DeePsy: Představení online nástroje pro zpětnou vazbu v psychoterapii

Roč.17,č.1(2023)

Abstrakt

Přestože je psychoterapie prokazatelně účinnou formou pomoci, její efektivita již několik desetiletí naráží na pomyslný strop. Jedním z možných důvodů je nedostatek bezprostřední zpětné vazby, která by terapeutům umožnila včas zachytit nejrůznější nesnáze v terapeutickém procesu a adekvátně na ně reagovat. Dosavadní výzkumy ukazují, že jako terapeuti máme tendenci nadhodnocovat své dovednosti a mnohdy nedokážeme u svých klientů včas rozpoznat nespokojenost či zhoršování stavu. Cílem tohoto textu je představit webovou aplikaci DeePsy –⁠ nástroj pro průběžné monitorování procesu a výsledků psychoterapie. Aplikace terapeutům nabízí průběžnou a systematickou zpětnou vazbu na jejich práci pomocí pravidelně administrovaných dotazníků a automatické analýzy nahrávek terapeutických sezení. Článek objasňuje základní principy, na nichž je aplikace postavena, a popisuje její aktuální podobu. Nabízí též zamyšlení nad problematikou zpětné vazby v širším kontextu kultury psychoterapeutické práce.


Klíčová slova:
rutinní monitorování procesu a výsledku; zpětná vazba; webová aplikace; DeePsy
Reference

Aafjes-Van Doorn, K., & Meisel, J. (2022). Implementing routine outcome monitoring in a psychodynamic training clinic: It's complicated. Counselling Psychology Quarterly. Advance online publication. https://doi.org/10.1080/09515070.2022.2110451

Aafjes-van Doorn, K., Porcerelli, J., & Müller-Frommeyer, L. C. (2020). Language style matching in psychotherapy: An implicit aspect of alliance. Journal of Counseling Psychology, 67(4), 509-522. https://doi.org/10.1037/cou0000433

American Psychological Association (2013). Recognition of psychotherapy effectiveness. Psychotherapy, 50(1), 102-109. https://doi.org/10.1037/a0030276

Barkham, M., Bewick, B., Mullin, T., Gilbody, S., Connell, J., Cahill, J., Mellor-Clark, J., Richards, D., Unsworth, G., & Evans, C. (2013). The CORE-10: A short measure of psychological distress for routine use in the psychological therapies. Counselling and Psychotherapy Research, 13(1), 3-13. https://doi.org/10.1080/14733145.2012.729069

Barkham, M., & Lambert, M. (2021). The efficacy and effectiveness of psychological therapies. In M. Barkham, W. Lutz, & L. G. Castonguay (Eds.), Bergin and Garffield's handbook of psychotherapy and behavior change (pp. 135-189). Wiley.

Barkham, M., Mellor-Clark, J., & Stiles, W. B. (2015). A CORE approach to progress monitoring and feedback: Enhancing evidence and improving practice. Psychotherapy, 52(4), 402-411. https://doi.org/10.1037/pst0000030

Bech, P., Olsen, L., Kjoller, M., & Rasmussen, N. (2003). Measuring well-being rather than the absence of distress symptoms: A comparison of the SF-36 mental health subscale and the WHO-Five well-being scale. International Journal of Methods in Psychiatric Research, 12(2), 85-91. https://doi.org/10.1002/mpr.145

Bickman, L., Kelley, S. D., Breda, C., de Andrade, A. R., & Riemer, M. (2011). Effects of routine feedback to clinicians on mental health outcomes of youths: Results of a randomized trial. Psychiatric Services, 62(12), 1423-1429. https://doi.org/10.1176/appi.ps.002052011

Brattland, H., Koksvik, J. M., Burkeland, O., Klöckner, C. A., Lara-Cabrera, M. L., Miller, S. D., Wampold, B., Ryum, T., & Iversen, V. C. (2019). Does the working alliance mediate the effect of routine outcome monitoring (ROM) and alliance feedback on psychotherapy outcomes? A secondary analysis from a randomized clinical trial. Journal of Counseling Psychology, 66(2), 234-246. https://doi.org/10.1037/cou0000320

Cao, J., Tanana, M., Imel, Z. E., Poitras, E., Atkins, D. C., & Srikumar, V. (2019). Observing dialogue in therapy: Categorizing and forecasting behavioral codes. https://arxiv.org/abs/1907.00326 https://doi.org/10.18653/v1/P19-1563

Cooper, M., & Norcross, J. C. (2016). A brief, multidimensional measure of clients' therapy preferences: The Cooper-Norcross Inventory of Preferences (C-NIP). International Journal of Clinical and Health Psychology, 16(1), 87-98. https://doi.org/10.1016/j.ijchp.2015.08.003

De Jong, K. Conijn, J. M., Gallagher, R. A. V., Reshetnikova, A. S., Heij, M., & Lutz, M. C. (2021). Using progress feedback to improve outcomes and reduce drop-out, treatment duration, and deterioration: A multilevel meta-analysis. Clinical Psychology Review, 85, 102002. https://doi.org/10.1016/j.cpr.2021.102002

De Jong, K., Timman, R., Hakkaart-Van Roijen, L., Vermeulen, P., Kooiman, K., Passchier, J., & Busschbach, J. Van. (2014). The effect of outcome monitoring feedback to clinicians and patients in short and long-term psychotherapy: A randomized controlled trial. Psychotherapy Research, 24(6), 629-639. https://doi.org/10.1080/10503307.2013.871079

De Jong, K., van Sluis, P., Nugter, M. A., Heiser, W. J., & Spinhoven, P. (2012). Understanding the differential impact of outcome monitoring: Therapist variables that moderate feedback effects in a randomized clinical trial. Psychotherapy Research, 22(4), 464-474. https://doi.org/10.1080/10503307.2012.673023

Evans, C., Carlyle, J.-A. (2021). Outcome measures and evaluation in counseling and psychotherapy. Sage.

Ewbank, M. P., Cummins, R., Tablan, V., Catarino, A., Buchholz, S., & Blackwell, A. D. (2021). Understanding the relationship between patient language and outcomes in internet-enabled cognitive behavioural therapy: A deep learning approach to automatic coding of session transcripts. Psychotherapy Research, 31(3), 300-312. https://doi.org/10.1080/10503307.2020.1788740

Farber, B. A. (2020). Disclosure, concealment, and dishonesty in psychotherapy: A clinically focused review. Journal of Clinical Psychology, 76(2), 251-257. https://doi.org/10.1002/jclp.22891

Flemotomos, N., Martinez, V. R., Chen, Z., Creed, T. A., Atkins, D. C., & Narayanan, S. (2021). Automated quality assessment of cognitive behavioral therapy sessions through highly contextualized language representations. PLoS ONE, 16(10), e0258639. https://doi.org/10.1371/journal.pone.0258639

Goldberg, S. B., Rousmaniere, T., Miller, S. D., Whipple, J., Nielsen, S. L., Hoyt, W. T., & Wampold, B. E. (2016). Do psychotherapists improve with time and experience? A longitudinal analysis of outcomes in a clinical setting. Journal of Counseling Psychology, 63(1), 1-11. https://doi.org/10.1037/cou0000131

Hannan, C., Lambert, M. J., Harmon, C., Nielsen, S. L., Smart, D. W., Shimokawa, K., & Sutton, S. W. (2005). A lab test and algorithms for identifying clients at risk for treatment failure. Journal of Clinical Psychology, 61(2), 155-163. https://doi.org/10.1002/jclp.20108

Hansen, N. B., Lambert, M. J., & Forman, E. M. (2002). The psychotherapy dose-response effect and its implications for treatment delivery services. Clinical Psychology: Science and Practice, 9(3), 329-343. https://doi.org/10.1093/clipsy.9.3.329

Hatfield, D., McCullough, L., Frantz, S. H. B., Krieger, K., Hatfi, D., McCullough, L., Frantz, S. H. B., & Krieger, K. (2010). Do we know when our clients get worse? An investigation of therapists' ability to detect negative client change. Clinical Psychology and Psychotherapy, 17(1), 25-32. https://doi.org/10.1002/cpp.656

Heimerl, F., Lohmann, S., Lange, S., & Ertl, T. (2014). Word Cloud Explorer: Text analytics based on word clouds. Paper presented at 47th Hawaii International Conference on System Sciences (pp. 1833-1842). https://doi.org/10.1109/HICSS.2014.231

Imel, Z. E., Pace, B. T., Soma, C. S., Tanana, M., Hirsch, T., Gibson, J., Georgiou, P., Narayanan, S., & Atkins, D. C. (2019). Design feasibility of an automated, machine-learning based feedback system for motivational interviewing. Psychotherapy. Advance online publication. https://doi.org/10.1037/pst0000221

Koole, S. L., & Tschacher, W. (2016). Synchrony in psychotherapy: A review and an integrative framework for the therapeutic alliance. Frontiers in Psychology, 7, 862. https://doi.org/10.3389/fpsyg.2016.00862

Kroenke, K., Spitzer, R. L., Williams, J. B. W., & Löwe, B. (2010). The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: A systematic review. General Hospital Psychiatry, 32(4), 345-359. https://doi.org/10.1016/j.genhosppsych.2010.03.006

Ladmanová, M., Řiháček, T., & Timuľák, L. (2022). Client-identified impacts of helpful and hindering events in psychotherapy: A qualitative meta-analysis. Psychotherapy Research, 32(6), 723-735. https://doi.org/10.1080/10503307.2021.2003885

Lambert, M. J. (2010). Prevention of treatment failure: The use of measuring, monitoring, and feedback in clinical practice. American Psychological Association. https://doi.org/10.1037/12141-000

Lambert, M. J. (2015). Progress feedback and the OQ-System: The past and the future. Psychotherapy, 52(4), 381-390. https://doi.org/10.1037/pst0000027

Loulová, Š. (2021). Klasifikační systém pro počítačové zpracování terapeutovy řeči v rámci individuálních psychoterapeutických sezení [Diplomová práce]. Masarykova univerzita. https://is.muni.cz/auth/th/f0ux5/Loulova_Diplomova_prace.pdf

Lutz, W., Rubel, J. A., Schwartz, B., Schilling, V., & Deisenhofer, A.-K. (2019). Towards integrating personalized feedback research into clinical practice: Development of the Trier Treatment Navigator (TTN). Behaviour Research and Therapy, 120, 103438. https://doi.org/10.1016/j.brat.2019.103438

Lyon, A. R., Lewis, C. C., Boyd, M. R., Hendrix, E., & Liu, F. (2016). Capabilities and characteristics of digital measurement feedback systems: Results from a comprehensive review. Adm Policy Ment Health, 43, 441-466. https://doi.org/10.1007/s10488-016-0719-4

Meier, S. T. (2015). Incorporating progress monitoring and outcome assessment into counseling and psychotherapy: A primer. Oxford University Press. https://doi.org/10.1093/med:psych/9780199356676.001.0001

Miller, S. D., Duncan, B. L., Sorrell, R., & Brown, G. S. (2005). The Partners for Change Outcome Management System. JCLP/In Session, 61(2), 199-208. https://doi.org/10.1002/jclp.20111

Miller, S. D., Hubble, M. A., Chow, D. L., & Seidel, J. A. (2013). The outcome of psychotherapy: Yesterday, today, and tomorrow. Psychotherapy, 50(1), 88-97. https://doi.org/10.1037/a0031097

Miller, S. D., Hubble, M. A., Chow, D., & Seidel, J. (2015). Beyond measures and monitoring: Realizing the potential of feedback-informed treatment. Psychotherapy, 52(4), 449-457. https://doi.org/10.1037/pst0000031

Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. https://doi.org/10.1561/9781601981516

Prescott, D. S., Measchalck, C. L., Miller, S. D. (Eds.). (2017). Feedback-informed treatment in clinical practice: Reaching for excellence. American Psychological Association. https://doi.org/10.1037/0000039-000

Rennie, D. L. (1994). Clients' deference in psychotherapy. Journal of Counseling Psychology, 41(4), 427-437. https://doi.org/10.1037/0022-0167.41.4.427

Řiháček, T., Elliott, R., Owen, J., Ladmanová, M., Coleman, J. J., & Bugatti, M. (2023). Session Reactions Scale-3: Initial psychometric evidence. Psychotherapy Research. Advance online publication. https://doi.org/10.1080/10503307.2023.2241983

Řiháček, T., & Matějka, P. (2021). Deep learning v psychoterapii: Strojová analýza nahrávek terapeutických sezení. E-psychologie, 15(3), 35-37. https://doi.org/10.29364/epsy.414

Shimokawa, K., Lambert, M. J., & Smart, D. W. (2010). Enhancing treatment outcome of patients at risk of treatment failure: Meta-analytic and mega-analytic review of a psychotherapy quality assurance system. Journal of Consulting and Clinical Psychology, 78(3), 298-311. https://doi.org/10.1037/a0019247

Solstad, S. M., Castonguay, L. G., & Moltu, C. (2019). Patients' experiences with routine outcome monitoring and clinical feedback systems: A systematic review and synthesis of qualitative empirical literature, Psychotherapy Research, 29(2), 157-170. https://doi.org/10.1080/10503307.2017.1326645

Straková, J., Straka, M., & Hajič, J. (2014). Open-source tools for morphology, lemmatization, POS tagging and named entity recognition. In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations (pp. 13-18). Association for Computational Linguistics. https://doi.org/10.3115/v1/P14-5003

Swift, J. K., & Greenberg, R. P. (2014). A treatment by disorder meta-analysis of dropout from psychotherapy. Journal of Psychotherapy Integration, 24(3), 193-207. https://doi.org/10.1037/a0037512

Walfish, S., McAlister, B., O'Donnell, P., & Lambert, M. J. (2012). An investigation of self-assessment bias in mental health providers. Psychological Reports, 110(2), 639-644. https://doi.org/10.2466/02.07.17.PR0.110.2.639-644

Widyassari, A. P., Rustad, S., Shidik, G. F., Noersasongko, E., Syukur, A., Affandy, A., & Setiadi, D. R. I. M. (2022). Review of automatic text summarization techniques & methods. Journal of King Saud University - Computer and Information Sciences, 34(4), 1029-1046. https://doi.org/10.1016/j.jksuci.2020.05.006

Zhang, J., Filbin, R., Morrison, C., Weiser, J., Danescu-Niculescu-Mizil, C. (2019). Finding your voice: The linguistic development of mental health counselors. https://arxiv.org/abs/1906.07194 https://doi.org/10.18653/v1/P19-1089

Metriky

0

Crossref logo

0


366

Views

285

PDF views