Validity, Reliability, and Bias

Articles published in 2021 in this theme: 9 (scroll down to load remaining articles)

2021

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Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison

Hsiao-Han Wang, Yu-Hsuan Lin

J Med Internet Res 2021 (Dec 24); 23(12):e26763

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A Personalized Approach Bias Modification Smartphone App (“SWiPE”) to Reduce Alcohol Use: Open-Label Feasibility, Acceptability, and Preliminary Effectiveness Study

Victoria Manning, Hugh Piercy, Joshua Benjamin Bernard Garfield, Stuart Gregory Clark, Mah Noor Andrabi, Dan Ian Lubman

JMIR Mhealth Uhealth 2021 (Dec 10); 9(12):e31353

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Differential Biases and Variabilities of Deep Learning–Based Artificial Intelligence and Human Experts in Clinical Diagnosis: Retrospective Cohort and Survey Study

Dongchul Cha, Chongwon Pae, Se A Lee, Gina Na, Young Kyun Hur, Ho Young Lee, A Ra Cho, Young Joon Cho, Sang Gil Han, Sung Huhn Kim, Jae Young Choi, Hae-Jeong Park

JMIR Med Inform 2021 (Dec 08); 9(12):e33049

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Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias

Christina M Hopkins, Hailey N Miller, Taylor L Brooks, Lihua Mo-Hunter, Dori M Steinberg, Gary G Bennett

JMIR Res Protoc 2021 (Nov 25); 10(11):e31307

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An Online Assessment to Evaluate the Role of Cognitive Biases and Emotion Regulation Strategies for Mental Health During the COVID-19 Lockdown of 2020: Structural Equation Modeling Study

Ivan Blanco, Teresa Boemo, Alvaro Sanchez-Lopez

JMIR Ment Health 2021 (Nov 02); 8(11):e30961

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A Web-Based Cognitive Bias Modification Intervention (Re-train Your Brain) for Emerging Adults With Co-occurring Social Anxiety and Hazardous Alcohol Use: Protocol for a Multiarm Randomized Controlled Pilot Trial

Katrina Prior, Elske Salemink, Reinout W Wiers, Bethany A Teachman, Monique Piggott, Nicola C Newton, Maree Teesson, Andrew J Baillie, Victoria Manning, Lauren F McLellan, Alison Mahoney, Lexine A Stapinski

JMIR Res Protoc 2021 (Jul 07); 10(7):e28667

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Authors’ Reply to: Minimizing Selection and Classification Biases Comment on “Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing”

Jose Luis Izquierdo, Joan B Soriano

J Med Internet Res 2021 (May 26); 23(5):e29405

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Minimizing Selection and Classification Biases. Comment on “Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing”

Francisco Martos Pérez, Ricardo Gomez Huelgas, María Dolores Martín Escalante, José Manuel Casas Rojo

J Med Internet Res 2021 (May 26); 23(5):e27142

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Cognitive Bias Modification Training to Improve Implicit Vitality in Patients With Breast Cancer: App Design Using a Cocreation Approach

Roos Wolbers, Christina Bode, Ester Siemerink, Sabine Siesling, Marcel Pieterse

JMIR Form Res 2021 (Mar 10); 5(3):e18325

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