Quantitative language features identify placebo responders in chronic back pain

被引:5
作者
Berger, Sara E. [1 ,2 ]
Branco, Paulo [1 ]
Vachon-Presseau, Etienne [3 ,4 ,5 ]
Abdullah, Taha B. [1 ]
Cecchi, Guillermo [2 ]
Apkarian, A. Vania [1 ,6 ,7 ,8 ]
机构
[1] Northwestern Univ, Dept Physiol, Feinberg Sch Med, Chicago, IL 60611 USA
[2] IBM Corp, Watson Res Ctr, Hlth Care & Life Sci Dept, Yorktown Hts, NY USA
[3] McGill Univ, Fac Dent, Montreal, PQ, Canada
[4] McGill Univ, Fac Med, Dept Anesthesia, Montreal, PQ, Canada
[5] McGill Univ, Alan Edwards Ctr Res Pain AECRP, Montreal, PQ, Canada
[6] Northwestern Univ, Feinberg Sch Med, Dept Phys Med & Rehabil, Chicago, IL 60611 USA
[7] Northwestern Univ, Feinberg Sch Med, Dept Anesthesia, Chicago, IL 60611 USA
[8] Northwestern Univ, Ctr Translat Pain Res, Feinberg Sch Med, Chicago, IL 60611 USA
基金
加拿大健康研究院;
关键词
Placebo response; Chronic back pain; Natural language processing; Interview; Semantic proximity; Machine learning; Psycholinguistics; WORDS; SPEECH; PERSONALITY; ANALGESIA; GENDER;
D O I
10.1097/j.pain.0000000000002175
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Although placebo effect sizes in clinical trials of chronic pain treatments have been increasing, it remains unknown if characteristics of individuals' thoughts or previous experiences can reliably infer placebo pill responses. Research using language to investigate emotional and cognitive processes has recently gained momentum. Here, we quantified placebo responses in chronic back pain using more than 300 semantic and psycholinguistic features derived from patients' language. This speech content was collected in an exit interview as part of a clinical trial investigating placebo analgesia (62 patients, 42 treated; 20 not treated). Using a nested leave-one-out cross-validated approach, we distinguished placebo responders from nonresponders with 79% accuracy using language features alone; a subset of these features-semantic distances to identity and stigma and the number of achievement-related words-also explained 46% of the variance in placebo analgesia. Importantly, these language features were not due to generic treatment effects and were associated with patients' specific baseline psychological traits previously shown to be predictive of placebo including awareness and personality characteristics, explaining an additional 31% of the variance in placebo analgesia beyond that of personality. Initial interpretation of the features suggests that placebo responders differed in how they talked about negative emotions and the extent that they expressed awareness to various aspects of their experiences; differences were also seen in time spent talking about leisure activities. These results indicate that patients' language is sufficient to identify a placebo response and implie that specific speech features may be predictive of responders' previous treatment.
引用
收藏
页码:1692 / 1704
页数:13
相关论文
共 51 条
[1]   Detection of acute 3,4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing [J].
Agurto, Carla ;
Cecchi, Guillermo A. ;
Norel, Raquel ;
Ostrand, Rachel ;
Kirkpatrick, Matthew ;
Baggott, Matthew J. ;
Wardle, Margaret C. ;
de Wit, Harriet ;
Bedi, Gillinder .
NEUROPSYCHOPHARMACOLOGY, 2020, 45 (05) :823-832
[2]   A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects [J].
Bedi, Gillinder ;
Cecchi, Guillermo A. ;
Slezak, Diego F. ;
Carrillo, Facundo ;
Sigman, Mariano ;
de Wit, Harriet .
NEUROPSYCHOPHARMACOLOGY, 2014, 39 (10) :2340-2348
[3]  
Biro D., 2010, The language of pain: Finding words, compassion, and relief
[4]   Automatic measurement of propositional idea density from part-of-speech tagging [J].
Brown, Cati ;
Snodgrass, Tony ;
Kemper, Susan J. ;
Herman, Ruth ;
Covington, Michael A. .
BEHAVIOR RESEARCH METHODS, 2008, 40 (02) :540-545
[5]   AUTOMATED ANALYSIS OF RECENTONSET AND PRODROMAL SCHIZOPHRENIA [J].
Cecchi, Guillermo ;
Corcoran, Cheryl .
SCHIZOPHRENIA BULLETIN, 2018, 44 :S76-S76
[6]   How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease [J].
Clarke, Natasha ;
Foltz, Peter ;
Garrard, Peter .
CORTEX, 2020, 129 :446-463
[7]   The Placebo Effect in Pain Therapies [J].
Colloca, Luana .
ANNUAL REVIEW OF PHARMACOLOGY AND TOXICOLOGY, VOL 59, 2019, 59 :191-211
[8]   Prediction of psychosis across protocols and risk cohorts using automated language analysis [J].
Corcoran, Cheryl M. ;
Carrillo, Facundo ;
Fernandez-Slezak, Diego ;
Bedi, Gillinder ;
Klim, Casimir ;
Javitt, Daniel C. ;
Bearden, Carrie E. ;
Cecchi, Guillermo A. .
WORLD PSYCHIATRY, 2018, 17 (01) :67-75
[9]   Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults - United States, 2016 [J].
Dahlhamer, James ;
Lucas, Jacqueline ;
Zelaya, Carla ;
Nahin, Richard ;
Mackey, Sean ;
DeBar, Lynn ;
Kerns, Robert ;
Von Korff, Michael ;
Porter, Linda ;
Helmick, Charles .
MMWR-MORBIDITY AND MORTALITY WEEKLY REPORT, 2018, 67 (36) :1001-1006
[10]  
Dario Gutierrez E., 2017, EMNLP 2017 C EMP MET, P2923, DOI DOI 10.18653/V1/D17-1316