Clinical bottom line
Digital cognitive behavioral therapy (dCBT) for hoarding disorder is an emerging intervention that offers a scalable, accessible alternative to traditional face-to-face CBT. Early evidence suggests dCBT can reduce hoarding symptoms and improve functional outcomes, particularly for patients facing barriers to in-person treatment. However, the evidence base remains limited, with most studies small, heterogeneous, and lacking long-term follow-up. Clinicians should consider dCBT as a promising adjunct or step in stepped-care models, especially when access to specialized hoarding disorder therapy is limited, but continue to prioritize comprehensive assessment and individualized treatment planning.
What the evidence shows
Hoarding disorder is characterized by persistent difficulty discarding possessions, leading to clutter that compromises living spaces and functioning. Cognitive behavioral therapy targeting hoarding disorder traditionally involves motivational interviewing, skills training, cognitive restructuring, and exposure to discarding and organizing tasks (Tompkins et al., 2017; Rasmussen et al., 2023). While effective, access to specialized CBT is often limited by geographic, financial, or stigma-related barriers.
Recent work has explored digital delivery of CBT components tailored for hoarding disorder, leveraging online platforms, interactive modules, and remote therapist support. These digital interventions aim to replicate core CBT elements such as psychoeducation, cognitive restructuring, and behavioral experiments in a flexible format.
Rasmussen et al. (2023) highlight preliminary trials showing that dCBT can produce moderate reductions in hoarding severity scales and improvements in quality of life measures. For example, structured online programs with therapist guidance yielded symptom improvements comparable to traditional CBT in small cohorts, though effect sizes varied. Stamatis et al. (2021) emphasize that digital CBT may enhance treatment adherence through convenience and real-time progress tracking.
Additional evidence from case studies and clinical reports (Farquhar et al., 2020) supports feasibility and acceptability of dCBT in older adults, a population often disproportionately affected by hoarding disorder and with limited mobility. Højgaard et al. (2023) also discuss adaptations of CBT for hoarding in younger populations, suggesting digital formats could facilitate early intervention.
Despite these encouraging findings, the literature remains sparse regarding optimal digital program design, intensity, and the role of therapist involvement. Juaneza et al. (2020) note that while digital CBT may reduce some barriers, challenges remain in addressing motivational deficits and comorbidities common in hoarding disorder.
Caveats and uncertainty
The current evidence for dCBT in hoarding disorder is largely hypothesis-generating and warrants cautious interpretation. Most studies are small, lack randomized controls, and have short follow-up durations, limiting conclusions about durability of treatment effects (Rasmussen et al., 2023; Stamatis et al., 2021). Heterogeneity in digital platforms, patient populations, and outcome measures complicates synthesis.
Moreover, hoarding disorder often co-occurs with cognitive deficits, executive dysfunction, and comorbid psychiatric conditions that may affect engagement with digital interventions (Tompkins et al., 2017). The extent to which dCBT can adequately address these complexities without in-person support is unclear.
There is also limited data on safety monitoring, risk management (e.g., fire hazards, sanitation), and crisis intervention protocols within digital formats. Clinicians should remain vigilant about these issues when considering dCBT.
Finally, digital literacy, access to technology, and patient preference may influence suitability and effectiveness, potentially exacerbating disparities if not carefully managed.
How this may change practice
Digital CBT for hoarding disorder represents a promising adjunct to traditional care, particularly for patients facing barriers to specialized in-person therapy. Clinicians might consider integrating dCBT into stepped-care models, initiating with digital interventions for mild-to-moderate cases or as a complement to face-to-face sessions.
Implementation should include careful patient selection, assessment of digital readiness, and ongoing monitoring of symptom response and safety. Hybrid models combining digital modules with periodic therapist contact may optimize engagement and outcomes.
As evidence evolves, dCBT could expand access to evidence-based treatment, reduce wait times, and support maintenance of gains post-discharge. However, clinicians should remain cautious, prioritizing comprehensive evaluation and individualized treatment planning until more robust data are available.