References
- 1Abdou, M., Kulmizev, A., Hershcovich, D., Frank, S., Pavlick, E., & Søgaard, A. (2021). Can language models encode perceptual structure without grounding? A case study in color. arXiv preprint arXiv:2109.06129. 10.18653/v1/2021.conll-1.9
- 2Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., et al. (2023). Gpt-4 technical report. arXiv preprint arXiv:2303.08774.
- 3AI@Meta (2024). Llama 3 model card.
- 4Allport, G. W. (1942). The use of personal documents in psychological science. Social Science Research Council Bulletin.
- 5Allport, G. W., & Vernon, P. E. (1930). The field of personality. Psychological bulletin, 27(10), 677. 10.1037/h0072589
- 6Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. 10.18637/jss.v067.i01
- 7Beck, J. S. (2020). Cognitive behavior therapy: Basics and beyond. Guilford Publications.
- 8Ben-Shachar, M. S., Lüdecke, D., & Makowski, D. (2020). effectsize: Estimation of effect size indices and standardized parameters. Journal of Open Source Software, 5(56), 2815. 10.21105/joss.02815
- 9Blanco-Cuaresma, S. (2024). Psychological assessments with large language models: A privacy-focused and cost-effective approach. arXiv preprint arXiv:2402.03435.
- 10Bolger, N. (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. The Guilford Press.
- 11Brans, K., Van Mechelen, I., Rimé, B., & Verduyn, P. (2014). To share, or not to share? Examining the emotional consequences of social sharing in the case of anger and sadness. Emotion, 14(6), 1062. 10.1037/a0037604
- 12Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877–1901.
- 13Burkhardt, H., Pullmann, M., Hull, T., Areán, P., & Cohen, T. (2022).
Comparing emotion feature extraction approaches for predicting depression and anxiety . In Proceedings of the eighth workshop on computational linguistics and clinical psychology (pp. 105–115). 10.18653/v1/2022.clpsych-1.9 - 14Bürkner, P.-C. (2017). brms: An r package for bayesian multilevel models using stan. Journal of statistical software, 80, 1–28. 10.18637/jss.v080.i01
- 15Chim, J., Tsakalidis, A., Gkoumas, D., Atzil-Slonim, D., Ophir, Y., Zirikly, A., Resnik, P., & Liakata, M. (2024a).
Overview of the clpsych 2024 shared task: Leveraging large language models to identify evidence of suicidality risk in online posts . In Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) (pp. 177–190). - 16Chim, J., Tsakalidis, A., Gkoumas, D., Atzil-Slonim, D., Ophir, Y., Zirikly, A., Resnik, P., & Liakata, M. (2024b).
Overview of the CLPsych 2024 shared task: Leveraging large language models to identify evidence of suicidality risk in online posts . In A. Yates, B. Desmet, E. Prud’hommeaux, A. Zirikly, S. Bedrick, S. MacAvaney, K. Bar, M. Ireland, & Y. Ophir (Eds.), Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) (pp. 177–190). St. Julians, Malta: Association for Computational Linguistics. - 17Cohen, K. A., Shroff, A., Nook, E. C., & Schleider, J. L. (2022). Linguistic distancing predicts response to a digital single-session intervention for adolescent depression. Behaviour Research and Therapy, 159, 104220. 10.1016/j.brat.2022.104220
- 18Cunningham, H., Ewart, A., Riggs, L., Huben, R., & Sharkey, L. (2023). Sparse autoencoders find highly interpretable features in language models. arXiv preprint arXiv:2309.08600.
- 19Demszky, D., Yang, D., Yeager, D. S., Bryan, C. J., Clapper, M., Chandhok, S., Eichstaedt, J. C., Hecht, C., Jamieson, J., Johnson, M., et al. (2023). Using large language models in psychology. Nature Reviews Psychology, 2(11), 688–701. 10.1038/s44159-023-00241-5
- 20Dercon, Q., Mehrhof, S. Z., Sandhu, T. R., Hitchcock, C., Lawson, R. P., Pizzagalli, D. A., Dalgleish, T., & Nord, C. L. (2024). A core component of psychological therapy causes adaptive changes in computational learning mechanisms. Psychological Medicine, 54(2), 327–337. 10.1017/S0033291723001587
- 21Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Yang, A., Fan, A., et al. (2024). The llama 3 herd of models. arXiv preprint arXiv:2407.21783.
- 22Edwards, L. J., Muller, K. E., Wolfinger, R. D., Qaqish, B. F., & Schabenberger, O. (2008). An r2 statistic for fixed effects in the linear mixed model. Statistics in medicine, 27(29), 6137–6157. 10.1002/sim.3429
- 23Eichstaedt, J. C., Kern, M. L., Yaden, D. B., Schwartz, H. A., Giorgi, S., Park, G., Hagan, C. A., Tobolsky, V. A., Smith, L. K., Buffone, A., et al. (2021). Closed-and open-vocabulary approaches to text analysis: A review, quantitative comparison, and recommendations. Psychological Methods, 26(4), 398. 10.1037/met0000349
- 24Elhage, N., Nanda, N., Olsson, C., Henighan, T., Joseph, N., Mann, B., Askell, A., Bai, Y., Chen, A., Conerly, T., et al. (2021). A mathematical framework for transformer circuits. Transformer Circuits Thread, 1(1), 12.
- 25Ferrando, J., Sarti, G., Bisazza, A., & Costa-jussà, M. R. (2024). A primer on the inner workings of transformer-based language models. arXiv preprint arXiv:2405.00208.
- 26Freud, S. (1966). Psychopathology of everyday life. WW Norton & Company.
- 27Gillan, C. M., Kosinski, M., Whelan, R., Phelps, E. A., & Daw, N. D. (2016). Characterizing a psychiatric symptom dimension related to deficits in goal-directed control. elife, 5,
e11305 . 10.7554/eLife.11305 - 28Gottschalk, L. A., & Gleser, G. C. (2022). The measurement of psychological states through the content analysis of verbal behavior. Univ of California Press. 10.2307/jj.8362616
- 29Gurnee, W., Nanda, N., Pauly, M., Harvey, K., Troitskii, D., & Bertsimas, D. (2023). Finding neurons in a haystack: Case studies with sparse probing. arXiv preprint arXiv:2305.01610.
- 30Holmes, D., Alpers, G. W., Ismailji, T., Classen, C., Wales, T., Cheasty, V., Miller, A., & Koopman, C. (2007). Cognitive and emotional processing in narratives of women abused by intimate partners. Violence against women, 13(11), 1192–1205. 10.1177/1077801207307801
- 31Jackson, J. C., Watts, J., List, J.-M., Puryear, C., Drabble, R., & Lindquist, K. A. (2022). From text to thought: How analyzing language can advance psychological science. Perspectives on Psychological Science, 17(3), 805–826. 10.1177/17456916211004899
- 32Jaeger, B. C., Edwards, L. J., Das, K., & Sen, P. K. (2017). An r 2 statistic for fixed effects in the generalized linear mixed model. Journal of applied statistics, 44(6), 1086–1105. 10.1080/02664763.2016.1193725
- 33Jeon, H., Yoo, D., Lee, D., Son, S., Kim, S., & Han, J. (2024).
A dual-prompting for interpretable mental health language models . In A. Yates, B. Desmet, E. Prud’hommeaux, A. Zirikly, S. Bedrick, S. MacAvaney, K. Bar, M. Ireland, & Y. Ophir (Eds.), Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) (pp. 247–255). St. Julians, Malta: Association for Computational Linguistics. - 34Kacewicz, E., Pennebaker, J. W., Davis, M., Jeon, M., & Graesser, A. C. (2014). Pronoun use reflects standings in social hierarchies. Journal of Language and Social Psychology, 33(2), 125–143. 10.1177/0261927X13502654
- 35Kahn, J. H., Tobin, R. M., Massey, A. E., & Anderson, J. A. (2007). Measuring emotional expression with the linguistic inquiry and word count. The American journal of psychology, 120(2), 263–286. 10.2307/20445398
- 36Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., & Amodei, D. (2020). Scaling laws for neural language models. arXiv preprint arXiv:2001.08361.
- 37Kroenke, K., Strine, T. W., Spitzer, R. L., Williams, J. B., Berry, J. T., & Mokdad, A. H. (2009). The phq-8 as a measure of current depression in the general population. Journal of affective disorders, 114(1–3), 163–173. 10.1016/j.jad.2008.06.026
- 38Kross, E., Bruehlman-Senecal, E., Park, J., Burson, A., Dougherty, A., Shablack, H., Bremner, R., Moser, J., & Ayduk, O. (2014). Self-talk as a regulatory mechanism: how you do it matters. Journal of personality and social psychology, 106(2), 304. 10.1037/a0035173
- 39Kross, E., Vickers, B. D., Orvell, A., Gainsburg, I., Moran, T. P., Boyer, M., Jonides, J., Moser, J., & Ayduk, O. (2017). Third-person self-talk reduces ebola worry and risk perception by enhancing rational thinking. Applied Psychology: Health and Well-Being, 9(3), 387–409. 10.1111/aphw.12103
- 40Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. 10.18637/jss.v082.i13
- 41Laffal, J. (1964). Freud’s theory of language. The Psychoanalytic Quarterly, 33(2), 157–175. 10.1080/21674086.1964.11926307
- 42Leshed, G., Hancock, J. T., Cosley, D., McLeod, P. L., & Gay, G. (2007). Feedback for guiding reflection on teamwork practices. In Proceedings of the 2007 ACM International Conference on Supporting Group Work (pp. 217–220). 10.1145/1316624.1316655
- 43Liu, Q., Wang, W., & Willard, J. (2025). Effects of prompt length on domain-specific tasks for large language models. arXiv preprint arXiv:2502.14255.
- 44Long, D. X., Dinh, D., Nguyen, N.-H., Kawaguchi, K., Chen, N. F., Joty, S., & Kan, M.-Y. (2025). What makes a good natural language prompt? arXiv preprint arXiv:2506.06950. 10.18653/v1/2025.acl-long.292
- 45Low, D. M., Rumker, L., Talkar, T., Torous, J., Cecchi, G., & Ghosh, S. S. (2020). Natural language processing reveals vulnerable mental health support groups and heightened health anxiety on reddit during covid-19: Observational study. Journal of medical Internet research, 22(10),
e22635 . 10.2196/22635 - 46Malgaroli, M., Hull, T. D., Zech, J. M., & Althoff, T. (2023). Natural language processing for mental health interventions: a systematic review and research framework. Translational Psychiatry, 13(1), 309. 10.1038/s41398-023-02592-2
- 47Mangalik, S., Eichstaedt, J. C., Giorgi, S., Mun, J., Ahmed, F., Gill, G., Ganesan, A. V., Subrahmanya, S., Soni, N., Clouston, S. A., et al. (2024). Robust language-based mental health assessments in time and space through social media. NPJ Digital Medicine, 7(1), 109. 10.1038/s41746-024-01100-0
- 48Marjieh, R., Sucholutsky, I., van Rijn, P., Jacoby, N., & Griffiths, T. L. (2024). Large language models predict human sensory judgments across six modalities. Scientific Reports, 14(1), 21445. 10.1038/s41598-024-72071-1
- 49Moran, T., & Eyal, T. (2022). Emotion regulation by psychological distance and level of abstraction: Two meta-analyses. Personality and Social Psychology Review, 26(2), 112–159. 10.1177/10888683211069025
- 50Newman, M. L., Groom, C. J., Handelman, L. D., & Pennebaker, J. W. (2008). Gender differences in language use: An analysis of 14,000 text samples. Discourse processes, 45(3), 211–236. 10.1080/01638530802073712
- 51Newman, M. L., Pennebaker, J. W., Berry, D. S., & Richards, J. M. (2003). Lying words: Predicting deception from linguistic styles. Personality and social psychology bulletin, 29(5), 665–675. 10.1177/0146167203029005010
- 52Newman, M. W. (2022). Value added? A pragmatic analysis of the routine use of phq-9 and gad-7 scales in primary care. General Hospital Psychiatry, 79, 15–18. 10.1016/j.genhosppsych.2022.09.005
- 53Nils, F., & Rimé, B. (2012). Beyond the myth of venting: Social sharing modes determine the benefits of emotional disclosure. European Journal of Social Psychology, 42(6), 672–681. 10.1002/ejsp.1880
- 54Nook, E. C., Ahn, H. E., Schleider, J. L., & Somerville, L. H. (2024). Emotion regulation is associated with increases in linguistic measures of both psychological distancing and abstractness. Affective Science, 1–14. 10.31219/osf.io/a2zv3
- 55Nook, E. C., Hull, T. D., Nock, M. K., & Somerville, L. H. (2022). Linguistic measures of psychological distance track symptom levels and treatment outcomes in a large set of psychotherapy transcripts. Proceedings of the National Academy of Sciences, 119(13),
e2114737119 . 10.1073/pnas.2114737119 - 56Nook, E. C., Nardini, C., Zacharek, S. J., Hommel, G., Spencer, H., Martino, A., Morra, A., Flores, S., Anderson, T., Marin, C. E., et al. (2023). Affective language spreads between anxious children and their mothers during a challenging puzzle task. Emotion, 23(6), 1513. 10.1037/emo0001203
- 57Nook, E. C., Schleider, J. L., & Somerville, L. H. (2017). A linguistic signature of psychological distancing in emotion regulation. Journal of Experimental Psychology: General, 146(3), 337. 10.1037/xge0000263
- 58Nook, E. C., Vidal Bustamante, C. M., Cho, H. Y., & Somerville, L. H. (2020). Use of linguistic distancing and cognitive reappraisal strategies during emotion regulation in children, adolescents, and young adults. Emotion, 20(4), 525. 10.1037/emo0000570
- 59Orvell, A., Vickers, B. D., Drake, B., Verduyn, P., Ayduk, O., Moser, J., Jonides, J., & Kross, E. (2021). Does distanced self-talk facilitate emotion regulation across a range of emotionally intense experiences? Clinical Psychological Science, 9(1), 68–78. 10.1177/2167702620951539
- 60Pennebaker, J. W. (2001). Linguistic inquiry and word count: Liwc 2001.
- 61Pennebaker, J. W., & Stone, L. D. (2003). Words of wisdom: language use over the life span. Journal of personality and social psychology, 85(2), 291. 10.1037/0022-3514.85.2.291
- 62Rathje, S., Mirea, D.-M., Sucholutsky, I., Marjieh, R., Robertson, C. E., & Van Bavel, J. J. (2024). Gpt is an effective tool for multilingual psychological text analysis. Proceedings of the National Academy of Sciences, 121(34),
e2308950121 . 10.1073/pnas.2308950121 - 63Razykov, I., Ziegelstein, R. C., Whooley, M. A., & Thombs, B. D. (2012). The phq-9 versus the phq-8—is item 9 useful for assessing suicide risk in coronary artery disease patients? Data from the heart and soul study. Journal of psychosomatic research, 73(3), 163–168. 10.1016/j.jpsychores.2012.06.001
- 64Rimé, B. (2009). Emotion elicits the social sharing of emotion: Theory and empirical review. Emotion review, 1(1), 60–85. 10.1177/1754073908097189
- 65Sahi, R. S., He, Z., Silvers, J. A., & Eisenberger, N. I. (2023). One size does not fit all: Decomposing the implementation and differential benefits of social emotion regulation strategies. Emotion, 23(6), 1522. 10.1037/emo0001194
- 66Sahi, R. S., Ninova, E., & Silvers, J. A. (2021). With a little help from my friends: Selective social potentiation of emotion regulation. Journal of Experimental Psychology: General, 150(6), 1237. 10.1037/xge0000853
- 67Sharma, A., Rushton, K., Lin, I. W., Nguyen, T., & Althoff, T. (2024). Facilitating self-guided mental health interventions through human-language model interaction: A case study of cognitive restructuring. In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1–29). 10.1145/3613904.3642761
- 68Shin, C., Lee, S.-H., Han, K.-M., Yoon, H.-K., & Han, C. (2019). Comparison of the usefulness of the phq-8 and phq-9 for screening for major depressive disorder: analysis of psychiatric outpatient data. Psychiatry investigation, 16(4), 300. 10.30773/pi.2019.02.01
- 69So, J.-h., Chang, J., Kim, E., Na, J., Choi, J., Sohn, J.-y., Kim, B.-H., Chu, S. H., et al. (2024). Aligning large language models for enhancing psychiatric interviews through symptom delineation and summarization: Pilot study. JMIR Formative Research, 8(1),
e58418 . 10.2196/58418 - 70Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: Liwc and computerized text analysis methods. Journal of language and social psychology, 29(1), 24–54. 10.1177/0261927X09351676
- 71Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al. (2023). Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971.
- 72Trope, Y., & Liberman, N. (2010). Construal-level theory of psychological distance. Psychological review, 117(2), 440. 10.1037/a0018963
- 73Uluslu, A. Y., Michail, A., & Clematide, S. (2024). Utilizing large language models to identify evidence of suicidality risk through analysis of emotionally charged posts. In Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) (pp. 264–269).
- 74Wang, Y., Inkpen, D., & Gamaarachchige, P. K. (2024). Explainable depression detection using large language models on social media data. In Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) (pp. 108–126).
- 75Wise, T., Robinson, O. J., & Gillan, C. M. (2023). Identifying transdiagnostic mechanisms in mental health using computational factor modeling. Biological Psychiatry, 93(8), 690–703. 10.1016/j.biopsych.2022.09.034
- 76Yang, K., Zhang, T., Kuang, Z., Xie, Q., Huang, J., & Ananiadou, S. (2024). Mentallama: interpretable mental health analysis on social media with large language models. In Proceedings of the ACM Web Conference 2024 (pp. 4489–4500). 10.1145/3589334.3648137
- 77Zaki, J., & Williams, W. C. (2013). Interpersonal emotion regulation. Emotion, 13(5), 803. 10.1037/a0033839
- 78Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., et al. (2023). A survey of large language models. arXiv preprint arXiv:2303.18223.
- 79Zuromski, K. L., Low, D. M., Jones, N. C., Kuzma, R., Kessler, D., Zhou, L., Kastman, E. K., Epstein, J., Madden, C., Ghosh, S. S., et al. (2024). Detecting suicide risk among us servicemembers and veterans: a deep learning approach using social media data. Psychological Medicine, 1–10. 10.1017/S0033291724001557