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akaturk Akademik ölçüm

Makale detayı · 2020 · article

A Combined Digital and Biomarker Diagnostic Aid for Mood Disorders (the Delta Trial): Protocol for an Observational Study.

ISSN1929-0748
YÖKSİS OpenAlex Açık erişim · gold
Yıl2020
Atıf20OpenAlex
Atıf17Semantic Scholar · 1 etkili
Yüzdelik%89,4
FWCI2,351,00 = dünya ortalaması
Scopus (SJR)Q3

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıJMIR research protocols
  • Katalog eşleşmesi (ISSN)JMIR Research Protocols
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

BACKGROUND: Mood disorders affect hundreds of millions of people worldwide, imposing a substantial medical and economic burden. Existing diagnostic methods for mood disorders often result in a delay until accurate diagnosis, exacerbating the challenges of these disorders. Advances in digital tools for psychiatry and understanding the biological basis of mood disorders offer the potential for novel diagnostic methods that facilitate early and accurate diagnosis of patients. OBJECTIVE: The Delta Trial was launched to develop an algorithm-based diagnostic aid combining symptom data and proteomic biomarkers to reduce the misdiagnosis of bipolar disorder (BD) as a major depressive disorder (MDD) and achieve more accurate and earlier MDD diagnosis. METHODS: Participants for this ethically approved trial were recruited through the internet, mainly through Facebook advertising. Participants were then screened for eligibility, consented to participate, and completed an adaptive digital questionnaire that was designed and created for the trial on a purpose-built digital platform. A subset of these participants was selected to provide dried blood spot (DBS) samples and undertake a World Health Organization World Mental Health Composite International Diagnostic Interview (CIDI). Inclusion and exclusion criteria were chosen to maximize the safety of a trial population that was both relevant to the trial objectives and generalizable. To provide statistical power and validation sets for the primary and secondary objectives, 840 participants were required to complete the digital questionnaire, submit DBS samples, and undertake a CIDI. RESULTS: The Delta Trial is now complete. More than 3200 participants completed the digital questionnaire, 924 of whom also submitted DBS samples and a CIDI, whereas a total of 1780 participants completed a 6-month follow-up questionnaire and 1542 completed a 12-month follow-up questionnaire. The analysis of the trial data is now underway. CONCLUSIONS: If a diagnostic aid is able to improve the diagnosis of BD and MDD, it may enable earlier treatment for patients with mood disorders. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18453.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

20atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yerel katalogda bu makaleye atıf yapan 3 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).

  1. 2021 A machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker dataAtıf 72 · OpenAlex
  2. 2020 Diagnostic prediction model development using data from dried blood spot proteomics and a digital mental health assessment to identify major depressive disorder among individuals presenting with low moodAtıf 18 · OpenAlex
  3. 2020 Diagnostic prediction model development using data from dried blood spot proteomics and a digital mental health assessment to identify major depressive disorder among individuals presenting with low moodAtıf 17 · OpenAlex

Yazarlar

14
  1. Tony Olmert 1
  2. Jason D Cooper 2
  3. Sung Yeon Sarah Han 3
  4. Giles Barton-Owen 4
  5. Lynn P. Farrag 5
  6. Emily Bell 6
  7. Lauren V. Friend 7
  8. SÜREYYA ÖZCAN KABASAKAL ORTA DOĞU TEKNİK ÜNİVERSİTESİ 8
  9. Nitin Rustogi 9
  10. Rhian L. Preece 10
  11. Pawel Eljasz 11
  12. Jakub Tomasik 12
  13. Dan Cowell 13
  14. Sabine Bahn 14