The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project
Open accessAbstract
OBJECTIVE: As part of the second phase of the North American Prodrome Longitudinal Study (NAPLS-2), Cannon and colleagues report, concurrently with the present article, on a risk calculator for the individualized prediction of a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS-2 psychosis risk calculator using an independent sample of patients at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP). METHOD: Of the total EDIPPP sample of 210 subjects rated as being at clinical high risk based on the Structured Interview for Prodromal Syndromes, 176 had at least one follow-up assessment and were included in the construction of a new prediction model with six predictor variables in the NAPLS-2 psychosis risk calculator (unusual thoughts and suspiciousness, symbol coding test performance, verbal learning test performance, decline in social functioning, baseline age, and family history). Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC). The NAPLS-2 risk calculator was then used to generate a psychosis risk estimate for each case in the external validation sample. RESULTS: The external validation model showed good discrimination, with an AUC of 0.790 (95% CI=0.644-0.937). In addition, the personalized risk generated by the risk calculator provided a solid estimation of the actual conversion outcome in the validation sample. CONCLUSIONS: Two independent samples of clinical high-risk patients converge to validate the NAPLS-2 psychosis risk calculator. This prediction calculator represents a meaningful step toward early intervention and the personalized treatment of psychotic disorders.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“176 (16.6, US); 0.79 (AUC) 292 199 (19.1, China); 0.63 (AUC) 293 98 (18.59, US); 0.71 (AUC) 294”
From Preventive psychiatry: a blueprint for improving the mental health of young people (2021) · cites this paper as [292]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Stone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., Goldberg, A. C., Gordon, D., Levy, D., Lloyd-Jones, D. M., et al. (2014) · Circulation · doi:10.1161/01.cir.0000437738.63853.7a · Cited by 7,081
Non-Parametric Statistics for the Behavioral Sciences.
Stuart, A., & Siegel, S. (1957) · Economica · doi:10.2307/2551606 · Cited by 3,403
Lindström, J., & Tuomilehto, J. O. (2003) · Diabetes Care · doi:10.2337/diacare.26.3.725 · Cited by 1,937 · cited 1×
“A number of risk calculators are now freely available to the public and can estimate the risk, for example, of prostate, ovarian, breast, pancreatic, and colorectal cancer(4–6), type 2 diabetes(7, 8), and cardiovascular disease (9–11).”
BackgroundRidker, P. M., Buring, J. E., Rifai, N., & Cook, N. R. (2007) · JAMA · doi:10.1001/jama.297.6.611 · Cited by 1,814
Miller, T. J., McGlashan, T. H., Rosen, J. L., Cadenhead, K. S., Ventura, J., McFarlane, W. R., Perkins, D. O., Pearlson, G. D., & Woods, S. W. (2003) · Schizophrenia Bulletin · doi:10.1093/oxfordjournals.schbul.a007040 · Cited by 1,800
Self-citationSome suggestions for measuring predictive performance
Sheiner, L. B., & Beal, S. L. (1981) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1007/bf01060893 · Cited by 1,618 · cited 1×
“MPE was calculated as the difference between the risk estimates generated by the external validation model and the NAPLS2 psychosis risk calculator, providing a metric for the tendency for overestimation/underestimation of risk(41).”
MethodBenedict, R. H. B., Schretlen, D., Groninger, L., & Brandt, J. (1998) · The Clinical Neuropsychologist · doi:10.1076/clin.12.1.43.1726 · Cited by 1,597
The Psychosis High-Risk State: A Comprehensive State-of-the-Art Review
Fusar-Poli, P., Borgwardt, S., Bechdolf, A., Addington, J., Riecher-Rössler, A., Schultze-Lutter, F., Keshavan, M., Wood, S., Ruhrmann, S., Seidman, L. J., et al. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.269 · Cited by 1,483 · cited 1×
“Advances include operationalizing and validating clinical criteria that identify individuals considered to be prodromal or at clinical high risk (CHR) for psychosis, approximately 29% of whom will develop a psychotic illness over two years(13).”
BackgroundSelf-citationPrognosis and prognostic research: what, why, and how?
Moons, K. G. M., Royston, P., Vergouwe, Y., Grobbee, D. E., & Altman, D. G. (2009) · BMJ · doi:10.1136/bmj.b375 · Cited by 1,337 · cited 1×
“Over time, prevention has progressed from identifying populations at risk to personalizing risk estimates(1, 2).”
Background
Research works printed but not linked: 3
- Keefe R, 1999, Brief Assessment of Cognition in Schizophrenia (BACS) Manual–A: Version 2.1
- Siegel S, 1988, Nonparametric Statistics for the Behavioral Sciences
- Loewy R, Schizophr Bull
Cited by
Sorted by citations
Items 101–169 of 169
Forsyth, J. K., & Bearden, C. E. (2023) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20230736 · Cited by 12
Li, Z., Zhang, T., Xu, L., Wei, Y., Tang, Y., Hu, Q., Liu, X., Li, X., Davis, J. M., Smith, R., et al. (2020) · Early Intervention in Psychiatry · doi:10.1111/eip.12988 · Cited by 12
“…symptoms; (e) Global Assessment of Functioning; (f) individual predictive risk of psychosis calculated by NAPLS-2 psychosis risk calculator (Carrion et al., 2016) and SHARP psychosis risk calculator (Zhang et al., 2019); (g) scores of MATRICS consensus cognitive battery (MCCB) (Kern et…”
MethodWorthington, M., Collins, M. A., Addington, J., Bearden, C. E., Cadenhead, K. S., Cornblatt, B. A., Keshavan, M. S., Mathalon, D. H., Perkins, D. O., Stone, W. S., et al. (2023) · Psychological Medicine · doi:10.1017/s0033291723002301 · Cited by 12
“While these models have shown promise and studies validating these models in external samples have been published (Carrión et al., 2016; Koutsouleris et al., 2021; Osborne & Mittal, 2019; Zhang et al., 2018a), barriers to clinical implementation remain.”
Self-citationPsychiatric Risk Assessment from the Clinician’s Perspective: Lessons for the Future
Cohen, A. S., Fedechko, T. L., Schwartz, E. K., Le, T. P., Foltz, P. W., Bernstein, J., Cheng, J., Rosenfeld, E. P., & Elvevåg, B. (2019) · Community Mental Health Journal · doi:10.1007/s10597-019-00411-x · Cited by 12
Assessment of Risk for Psychosis
Shapiro, D. I., Li, H., Kline, E. R., & Niznikiewicz, M. A. (2019) · Springer eBooks · doi:10.1007/978-3-030-17336-4_2 · Cited by 13
Tognin, S., Vieira, S., Oliver, D., Cullen, A. E., Kempton, M. J., Fusar‐Poli, P., Mechelli, A., Dazzan, P., Merritt, K., Maat, A., et al. (2025) · Schizophrenia · doi:10.1038/s41537-025-00598-x · Cited by 11
“For example, the NAPLS risk calculator to transition to psychosis 6 generalised well to other North American sites 31 but had a modest performance in a sample from Shanghai 32 .”
Cognitive Dysfunction as a Risk Factor for Psychosis
Karcher, N. R., Merchant, J. T., Pine, J. G., & Kilçiksiz, C. M. (2022) · Current topics in behavioral neurosciences · doi:10.1007/7854_2022_387 · Cited by 11
Zoghbi, A. W., Bernanke, J. A., Gleichman, J., Masucci, M. D., Corcoran, C. M., Califano, A., Segovia, J., Colibazzi, T., First, M. B., Brucato, G., et al. (2019) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2019.04.018 · Cited by 11
“The identification of individuals at clinical high-risk (CHR) for psychosis holds promise for early intervention to prevent or alter the course of psychotic illnesses, such as schizophrenia or schizoaffective disorder.”
BackgroundInfluentialRaballo, A., Poletti, M., & Preti, A. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.01.020 · Cited by 11
Addington, J., Liu, L., Braun, A., Auther, A. M., Calkins, M. E., Cornblatt, B. A., Corcoran, C. M., Fusar‐Poli, P., Kerr, M., Mourgues, C., et al. (2025) · Schizophrenia · doi:10.1038/s41537-025-00556-7 · Cited by 10
“…social functioning in the year before entering the study (de fi ned as having a 1 point or greater drop on the GF: Social scale from the highest level to the current (baseline) level of functioning) was found to be a signi fi cant predictor of psychosis in the NAPLS Psychosis Risk Calculator 20,21 .”
Self-citationAllott, K., Yassin, W., Alameda, L., Billah, T., Borders, O., Buccilli, K., Carrión, R. E., Castillo-Passi, R. I., Cho, K. I. K., Chin, K., et al. (2025) · Schizophrenia · doi:10.1038/s41537-025-00578-1 · Cited by 9
“The utility of cognitive measures in risk calculators has been replicated in independent CHR cohorts 7,8 , and shown promise cross-culturally 20 .”
Self-citationBiomarker Profiles in Psychosis Risk Groups Within Unaffected Relatives Based on Familiality and Age
Türközer, H. B., Ivleva, E. I., Palka, J. M., Clementz, B. A., Shafee, R., Pearlson, G. D., Sweeney, J. A., Keshavan, M. S., Gershon, E. S., & Tamminga, C. A. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbab013 · Cited by 9
The Current State of the Clinical High Risk for Psychosis Research Paradigm
Cannon, T. D. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.06.008 · Cited by 9
Cumulative Environmental Risk in Early Life: Associations With Schizotypy in Childhood
O’Hare, K., Watkeys, O. J., Whitten, T., Dean, K., Laurens, K. R., Tzoumakis, S., Harris, F., Carr, V. J., & Green, M. J. (2022) · Schizophrenia Bulletin · doi:10.1093/schbul/sbac160 · Cited by 9
Early Detection of Psychosis Vulnerability: Progress, Opportunity, and Caution
Carpenter, W. T. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.16060746 · Cited by 9
Mathalon, D. H., Nicholas, S., Roach, B. J., Billah, T., Lavoie, S., Whitford, T. J., Hamilton, H., Addamo, L., Anohkin, A., Bekinschtein, T. A., et al. (2025) · Schizophrenia · doi:10.1038/s41537-025-00622-0 · Cited by 8
Self-citationAttenuated first‐rank symptoms and conversion to psychosis in a clinical high‐risk cohort
Crump, F. M., Arndt, L. Y., Grivel, M. M., Horga, G., Corcoran, C. M., Brucato, G., & Girgis, R. R. (2017) · Early Intervention in Psychiatry · doi:10.1111/eip.12529 · Cited by 8
“…2017 John Wiley & Sons Australia, Ltd 1213 the SIPS is significantly predictive of transition to psychosis (Addington et al., 2015; Cannon et al., 2016), and has demonstrated external validity in other samples (Carrión et al., 2016; Ruhrmann et al., 2010), including our own (Brucato et al., 2017).”
BackgroundInfluentialCumulative environmental risk in early life is associated with mental disorders in childhood
O’Hare, K., Watkeys, O. J., Whitten, T., Dean, K., Laurens, K. R., Harris, F. A. J., Carr, V. J., & Green, M. J. (2022) · Psychological Medicine · doi:10.1017/s0033291722001702 · Cited by 8
“…a surge of interest in using ERSs to examine their association with psychotic disorders, both to enhance risk prediction (e.g. Cannon et al., 2016; Carrión et al., 2016; Moore et al., 2021; Padmanabhan, Shah, Tandon, & Keshavan, 2017) and to help understand the impact of the environment on the…”
Are We There Yet? Predicting Conversion to Psychosis Using Machine Learning
Smucny, J., Davidson, I. A. K., & Carter, C. S. (2023) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20220973 · Cited by 8
Self-citationCadenhead, K. S., Duncan, E., Addington, J., Bearden, C. E., Cannon, T. D., Cornblatt, B. A., Mathalon, D. H., McGlashan, T. H., Perkins, D. O., Seidman, L. J., et al. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00833 · Cited by 8
Self-citationBonnett, L. J., Hunt, A., Flores, A., Smith, C. T., Varese, F., Byrne, R. E., Law, H., Milicevic, M., Carney, R., Parker, S., et al. (2025) · Schizophrenia · doi:10.1038/s41537-025-00582-5 · Cited by 7
“The NAPLS-2 model was externally validated 46 in 210 subjects from the Early Detection, Intervention, and Prevention of Psychosis Program 24 and showed good discrimination, with an AUC of 0.790 (95% CI = 0.644-0.937), although in this validation study the researchers did not include trauma and…”
InfluentialSelf-citationChoi, S., Kyeong, S.-H., Cho, K. I. K., Yun, J., Lee, T. Y., Park, H. Y., Kim, S. N., & Kwon, J. S. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.03.028 · Cited by 7
Research Trends in Individuals at High Risk for Psychosis: A Bibliometric Analysis
Lee, T. Y., Lee, S. S., Gong, B.-G., & Kwon, J. S. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.853296 · Cited by 6
Williams, T. F., Powers, A. R., Ellman, L. M., Corlett, P. R., Strauss, G. P., Schiffman, J. E., Waltz, J. A., Silverstein, S. M., Woods, S. W., Walker, E. F., et al. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.05.006 · Cited by 7
“The NAPLS-RC can be scored through an online calculator (http://riskcalc.org/napls/) and uses SIPS ratings and participant age, as well as several other measures that were administered: the Brief Assessment of Cognition in Schizophrenia (Keefe et al., 2004), the Hopkins Verbal Learning Test-Revised (Brandt and Benedic…”
Validation of the youth mood recurrences risk calculator in an adult sample with bipolar disorder
Fiedorowicz, J. G., Merranko, J. A., Iyengar, S., Hower, H. M., Gill, M. K., Yen, S., Goldstein, T. R., Strober, M. A., Hafeman, D., Keller, M. B., et al. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.09.037 · Cited by 6
Calkins, M. E., Woods, S. W., Bearden, C. E., Liu, L., Moore, T. M., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., McGlashan, T. H., Perkins, D. O., et al. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.08.014 · Cited by 7
Self-citationMiklowitz, D. J., Addington, J., O’Brien, M. P., Denenny, D. M., Weintraub, M. J., Zinberg, J. L., Mathalon, D. H., Cornblatt, B. A., Friedman‐Yakoobian, M. S., Stone, W. S., et al. (2021) · Early Intervention in Psychiatry · doi:10.1111/eip.13208 · Cited by 6
Self-citationWilliams, T. F., Ellman, L. M., Schiffman, J. E., & Mittal, V. A. (2022) · Schizophrenia Bulletin Open · doi:10.1093/schizbullopen/sgac015 · Cited by 5
Ologundudu, O. M., Palaniyappan, L. K., Cipriano, L. E., Wijnen, B. F. M., Anderson, K. K., & Ali, S. (2023) · Schizophrenia Research · doi:10.1016/j.schres.2023.09.015 · Cited by 5
Psychosis Risk Syndrome: What Now?
Sentissi, O., ANDREOU, M. A., Moeglin, C., Curtis, L., & BROSCH, M. S. (2017) · Journal of Psychiatric Practice · doi:10.1097/pra.0000000000000272 · Cited by 5
Ford, E., Stone, J. M., Oliver, D., Fell, B., Roque, G., Robertson, S., Fusar‐Poli, P., & Greenwood, K. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1584719 · Cited by 4
Kuhney, F. S., Strauss, G. P., Walker, E. F., James, S. H., & Mittal, V. A. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf032 · Cited by 4
Loch, A. A., Ara, A., Hortêncio, L., Marques, J. H., Talib, L. L., Andrade, J. C., Serpa, M. H., Sanchez, L., Alves, T. M., van de Bilt, M. T., et al. (2021) · Neuroscience Letters · doi:10.1016/j.neulet.2021.136358 · Cited by 4
Moe, A. M., Cowan, H. R., Manges, M. E., Wastler, H. M., Hamilton, S. A., Kilicoglu, M. F. V., Holmes, A. C., & Breitborde, N. J. K. (2024) · Early Intervention in Psychiatry · doi:10.1111/eip.13590 · Cited by 4
“In the past decade, there have been significant advances in understanding the CHR-P state and risk factors for conversion to psychosis (Cannon et al., 2016; Carrión et al., 2016), but less is known about the effectiveness of interventions for CHR-P.”
Penalized angular regression for personalized predictions
Hellton, K. H. (2022) · Scandinavian Journal of Statistics · doi:10.1111/sjos.12574 · Cited by 3
“The ambition to perform personalization when predicting is becoming an important feature of many applications: medicine (Cheng et al., 2012; Carri´on et al., 2016), marketing (Tang et al., 2013), item recommendation (Rafailidis et al., 2014), nutrition (Zeevi et al., 2015), education (Reber et al.,…”
BackgroundGrossman, M., Best, M. W., Harrison, A. G., & Bowie, C. R. (2018) · Early Intervention in Psychiatry · doi:10.1111/eip.12713 · Cited by 3
Psychiatric Diagnoses and Treatment Preceding Schizophrenia in Adolescents Aged 9–17 Years
Kang-Yi, C. D., Chao, B., Teng, S., Locke, J. J., Mandell, D., Wong, Y. I., & Epperson, C. N. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00487 · Cited by 3
Preventive strategies for severe mental disorders
Chakrabarti, S. (2017) · Indian Journal of Social Psychiatry · doi:10.4103/ijsp.ijsp_40_17 · Cited by 3
“In these studies, the presence of UHR criteria along with unusual thought content, decline in social functioning, neurocognitive impairments, and young age have been able to predict psychosis with a 71%–79% accuracy rate.[51,64]”
BackgroundEarly interventions for psychosis
Goldman, M. B. (2021) · Current Psychiatry · doi:10.12788/cp.0176 · Cited by 3
Stepped Care for Youths at Clinical High Risk for Psychosis
Broekhuijse, A., Saxena, A., Walsh, B. C., Mourgues, C., Mukhtar, H., Howard, S., Woods, S. W., Powers, A. R., & Farina, E. A. (2026) · Psychiatric Services · doi:10.1176/appi.ps.20250688 · Cited by 2
Sprüngli‐Toffel, E., Studerus, E., Curtis, L., Conchon, C., Alameda, L., Bailey, B. K., Caron, C., Haase, C., Gros, J., Herbrecht, E., et al. (2024) · Revista de Psiquiatría y Salud Mental · doi:10.1016/j.sjpmh.2024.09.001 · Cited by 2
Brown, L., & Griffiths, S. L. (2025) · BJPsych Bulletin · doi:10.1192/bjb.2024.112 · Cited by 1
Addington, J., Shalev, A., Liu, L., Jahraus, C., Chu, M. P., Farina, E., Fusar‐Poli, P., Marcy, P., Núñez, Á., Calkins, M. E., et al. (2025) · Schizophrenia Bulletin Open · doi:10.1093/schizbullopen/sgaf013 · Cited by 1
“Third, since attenuated psychotic symptoms (APSs) and social functioning have in earlier studies been predictive of later transition to psychosis, 11-13 we will examine whether the severity of APSs and social functioning deficits vary among the different recruitment sources and whether there are…”
Self-citationLatent Multimodal Profiles Associated With Psychosis-Like Experiences at Follow-Up
Zoupou, E., Karcher, N. R., Jackson, J. J., & Barch, D. M. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.10.017 · Cited by 2
Machine learning enables efficient neurocognitive profiling in patients with schizophrenia
Chen, R. Y., Greenwood, T. A., BRAFF, D. L., Lazzeroni, L. C., Swerdlow, N. R., Calkins, M. E., Freedman, R., Green, M. F., Gur, R. C., Gur, R. E., et al. (2026) · Nature Mental Health · doi:10.1038/s44220-025-00568-3 · Cited by 1
“For example, applying these abbreviated neurocognitive tasks toward prodromal participants could enable early identification of individuals who are most likely to develop psychosis 11,27,71 .”
Hafeman, D., & Birmaher, B. B. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812347-8.00001-4 · Cited by 1
Hirsch, F., Bumanglag, Â., Zhang, Y., & Wohlschlaeger, A. M. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103657 · Cited by 2
“However, cognitive impairment is predictive of developing psychosis in high-risk individuals (Carri ´ on et al., 2016; Seidman et al., 2016) and is a core feature across different manifestations of PSD (Bora & Pantelis, 2015).”
BackgroundMacDonald, A. N., Goines, K., Novacek, D. M., & Walker, E. F. (2016) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/2372732216684852 · Cited by 1
“A psychosis-risk calculator that weights multiple risk indicators (e.g., symptom type, age, family history, functioning) to predict psychosis conversion was recently published (Cannon et al., 2016; Carrión et al., 2016).”
BackgroundMethodMakarewicz, A., Karakuła‐Juchnowicz, H., & Łobejko, Ł. (2017) · Current Problems of Psychiatry · doi:10.1515/cpp-2017-0005 · Cited by 1
“Badanie NALPS [98] poszukiwało skutecznych metod oceny ryzyka rozwoju psychozy, umożliwiających wczesną interwencję i spersonalizowane leczenie.”
BackgroundMethodInfluentialEarly Intervention in Psychosis: From Science to Services
Smith, T. E., & Dixon, L. B. (2019) · Springer eBooks · doi:10.1007/978-3-030-11908-9_11 · Cited by 1
Freedman, R., Lewis, D. A., Michels, R., Pine, D. S., Rush, A. J., Schultz, S. K., Tamminga, C. A., & Pier, K. S. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.16101120 · Cited by 1
Multivariate brain-based dimensions of child psychiatric problems: degrees of generalizabilityPreprint
Xu, B., Dall’Aglio, L., Flournoy, J. C., Bortsova, G., Tervo‐Clemmens, B., Collins, P. F., de Bruijne, M., Luciana, M. M., Marquand, A. F., Wang, H., et al. (2023) · medRxiv · doi:10.1101/2023.03.12.23287158 · Cited by 1
Introduction to the JINS Special Issue: Preclinical Prediction
Woodard, J. L., Seidman, L. J., & Stout, J. C. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617716000941
“…of developing a psychotic illness, and advances have been made in prediction of transition to psychosis from a CHR stage (Cannon et al., 2008, 2016; Carrion et al., 2016), including the usage of neuropsychological measures (Giuliano et al., 2012; Seidman, Giuliano, & Walker, 2010; Seidman et al.,…”
BackgroundPredicting Psychosis with Accuracy
DeLisi, L. E. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.02.013
“This result was then replicated by Carrión et al. (2016) in an independent sample of patients.”
BackgroundResultChoi, S., Cho, H.-K., & Lee, M.-K. (2017) · Journal of korean Academy of Child and Adolescent Psychiatry · doi:10.5765/jkacap.2017.28.2.132
Biological endophenotypes of prodromal psychosis and depression
Berger, M. (2018) · ResearchOnline at James Cook University (James Cook University) · doi:10.25903/5d2d186d20e3f
Gawęda, Ł., & Nelson, B. (2020) · Early Intervention in Psychiatry · doi:10.1111/eip.12891
“Existing predictive models (eg, risk calculators) (Cannon et al., 2016a; Carrion et al., 2016; Fusar-Poli et al., 2018) predict future risk of developing full-blown disorders (eg, psychosis) in high-risk samples based on backward chaining.”
BackgroundQuagliato, L. A., Dalvi-Garcia, F., & Nardi, A. E. (2023) · Anais da Academia Nacional de Medicina · doi:10.52130/27639878-aanm2023v194n1p20-25
Chapter 20. Using Technology to Advance Early Psychosis Intervention
Ben‐Zeev, D., & Buck, B. (2019) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781615379217.lg20
Chapter 2. Growth of Early Intervention in Psychosis in the United States
Hardy, K. V., Ballon, J. S., Noordsy, D. L., & Adelsheim, S. N. (2019) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781615379217.lg02
Self-citationChapter 12. Assessment, Prognosis, and Treatment of Subthreshold Mood Symptoms
Hafeman, D., & Spada, M. L. (2019) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781615379200.lg12
Keshavan, M. S., Lizano, P. L., Perry, S. W., Prasad, K. M. R., & Licinio, J. (2020) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781615379194.lg05
Decoding Psychosis Risk: Neuroanatomical Correlates of the NAPLS-2 Calculator in the PRONIA Cohort
Neuner, L., Weyer, C., Kambeitz‐Ilankovic, L., Korda, A. I., Dwyer, D., Antonucci, L. A., Kambeitz, J. P., Upthegrove, R., Salokangas, R. K. R., Hietala, J. A., et al. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf135
Impairments of Language and Communication in the Different Phases of Schizophrenia
Cabezas, A. S., Heim, S., & Jimeno, N. (2025) · Zeitschrift für Neuropsychologie · doi:10.1024/1016-264x/a000421
Stepped care for young people at clinical high risk for psychosis: a real-world studyPreprint
Broekhuijse, A., Saxena, A., Walsh, B. C., Mourgues, C., Mukhtar, H., Howard, S., Woods, S. W., Powers, A. R., & Farina, E. A. (2026) · medRxiv · doi:10.64898/2026.02.05.26345683
Arnovitz, M. D., Cornblatt, B. A., Auther, A. M., McLaughlin, D., Addington, J., Bearden, C. E., Cadenhead, K. S., Cannon, T. D., Keshavan, M. S., Mathalon, D. H., et al. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf244
Self-citationPelizza, L., Leuci, E., Quattrone, E., Lisi, A. D., Palmisano, D., Pupo, S., Paulillo, G., Pellegrini, C., Pellegrini, P., & Menchetti, M. (2026) · Early Intervention in Psychiatry · doi:10.1111/eip.70167
“In fact, baseline AP prevalence rate varies widely across countries, ranging from 6% reported in the NAPLS-2 (‘North American Prodrome Longitudinal Study-2’) (Carrión et al. 2016) to 79% found in the SOPRES (‘Taiwan's Study On the psychopatho-logic PRogress of Early Schizophrenia-like disorder’) study (Liu et al. 2011…”
Addington, J., Chu, M., Liu, L., HEINSSEN, R. K., Auther, A. M., Bearden, C. E., Cannon, T. D., Carrión, R. E., Keshevan, M., Mathalon, D. H., et al. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf258
“23 External validation of the NAPLS calculator 24 supported decline in social functioning as an important component of the model.”
Self-citationResilience Pathways in Psychosis
Vinogradov, S. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf190
Metadata
- Authors
- Carrión, R. E., Cornblatt, B. A., Burton, C. Z., Tso, I. F., Auther, A. M., Adelsheim, S., Calkins, R., Carter, C. S., Niendam, T., Sale, T. G., Taylor, S. F., & McFarlane, W. R.
- Affiliations
- Northwell Health (US)
- ORCID
- Venue
- American Journal of Psychiatry
- Published
- 2016-10-01
- Volume
- 173
- Issue
- 10
- Pages
- 989-996
- ISSN
- 0002-953X (ISSN-L)
- 1535-7228
- PMC
- PMC5048503
- OpenAlex
- W2462155653
- Cited by
- 170
- References
- 47
- Citations by year
- 2026: 4 · 2025: 15 · 2024: 7 · 2023: 13 · 2022: 12 · 2021: 16 · 2020: 24 · 2019: 30 · 2018: 21 · 2017: 21 · 2016: 7
- FWCI
- 23.39
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- PDXScholar (Portland State University) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (KL2TR000434)
- National Institute of Mental Health (R01MH061523, P30MH074543, R01MH059883, K23MH087708, R21MH101676, K23MH108823, U01MH081857)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Keywords
- psychosis prediction, clinical high risk for psychosis, external validation, early detection and intervention, prodromal psychosis, transition to psychosis, suspicion, symbol coding, verbal learning, family history (medicine), personalized treatment
- MeSH terms
- Adolescent, Adult, Child, Female, Humans, Longitudinal Studies, Male, Models, Psychological, Predictive Value of Tests, Psychiatric Status Rating Scales, Psychotic Disorders, Risk Factors, Early Diagnosis, Young Adult, Prodromal Symptoms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
