ABSTRACT
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.
ABSTRACT
Gene regulatory networks are shaped by selection for advantageous gene expression patterns. Can we use this fact to predict and explain the structure and properties of gene regulatory networks? Here we address this question with evolutionary simulations of small (two to four genes) transcriptional regulatory networks. Each modeled network is tested for the frequency with which it evolves to produce a bimodal spatial expression pattern of a target gene (the output), in response to a linear trigger gradient (the input). By including network features such as the organisation of binding sites that do not evolve in the model, we can compare the relative chances of evolutionary success between networks differing only in these features. Specifically, we show that networks with competitive binding sites (where binding of one transcription factor excludes another) are more likely to evolve bimodal patterns of gene repression than are networks with independent binding sites (where binding of multiple transcription factors can occur simultaneously). These predictions have implications for the likely structure of gene regulatory networks carrying out bimodal (including bistable) gene expression functions in vivo. The capacity to predict the evolution of structure-function relationships in gene regulatory networks is constrained by gaps in current understanding such as the unknown prior probabilities of the network features, and the quantitative nature of the molecular interactions involved in gene expression. Methods for the circumvention of these constraints, and the potential of the evolutionary modeling approach, are discussed.
Subject(s)
Evolution, Molecular , Genes, Regulator , Binding Sites , Models, Theoretical , Transcription Factors/metabolismABSTRACT
Feed forward loops (FFLs) are gene regulatory network motifs. They exist in different types, defined by the signs of the effects of genes in the motif on one another. We examine 36 feed forward loops in Escherichia coli, using evolutionary simulations to predict the forms of FFL expected to evolve to generate the pattern of expression of the output gene. These predictions are tested using likelihood ratios, comparing likelihoods of the observed FFL structures with their likelihoods under null models. The very high likelihood ratios generated, of over 10(11), suggest that evolutionary simulation is a valuable component in the explanation of FFL structure.