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Name: Yin Wu

Email: yin.wu@mail.mcgill.ca

Position: Research Associate 

Biography:

Dr. Wu is currently a Research Associate with Dr. Thombs’ team where she also contributes to the DEPRESSD Project as a steering committee member in September 2022. She is an instructor in the Department of Epidemiology at McGill University as well. She completed her Ph.D. in education psychology and quantitative methods at University at Buffalo in 2017, during which she got her advanced certificate in applied statistical analysis of New York state. Her research dual focuses on both application of quantitative data analysis methodology and psychometrics in improving psychological health and well-being. She is involved in the DEPRESSD project of individual patient data meta-analyses on the diagnostic accuracy of depression screening tools, living systematic review of mental health in COVID-19, and survey design and scale development for mental health outcomes and psychometrics for the SPIN cohort.

Awards & Honors: 

- McGill MedStar Award for Trainees, McGill University ($500). 2021

- Lady Davis Institute for Medical Research, Paper of the Month. July 2021, Lady Davis Institute for Medical Research. 2021

- The Fonds de Recherche Québec - Santé (FRQS, Quebec Health Research Fund) Postdoctoral Training Fellowship, FRQS ($45,000/year). 2019-2021

- Utting Postdoctoral Fellowship for Studies in Depression, Department of Psychiatry, McGill University (Declined – Accepted only $5,000 training supplement). 2019

- Utting Postdoctoral Fellowship for Studies in Depression, Department of Psychiatry, McGill University ($50,000). 2018

- The Peter Drapiewski Scholarship, Graduation School of Education, University at Buffalo ($2,500). 2016                                                     - American Educational Research Association (AERA) Grants Program – Institute on Statistical Analysis: Causal Analysis Using International Data. (Funded by National Science Foundation) ($3,500). 2015

- The Paul A. and Margaret E. Bacon Scholarship, Graduation School of Education, University at Buffalo ($400). 2015

- Outstanding Graduate Student Award, South China Normal University ($300). 2011

 

Grants:

- Canadian Institutes of Health Research (CIHR) Project Grant: The DEPRESsion Screening Data (DEPRESSD) Project: A Novel International Individual Participant Data Meta-analysis Collaboration to Advance Research on Depression Screening Tool Accuracy, Develop Statistical Methodology, and Conduct Meta-Research. (PIs: Thombs B. D., Benedetti A.; Co-investigators: Wu Y, et al., $1,365,526). 2022-2027

 

- Canada Research Coordinating Committee, Social Sciences and Humanities Research Council - New Frontiers in Research Fund: Comparison of Depression Research Diagnoses and Symptom Scores Obtained via Conventional In-person and Alternative Methodologies. (PIs: Benedetti A, Thombs B. D.; Co-investigators: Wu Y, et al., $237,861). 2022-2023                                                                         

- CIHR Operating Grant: Loneliness Among Older Adults in COVID-19: A Living Systematic Review of Changes in Loneliness from Pre-COVID-19, Association with Mental Health Outcomes, and Effects of Interventions. (PIs: Benedetti A, Thombs B. D.; Co-investigators: Wu Y, et al., $184,499). 2022-2024

 

- CIHR Project Grant: Statistical Methodology for Prediction Modelling to Improve Depression Screening with Individualized Risk Estimates in the Context of Individual Participant Data Meta-analysis. (PIs: Benedetti A, Thombs B. D.; Co-investigators: Wu Y, et al., $279,224).   2021-2024

 

- CIHR Operating Grant: Mental Health during the COVID-19 Pandemic: An Ongoing Living Systematic Review of Mental Health Burden and Intervention Effectiveness to Inform Management Strategies During and Post-COVID-19. (PIs: Benedetti A, Thombs BD; Co-investigators: Wu Y, et al., $220,052). 2021-2022

 

- CIHR Project Grant: The DEPRESsion Screening Data (DEPRESSD) Project: Continuous Updating of Databases for Individual Participant Data Meta-analyses of Depression Screening Test Accuracy. (PIs: Thombs BD, Benedetti A; Co-investigators: Wu Y, et al., $100,000). 2021

 

- CIHR Project Grant: Statistical Methodology for Prediction Modelling to Improve Depression Screening with Individualized Risk Estimates in the Context of Individual Participant Data Meta-analysis. (PIs: Benedetti A, Thombs BD; Co-investigators: Wu Y, et al., $100,000).     2021

 

- CIHR Operating Grant: Identifying Effective Mental Health Interventions and Populations in Need: A COVID-19 Living Systematic Review. (PIs: Thombs BD, Benedetti A; Co-investigators: Wu Y, et al., $ 199,836). 2020-2021

 

- CIHR Operating Grant: Identification of Factors to Improve Effectiveness and Implementation of a Multi-faceted COVID-19 Mental Health Intervention: Follow-up to the SPIN-CHAT Trial. (PIs: Thombs BD, Benedetti A; Co-investigators: Wu Y, et al., $ 89,801). 2020-2021

 

- CIHR Operating Grant: Partially Nested Randomized Controlled Trial to Evaluate the Effectiveness of the Scleroderma Patient-centered Intervention Network COVID-19 Home- isolation Activities Together (SPIN-CHAT) Program to Reduce Anxiety among Vulnerable Persons with a Pre-existing Medical Condition. (PIs: Thombs BD, Kwakkenbos L, Benedetti A; Co-investigators: Wu Y, et al., $156,353). 2020-2021

 

- CIHR Operating Grant: Mental Health during the COVID-19 Pandemic: A Living Systematic Review of Mental Health Burden, Factors Associated with Mental Health Outcomes, and Intervention Effectiveness in the General Population and Vulnerable Populations. (PIs: Thombs BD, Benedetti A; Co-investigators: Wu Y, et al., $50,000). 2020-2021

 

- CIHR Project Scheme Grant: Diagnostic Accuracy of the Patient Health Questionnaire-9 for Detecting Major Depression: An Updated Systematic Review and Independent Participant Data Meta-analysis. (PIs: Benedetti A, Thombs BD; Co-investigators: Wu Y, et al., $217,500). 2019-2021

                                                                                                           

Courses Taught:

- Adjunct Lecturer for Course: EPI613—Introduction to Statistical Software (2018 Fall, 2019 Fall & 2020 Fall (online)), Department of Epidemiology, Biostatistics and Occupational Health, McGill University, September 2018 - Present.

                          

- Adjunct Instructor for Course: CEP400—Educational Psychology (2015 Spring, 2015 Fall, 2016 Spring & 2016 Fall: online), Department of Counseling, School and Educational Psychology, Graduate School of Education, University at Buffalo, January 2015 - May 2017.

 

Publications (Selected):

Dal Santo T, Sun Y, Wu Y, He C, Wang Y, Jiang X, Li K, Bonardi O, Krishnan A, Boruff JT, Rice DB. Systematic review of mental health symptom changes by sex or gender in early-COVID-19 compared to pre-pandemic. Sci Rep. 2022;12:11417.

 

Gordon JK, Showalter K, Wu Y, Kwakkenbos L, Carrier ME, Henry RS, Østbø N, Nordlund J, Bourgeault A, Cañedo-Ayala M, Carboni-Jiménez A. Systemic sclerosis and COVID-19 vaccines: a SPIN Cohort study. Lancet Rheumatol. 2022;4(4):e243-6.

 

Moore A, Wu Y, Kwakkenbos L, Silveira K, Straus S, Brouwers M, Grad R, Thombs BD. The patient engagement evaluation tool was valid for clinical practice guideline development. J Clin Epidemiol. 2022;143:61-72.

 

Negeri ZF, Levis B, Sun Y, He C, Krishnan A, Wu Y, Bhandari PM, Neupane D, Brehaut E, Benedetti A, Thombs BD. Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression: updated systematic review and individual participant data meta-analysis. BMJ 2021;375:n2183. 

 

Wu Y, Levis B, Sun Y, et al. Accuracy of the Hospital Anxiety and Depression Scale Depression Subscale (HADS-D) to Screen for Major Depression: Systematic Review and Individual Participant Data Meta-analysis. BMJ. 2021; 10;373:n972. doi: https://doi.org/10.1136/bmj.n972. 

 

Lyubenova A, Neupane D, Levis B, Wu Y, et al. Depression prevalence based on the EPDS compared to Structured Clinical Interview for DSM classification: systematic review and individual participant data meta-analysis. Int J Methods Psychiatr Res. 2020; doi: 10.1002/mpr.1860.

 

Fischer F, Levis B, Falk C, Sun Y, Ioannidis JPA, Cuijpers P, Shrier I, Benedetti A, Thombs BD, and the DEPRESsion Screening Data (DEPRESSD) PHQ Collaboration (including Wu Y). Comparison of different scoring methods based on latent variable models of the PHQ-9: an individual participant data meta-analysis. Psychol Med. 2021; doi: 10.1017/S0033291721000131. 

 

Harel D, Levis B, Ishihara M, Levis AW, Thombs, BD, Benedetti A, and the DEPRESsion Screening Data (DEPRESSD) EPDS Collaboration (including Wu Y). Shortening the Edinburgh Postnatal Depression Scale (EPDS) using optimal test assembly methods. Acta Psychiatr Scan. 2020; doi: 10.1111/acps.13272. 

 

Wu Y, Levis B, Ioannidis JPA, Benedetti A, Thombs, BD, DEPRESsion Screening Data (DEPRESSD) Collaboration. Probability of major depression classification based on the SCID, CIDI and MINI Diagnostic Interviews: a synthesis of three individual participant data meta-analyses. Psychother Psychosom. 2021;90:28-40. doi: 10.1159/000509283.

 

Wu Y, Kwakkenbos L, Henry RS, et al. Factors associated with fears due to COVID-19: a Scleroderma Patient-centered Intervention Network (SPIN) COVID-19 Cohort study. J Psychosom Res. 2020;140:110314.

 

Brehaut E, Neupane D, Levis B, Wu Y, et al. Depression prevalence using the HADS-D compared to SCID major depression classification: an individual participant data meta-analysis. J Psychosom Res. 2020. 139:110256. doi:10.1016/j.jpsychores.2020.110256.

 

Wu Y, Kwakkenbos L, Henry RS, et al. Validation of the COVID-19 Fears Questionnaires for Chronic Medical Conditions: a Scleroderma Patient-Centered Intervention Network COVID-19 Cohort study. J Psychosom Res. 2020;139:110271. doi: 10.1016/j.jpsychores.2020.110271.

 

Thombs BD, Kwakkenbos L, Carrier ME, Bourgeault A, Tao L, Harb S, Gagarine M, Rice D, Bustamante L, Ellis K, Duchek D, Wu Y, et al. Protocol for a partially nested randomised controlled trial to evaluate the effectiveness of the scleroderma patient-centered intervention network COVID-19 home-isolation activities together (SPIN-CHAT) program to reduce anxiety among at-risk scleroderma patients. J Psychosom Res. 2020;135:110132. doi: 10.1016/j.jpsychores.2020.110113. 

 

Thombs BD, Bonardi O, Rice DB, Boruff JT, Azar M, He C, Markham S, Sun Y, Wu Y, et al. Curating evidence on mental health during COVID-19: A living systematic review. J Psychosom Res. 2020;133:110113. doi: 10.1016/j.jpsychores.2020.110132.

 

Levis B, Negeri Z, Sun Y, Benedetti A, Thombs BD, DEPRESsion Screening Data (DEPRESSD) EPDS Group (including Wu Y). Accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression among pregnant and postpartum women: systematic review and meta-analysis of individual participant data. BMJ. 2020;371:m4022. 

 

Thombs BD, Levis B, Lyubenova A, Neupane D, Negeri Z, Wu Y, et al. Overestimation of postpartum depression prevalence based on a 5-item version of the EPDS: systematic review and individual participant data meta-analysis. Can J Psychiatry. 2020;65:835-44. doi: 10.1177/0706743720934959. 

 

Benedetti A, Levis B, Rücker G, Jones HE, Ioannidis JPA, Thombs BD, and the DEPRESSD Collaboration (including Wu Y). An empirical comparison of three methods for multiple cut-off diagnostic test meta-analysis of the Patient Health Questionnaire-9 (PHQ-9) depression screening tool using published data versus individual level data. Res Synth Methods. 2020;11:833-48. 

 

Levis B, Sun Y, He C, Wu Y, et al. Accuracy of the PHQ-2 alone and in combination with the PHQ-9 for screening to detect major depression: systematic review and meta-analysis. JAMA. 2020;323:2290–2300. 

 

Lee J, Liu K, Wu Y. Does the Asian catch-up model of world-class universities work? Revisiting the zero-sum game of global university rankings and government policies. Educ Res Policy Pract. 2020;19:319-343. https://doi.org/10.1007/s10671-020-09261-x. 

 

Levis B, Benedetti A, Ioannidis JPA, Sun Y, Negeri Z, He C, Wu Y, et al. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis. J Clin Epidemiol. 2020;122:115-128. 

 

McGrath S, Zhao XF, Steele R, Thombs BD, Benedetti A, and the DEPRESsion Screening Data (DEPRESSD) Collaboration(including Wu Y). Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Stat Methods Med Res. 2020. doi: 10.1177/0962280219889080.

 

Wu Y, Levis B, Sun Y, et al. Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale – Depression Subscale scores: an individual participant data meta-analysis of 73 primary studies. J Psychosom Res. 2020;129:109892. doi: 10.1016/j.jpsychores.2019.109892.

 

He C, Levis B, Riehm KE, Saadat N, Levis AW, Azar M, Rice DB, Krishnan A, Wu Y, et al. The Accuracy of the Patient Health Questionaire-9 (PHQ-9) algorithm for screening to detect major depression: An individual participant data meta-analysis. Psychother Psychosom. 2020;89(1):25-37. [IF=13.7]

 

Levis B, McMillan D, Sun Y, Saadat N, He C, Rice DB, Krishnan A, Wu Y, et al. Comparison of major depression diagnostic classification probability using the SCID, CIDI and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta-analysis. Int J Methods Psychiatr Res. 2020;28(4):e1803. 

 

Wu Y, Levis B, Riehm KE, et al. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis. Psychol Med. 2020;50(8):1368-1380. https://doi.org/10.1017/S0033291719001314. 

 

Lee J, Kim N, Wu Y. College readiness and engagement gaps between domestic and international students: re-envisioning educational diversity and equity for global campus. J Higher Educ. 2019;77(3):505-523. 

 

Benedetti A, Wu Y, Levis B, et al. Diagnostic accuracy of the Geriatric Depression Scale-30, Geriatric Depression Scale-15, Geriatric Depression Scale-5 and Geriatric Depression Scale-4 for detecting major depression: protocol for a systematic review and individual participant data meta-analysis. BMJ Open. 2018;8(12):e026598.

 

Thombs BD, Levis B, Rice BD, Wu Y, Benedetti A. Reducing waste and increasing the usability of psychiatry research: The family of EQUATOR reporting guidelines and one of its newest members – the PRISMA-DTA Statement. Can J Psychiatry. 2018; 63(8):509-512. 

Lee J, Wu Y. Is the Common Core racing U.S. to the top? Tracking state proficiency standards and achievement. Educ Policy Anal Arch. 2017;25(35):1-19. 

 

Wu Y. Universal beliefs and specific practices: Students’ math self-efficacy and its influencing factors between the United States and China. Int Educ Stud. 2016;9(12):61-74. 

 

Wu Y, Chen X, Zheng X. Post-traumatic stress symptoms and mental health and correlates among women after being exposed to the Wenchuan Earthquake. Chin J Clin Psychol. 2011;19(1):92-95. 

 

Li Y, Wang R, Wu Y, et al. Investigation and analysis quality of life and its influencing factors in the elderly. Chinese Journal of Geriatrics. 2011;30(03):248-250. 

 

Wu Y. The testing of the reliability and validity of questionnaires about college students’ dormitory interpersonal harmony. Journal of Changzhi Medical College. 2010;24(2):97-99. 

 

Wu Y, Chen X. Report of investigation of Guangzhou middle school students experienced traumatic events: Case study of a middle school of Yuexiu district. Journal of Shanxi Teachers University: Social Science. 2010;37(S1):138-140. 

 

Wu Y. Investigation and analysis on the state of mind, family function and social support of pregnant and lying-in women in Changzhi city. Chin Nurs Res. 2010;24(30):2759,2819. 

 

Li Y, Wang R, Wu Y, et al. Quality of life of elderly caregivers living in Changzhi city. Chinese Journal of Health Management. 2010;04(05):272-274. 

 

Rong SL, Wang YJ, Wang XL, Lu YX, Wu Y, et al. Recombinant proteins secreted from tissue-engineered bioartificial muscle improve cardiac dysfunction and suppress cardiomyocyte apoptosis in rats with heart failure. Chin Med J. 2010;123(24):3626-2633

 

Session Organizer/Chair/Moderator:

- Symposium Organizer/Chair. (2020, May). Addressing challenges in evaluating depression screening tool accuracy via individual participant data meta-analysis. Interdisciplinary Conference in Psychology (presented virtually due to COVID-19).

Oral Conference Presentations (selected):

- Wu Y, Levis B, Ioannidis JPA, Benedetti A, Thombs BD, and the DEPRESsion Screening Data (DEPRESSD) Collaboration. Major depression classification based on different diagnostic interviews: a synthesis of individual participant data meta-analyses. Methods for Evaluation of medical prediction Models, Tests and Biomarkers (MEMTAB) Conference. Leuven, Belgium. December 2020.

- Negeri ZF, Levis B, Wu Y, Thombs BD, Benedetti A and the DEPRESSED PHQ Collaboration. Latent class models for individual participant data meta-analyses of diagnostic test accuracy studies with imperfect reference standards. 27th Cochrane Colloquium. Toronto, ON, Canada, October 2020. (cancelled due to COVID-19).

- Levis B, Sun Y, He C, Wu Y, Krishnan A, Bhandari PM, Neupane D, Imran M, Brehaut E, Negeri ZF, Fischer FH, Benedetti A, Thombs BD, and the DEPRESSD PHQ Collaboration. Screening for depression with the Patient Health Questionnaire-2 (PHQ-2) alone and in combination with the PHQ-9: individual participant data meta-analysis. 27th Cochrane Colloquium. Toronto, ON, Canada. October 2020. (cancelled due to COVID-19).

- Levis B, Dehtiarova Y, Sun Y, Wu Y, Benedetti A, Thombs BD, and the DEPRESSD PHQ Collaboration. depressionscreening100.com/phq: a practice-based perspective to using the Patient Health Questionnaire-9 to screen for depression. 27th Cochrane Colloquium. Toronto, ON, Canada. October 2020. (cancelled due to COVID-19).

- Wu Y, Levis B, Ioannidis JPA, Benedetti A, Thombs BD, DEPRESsion Screening Data (DEPRESSD) Collaboration. Major depression classification based on different diagnostic interviews: a synthesis of individual participant data meta-analyses. In Wu Y (Chair). Addressing challenges in evaluating depression screening tool accuracy via individual participant data meta-analysis (Symposium). 9th Interdisciplinary Conference in Psychology (ICP). Ottawa, ON, Canada. May 2020 (presented virtually due to COVID-19).

- Wu Y, Levis B, Ioannidis JPA, Benedetti A, Thombs BD, and the DEPRESsion Screening Data (DEPRESSD) Collaboration. Major depression classification based on the SCID, CIDI and MINI diagnostic interviews: a meta-analysis of individual participant data meta-analyses. In Levis B (Chair). Use of individual participant data meta-analysis to address challenges in evaluating depression screening tool accuracy (Symposium). 81st Canadian Psychological Association Annual Convention. Montreal, QC, Canada. May 2020. (presented virtually due to COVID-19).