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In response, interest has grown in technology\u2010based interventions, including therapy software, virtual reality (VR) and artificial intelligence (AI) tools. However, current evidence for the effectiveness of technology is fragmented, and no recent review offers a comprehensive synthesis across these three modalities.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>This review examined the range of technologies used in aphasia assessment and therapy and summarised their effectiveness across different intervention targets. The two research questions were: (1) What types of technology have been investigated for assessing and treating people with aphasia (PWA)? (2) How effective is the use of technology in the assessment and treatment of PWA?<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A systematic search of four databases (PubMed, PsycINFO, Web of Science and Scopus) covering the period 2013 to May 2026 identified 67 included studies, of which 14 were randomised controlled trials. Studies reporting quantitative outcomes, were peer\u2010reviewed, and focused on technology\u2010based intervention for PWA were eligible. Quality was appraised using the NICE checklist. The GRADE framework was applied to evaluate certainty of evidence for each intervention target. Findings were then synthesised narratively due to heterogeneity across study designs, and outcome measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Three technology types were identified: computerised speech and language therapy (CSLT) (38 studies), VR (17 studies) and AI (13 studies). AI was used predominantly for aphasia assessment and classification. The strongest and most consistent evidence related to word\u2010finding, where high certainty of evidence was supported by multiple RCTs delivering therapy at or above the recommended 20\u2010h threshold. For language production and comprehension, functional communication, and reading, outcomes were more variable, reflecting moderate certainty of evidence, and inconsistent dose adherence. Writing interventions received a low certainty rating, reflecting small samples, limited blinding and task\u2010specific rather than generalised gains. Across domains, higher\u2010dose studies were consistently associated with better outcomes, which may suggest that technology functions primarily as a tool to enable high\u2010intensity practice rather than as an independently effective treatment ingredient.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>CSLT, VR and AI tools show promise as adjuncts to face\u2010to\u2010face SLT for aphasia assessment and rehabilitation. Word\u2010finding interventions delivered at recommended doses have the strongest evidence base. Some studies did not use technology to support the recommended therapy dose. For other intervention targets, larger, higher\u2010dose trials are needed. Future research should also examine whether integrating different technology types could offer additional clinical benefit.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>WHAT THIS PAPER ADDS<\/jats:title>\n                    <jats:p>\n                      <jats:italic>What is already known about the subject<\/jats:italic>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Previous systematic reviews have demonstrated the emerging role of technology in aphasia rehabilitation, with earlier work focusing primarily on computer\u2010based therapy or AI technologies. However, these reviews were either narrow in scope (targeted specific technology type), or outdated.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                      <jats:italic>What this study adds to the existing knowledge<\/jats:italic>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>This review provides an updated, cross-technology synthesis encompassing AI, virtual reality, and computerised speech\u2010and\u2010language therapy. It outlines how these tools were applied within the studies in the literature. The review also identifies persistent limitations in therapy dosage across studies, underscoring the need for future higher\u2010dose trials to confirm the certainty of evidence across different intervention targets.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                      <jats:italic>What are the clinical implications of this study?<\/jats:italic>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>The growing evidence for computerised speech and language therapy, virtual reality, and artificial intelligence tools continues to support their role as adjuncts to face to face SLT, particularly for language assessment and targeted word\u2010finding interventions. These technologies may extend therapy provision beyond clinical hours, enable therapeutic doses of practice to be achieved, and improve consistency in assessment procedures.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/1460-6984.70322","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T08:05:06Z","timestamp":1788854706000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the Effectiveness of Technology\u2010Based Interventions in Aphasia Rehabilitation: A Systematic Review"],"prefix":"10.1111","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7219-1694","authenticated-orcid":false,"given":"Bader","family":"Alhejji","sequence":"first","affiliation":[{"name":"College of Health Rehabilitation Sciences Speech and Hearing Disorders King Abdulaziz University  Jeddah Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9418-8726","authenticated-orcid":false,"given":"Stuart","family":"Cunningham","sequence":"additional","affiliation":[{"name":"School of Allied Health Professions Nursing and Midwifery University of Sheffield  Sheffield UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8952-335X","authenticated-orcid":false,"given":"Samantha","family":"Dorney","sequence":"additional","affiliation":[{"name":"Department of Neuroscience University of Sheffield  Sheffield UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2335-7104","authenticated-orcid":false,"given":"Rebecca","family":"Palmer","sequence":"additional","affiliation":[{"name":"School of Medicine and Population Health University of Sheffield  Sheffield UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"key":"e_1_2_17_2_1","doi-asserted-by":"crossref","unstructured":"Abad A. 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