A Content Validity Study of AIMIT (Assessing Interpersonal Motivation in Transcripts). (20th May 2015) - Fassone, Giovanni
Abstract : Multi‐motivational theories of human relatedness state that different motivational systems with an evolutionary basis modulate interpersonal relationships. The reliable assessment of their dynamics may usefully inform the understanding of the therapeutic relationship. The coding system of the Assessing Interpersonal Motivation in Transcripts (AIMIT) allows to identify in the clinical the activity of five main interpersonal motivational systems (IMSs): attachment (care‐seeking), caregiving, ranking, sexuality and peer cooperation. To assess whether the criteria currently used to score the AIMIT are consistently correlated with the conceptual formulation of the interpersonal multi‐motivational theory, two different studies were designed. Study 1: Content validity as assessed by highly qualified independent raters. Study 2: Content validity as assessed by unqualified raters. Results of study 1 show that out of the total 60 AIMIT verbal criteria, 52 (86.7%) met the required minimum degree of correspondence. The average semantic correspondence scores between these items and the related IMSs were quite good (overall mean: 3.74, standard deviation: 0.61). In study 2, a group of 20 naïve raters had to identify each prevalent motivation (IMS) in a random sequence of 1000 utterances drawn from therapy sessions. Cohen's Kappa coefficient was calculated for each rater with reference to each IMS and then calculated the average Kappa for all raters for each IMS. All average Kappa values were satisfactory (>0.60) and ranged between 0.63 (ranking system) and 0.83 (sexuality system). Data confirmed the overall soundness of AIMIT's theoretical–applicative approach. Results are discussed, corroborating the hypothesis that the AIMIT possesses the required criteria for content validity. Copyright © 2015 John Wiley & Sons, Ltd. Key Practitioner Message: Assessing Interpersonal Motivations in psychotherapy transcripts as a useful tool to better understand links between motivational systems and intersubjectivity. A step forward in the knowledge of evolutionary cognitivism and a contribution to the bio‐psycho‐social model of human relatedness and interpersonal neurobiology.