Automated analysis of free speech predicts psychosis onset in high-risk youths
Open accessAbstract
Background/Objectives: Psychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals. AIMS: In this proof-of-principle study, our aim was to test automated speech analyses combined with Machine Learning to predict later psychosis onset in youths at clinical high-risk (CHR) for psychosis. Methods: Thirty-four CHR youths (11 females) had baseline interviews and were assessed quarterly for up to 2.5 years; five transitioned to psychosis. Using automated analysis, transcripts of interviews were evaluated for semantic and syntactic features predicting later psychosis onset. Speech features were fed into a convex hull classification algorithm with leave-one-subject-out cross-validation to assess their predictive value for psychosis outcome. The canonical correlation between the speech features and prodromal symptom ratings was computed. Results: Derived speech features included a Latent Semantic Analysis measure of semantic coherence and two syntactic markers of speech complexity: maximum phrase length and use of determiners (e.g., which ). These speech features predicted later psychosis development with 100% accuracy, outperforming classification from clinical interviews. Speech features were significantly correlated with prodromal symptoms. Conclusions: Findings support the utility of automated speech analysis to measure subtle, clinically relevant mental state changes in emergent psychosis. Recent developments in computer science, including natural language processing, could provide the foundation for future development of objective clinical tests for psychiatry.
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
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?
Vocal quality changes are associated with cognitive disorders.
“There is evidence that there are vocal quality changes associated with cognitive disorders [95].”
From A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders (2020) · cites this paper as [95]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Landauer, T. K., & Dumais, S. T. (1997) · Psychological Review · doi:10.1037/0033-295x.104.2.211 · Cited by 6,282 · see citing works
Natural language processing with Python
Bird, S., Klein, E., & Loper, E. (2009) · CERN Document Server (European Organization for Nuclear Research) · Cited by 3,472 · see citing works
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 · see citing works
Quantifying incoherence in speech: An automated methodology and novel application to schizophrenia
Elvevåg, B., Foltz, P. W., Weinberger, D. R., & Goldberg, T. E. (2007) · Schizophrenia Research · doi:10.1016/j.schres.2007.03.001 · Cited by 363 · see citing works
Adler, C. M., Malhotra, A. K., Elman, I., Goldberg, T. E., Egan, M. F., Pickar, D., & Breier, A. F. (1999) · American Journal of Psychiatry · doi:10.1176/ajp.156.10.1646 · Cited by 337 · see citing works
Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis
Mota, N. B., Vasconcelos, N. A. P., Lemos, N., Pieretti, A. C., Kinouchi, O., Cecchi, G. A., Copelli, M., & Ribeiro, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034928 · Cited by 265 · see citing works
Self-citationUsing data mining methods to build customer profiles
Adomavičius, G., & Tuzhilin, A. (2001) · Computer · doi:10.1109/2.901170 · Cited by 235 · see citing works
Predicting the Risk of Suicide by Analyzing the Text of Clinical Notes
Poulin, C., Shiner, B. R., Thompson, P., Vepštas, L., Young‐Xu, Y., Goertzel, B., Watts, B. V., Flashman, L. A., & McAllister, T. W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0085733 · Cited by 168 · see citing works
Elvevåg, B., Foltz, P. W., Rosenstein, M., et al. (2009) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2009.05.002 · Cited by 134 · see citing works
A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects
Bedi, G., Cecchi, G., Slezak, D. F., Carrillo, F., Sigman, M., & de Wit, H. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2014.80 · Cited by 88 · see citing works
Self-citationTwenty-Five Years of Progress: The View from NIMH and NINDS
Insel, T. R., & Landis, S. C. (2013) · Neuron · doi:10.1016/j.neuron.2013.09.041 · Cited by 87 · see citing works
DeVylder, J., Muchomba, F. M., Gill, K. E., Ben‐David, S., Walder, D. J., Malaspina, D., & Corcoran, C. M. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.08.008 · Cited by 81 · see citing works
Self-citationHolshausen, K., Harvey, P. D., Elvevåg, B., Foltz, P. W., & Bowie, C. R. (2013) · Cortex · doi:10.1016/j.cortex.2013.02.006 · Cited by 79 · see citing works
Gooding, D. C., Ott, S. L., Roberts, S. A., et al. (2012) · Psychological Medicine · doi:10.1017/s0033291712001791 · Cited by 57 · see citing works
Phenomenological Research in Schizophrenia: From Philosophical Anthropology to Empirical Science
Davidson, L. (1994) · Journal of Phenomenological Psychology · doi:10.1163/156916294x00133 · Cited by 41 · see citing works
The Subjective Experience of Youths at Clinically High Risk of Psychosis: A Qualitative Study
Ben‐David, S., Birnbaum, M. L., Eilenberg, M. E., et al. (2014) · Psychiatric Services · doi:10.1176/appi.ps.201300527 · Cited by 36 · see citing works
Youth mental health reform and early intervention: encouraging early signs
McGorry, P. D., & Purcell, R. (2009) · Early Intervention in Psychiatry · doi:10.1111/j.1751-7893.2009.00128.x · Cited by 28 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A Review of the Role of Artificial Intelligence in Healthcare
Al Kuwaiti, A., Nazer, K., Al-Reedy, A., Al-Shehri, S., Al-Muhanna, A., Subbarayalu, A. V., Al Muhanna, D., & Al-Muhanna, F. A. (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13060951 · Cited by 915 · see citing works
Fiske, A., Henningsen, P., & Buyx, A. (2019) · Journal of Medical Internet Research · doi:10.2196/13216 · Cited by 857 · see citing works
Torous, J., Kiang, M. V., Lorme, J., & Onnela, J.-P. (2016) · JMIR Mental Health · doi:10.2196/mental.5165 · Cited by 758 · see citing works
“There is increasing evidence of the clinical value of voice data in schizophrenia in predicting conversation from prodromal state [30], and there is also much literature on the value of correlating such data with changes in symptoms [31,32].”
BackgroundMachine learning and natural language processing in mental health: systematic review
Le Glaz, A., Haralambous, Y., Kim-Dufor, D.-H., Lenca, P., Billot, R., Ryan, T. C., Marsh, J., DeVylder, J., Walter, M., Berrouiguet, S., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/15708 · Cited by 576 · see citing works
“Each community has a central node: Perlis et al [55] are cited in 7 other papers, Jackson et al [73] are cited in 4 other papers, Carrell et al [74] and Afshar et al [75] are cited in 2 other papers, and Bedi et al [39] are cited in 2 other papers.”
InfluentialThe entropic brain - revisited
Carhart-Harris, R. L. (2018) · Neuropharmacology · doi:10.1016/j.neuropharm.2018.03.010 · Cited by 522 · see citing works
D’Alfonso, S. (2020) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2020.04.005 · Cited by 408 · see citing works
The WPA-Lancet psychiatry commission on the future of psychiatry
Bhugra, D., Tasman, A., Pathare, S., Priebe, S., Smith, S., Torous, J., Arbuckle, M. R., Langford, A., Alarcón, R. D., Chiu, H. F. K., et al. (2017) · The Lancet Psychiatry · doi:10.1016/s2215-0366(17)30333-4 · Cited by 392 · see citing works
Karaca, O., Çalışkan, S. A., & Demir, K. (2021) · BMC Medical Education · doi:10.1186/s12909-021-02546-6 · Cited by 377 · see citing works
Xu, J., Yang, P., Xue, S., Sharma, B., Sanchez-Martin, M., Wang, F., Beaty, K. A., Dehan, E., & Parikh, B. (2019) · Human Genetics · doi:10.1007/s00439-019-01970-5 · Cited by 305 · see citing works
Martinez-Martin, N., & Kreitmair, K. (2018) · JMIR Mental Health · doi:10.2196/mental.9423 · Cited by 221 · see citing works
Data mining for health: staking out the ethical territory of digital phenotyping
Martinez-Martin, N., Insel, T. R., Dagum, P., Greely, H. T., & Cho, M. K. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0075-8 · Cited by 218 · see citing works
Artificial Intelligence-Assisted Online Social Therapy for Youth Mental Health
D'Alfonso, S., Santesteban-Echarri, O., Rice, S., Wadley, G., Lederman, R., Miles, C., Gleeson, J., & Alvarez-Jimenez, M. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00796 · Cited by 192 · see citing works
“…to more general, publicly used sites where users will have a variety of conditions and are not pre-known trial participants, there is also the potential to deliver therapy content particularly relevant to a certain mental health condition based on analysis of a user’s content (Bedi et al., 2015).”
BackgroundLanguage as a biomarker for psychosis: a natural language processing approach
Corcoran, C. M., Mittal, V. A., Bearden, C. E., E. Gur, R., Hitczenko, K., Bilgrami, Z., Savic, A., Cecchi, G. A., & Wolff, P. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.04.032 · Cited by 186 · see citing works
Self-citationMota, N. B., Copelli, M., & Ribeiro, S. (2017) · npj Schizophrenia · doi:10.1038/s41537-017-0019-3 · Cited by 157 · see citing works
Self-citationBirnbaum, M. L., Ernala, S. K., Rizvi, A. F., De Choudhury, M., & Kane, J. M. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7956 · Cited by 168 · see citing works
“Furthermore, classifiers designed to automatically sort individual cases into diagnostic categories have achieved success in recognizing participants with psychotic disorders from healthy controls based on linguistic differences in writing samples [15] and speech [13,18].”
BackgroundResultGarcía, A. M., Carrillo, F., Orozco-Arroyave, J. R., Trujillo, N., Vargas Bonilla, J. F., Fittipaldi, S., Adolfi, F., Nöth, E., Sigman, M., Fernández Slezak, D., et al. (2016) · Brain and Language · doi:10.1016/j.bandl.2016.07.008 · Cited by 144 · see citing works
Self-citationAltszyler, E., Ribeiro, S., Sigman, M., & Fernández Slezak, D. (2017) · Consciousness and Cognition · doi:10.1016/j.concog.2017.09.004 · Cited by 128 · see citing works
Self-citationAutomatic detection of Incoherent speech for diagnosing schizophrenia
Iter, D., Yoon, J., & Jurafsky, D. (2018) · Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic · doi:10.18653/v1/w18-0615 · Cited by 115 · see citing works
Salazar de Pablo, G., Catalan, A., & Fusar-Poli, P. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.3561 · Cited by 103 · see citing works
Linguistic Markers Indicating Therapeutic Outcomes of Social Media Disclosures of Schizophrenia
Ernala, S. K., Rizvi, A. F., Birnbaum, M. L., Kane, J. M., & De Choudhury, M. (2017) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3134678 · Cited by 99 · see citing works
A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders
Voleti, R., Liss, J. M., & Berisha, V. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2019.2952087 · Cited by 96 · see citing works
Irving, J., Patel, R., Oliver, D., Colling, C., Pritchard, M., Broadbent, M., Baldwin, H., Stahl, D., Stewart, R., & Fusar-Poli, P. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaa126 · Cited by 92 · see citing works
Fusar-Poli, P., Sullivan, S. A., Shah, J. L., & Uhlhaas, P. J. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00774 · Cited by 92 · see citing works
Sanfelici, R., Dwyer, D. B., Antonucci, L. A., & Koutsouleris, N. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.02.009 · Cited by 82 · see citing works
Zhang, L., Duvvuri, R., Chandra, K. K. L., Nguyen, T., & Ghomi, R. H. (2020) · Depression and Anxiety · doi:10.1002/da.23020 · Cited by 67 · see citing works
Chandler, C., Foltz, P. W., & Elvevåg, B. (2019) · Schizophrenia Bulletin · doi:10.1093/schbul/sbz105 · Cited by 61 · see citing works
Meyer, N., Kerz, M., Folarin, A., Joyce, D. W., Jackson, R., Karr, C., Dobson, R., & MacCabe, J. (2018) · JMIR mHealth and uHealth · doi:10.2196/mhealth.8292 · Cited by 58 · see citing works
Truong, N. M., Vo, T. Q., Tran, H. T. B., Nguyen, H. T., & Pham, V. N. H. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e22653 · Cited by 56 · see citing works
Willits, J. A., Rubin, T., Jones, M. N., Minor, K. S., & Lysaker, P. H. (2018) · Schizophrenia Research · doi:10.1016/j.schres.2017.11.014 · Cited by 46 · see citing works
Eyigoz, E., Courson, M., Sedeño, L., Rogg, K., Orozco-Arroyave, J. R., Nöth, E., Skodda, S., Trujillo, N., Rodríguez, M., Rusz, J., et al. (2020) · Cortex · doi:10.1016/j.cortex.2020.08.020 · Cited by 44 · see citing works
Self-citationFang, C., Markuzon, N., Patel, N., & Rueda, J.-D. (2022) · Value in Health · doi:10.1016/j.jval.2022.06.004 · Cited by 36 · see citing works
Smith, K. E., Mason, T. B., Juarascio, A., Schaefer, L. M., Crosby, R. D., Engel, S. G., & Wonderlich, S. A. (2019) · International Journal of Eating Disorders · doi:10.1002/eat.23124 · Cited by 34 · see citing works
Clinical efficacy of pre-trained large language models through the lens of aphasia
Cong, Y., LaCroix, A. N., & Lee, J. (2024) · Scientific Reports · doi:10.1038/s41598-024-66576-y · Cited by 25 · see citing works
Rezazadeh, H., Ahmadipour, H., & Salajegheh, M. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04516-6 · Cited by 22 · see citing works
Khan, W. U., & Seto, E. (2023) · Journal of Medical Internet Research · doi:10.2196/43386 · Cited by 15 · see citing works
Identifying Splitting Through Sentiment Analysis
Colibazzi, T., Abrami, A., Stern, B., Caligor, E., Fertuck, E. A., Lubin, M., Clarkin, J., & Cecchi, G. (2023) · Journal of Personality Disorders · doi:10.1521/pedi.2023.37.1.36 · Cited by 2 · see citing works
Self-citation
- Authors
- Bedi, G., Carrillo, F., Cecchi, G. A., Slezak, D. F., Sigman, M., Mota, N. B., Ribeiro, S., Javitt, D. C., Copelli, M., & Corcoran, C. M.
- Affiliations
- New York State Psychiatric Institute (US)
- Universidad de Buenos Aires (AR)
- IBM Research - Thomas J. Watson Research Center (US)
- Universidade Federal do Rio Grande do Norte (BR)
- Universidade Federal de Pernambuco (BR)
- Corresponding author
- Cecchi, Guillermo A
- Corcoran, Cheryl M
- ORCID
- Venue
- npj Schizophrenia
- Published
- 2015-08-26
- Volume
- 1
- Issue
- 1
- Pages
- 15030-15030
- ISSN
- 2334-265X (ISSN-L)
- PMC
- PMC4849456
- OpenAlex
- W1267646904
- Cited by
- 673
- References
- 17
- Citations by year
- 2026: 47 · 2025: 62 · 2024: 66 · 2023: 69 · 2022: 82 · 2021: 103 · 2020: 83 · 2019: 67 · 2018: 32 · 2017: 39 · 2016: 20 · 2015: 2
- FWCI
- 25.14
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Schizophrenia (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Americanae (AECID Library) (publishedVersion, other-oa)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
- Repositorio Digital Universidad Torcuato Di Tella (submittedVersion, cc-by)
- Americanae (AECID Library) (submittedVersion, other-oa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- Funders
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2013-07699-0)
- National Institutes of Health (UL1TR000040)
- National Institute of Mental Health (P50MH086385, K23MH066279, R21MH086125)
- National Institute on Drug Abuse (K23DA034877)
- National Center for Advancing Translational Sciences (TR000040)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
- Keywords
- automated speech analysis, psychosis onset prediction, prodromal psychosis, latent semantic analysis, syntactic complexity, semantic coherence, natural language processing, 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
