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A text mining approach to characterizing interpersonal stress among individuals with a nonsuicidal self-injury history

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Abstract

Interpersonal difficulties are salient among those with a history of NSSI, preceding NSSI urges and behaviors. Yet, limited research has focused on identifying which aspects of interpersonal stress may confer risk for NSSI. The current study aimed to leverage data from two samples (combined n = 206; n = 114 with NSSI history) of participant-driven interviews regarding a recent interpersonal stressor to enhance the field’s knowledge of interpersonal difficulties in relation to NSSI risk. Using topic modeling to extract thematic information, analyses identified four main topics: daily difficulties; family members; adjectives/verbal fillers; and friendship/romantic relationships. Relationships between the topics and three predictors (i.e., NSSI history, emotion dysregulation, sample) were examined. In one sample, the proportion of ‘adjectives/verbal fillers’ was greater for participants with a NSSI history and at higher levels of emotion dysregulation. Across samples, for participants with a NSSI history, ‘adjectives/verbal fillers’ and ‘friendship/romantic partners’ increased with levels of emotion dysregulation. Findings highlight a greater use of adjectives and verbal fillers among individuals with a history of NSSI and higher levels of emotion dysregulation. This pattern of language may serve as an indicator of a specific aspect of emotion regulation difficulties that confers risk for NSSI.

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Data availability

The datasets analyzed as part of the current study are available from the corresponding author upon reasonable request.

Notes

  1. We used the stop word list from the NLTK Python text mining library (Bird et al., 2009), although negation words (“no”, “nor”, “not”, “don’t”, “hasn’t”, “haven’t”, “isn’t”, “shouldn’t”, “wasn’t”, “weren’t”, “won’t”, “wouldn’t”) were not removed from the responses.

  2. Because some words are highly probable across all or several topics, word probabilities alone are not always sufficient to interpret a topic. Term scores emphasize words that uniquely represent each topic by downweighting words that are highly probable across many topics.

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Acknowledgements

This project was partially supported by 1F31MH107156-01A1 awarded to Brooke A. Ammerman.

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  1. Kenneth Tyler Wilcox

    Present address: Department of Psychology, Cornell University, Ithaca, NY, USA

Authors and Affiliations

  1. Department of Psychology, University of Notre Dame, Notre Dame, IN, USA

    Kenneth Tyler Wilcox, Ross Jacobucci & Brooke A. Ammerman

  2. University of Massachusetts, Amherst, MA, USA

    Katherine L. Dixon-Gordon & Elinor E. Waite

  3. Department of Psychology, Temple University, Philadelphia, PA, USA

    Michael S. McCloskey

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Correspondence to Brooke A. Ammerman.

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Wilcox, K.T., Jacobucci, R., Dixon-Gordon, K.L. et al. A text mining approach to characterizing interpersonal stress among individuals with a nonsuicidal self-injury history. Curr Psychol 43, 10075–10085 (2024). https://doi.org/10.1007/s12144-023-05056-4

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