Article, 2024

Measuring narrative identity: rater coding versus questionnaire-based approaches

Memory, ISSN 0965-8211, 10.1080/09658211.2024.2359503

Contributors

Gehrt T.B. 0000-0002-9492-9448 (Corresponding author) [1] [2] Nielsen N.P. 0000-0001-8320-2991 [2] Hoyle R.H. [3] Rubin D.C. 0000-0003-1756-3531 [2] [3] Berntsen D. 0000-0001-5941-314X [2]

Affiliations

  1. [1] Prehospital Emergency Medical Services
  2. [NORA names: Other Hospitals; Hospital; Denmark; Europe, EU; Nordic; OECD];
  3. [2] Aarhus University
  4. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD];
  5. [3] Duke University
  6. [NORA names: United States; America, North; OECD]

Abstract

Narrative identity–how individuals narrate their lived and remembered past–is usually assessed via independent rater coding, but new methods relying on self-report have been introduced. To test the assumption that different methods assess aspects of the same underlying construct, studies measuring similar components of narrative identity with different methods are needed. However, such studies are surprisingly rare. To begin to fill this gap, the present study compared the narrative variables, temporal coherence, causal coherence, and thematic coherence, measured via rater coding of participants’ self-generated narratives of the remembered past and via subscales of the self-report measure Awareness of Narrative Identity Questionnaire (ANIQ). The results showed that the ANIQ subscales did not correlate significantly with their corresponding rater-coded dimension, and that the ANIQ subscales were generally unrelated to the other rater-coded dimensions. Furthermore, an exploratory factor analysis demonstrated that the ANIQ subscales loaded together on a factor that did not include any rater-coded variables. The findings suggest that the narrative variables share little empirical overlap when assessed via the ANIQ and rater coding of self-generated narratives.

Keywords

Narrative identity, autobiographical memory, rater coding, self-report

Data Provider: Elsevier