How New Technologies Can Improve Prediction, Assessment, and Intervention in Obsessive-Compulsive Disorder (e-OCD): Review
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Abstract
Background: New technologies are set to profoundly change the way we understand and manage psychiatric disorders, including obsessive-compulsive disorder (OCD). Developments in imaging and biomarkers, along with medical informatics, may well allow for better assessments and interventions in the future. Recent advances in the concept of digital phenotype, which involves using computerized measurement tools to capture the characteristics of a given psychiatric disorder, is one paradigmatic example. Objective: The impact of new technologies on health professionals’ practice in OCD care remains to be determined. Recent developments could disrupt not just their clinical practices, but also their beliefs, ethics, and representations, even going so far as to question their professional culture. This study aimed to conduct an extensive review of new technologies in OCD. Methods: We conducted the review by looking for titles in the PubMed database up to December 2017 that contained the following terms: [Obsessive] AND [Smartphone] OR [phone] OR [Internet] OR [Device] OR [Wearable] OR [Mobile] OR [Machine learning] OR [Artificial] OR [Biofeedback] OR [Neurofeedback] OR [Momentary] OR [Computerized] OR [Heart rate variability] OR [actigraphy] OR [actimetry] OR [digital] OR [virtual reality] OR [Tele] OR [video]. Results: We analyzed 364 articles, of which 62 were included. Our review was divided into 3 parts: prediction, assessment (including diagnosis, screening, and monitoring), and intervention. Conclusions: The review showed that the place of connected objects, machine learning, and remote monitoring has yet to be defined in OCD. Smartphone assessment apps and the Web Screening Questionnaire demonstrated good sensitivity and adequate specificity for detecting OCD symptoms when compared with a full-length structured clinical interview. The ecological momentary assessment procedure may also represent a worthy addition to the current suite of assessment tools. In the field of intervention, CBT supported by smartphone, internet, or computer may not be more effective than that delivered by a qualified practitioner, but it is easy to use, well accepted by patients, reproducible, and cost-effective. Finally, new technologies are enabling the development of new therapies, including biofeedback and virtual reality, which focus on the learning of coping skills. For them to be used, these tools must be properly explained and tailored to individual physician and patient profiles.
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Delivering OCS treatment via video-conferencing holds promise to be at least equally effective as face-to-face treatment.
“These findings are confirmed in a meta-analysis which found that delivering OCS treatment via video-conferencing holds promise to be at least equally effective as face-to-face treatment but comparison studies with face-to-face control groups are necessary [14].”
From Personalized exposure and experience sampling method feedback versus exposure as usual for obsessive–compulsive disorder: a study protocol for a randomized controlled trial (2024) · cites this paper as [14]
The Results > Interventions section (page not provided) reports that videoconference treatment was effective and that face-to-face control studies are lacking. Its table reports one small comparison in children with no significant difference in responder status, which supports cautious promise but does not establish equal effectiveness generally. The cited paper is a review, not the meta-analysis described in the citing sentence. (LLM, conf=0.87)
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“Few studies have specifically focused on computerized CBT for OCD, of which 6 [64-69] featured computer-driven telephone interview system (BT Steps).”
Salomoni, G., Grassi, M., Mosini, P., Riva, P., Cavedini, P., & Bellodi, L. (2009) · Journal of Clinical Psychopharmacology · doi:10.1097/jcp.0b013e3181aba68f · Cited by 41 · cited 1× · see citing works
“…perceptron (ie, supervised artificial neural network) was compared with a classic logistic regression model, it was found to have a considerably better predictive performance (93.3% vs 61.5%), when it came to correctly classifying patients as nonresponders to treatment (46.9% of participants) [83].”
InfluentialBourla, A., Ferreri, F., Ogorzelec, L., Guinchard, C., & Mouchabac, S. (2017) · L Encéphale · doi:10.1016/j.encep.2017.07.007 · Cited by 41 · cited 1× · see citing works
“Several digital phenotype models are now emerging for schizophrenia [6] and mood disorders [7].”
Self-citationLovell, K., Bower, P., Gellatly, J. L., Byford, S., Bee, P., McMillan, D., Arundel, C., Gilbody, S. M., Gega, L., Hardy, G. E., et al. (2017) · PLoS Medicine · doi:10.1371/journal.pmed.1002337 · Cited by 40 · cited 1× · see citing works
“It should be noted that BT Steps was subsequently modified to be used online, and its name was changed to OCFighter [57], but Lovell et al found that, when used with low intensity, OCFighter does not lead to clinically significant benefits, although it may reduce uptake of therapist-led CBT [72].”
A Virtual Reality Game to Assess Obsessive-Compulsive Disorder
van Bennekom, M. J., Kasanmoentalib, M. S., de Koning, P. P., & Denys, D. A. J. P. (2017) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2017.0107 · Cited by 40 · cited 1× · see citing works
“A pilot study comparing 8 patients with OCD and 8 healthy controls showed that VR is capable of triggering OCD symptoms in patients, allowing clinicians to directly observe and assess OCD symptoms [27].”
Laforest, M., Bouchard, S., Bossé, J., & Mesly, O. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00099 · Cited by 39 · cited 2× · see citing works
“Laforest et al [77] enrolled 3 adults with contamination OCD and exposed them to 2 virtual environments: a training environment (neutral) and an experimental (contaminated) environment.”
Rees, C. S., Anderson, R., Kane, R. T., & Finlay‐jones, A. L. (2016) · JMIR Mental Health · doi:10.2196/mental.5363 · Cited by 37 · cited 1× · see citing works
“The results are summarized in Multimedia Appendix 1 [52-62].”
Lenhard, F., Vigerland, S., Engberg, H., Hallberg, A., Thermaenius, H., & Serlachius, E. (2016) · PLOS ONE · doi:10.1371/journal.pone.0164311 · Cited by 37 · cited 1× · see citing works
“Most concluded that a Web-based treatment is effective, highly acceptable to patients with OCD [50], and may reduce barriers to treatment access [51].”
Nguyen, D., Klein, B., Meyer, D., Austin, D., & Abbott, J.-A. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4195 · Cited by 35 · cited 1× · see citing works
“…Psychological Assessment System, a Web-based, self-report, multidisorder, clinical assessment and referral system showed a fair agreement with the clinical interview for OCD (kappa=0.39) [19] XSL • FO RenderX With an EMA, patients respond to a series of questions based on their reported symptoms.”
InfluentialInternet-Based Cognitive Behavioral Therapy for Obsessive-Compulsive Disorder in Korea
Seol, S.-H., Kwon, J. S., Kim, Y. Y., Kim, S. N., & Shin, M.-S. (2016) · Psychiatry Investigation · doi:10.4306/pi.2016.13.4.373 · Cited by 35 · see citing works
Lind, C., Boschen, M. J., & Morrissey, S. (2013) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2012.09.004 · Cited by 33 · cited 1× · see citing works
“Technologies can also be used to augment traditional CBT [38,39], and could address issues of accessibility and effectiveness by increasing treatment adherence.”
Process-outcome analysis in computer-aided treatment of obsessive-compulsive disorder
Kirkby, K. C., Berríos, G. E., Daniels, B. A., Menzies, R. G., Clark, A. A., & Romano, A. (2000) · Comprehensive Psychiatry · doi:10.1053/comp.2000.7431 · Cited by 33 · cited 1× · see citing works
“…study, patients underwent three 45-min sessions at weekly intervals on an interactive computer program that provided vicarious exposure and response prevention for OCD, but no significant change in Y-BOCS scores was reported, although a significant change in depressive symptoms was observed [73].”
Kobak, K., Greist, R., Jacobi, D., Levy-Mack, H., & Greist, J. (2015) · Annals of General Psychiatry · doi:10.1186/s12991-015-0048-0 · Cited by 32 · cited 1× · see citing works
“Few studies have specifically focused on computerized CBT for OCD, of which 6 [64-69] featured computer-driven telephone interview system (BT Steps).”
Mas, S., Gassó, P., Morer, Á., Calvo, A., Bargalló, N., Lafuente, A., & Lázaro, L. (2016) · PLoS ONE · doi:10.1371/journal.pone.0153846 · Cited by 31 · cited 1× · see citing works
“Their model classified child and adolescent patients with OCD by disease severity with an accuracy of 90% in the test set and 70% in the validation sample [36].”
Kalanthroff, E., Steinman, S. A., Schmidt, A. B., Campeas, R., & Simpson, H. B. (2018) · Psychotherapy and Psychosomatics · doi:10.1159/000481199 · Cited by 29 · cited 1× · see citing works
“Kalanthroff et al [75] developed a program called Personalized-Computerized Inhibitory Training (P-CIT) that sought to improve patients’ ability to inhibit responses when exposed to images that were related to their specific OCD symptoms.”
Treatment Outcome and Predictors of Internet Guided Self-Help for Obsessive-Compulsive Disorder
Diefenbach, G. J., Wootton, B. M., Bragdon, L. B., Moshier, S. J., & Tolin, D. F. (2015) · Behavior Therapy · doi:10.1016/j.beth.2015.06.001 · Cited by 28 · cited 1× · see citing works
“The results are summarized in Multimedia Appendix 1 [52-62].”
Barber, T. X. (1971) · Medical Entomology and Zoology · Cited by 27 · see citing works
Three decades of telemedicine in obsessive-compulsive disorder: A review across platforms
Aboujaoude, E. (2017) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2017.06.003 · Cited by 23 · cited 2× · see citing works
“It is easy to digitally transpose CBT using personalized modular programs in a smartphone app, on the internet, or in a VR program (for a review see Aboujaoude [37]).”
Lovell, K., & Bee, P. (2011) · Journal of Mental Health · doi:10.3109/09638237.2011.608745 · Cited by 22 · cited 1× · see citing works
“For a review see Lovell and Bee [71].”
A clinical case study of the use of ecological momentary assessment in obsessive compulsive disorder
Tilley, P. J. M., & Rees, C. S. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00339 · Cited by 20 · cited 1× · see citing works
“In a clinical case study of EMA use in 3 adults diagnosed with OCD, Tilley and Rees [21] compared the numbers and types of obsessions and compulsions captured using the Y-BOCS, compared with an SMS-based EMA.”
Deng, X., Wang, G., Zhou, L., Zhang, X., Yang, M., Han, G., Tu, Z., & Liu, B. (2014) · PubMed Central · doi:10.11919/j.issn.1002-0829.214067 · Cited by 18 · cited 1× · see citing works
“…treatment was considered effective in 86.5% of participants in the study group and in 62.9% of participants in the control group, with mean decreases in the Y-BOCS score of 14.44 (study group) and 13.2 (control group)—a statistically significant ( P =.003) but clinically irrelevant difference [82].”
InfluentialWorking Alliance in Internet-Based Cognitive-Behavioral Therapy for Obsessive-Compulsive Disorder
Herbst, N., Franzen, G., Voderholzer, U., Thiel, N., Knaevelsrud, C., Hertenstein, E., Nissen, C., & Külz, A. K. (2016) · Psychotherapy and Psychosomatics · doi:10.1159/000441282 · Cited by 18 · see citing works
Kim, K. K., Roh, D. D., Kim, S. I., & Kim, C. (2012) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2011.12.010 · Cited by 16 · cited 1× · see citing works
“Kim et al [76] used a virtual environment to produce variations in arrangement anxiety in 24 patients with compulsive arranging symptoms.”
Olbrich, H., Stengler, K., & Olbrich, S. (2016) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2016.01.001 · Cited by 16 · cited 1× · see citing works
“This app delivers an audio message (recorded alarm signal) if a compulsive behavior is suspected (ie, if the patient takes too long to cover a predefined distance) [48].”
Trambaiolli, L. R., Biazoli, C. E., Balardin, J. B., Hoexter, M. Q., & Sato, J. R. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.06.061 · Cited by 16 · cited 1× · see citing works
“Classification accuracy ranged from 52.56% (no feature selection) to 71.64% ( t test with feature selection) [32].”
InfluentialPresenting a Spatial-Geometric EEG Feature to Classify BMD and Schizophrenic Patients
Alimardani, F., Boostani, R., & Blankertz, B. (2016) · International Journal of Advances in Telecommunications Electrotechnics Signals and Systems · doi:10.11601/ijates.v5i2.143 · Cited by 11 · cited 1× · see citing works
“ML-based EEG classification is gaining interest for several psychiatric disorders, as it has very high classification accuracy among mood disorders, up to 98.95% classification accuracy for bipolar disorder versus schizophrenia [34], and 80.19% for unipolar versus bipolar depressive disorder [30].”
InfluentialLemon, C. A., Liu, N., Lane, S., Sud, A., Branley, J. M., Khadra, M. H., & Kim, J. (2017) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2017.0194 · Cited by 10 · see citing works
Use of EMG biofeedback in behavioral treatment of an obsessive-phobic-depressive syndrome.
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Morgiève, M., N’Diaye, K., Clair, A.-H., Pelissolo, A., & Mallet, L. (2016) · L Encéphale · doi:10.1016/j.encep.2016.03.004 · Cited by 3 · cited 1× · see citing works
“One study focused on a computerized psychoeducative tool as an add-on to standard CBT, reporting variable acceptance across patients and no difference in the Y-BOCS score reduction when compared with a group using standard CBT alone [74].”
Mouchabac, S., & Guinchard, C. (2013) · L information psychiatrique · doi:10.3917/inpsy.8910.0811 · Cited by 3 · see citing works
Self-citationMouchabac, S., & Guinchard, C. (2014) · L information psychiatrique · doi:10.1684/ipe.2013.1131 · Cited by 2 · see citing works
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- [10]Eichenberg C Wolters C IntechOpen 2012 2017-12-29 Virtual Realities in the Treatment of Mental Disorders: A Review of the Current State of Research. https://www.intechopen.com/books/virtual-reality-in-psychological-medical- and-pedagogical-applications/virtual-realities-in-the-treatment-of-mental-disorders-a-review-of-the-current-state-of-research
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Virtual reality in the diagnostic and therapy for mental disorders: A systematic review
Wiebe, A., Kannen, K., Selaskowski, B., Mehren, A., Thöne, A.-K., Pramme, L., Blumenthal, N., Li, M., Asché, L., Jonas, S., et al. (2022) · Clinical Psychology Review · doi:10.1016/j.cpr.2022.102213 · Cited by 223 · see citing works
Fineberg, N. A., Hollander, E., Pallanti, S., Walitza, S., Grünblatt, E., Dell’Osso, B. M., Albert, U., Geller, D. A., Brakoulias, V., Janardhan Reddy, Y. C., et al. (2020) · International Clinical Psychopharmacology · doi:10.1097/yic.0000000000000314 · Cited by 161 · see citing works
“Accordingly, using digital technology along with big data analyses may enable the potential to characterize the ‘digital phenotype’ of the disorder (Ferreri et al., 2019) and to identify those individuals most at risk (e.g., by monitoring online internet usage in comparison with changes in diurnal…”
BackgroundMethodThe impact of coronavirus (COVID-19) in the diagnosis and treatment of obsessive-compulsive disorder
Fontenelle, L. F., & Miguel, E. C. (2020) · Depression and Anxiety · doi:10.1002/da.23037 · Cited by 96 · see citing works
“(Fineberg et al., 2020) By the same token, we also feel that the pandemia provides increased room for testing the role of ERP delivered thought new technologies, such as virtual reality (Ferreri et al., 2019).”
BackgroundThe use of virtual reality in assessment and treatment of anxiety and related disorders
Meyerbröker, K., & Nexhmedin Morina, B. (2021) · Clinical Psychology & Psychotherapy · doi:10.1002/cpp.2623 · Cited by 60 · see citing works
Saad, A., Bruno, D., Camara, B., D’Agostino, J., & Bolea-Alamanac, B. M. (2021) · JMIR Mental Health · doi:10.2196/27404 · Cited by 33 · see citing works
Dehghan, B., Saeidimehr, S., Sayyah, M., & Rahim, F. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.733584 · Cited by 30 · see citing works
“Direct measurements of the main symptoms of OCD in the clinical office, especially using new technologies such as computer-based methods, may lead to more objective and comprehensive prevention and assessment of the disease (8).”
MethodMouchabac, S., Maatoug, R., Conejero, I., Adrien, V., Bonnot, O., Millet, B., Ferreri, F., & Bourla, A. (2021) · Brain Sciences · doi:10.3390/brainsci11111454 · Cited by 28 · see citing works
Self-citationA review of detection techniques for depression and bipolar disorder
Highland, D., & Zhou, G. (2022) · Smart Health · doi:10.1016/j.smhl.2022.100282 · Cited by 28 · see citing works
Hollmann, K., Allgaier, K., Hohnecker, C. S., Lautenbacher, H., Bizu, V., Nickola, M., Wewetzer, G., Wewetzer, C., Ivarsson, T., Skokauskas, N., et al. (2021) · Journal of Neural Transmission · doi:10.1007/s00702-021-02409-w · Cited by 24 · see citing works
“The number of studies on the internet-based treatment of pediatric OCD is still small, but there are already first indications that internet-based approaches are effective (Hollis et al. 2017; Ferreri et al. 2019): The study by Lenhard and colleagues (2017a, b) compared an internet-based CBT program with therapist sup…”
BackgroundFrank, A. C., Li, R., Peterson, B. S., & Narayanan, S. S. (2023) · JMIR Mental Health · doi:10.2196/45572 · Cited by 25 · see citing works
Olbrich, H., Jahn, I., Stengler, K., Seifritz, E., & Colla, M. (2022) · Clinical Neurophysiology · doi:10.1016/j.clinph.2022.02.029 · Cited by 23 · see citing works
“with biofeedback (Ferreri et al., 2019) on HRV parameters might not necessarily lead to more successful treatments.”
BackgroundAn Integrative Engagement Model of Digital Psychotherapy: Exploratory Focus Group Findings
Zech, J. M., Johnson, M., Pullmann, M. D., Hull, T. D., Althoff, T., Munson, S. A., Fridling, N., Litvin, B., Wu, J., & Areán, P. A. (2023) · JMIR Formative Research · doi:10.2196/41428 · Cited by 18 · see citing works
“Beyond their growing market share, DMH interventions have been found to be widely acceptable and clinically efficacious in treating a range of mental health issues, including anxiety disorders [4], depression [5], obsessive-compulsive disorder [6], substance dependence [7], and behavioral addictions [8].”
BackgroundEarly Identification and Intervention in Pediatric Obsessive-Compulsive Disorder
Liu, X., & Fan, Q. (2023) · Brain Sciences · doi:10.3390/brainsci13030399 · Cited by 16 · see citing works
Castle, D. J., Feusner, J. D., Laposa, J. M., Richter, P. M. A., Hossain, R., Lusicic, A., & Drummond, L. M. (2022) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2022.152357 · Cited by 15 · see citing works
Wahl, K., Scholl, P., Wirth, S., Miché, M., Häni, J., Schülin, P., & Lieb, R. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105280 · Cited by 15 · see citing works
Meta-Review of Wearable Devices for Healthcare in the Metaverse
Vahdati, M., Laamarti, F., & Saddik, A. E. (2024) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3705320 · Cited by 11 · see citing works
“…[11] CDSI [11, 91] Chronic disease management TCDM [34, 35, 58, 63, 74] Disease diagnosis and treatment MHDT [13, 14, 21, 30, 34, 41, 94] TRS [3, 4, 30, 44, 57, 59, 73, 78, 93] Rehabilitation SR [73] ATD [25, 59, 74, 78, 85] PNR [6, 7, ADL [84, 96] Long-term medical aids SDMA [38, 42] TMA [34,…”
InfluentialConducting a VR Clinical Trial in the Era of COVID-19
Stradford, J., Sakhare, A. R., Ravichandran, R., Schroeder, E. T., Michener, L. A., & Pa, J. (2021) · Frontiers in Virtual Reality · doi:10.3389/frvir.2021.639478 · Cited by 11 · see citing works
“, 2013), obsessive-compulsive disorder (Ferreri et al., 2019), panic disorder (Pompoli et al.”
BackgroundWahl, K., Scholl, P., Miché, M., Wirth, S., Burchard, R., & Lieb, R. (2023) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2023.100845 · Cited by 9 · see citing works
Fink‐Lamotte, J., Kursim, A., & Exner, C. (2023) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2023.100804 · Cited by 8 · see citing works
Kathiravan, S., & Chakrabarti, S. (2023) · World Journal of Psychiatry · doi:10.5498/wjp.v13.i2.60 · Cited by 8 · see citing works
Neural Decoding of Multi-Modal Imagery Behavior Focusing on Temporal Complexity
Furutani, N., Nariya, Y., Takahashi, T., Ito, H., Yoshimura, Y., Hiraishi, H., Hasegawa, C., Ikeda, T., & Kikuchi, M. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00746 · Cited by 7 · see citing works
Klein, C. S., Hollmann, K., Kühnhausen, J., Alt, A. K., Pascher, A., Seizer, L., Primbs, J., Ilg, W., Thierfelder, A., Severitt, B., et al. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1384540 · Cited by 6 · see citing works
Mukai, K., Yamanishi, K., Ogino, S., Hosoi, Y., Hayashida, K., & Matsunaga, H. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1593384 · Cited by 5 · see citing works
Wilhelm, S., Greenberg, J. L., Jacoby, R. J., Weingarden, H. M., Hoeppner, S. S., Klare, D. L., Snorrason, Í., Jaroszewski, A. C., McCoy, T. H., & Harrison, O. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-02230-9 · Cited by 5 · see citing works
“Digitally-based treatments (e.g., internet or smartphone) can address these barriers as they offer more fl exibility for patients, are scalable and cost-effective 11,12 , and offer standardized therapeutic content while signi fi cantly reducing clinician effort 13 .”
Olesen, K. V., Lønfeldt, N. N., Das, S., Pagsberg, A. K., & Clemmensen, L. K. H. (2023) · JMIR Research Protocols · doi:10.2196/48571 · Cited by 5 · see citing works
“Automatic, continuous detection of these OCD signals would facilitate close monitoring of patient treatment progress and allow for more targeted interventions and evaluation of treatment in the real world [14,15].”
Riesco, L. R., & Senín‐Calderón, C. (2021) · Ansiedad y Estrés · doi:10.5093/anyes2022a5 · Cited by 8 · see citing works
“…y tratamiento en salud mental, ninguna de ellas trata exclusivamente de aplicaciones móviles (incluyen otras TICs: realidad virtual, plataformas web, telepsicología, etc.) ni se centran en aplicaciones disponibles para población española (Ferreri et al, 2019; Kerst et al., 2020; Yim et al., 2020).”
BackgroundA VR Game for Obsessive-Compulsive Disorders Therapy
Torrão, A. R., Natário, J., Carvalho, P. S., Silva, C. M., & Silva, F. G. M. (2021) · International Conference on Graphics and Interaction (ICGI) · doi:10.1109/icgi54032.2021.9655282 · Cited by 4 · see citing works
Clinical Psychology in the Age of in the new technology : focusing on the recent studies trends
Song, H. (2019) · 한국심리학회지: 일반 · doi:10.22257/kjp.2019.12.38.4.549 · Cited by 3 · see citing works
Dietel, F. A., & Buhlmann, U. (2023) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2023.100847 · Cited by 2 · see citing works
Martínez‐Cengotitabengoa, M., Sánchez-Martínez, A., Long‐Martinez, D., Sánchez-Martínez, M., Peters‐Corbett, A., Pugh, E. J., Field, F. W. F., & Martínez‐Cengotitabengoa, M. (2022) · Journal of Investigative Psychology and Offender Profiling · doi:10.1002/jip.1589 · Cited by 2 · see citing works
“…its viability for treating patients but also for conducting online psychological evaluations, for example, in patients with suicidal risk (Exner-Cortens et al., 2021), neurodevelopmental disorders (Valentine et al., 2021) or obsessive-compulsive disorder among others (Ferreri et al., 2019).”
BackgroundSoltanmohammadlou, S., Farani, A. R., Shariat, S. V., & Habibi, M. (2022) · Iranian Journal of Psychiatry and Behavioral Sciences · doi:10.5812/ijpbs-118186 · Cited by 2 · see citing works
KI-basierte Interventionen in Psychiatrie und Psychotherapie
Friedrich, O., Schleidgen, S., & Seifert, J. (2023) · Techno:Phil · doi:10.1007/978-3-662-65868-0_11 · Cited by 2 · see citing works
Technological Interventions for Obsessive–Compulsive Disorder Management
Borgnis, F., & Pedroli, E. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-818697-8.00096-0 · Cited by 2 · see citing works
Hoogerwerf, E., Greeven, A., Goekoop, R., & Spinhoven, P. (2024) · Trials · doi:10.1186/s13063-023-07780-5 · Cited by 1 · see citing works
“These findings are confirmed in a meta-analysis which found that delivering OCS treatment via video-conferencing holds promise to be at least equally effective as face-to-face treatment but comparison studies with face-to-face control groups are necessary [14].”
ResultWang, R., Zhang, K., Wang, Y., Brown, K. R., & Zhao, Y. (2025) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3663547.3746394 · Cited by 2 · see citing works
Ethical challenges in EEG neurofeedback: a systematic review of gaps, risks, and responsibilities
Ölçüoğlu, R., & Yildirim, R. V. (2026) · BMC Medical Ethics · doi:10.1186/s12910-026-01408-4 · Cited by 1 · see citing works
“Concurrently, Ferreri et al. [12, 22] sounded a note of caution regarding digital divides and the exclusion of low-income groups from emerging interventions.”
InfluentialShankhwar, N., Ünal, A., & Singh, S. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-26466-5.00012-x · Cited by 1 · see citing works
A Virtual Reality Game as a Tool for Psychotherapy With OCD Patients
Torrão, A. R., Natário, J., Carvalho, P. S., Silva, C. M., & Silva, F. G. M. (2022) · International Journal of Creative Interfaces and Computer Graphics · doi:10.4018/ijcicg.311834 · Cited by 1 · see citing works
Devices, Mobile Health and Digital Phenotyping
Volpe, U., Elkholy, H. A., Gargot, T., da Costa, M. P., & Orsolini, L. (2023) · Springer eBooks · doi:10.1007/978-3-030-42825-9_151-1 · Cited by 1 · see citing works
Imai, H., Luo, Y., Funada, S., Hashimoto, T., Matsuishi, K., Takamatsu, T., Yoshihara, Y., Hiraoka, Y., Mizui, Y., Hayasaka, Y., et al. (2025) · Psychiatry and Clinical Neurosciences Reports · doi:10.1002/pcn5.70065 · Cited by 1 · see citing works
“12,13 In fact, a systematic review has shown that self ‐ help programs without therapist involvement for OCD are effective.”
Puglia, G. V., Villela, B. A. D. S., Cury, C. R., Domingues, J. C. M., Taco, L. G., & Caneschi, M. D. (2021) · Brazilian Journal of Health Review · doi:10.34119/bjhrv4n6-163 · Cited by 1 · see citing works
Remote monitoring of depression severity: A machine learning approachPreprint
Holstein, V., Rahimi-Eichi, H., Emden, D., Gutfleisch, L., Refisch, A., Goltermann, J., Leenings, R., Winter, N. R., Kircher, T. T. J., Nenadić, I., et al. (2023) · medRxiv · doi:10.1101/2023.08.22.23294431 · Cited by 1 · see citing works
Can we talk about a COVID-19 related “New Normal” for Obsessive Compulsive Disorder?
Gözpınar, N., & Görmez, V. (2020) · Journal of Cognitive-Behavioral Psychotherapy and Research · doi:10.5455/jcbpr.9988
Mohammadlou, S. S., Farani, A. R., Shariat, V., & Habibi, M. (2022) · Smart Health · doi:10.1016/j.smhl.2022.100280
Durna, G., & Yorulmaz, O. (2023) · Klinik Psikoloji Dergisi · doi:10.57127/kpd.26024438m0000106
Online Exposure and Response Prevention for Obsessive-Compulsive Disorder: A Case Report
Mishra, E., & Grover, S. (2023) · Journal of SAARC Psychiatric Federation · doi:10.4103/jspf.jspf_2_24
Voderholzer, U., Rubart, A., Kathmann, N., Staniloiu, A., Kordon, A., & Zurowski, B. (2024) · Springer eBooks · doi:10.1007/978-3-662-67878-7_2
Devices, Mobile Health, and Digital Phenotyping
Volpe, U., Elkholy, H. A., Gargot, T., da Costa, M. P., & Orsolini, L. (2024) · Springer eBooks · doi:10.1007/978-3-030-51366-5_151
Satılmaz, M. F., Aslan, M. G., & Beşenek, M. (2024) · Clinical Pediatrics · doi:10.1177/00099228241304469
Özer, Ö., Öztemür, G., Altınöz, A. E., Köksal, B., Doğan, U., Batmaz, S., Gür, R., & Altınok, A. (2025) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2025.101443
“Recent experimental studies have shown that internet-based interventions are useful for a variety of problems, including depressive mood [21,22], stress management [23], social anxiety [24,25], obsessive-compulsive disorder [26,27], substance and alcohol use [28,29], and suicide prevention [30].”
Sheikh, M. A. (2025) · Mindfulness · doi:10.1007/s12671-025-02688-4
“These innovations hold promise for refining alignment with symptom profiles, treat-ment responses, and mechanistic targets (Chien et al., 2022; Ferreri et al., 2019).”
Chakrabarti, S., Kathiravan, S., & Sarah, N. (2026) · World Journal of Psychiatry · doi:10.5498/wjp.v16.i2.111577
Cognitive Behavioral Therapy With Exposure and Response Prevention for Obsessive-Compulsive Disorder
Ward, H. E., Moran-Meder, E., & McKay, D. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-29009-1.00140-2
- Authors
- Ferreri, F., Bourla, A., Peretti, C.-S., Segawa, T., Jaafari, N., & Mouchabac, S.
- Affiliations
- Sorbonne Université (FR)
- Corresponding author
- Bourla, Alexis
- ORCID
- Venue
- JMIR Mental Health
- Publisher
- JMIR Publications Inc.
- Published
- 2019-12-10
- Volume
- 6
- Issue
- 12
- Pages
- e11643
- ISSN
- 2368-7959 (ISSN-L)
- PMC
- PMC6930507
- OpenAlex
- W2921079094
- Cited by
- 53
- References
- 90
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 6 · 2023: 13 · 2022: 10 · 2021: 9 · 2020: 4 · 2019: 1
- FWCI
- 0.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Mental Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Obsessive-Compulsive Spectrum Disorders
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- obsessive-compulsive disorder, digital phenotyping, mobile application, ecological momentary assessment, remote monitoring, wearable devices, machine learning, cognitive behavioral therapy, biofeedback, virtual reality, actigraphy, heart rate variability, telemedicine, clinical practice change
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