Barriers and Facilitators for Referrals of Primary Care Patients to Blended Internet-Based Psychotherapy for Depression: Mixed Methods Study of General Practitioners’ Views
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Abstract
Background: Major depressive disorder (MDD) is highly prevalent and often managed by general practitioners (GPs). GPs mostly prescribe medication and show low referral rates to psychotherapy. Many patients remain untreated. Blended psychotherapy (bPT) combines internet-based interventions with face-to-face psychotherapy and could increase treatment access and availability. Effectively implementing bPT in routine care requires an understanding of professional users’ perspectives and behavior. Objective: This study aims to identify barriers and facilitators perceived by GPs in referring patients to bPT. Explanations for variations in referral rates were examined. Methods: Semistructured interviews were conducted with 12 of 110 GPs participating in a German randomized controlled trial (RCT) to investigate barriers to and facilitators for referrals to bPT for MDD (10 web-based modules, app-based assessments, and 6 face-to-face sessions). The interview guide was based on the theoretical domains framework. The interviews were audio recorded and transcribed verbatim, and the qualitative content was analyzed by 2 independent coders (intercoder agreement, k=0.71). A follow-up survey with 12 interviewed GPs enabled the validation of emergent themes. The differences in the barriers and facilitators identified between groups with different characteristics (eg, GPs with high or low referral rates) were described. Correlations between referrals and characteristics, self-rated competences, and experiences managing depression of the RCT-GPs (n=76) were conducted. Results: GPs referred few patients to bPT, although varied in their referral rates, and interviewees referred more than twice as many patients as RCT-GPs (interview-GPs: mean 6.34, SD 9.42; RCT-GPs: mean 2.65, SD 3.92). A negative correlation was found between GPs’ referrals and their self-rated pharmacotherapeutic competence, r(73)=−0.31, P<.001. The qualitative findings revealed a total of 19 barriers (B) and 29 facilitators (F), at the levels of GP (B=4 and F=11), patient (B=11 and F=9), GP practice (B=1 and F=3), and sociopolitical circumstances (B=3 and F=6). Key barriers stated by all interviewed GPs included “little knowledge about internet-based interventions” and “patients’ lack of familiarity with technology/internet/media” (number of statements, each k=22). Key facilitators were “perceived patient suitability, e.g. well-educated, young” (k=22) and “no conflict with GP’s role” (k=16). The follow-up survey showed a very high agreement rate of at least 75% for 71% (34/48) of the identified themes. Descriptive findings indicated differences between GPs with low and high referral rates in terms of which and how many barriers (low: mean 9.75, SD 1.83; high: mean 10.50, SD 2.38) and facilitators (low: mean 18.25, SD 4.13; high: mean 21.00; SD 3.92) they mentioned. Conclusions: This study provides insights into factors influencing GPs’ referrals to bPT as gatekeepers to depression care. Barriers and facilitators should be considered when designing implementation strategies to enhance referral rates. The findings should be interpreted with care because of the small and self-selected sample and low response rates.
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Fear that some students might have too little experience with new technologies and might not be familiar with the respective tools has been shown to be a barrier to the prescription of DTx.
“This also appears to be a very important finding for health care providers because the fear that some students might have too little experience with new technologies and might not be familiar with the respective tools has been shown to be a barrier to the prescription of DTx [61,62].”
From Barriers to and Facilitators of a Blended Cognitive Behavioral Therapy Program for Depression and Anxiety Based on Experiences of University Students: Qualitative Interview Study (2023) · cites this paper as [61]
The Results (Qualitative Findings) and Discussion (Principal Findings) identify GPs’ concern that some patients lack experience with technology as a barrier to referral. The source concerns patients referred to blended internet-based psychotherapy for depression, not students or the prescription of DTx generally. (LLM, conf=0.88)
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- Authors
- Titzler, I., Berking, M., Schlicker, S., Riper, H., & Ebert, D. D.
- Affiliations
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- GGZ inGeest (NL)
- Corresponding author
- Titzler, Ingrid
- Venue
- JMIR Mental Health
- Publisher
- JMIR Publications Inc.
- Published
- 2020-08-18
- Volume
- 7
- Issue
- 8
- Pages
- e18642
- ISSN
- 2368-7959 (ISSN-L)
- PMC
- PMC7463410
- OpenAlex
- W3042992466
- Cited by
- 25
- References
- 69
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 4 · 2023: 6 · 2022: 6 · 2021: 1
- FWCI
- 2.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Mental Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- VU Research Portal (publishedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- OPUS Repository (Kooperativer Bibliotheksverbund Berlin-Brandenburg) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- European Commission (603098)
- Friedrich-Alexander-Universität Erlangen-Nürnberg
- Deutsche Forschungsgemeinschaft
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- major depressive disorder, internet-based psychotherapy, general practitioners, primary care, treatment access, Theoretical Domains Framework
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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