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Record W4388662282 · doi:10.1080/10503307.2023.2280240

Predicting resistance management skill from psychotherapy experience, intellectual humility and emotion regulation

2023· article· en· W4388662282 on OpenAlexaff
Alyssa A. Di Bartolomeo, Udi Alter, David A. Olson, Max B. Cooper, Tali Boritz, Henny A. Westra

Bibliographic record

VenuePsychotherapy Research · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyPsychotherapistHumilityResistance (ecology)CognitionClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Objective Resistance management in psychotherapy remains a foundational skill that is associated with positive client outcomes (Westra, H. A., & Norouzian, N. (2018). Using motivational interviewing to manage process markers of ambivalence and resistance in cognitive behavioral therapy. Cognitive Therapy and Research, 42(2), 193–203). However, little is known about which therapist characteristics contribute to successful management of resistance. Research has suggested that psychotherapy performance does not improve with experience (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), that psychotherapists lack humility (Macdonald, J., & Mellor-Clark, J. (2015). Correcting psychotherapists’ blindsidedness: Formal feedback as a means of overcoming the natural limitations of therapists. Clinical Psychology & Psychotherapy, 22(3), 249–257), and that difficult therapeutic moments may dysregulate therapist emotions (Muran, J. C., & Eubanks, C. F. (2020). Therapist performance under pressure: Negotiating emotion, difference, and rupture. American Psychological Association). This study aimed to 1) identify whether psychotherapy experience (i.e., training versus no training and number of years of psychotherapy experience) was associated with resistance management skill, and 2) identify whether humility and difficulties regulating emotions among trained individuals were each associated with resistance management.Method: A sample of 76 trained and 98 untrained participants were recruited for the present study. All participants completed the Comprehensive Intellectual Humility Scale (CIHS, Krumrei-Mancuso, E. J., & Rouse, S. V. (2016). The development and validation of the comprehensive intellectual humility scale. Journal of Personality Assessment, 98(2), 209–221), the Difficulties in Emotion Regulation Scale (DERS; Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral Assessment, 26(1), 41–54), and the Resistance Vignette Task (RVT; Westra, H. A., Nourazian, N., Poulin, L., Hara, K., Coyne, A., Constantino, M. J., Olson, D., & Antony, M. M. (2021). Testing a deliberate practice workshop for developing appropriate responsivity to resistance markers: A randomized clinical trial. Psychotherapy, 58, 175–185 ) which was used to assess resistance management skill.Results: Trained individuals performed significantly better on resistance management than untrained individuals; however, years of experience within the trained sample were not associated with resistance management. Conversely, lower humility and greater difficulties regulating emotions were each associated with significantly poorer resistance management in trained individuals.Conclusion: These findings suggest the possibility of improving training to focus on key skills, like resistance management, through supporting humility and emotion regulation in training, as opposed to simply acquiring more experience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.455
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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