OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Predicting suicidal behaviours using clinical instruments: Systematic review and meta-analysis of positive predictive values for risk scales
Gregory Carter, Allison Milner, Katie McGill, et al.
The British Journal of Psychiatry (2017) Vol. 210, Iss. 6, pp. 387-395
Open Access | Times Cited: 307

Showing 1-25 of 307 citing articles:

Prediction Models for Suicide Attempts and Deaths
Bradley E. Belsher, Derek J. Smolenski, Larry D. Pruitt, et al.
JAMA Psychiatry (2019) Vol. 76, Iss. 6, pp. 642-642
Closed Access | Times Cited: 411

Time for united action on depression: a Lancet–World Psychiatric Association Commission
Helen Herrman, Vikram Patel, Christian Kieling, et al.
The Lancet (2022) Vol. 399, Iss. 10328, pp. 957-1022
Open Access | Times Cited: 283

Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning
Colin G. Walsh, Jessica D. Ribeiro, Joseph C. Franklin
Journal of Child Psychology and Psychiatry (2018) Vol. 59, Iss. 12, pp. 1261-1270
Closed Access | Times Cited: 215

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances
Sumithra Velupillai, Hanna Suominen, Maria Liakata, et al.
Journal of Biomedical Informatics (2018) Vol. 88, pp. 11-19
Open Access | Times Cited: 207

Suicide prediction models: a critical review of recent research with recommendations for the way forward
Ronald C. Kessler, Robert M. Bossarte, Alex Luedtke, et al.
Molecular Psychiatry (2019) Vol. 25, Iss. 1, pp. 168-179
Open Access | Times Cited: 169

Association between suicidal ideation and suicide: meta-analyses of odds ratios, sensitivity, specificity and positive predictive value
Catherine McHugh, Amy Corderoy, Christopher Ryan, et al.
BJPsych Open (2019) Vol. 5, Iss. 2
Open Access | Times Cited: 168

Assessment of suicide risk in mental health practice: shifting from prediction to therapeutic assessment, formulation, and risk management
Keith Hawton, Karen Lascelles, Alexandra Pitman, et al.
The Lancet Psychiatry (2022) Vol. 9, Iss. 11, pp. 922-928
Open Access | Times Cited: 94

Machine learning in suicide science: Applications and ethics
Kathryn P. Linthicum, Katherine Musacchio Schafer, Jessica D. Ribeiro
Behavioral Sciences & the Law (2019) Vol. 37, Iss. 3, pp. 214-222
Closed Access | Times Cited: 130

Nonlinear change processes and the emergence of suicidal behavior: A conceptual model based on the fluid vulnerability theory of suicide
Craig J. Bryan, Jonathan Butner, Alexis M. May, et al.
New Ideas in Psychology (2019) Vol. 57, pp. 100758-100758
Open Access | Times Cited: 111

Depression in primary care: part 1—screening and diagnosis
Erin Ferenchick, Parashar Pravin Ramanuj, Harold Alan Pincus
BMJ (2019), pp. l794-l794
Open Access | Times Cited: 107

Doctors, suicide and mental illness
Clare Gerada
BJPsych Bulletin (2018) Vol. 42, Iss. 4, pp. 165-168
Open Access | Times Cited: 104

Machine learning for suicide risk prediction in children and adolescents with electronic health records
Chang Su, Robert H. Aseltine, Riddhi Doshi, et al.
Translational Psychiatry (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 96

The relationship between entrapment and suicidal behavior through the lens of the integrated motivational–volitional model of suicidal behavior
Rory C. O’Connor, Gwendolyn Portzky
Current Opinion in Psychology (2017) Vol. 22, pp. 12-17
Open Access | Times Cited: 95

Understanding the effects of emotional reactivity on depression and suicidal thoughts and behaviors: Moderating effects of childhood adversity and resilience
Benjamin G. Shapero, Amy Farabaugh, Olga Terechina, et al.
Journal of Affective Disorders (2018) Vol. 245, pp. 419-427
Closed Access | Times Cited: 95

Stigma, biomarkers, and algorithmic bias: recommendations for precision behavioral health with artificial intelligence
Colin G. Walsh, Beenish Moalla Chaudhry, Prerna Dua, et al.
JAMIA Open (2020) Vol. 3, Iss. 1, pp. 9-15
Open Access | Times Cited: 95

Can we usefully stratify patients according to suicide risk?
Matthew Large, Christopher Ryan, Gregory Carter, et al.
BMJ (2017), pp. j4627-j4627
Open Access | Times Cited: 89

Sleep problems and suicide risk in youth: A systematic review, developmental framework, and implications for hospital treatment
Jaclyn C. Kearns, Daniel D.L. Coppersmith, Angela C. Santee, et al.
General Hospital Psychiatry (2018) Vol. 63, pp. 141-151
Closed Access | Times Cited: 89

Machine learning methods for developing precision treatment rules with observational data
Ronald C. Kessler, Robert M. Bossarte, Alex Luedtke, et al.
Behaviour Research and Therapy (2019) Vol. 120, pp. 103412-103412
Open Access | Times Cited: 77

Effects of Game-Based Learning on Students’ Achievement in Science: A Meta-Analysis
Hao Lei, Ming Ming Chiu, Danyi Wang, et al.
Journal of Educational Computing Research (2022) Vol. 60, Iss. 6, pp. 1373-1398
Closed Access | Times Cited: 66

Columbia-Suicide Severity Rating Scale Screen Version: initial screening for suicide risk in a psychiatric emergency department
Johan Bjureberg, Marie Dahlin, Andreas Carlborg, et al.
Psychological Medicine (2021) Vol. 52, Iss. 16, pp. 3904-3912
Open Access | Times Cited: 64

Psychobiological risk factors for suicidal thoughts and behaviors in adolescence: a consideration of the role of puberty
Tiffany C. Ho, Anthony J. Gifuni, Ian H. Gotlib
Molecular Psychiatry (2021) Vol. 27, Iss. 1, pp. 606-623
Open Access | Times Cited: 59

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