000			01984nam a2200241Ia 4500
008			180926s2016 xx 000 0 und d
040			_cMANILA TYTANA COLLEGES LIBRARY
100			_aCan, Dogan.
245		0	_aIt sounds like : _ba natural language processing approach to detecting counselor reflections in motivational interviewing / _cDogan Can, Rebeca A. Marín, Panayiotis G. Georgiou, Zac E. Imel, David C. Atkins, Shrikanth S. Narayanan
260			_cApril 2016
336			_atext
337			_aunmediated
338			_avolume
440			_n63 : 3, page 343-350 _aJournal of Counseling Psychology
520			_aThe dissemination and evaluation of evidence-based behavioral treatments for substance abuse problems rely on the evaluation of counselor interventions. In Motivational Interviewing (MI), a treatment that directs the therapist to utilize a particular linguistic style, proficiency is assessed via behavioral coding-a time consuming, nontechnological approach. Natural language processing techniques have the potential to scale up the evaluation of behavioral treatments such as MI. We present a novel computational approach to assessing components of MI, focusing on 1 specific counselor behavior-reflections, which are believed to be a critical MI ingredient. Using 57 sessions from 3 MI clinical trials, we automatically detected counselor reflections in a maximum entropy Markov modeling framework using the raw linguistic data derived from session transcripts. We achieved 93% recall, 90% specificity, and 73% precision. Results provide insight into the linguistic information used by coders to make ratings and demonstrate the feasibility of new computational approaches to scaling up the evaluation of behavioral treatments.
521			_aPsychology.
650			_aDissemination.
650			_aFidelity assessment.
650			_aMotivational interviewing.
650			_aNatural language processing.
942			_2lcc _cA
998			_c82495 _d140858
999			_c79037 _d79037