A survey on AI and decision support systems in psychiatry – Uncovering a dilemma

Bertl, Markus; Ross, Peeter; Draheim, Dirk

doi:10.1016/j.eswa.2022.117464

Cited by 20 publications

(2 citation statements)

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“…AI leverages logic and can make predictions based on experience or inputs, and therefore, it can serve as an important tool for clinicians, helping to make sense of treatment data, support clinical decisions, and reduce administrative burden [ 15 ]. However, to date, there has not been a widespread implementation of AI-powered digital decision support systems and tools for operational efficiency in mental health care [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial

Sadeh‐Sharvit¹,

Camp²,

Horton³

et al. 2023

J Med Internet Res

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Background The need for scalable delivery of mental health care services that are efficient and effective is now a major public health priority. Artificial intelligence (AI) tools have the potential to improve behavioral health care services by helping clinicians collect objective data on patients’ progress, streamline their workflow, and automate administrative tasks. Objective The aim of this study was to determine the feasibility, acceptability, and preliminary efficacy of an AI platform for behavioral health in facilitating better clinical outcomes for patients receiving outpatient therapy. Methods The study was conducted at a community-based clinic in the United States. Participants were 47 adults referred for outpatient, individual cognitive behavioral therapy for a main diagnosis of a depressive or anxiety disorder. The platform provided by Eleos Health was compared to treatment-as-usual (TAU) approach during the first 2 months of therapy. This AI platform summarizes and transcribes the therapy session, provides feedback to therapists on the use of evidence-based practices, and integrates these data with routine standardized questionnaires completed by patients. The information is also used to draft the session’s progress note. Patients were randomized to receive either therapy provided with the support of an AI platform developed by Eleos Health or TAU at the same clinic. Data analysis was carried out based on intention-to-treat approach from December 2022 to January 2023. The primary outcomes included the feasibility and acceptability of the AI platform. Secondary outcomes included changes in depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) scores as well as treatment attendance, satisfaction, and perceived helpfulness. Results A total of 72 patients were approached, of whom 47 (67%) agreed to participate. Participants were adults (34/47, 72% women and 13/47, 28% men; mean age 30.64, SD 11.02 years), 23 randomized to the AI platform group, and 24 to TAU. Participants in the AI group attended, on average, 67% (mean 5.24, SD 2.31) more sessions compared to those in TAU (mean 3.14, SD 1.99). Depression and anxiety symptoms were reduced by 34% and 29% in the AI platform group versus 20% and 8% for TAU, respectively, with large effect sizes for the therapy delivered with the support of the AI platform. No group difference was found in 2-month treatment satisfaction and perceived helpfulness. Further, therapists using the AI platform submitted their progress notes, on average, 55 hours earlier than therapists in the TAU group (t=–0.73; P<.001). Conclusions In this randomized controlled trial, therapy provided with the support of Eleos Health demonstrated superior depression and anxiety outcomes as well as patient retention, compared with TAU. These findings suggest that complementing the mental health services provided in community-based clinics with an AI platform specializing in behavioral treatment was more effective in reducing key symptoms than standard therapy. Trial Registration ClinicalTrials.gov NCT05745103; https://classic.clinicaltrials.gov/ct2/show/NCT05745103

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Section: Introductionmentioning

confidence: 99%

Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial

Sadeh‐Sharvit¹,

Camp²,

Horton³

et al. 2023

J Med Internet Res

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“…Meskipun begitu, menurut penelitian tentang survei pada penggunaan artificial intelligence (AI) dan DSS dalam psikiatri menunjukkan bahwa banyak data tentang pasien tetapi tidak digunakan secara optimal untuk pencegahan penyakit, diagnosis, maupun proses pengobatan dan penggunaan data medis manual hampir tidak mungkin karena peningkatan data yang besar (Bertl et al, 2022).…”

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DEDIAVER Sebagai Aplikasi Alternatif Tes Denver II untuk Tes Deteksi Dini Perkembangan Anak

Kurniawati

Prabowo

2022

J. Kaji. Ilm.

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Salah satu fokus riset dan inovasi di Indonesia adalah mendorong pembangunan ketahanan dan kemandirian Kesehatan dan salah satu yang menjadi perhatian adalah perkembangan anak. Menurut Ikatan Dokter Anak Indonesia (IDAI) ada sekitar 5-10% anak diperkirakan mengalami keterlambatan perkembangan dan sekitar 1-3% di bawah usia 5 tahun mengalami keterlambatan perkembangan umum. Deteksi Dini Perkembangan Anak Berdasarkan Tes Denver II (DEDIAVER) merupakan sebuah aplikasi decision support system (DSS) yang dapat digunakan untuk deteksi dini perkembangan anak menggunakan instrumen Tes Denver II. Tujuan dari penelitian ini adalah melakukan pengujian lanjutan atau evaluasi aplikasi DEDIAVER. Hal ini dilakukan sebagai salah satu upaya untuk menilai kelayakan aplikasi DEDIAVER sebagai aplikasi alternatif Tes Denver II untuk tes deteksi dini perkembangan anak. Pengujian dilakukan dengan mencocokkan hasil Tes Denver II yang dilakukan secara manual dengan hasil dari aplikasi DEDIAVER. Hasilnya, untuk tes anak usia 0-2 tahun mendapatkan total akurasi untuk setiap sektor perkembangan dan usia sebesar 90,67% sedangkan untuk tes anak usia lebih dari 2-6 tahun mendapatkan total akurasi sebesar 36%. Akurasi dari tes untuk usia lebih dari 2-6 tahun hanya 36% diakibatkan karena perbedaan perhitungan usia dari aplikasi yang mencapai 4-6 bulan lebih tua dari usia sebenarnya yang mengakibatkan pertanyaan yang muncul di atas usia anak sehingga anak gagal melakukan tugas pada usianya.

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How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare

Bertl,

Klementi,

Piho

et al. 2023

Lecture Notes in Computer Science

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A survey on AI and decision support systems in psychiatry – Uncovering a dilemma

Cited by 20 publications

References 110 publications

Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial

Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial

DEDIAVER Sebagai Aplikasi Alternatif Tes Denver II untuk Tes Deteksi Dini Perkembangan Anak

How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare

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