{"doi":"10.2196/preprints.99718","title":"Cognitive Behavioral Therapy–Based Digital Interventions for Illicit Substance Use Disorders: A Scoping Review of Intervention Design, Efficacy Indicators, and Methodological Gaps (Preprint)","abstract":"<sec>\n                  <title>BACKGROUND</title>\n                  <p>Illicit substance use poses severe global burdens. Digital interventions utilizing cognitive behavioral therapy offer accessible treatment alternatives, but evidence regarding their design and effectiveness remains fragmented.</p>\n                </sec>\n                <sec>\n                  <title>OBJECTIVE</title>\n                  <p>This review synthesized current evidence on cognitive behavioral therapy based digital interventions for illicit substance use disorders, focusing on theoretical frameworks, efficacy indicators, and methodological limitations.</p>\n                </sec>\n                <sec>\n                  <title>METHODS</title>\n                  <p>Following the PRISMA-ScR guidelines, we searched PubMed, Embase, Web of Science, and PsycINFO for studies published up to February 16, 2026. Eligible studies were empirical trials of digital interventions using cognitive behavioral therapy for illicit substance use disorders. Studies focusing solely on alcohol or nicotine were excluded.</p>\n                </sec>\n                <sec>\n                  <title>RESULTS</title>\n                  <p>A total of 30 studies were included. Interventions targeted polysubstance, cannabis, stimulant, and sedative use. Programs were mainly web- or app-based, often combined with motivational interviewing, contingency management, or mindfulness approaches. Core components were therapeutic modules, self-tracking, rewards, and feedback. While primary outcomes often demonstrated substance use reduction, interpretation was hindered by prevalent reliance on self-reported data, inconsistent baseline controls, and the use of bundled multicomponent packages.</p>\n                </sec>\n                <sec>\n                  <title>CONCLUSIONS</title>\n                  <p>Digital interventions based on cognitive behavioral therapy show potential to reduce illicit substance use and support psychosocial recovery. To advance clinical utility, future research must implement substance-specific designs, integrate objective outcome measures, and adopt modular trial designs to isolate active therapeutic mechanisms.</p>\n                </sec>","journal":null,"year":null,"id":645231,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1679957,"name":"Su-Ji Jung","orcid":null,"position":1,"is_corresponding":false},{"id":1679958,"name":"Mi-Ju Kang","orcid":null,"position":2,"is_corresponding":false},{"id":1679959,"name":"Young-Hoon Chon","orcid":null,"position":3,"is_corresponding":false},{"id":1679960,"name":"Na-Rae Lee","orcid":null,"position":4,"is_corresponding":false},{"id":1679961,"name":"Kyuil Hwang","orcid":null,"position":5,"is_corresponding":false},{"id":1171521,"name":"In Young Choi","orcid":"0000-0002-2860-9411","position":6,"is_corresponding":false},{"id":1564753,"name":"Dai-Jin Kim","orcid":"0000-0001-9408-5639","position":7,"is_corresponding":false},{"id":1564754,"name":"Ji-Won Chun","orcid":"0000-0002-0629-0358","position":8,"is_corresponding":false},{"id":1679956,"name":"Sung-Min Kim","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Cognitive Behavioral Therapy–Based Digital Interventions for Illicit Substance Use Disorders: A Scoping Review of Intervention Design, Efficacy Indicators, and Methodological Gaps (Preprint)","abstract":"<sec>\n                  <title>BACKGROUND</title>\n                  <p>Illicit substance use poses severe global burdens. Digital interventions utilizing cognitive behavioral therapy offer accessible treatment alternatives, but evidence regarding their design and effectiveness remains fragmented.</p>\n                </sec>\n                <sec>\n                  <title>OBJECTIVE</title>\n                  <p>This review synthesized current evidence on cognitive behavioral therapy based digital interventions for illicit substance use disorders, focusing on theoretical frameworks, efficacy indicators, and methodological limitations.</p>\n                </sec>\n                <sec>\n                  <title>METHODS</title>\n                  <p>Following the PRISMA-ScR guidelines, we searched PubMed, Embase, Web of Science, and PsycINFO for studies published up to February 16, 2026. Eligible studies were empirical trials of digital interventions using cognitive behavioral therapy for illicit substance use disorders. Studies focusing solely on alcohol or nicotine were excluded.</p>\n                </sec>\n                <sec>\n                  <title>RESULTS</title>\n                  <p>A total of 30 studies were included. Interventions targeted polysubstance, cannabis, stimulant, and sedative use. Programs were mainly web- or app-based, often combined with motivational interviewing, contingency management, or mindfulness approaches. Core components were therapeutic modules, self-tracking, rewards, and feedback. While primary outcomes often demonstrated substance use reduction, interpretation was hindered by prevalent reliance on self-reported data, inconsistent baseline controls, and the use of bundled multicomponent packages.</p>\n                </sec>\n                <sec>\n                  <title>CONCLUSIONS</title>\n                  <p>Digital interventions based on cognitive behavioral therapy show potential to reduce illicit substance use and support psychosocial recovery. To advance clinical utility, future research must implement substance-specific designs, integrate objective outcome measures, and adopt modular trial designs to isolate active therapeutic mechanisms.</p>\n                </sec>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W7159807361","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://doi.org/10.2196/preprints.99718","host_type":""}],"fields_of_study":["Digital Mental Health Interventions","Substance Abuse Treatment and Outcomes","Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes"],"mesh_terms":[],"keywords":["Psychological intervention","Cognitive behavioral therapy","PsycINFO","Cognitive therapy","Mindfulness","Contingency management","Motivational interviewing","Psychosocial","Cognition","Intervention (counseling)"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-09T03:50:20.248046Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}