Exploring the relationship between reflective function and recovery process of borderline users on Instagram: a multimethod study through computerized and thematic analysis

The use of computerized stylistic measures, which allows to evaluate psychological states from linguistic markers (Mergenthaler & Bucci, 1999), is increasing in clinical psychology research (Mariani et al., 2013). As for our knowledge, despite the extensive research on offline narratives of borderline patients (BPD) (Bateman & Fonagy, 2004), no studies on reflective functioning (RF) in online social networks have been conducted using computerized language style analysis. Furthermore, while there is an increasing interest in the recovery-oriented approach (Maone & D'avanzo, 2015), there are few studies on the experience of recovery in BPD (Ng, Bourke & Grenyer, 2016). This study aims to evaluate the reflective style in narratives shared online by borderline users and to investigate its relation to the users’ recovery process. The participants were 14 active Instagram users (Hu et al., 2014) with a self-reported diagnosis of BPD. Two groups of users were distinguished on the basis of the hashtags #BPD and #BPDrecovery. Seventy randomized narratives were extracted from users accounts, 35 in each group. A multi-method approach was adopted: 1) computerized reflective functioning (CRF) (Fertuck et al., 2012), a stylistic analysis of RF that identifies RF related lexical markers from transcribed or written text 2) a thematic analysis of recovery processes by using the theoretical framework CHIME (Leamy et al., 2011), which identifies five recovery processes of different complexity (e.g. hope and optimism, meaning and purpose, etc.). The results indicated that the narratives of the #BPDrecovery group were significantly more reflective (p=0.02) than those of the #BPD group. Moreover, the #BPDrecovery group presented more advanced recovery processes than the #BPD group. Overall, these results suggest that a multi-method analysis approach may allow a more thorough understanding of the relationship between RF and recovery in an online setting.