individual differences and dynamic changes during therapy. Understanding different symptom trajectories and their associations with treatment outcome would allow early detection of non-responders and treatment adjustments.Methods: Patients with anxiety disorders reported on demographics, clinical history, treatment motivation, and expectations before randomization to TD-CBT or wait-list. We analyzed data from the treatment group who provided symptom ratings every session and post-treatment follow-up (N = 64, 71.9% female, age: M = 32.67, SD = 11.91). Using latent class growth analysis (LCGA), we identified symptom trajectory classes and tested whether these could be predicted from baseline data. We also examined associations between classes and treatment outcome, using multilevel modeling and considering reliable change indices. Results: LCGA revealed four distinct trajectory classes: low severity - improved (32.81%), high severity - improved (29.69%), high severity-stagnant (18.75%), and low severity - worsened (18.75%). Only number of comorbidities emerged as a significant predictor of class, with patients in the high severity - stagnant group having more comorbidities. They also showed higher symptom severity at baseline and follow-ups compared to other classes, despite clear improvement.Conclusions: During TD-CBT, latent classes of symptom change can be distinguished and point to malleable factors already present at pre-treatment. Particularly patients with high initial burden and a higher number of comorbidities may require monitoring and adaptive treatment strategies, which should be explored in future studies.

Evidence suggests that blended therapy combining face-to-face psychotherapy with digital components may reduce treatment dropout, yet definitions of dropout vary widely. This variability is particularly pronounced in blended therapy, where dropout may involve discontinuation of in-person sessions, disengagement from digital components, or both. This study aimed to identify operational definitions of treatment dropout in blended therapy and to examine how different definitions influence dropout rates, treatment outcomes, and usage patterns. A scoping review identified 14 studies reporting operational definitions of dropout. Five synthesized definitions were applied to data from a large blended therapy trial, revealing variation in dropout rates and their associations with depressive symptoms, anxiety, and life satisfaction. Cluster analysis further identified distinct digital usage patterns. These findings highlight the need for transparent and differentiated reporting of dropout definitions in blended therapy research to improve comparability and interpretation across studies.

OBJECTIVE:Blended care (BC), the integration of Internet-based interventions into psychotherapy (PT), is thought of as a promising approach to enhance PT's effectiveness and efficiency. This randomized controlled trial aimed to investigate the effectiveness as well as the implementation and usage of BC with transdiagnostic online modules compared to PT in routine care in Germany. Routine outpatient PT is delivered by licensed psychotherapists across different therapeutic orientations (cognitive behavioral therapy, psychodynamic, systemic), with variable treatment lengths and procedures. METHOD:Psychotherapists in routine outpatient care recruited 1,159 patients who were randomized to BC or PT. The primary outcome was self-reported mental distress (the composite of anxiety and depression); secondary outcomes included self-reported satisfaction with life, level of functioning, eating pathology, and drug and alcohol use, as well as therapist-rated severity and changes. Outcomes were measured at baseline, 6 weeks, 12 weeks, 6 months, and 12 months. We examined whether BC and PT groups changed differently over time using linear mixed models. We also investigated differences in sessions and terminations and report usage metrics of the BC platform. RESULTS:Contrary to our hypotheses, we did not find differences between BC and PT in outcomes, including anxiety, depression, satisfaction with life, level of functioning, eating pathology, alcohol and drug use, therapist-rated severity, and satisfaction with treatment at 6 months postrandomization (all p > .05). BC and PT did not differ in the number of sessions or terminations. Regarding usage of the BC platform, 534 patients (91.6%) received at least one online chapter, with M = 7.26 (SD = 7.01) of a total of 39 online chapters assigned on average, and patients logged in M = 19.73 (SD = 24.66) times and spent M = 367.14 (SD = 338.27) minutes on the platform. CONCLUSIONS:In this real-world application of BC, therapists had considerable flexibility in implementing BC and integrating Internet-based interventions with sessions. Our findings suggest that the benefits observed in more structured BC setups may not fully translate to a flexible and transdiagnostic BC setup in routine care, potentially due to variations in implementation and adherence. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Background:Internet-based interventions (IBIs) offer the potential for personalization through various mechanisms and components. Objective:This systematic review aimed to synthesize evidence on the personalization of treatment components within IBIs targeting diverse mental health conditions. Specifically, we focused on studies that directly compared personalized components to standardized ones to isolate the impact of personalization on mental health outcomes and treatment adherence. Results:Thirteen studies were identified that compared personalized to non-personalized components, with the personalization of IBI content and personalized guidance investigated the most. Apart from one study that personalized more than one IBI component, studies did not find a significant positive effect of personalization on mental health outcomes. Two studies reported better adherence for human feedback personalized to user input than for the automated non-personalized guidance. Discussion:The results reveal a gap between the theoretical potential of personalization in IBIs and the current evidence supporting its impact on outcomes and adherence. The diversity in personalization strategies across studies complicates the ability to draw definitive conclusions. To address this, more detailed descriptions of how personalization is both implemented and communicated to patients are recommended.

Introduction:Psychotherapists may act as bottlenecks in the integration of digital interventions into psychotherapy, known as blended care (BC). In the literature, various factors are discussed as potential inclusion, exclusion, or limiting criteria in BC. Method:Our aim for this interview study was to gain a deeper understanding of the factors psychotherapists consider when inviting patients to participate in BC. For this purpose, we interviewed seven psychotherapists with a psychodynamic and seven psychotherapists with a cognitive behavioral background who participated in a naturalistic trial on BC in routine outpatient psychotherapy. Results:Psychotherapists considered few fixed inclusion or exclusion criteria when considering which patients to introduce BC to. The basic technical requirements had to be met and the patients had to be "fit for outpatient therapy". Psychotherapists found patients' response to BC, like their motivation, to be a decisive factor when considering BC. Discussion:Psychotherapists emphasized patient motivation for BC as a potential bottleneck in its implementation. Therefore, a successful implementation strategy should focus on strengthening both psychotherapists' and patients' motivation to engage with BC. The openness of psychotherapists towards patient characteristics suggests that BC in outpatient care may target a broad patient population.

OBJECTIVE:This study evaluated the acceptability and preliminary effectiveness of the UP in blended format, combining face-to-face UP sessions with the use of the UP-App, versus Treatment as Usual (TAU) for treating Emotional disorders (ED) in Spanish specialized mental health units. METHODS:A total of 76 adults presenting a diagnosis of ED were randomly assigned to UP + APP (n = 40) or TAU (n = 36) and completed self-report questionnaires at baseline, 3 and 6 months after treatment onset. RESULTS:Improvements in both conditions for ODSIS (b = -2.84; T = -2.36), depressed mood (b = -6.85; T = 0.01), and the describing facet of mindfulness were found (b = 4.01; T = 2.31). No significant differences were found between both conditions in terms of treatment outcomes or in the Time∗Condition interaction. However, engagement with the UP-App understood as number of completed UP-App modules was related to improvements in emotion regulation and the acting with awareness facet of mindfulness, especially at 6 months, suggesting a possible time-dependent effect and UP-App modules completed. The UP-App showed good usability at 3 months (76.47) and excellent at 6 months (83.96), but low adherence (7.5% completers). Satisfaction with the treatment was similar in both conditions. CONCLUSIONS:This study suggests that the UP + APP may be as effective as TAU for ED in the SNHS. However, high dropout rates and low adherence to the UP-App constrain these results. Future research should explore a modified implementation format of the UP + APP ensuring a greater presence of the therapist, as well as an updated version of the UP-App incorporating feedback from the current study and new functionalities, in an RCT with a larger sample, as well as comparing standard UP vs UP + APP to determine the unique contribution of the UP-App on effectiveness, adherence, and user experience with UP.Trial registration:ClinicalTrials.gov identifier: NCT04304911.

Introduction:Internet-based interventions (IBI) increase access to evidence-based treatments for mental disorders, but knowledge of their mechanisms of change is limited. Self-efficacy, a key factor in psychotherapy, is especially relevant in IBI due to its self-help focus. We investigated self-efficacy and related constructs as outcomes, predictors/moderators, and mediators in randomized controlled trials. Methods:A systematic search was conducted across PsycINFO, PubMed, CINAHL, and Web of Science. Two reviewers selected studies, extracted data, and assessed bias. Effects were quantified using random effect models and supplemented by narrative syntheses and box score visualizations. Results:70 studies (N = 17,407 participants) were included. IBI showed moderate effects on self-efficacy in within (d = 0.47) and between (d = 0.46) comparisons, with guided interventions having the largest effect (d = 0.66). Findings on self-efficacy as a predictor/moderator were mixed, though some studies suggested individuals with lower self-efficacy benefit more. Self-efficacy emerged as a mediator through which IBI affected treatment outcomes. Conclusion:Self-efficacy appears influential in IBI efficacy and may itself be a valuable treatment target. However, mixed results and methodological limitations in mediator studies highlight the need for further research, particularly on long-term effects.

Background: Internet-based interventions (IBIs) offer the potential for personalization through various mechanisms and components. Objective: This systematic review aimed to synthesize evidence on the personalization of treatment components within IBIs targeting diverse mental health conditions. Specifically, we focused on studies that directly compared personalized components to standardized ones to isolate the impact of personalization on mental health outcomes and treatment adherence.Results: Twelve studies were identified that compared personalized to non-personalized components, with the majority focusing on the personalization of IBI content. Apart from one study that personalized more than one IBI component, studies did not find a significant positive effect of personalization on mental health outcomes or adherence.Discussion: The results reveal a gap between the theoretical potential of personalization in IBIs and the current evidence supporting its impact on outcomes and adherence. The diversity in personalization strategies across studies further complicates the ability to draw definitive conclusions. To address this, more detailed descriptions of how personalization is both implemented and communicated to patients are recommended.

Blended Care (BC) has emerged as a promising approach to address the growing demand for accessible mental health treatment. While BC is effective for various mental disorders, little is known about the mechanisms through which BC leads to change and how they compare to traditional psychotherapy. This study investigates whether therapeutic alliance, general and mental health self-efficacy, and therapeutic agency function as mechanisms of change in BC and face-to-face psychotherapy (PT). We conducted a secondary analysis of a randomized controlled trial (N = 1,159 patients) comparing BC to PT in routine outpatient care in Germany. Mechanism and outcome variables (mental distress, satisfaction with life) were assessed at four time points over six months. Random-intercept cross-lagged panel models (RI-CLPM) were used to differentiate stable between-person associations from temporal within-person effects. Both self-efficacy constructs and therapeutic alliance were associated with better outcomes in both treatments. Agency was associated with higher life satisfaction but not symptom reduction. Temporal effects indicated that increases in mental health self-efficacy and therapeutic alliance predicted improved outcomes at the following time point. General self-efficacy and agency showed inconsistent effects, with counterintuitive findings in the BC group where higher self-efficacy and agency predicted more distress or less life satisfaction. Outcomes also predicted changes in mechanisms, indicating reciprocal dynamics. Differences between BC and PT were only significant for general self-efficacy. Our findings suggest that therapeutic change is dynamic and reciprocal. The unexpected association of higher self-efficacy and increased distress in the BC group needs replication.

Internet-based interventions (IBIs) are effective for treating depression, but they can also lead to negative effects in some participants. There is no consensus on which specific characteristics of negative effects clinicians and researchers should focus on. Studies often combine distinct (sub)categories of negative effects, complicating interpretation. This study aimed to identify specific (sub)categories of negative effects related to depression and adherence and explore their predictors. In a sample of participants undergoing an IBI for depression (N = 1610; 61% female), 113 participants (7%) reported experiencing at least one negative effect. 110 qualitatively reported negative effects and were categorized into a framework consisting of two main categories (treatment-related vs. patient-related) of negative effects, divided into five subcategories (format, contact, implementation, symptoms, and insight). No differences in adherence were observed between any (sub)categories of negative effects; however, participants who reported treatment-related negative effects showed significantly lower symptom improvement than those reporting patient-related negative effects. No patient demographic characteristics predicted any negative effects. Differentiating treatment- and patient-related negative effects could enhance future research and intervention efforts.

Abstract Background Internet-based interventions (IBIs) are a low-threshold treatment for individuals with depression. However, comparisons of IBI against unstandardized care-as-usual (CAU) are scarce. Moreover, little evidence is available if IBI has an add-on effect for individuals already receiving an evidence-based treatment such as antidepressants and/or psychotherapy. Method This parallel, two-arm RCT (1:1 allocation ratio, simple randomization) examines the effectiveness of a therapist-guided cognitive-behavioral IBI compared to unstandardized CAU in a self-selected sample of adults (≥ 18 years). Eligible individuals reported (a) mild (BDI-II score ≥ 14) to moderately severe (PHQ-9 ≤ 19) symptoms of depression, (b) no acute suicidal ideations, (c) no acute or lifetime (hypo-)mania and/or symptoms of psychosis. We assigned eligible individuals to an intervention (INT) arm or an unstandardized CAU-arm (i.e., we imposed no restrictions on what individuals were allowed to do in the 8-week waiting period). Individuals in the INT-arm got access to a 7-module CBT-based IBI. The primary endpoint is depressive symptom load 9 to 11 weeks after randomization. Secondary endpoints included anxiety, self-efficacy, and perceived social support. We report effects for the entire sample (N = 1899), as well as for individuals using the IBI as a stand-alone intervention (n = 1408) or as an add-on to antidepressants (n = 367), psychotherapy (n = 73), or antidepressants and psychotherapy (n = 51). Patients entered the trial with these concurrent treatments (i.e., they were not randomly assigned). Results Concerning all randomized individuals, 62.5% of individuals in the INT-arm accessed all treatment modules within 11 weeks. Individuals assigned to the INT-arm reported significantly lower depressive symptoms (PHQ-9: − 2.5, 95% CI [− 2.9, − 2.0], d = − 0.7; BDI-II: − 5.3, 95% CI [− 6.5, − 4.1], d = − 0.8) and higher rates of ≥ 50% symptom improvements (PHQ-9: 38.5% vs. 14.3%; BDI-II: 44.6% vs. 14.8%) compared to individuals assigned to the CAU-arm. Secondary outcomes also favored INT over CAU, with effect sizes ranging from |d|= 0.18 (social support) to 0.62 (anxiety). Rates of deterioration (PHQ-9: 4.1%; BDI-II: 3.4%) and self-reported side effects (10.5%) were low in the INT-arm. Similar patterns emerged for all strata. However, the between-arm differences failed to reach significance within the strata of individuals using the IBI as an add-on to psychotherapy. Conclusion Our results show that providing interested adults access to the therapist-guided, cognitive-behavioral IBI under investigation is associated with improved mental health outcomes, whether individuals use the IBI as a stand-alone or add-on intervention to another evidence-based treatment. This finding aligns with available studies indicating that IBIs should be considered a low-threshold treatment option for individuals with depression. Trial registration The trial was registered at the Deutsches Studienregister (Trial-Registriation Number/DRKS-ID: DRKS00021106, Date: 25.06.2020).

Discrimination is a risk factor for adverse mental health. Regional examinations are necessary to account for the sociocultural context that shapes lived experiences of marginalized groups. This meta-analytic review examined how multiple forms of discrimination are considered in German mental health research and analyzed the relationship of perceived discrimination with depressive and posttraumatic stress symptoms (i=36 studies; N=45,527). Discrimination was significantly associated with depressive (r=0.26, p<.001) and posttraumatic stress symptoms (r=0.23, p<.01). Subgroup analyses revealed a smaller effect size for studies which examined discrimination based on mental health vs. other forms of discrimination. Frequency of published reports has increased over the past 20 years (b=0.27, p<.001), but data gaps for several populations, discrimination forms and validated measures continue to exist. The findings emphasize the need for improved methodological assessment and broader inclusion of discrimination in German mental health research along with targeted interventions to reduce its impact.

Abstract Background Sexual problems and well-being are critical areas of mental health that remain under-addressed in traditional psychotherapeutic settings. From a patient’s view, reasons include feelings of discomfort and fear of stigma. Internet- and mobile-based interventions (IMIs) may offer a way to reach this population and provide necessary support. Thus far, few studies investigated IMIs for sexual problems, mostly targeting specific disorders, like erectile dysfunction or vaginismus. This study aimed to identify the key requirements for developing an IMI for a broader range of sexual problems and sexual well-being from the perspective of potential users. Method To gather insights into user needs and preferences, we conducted 13 semi-structured interviews with adult participants in Germany that reported to have sexual problems. Interviews were analyzed using qualitative content analysis. Categories were established deductively-inductively from transcribed interview records. Our theory-based interview schedule informed the initial deductive coding system, while inductive categories emerged through multiple review rounds of the interview transcripts by all researchers. We also ensured inter-rater reliability. Results Key findings revealed that expert knowledge and destigmatization are crucial components for a potential IMI for sexual problems and well-being. Preferred content topics included communication, dealing with sexualized violence, and sexual preferences. While most participants were open to using a potential IMI with their partners and preferred on-demand professional support, the study also highlighted the importance of avoiding insensitivity and inappropriate content related to sexual abuse. Conclusions This study underlines the importance of developing an IMI targeting sexual problems that is inclusive, responsive to diverse user needs, and adaptable to various psychotherapeutic contexts.