The longitudinal effect of social recognition on PTSD symptomatology and vice versa: Evidence from a population-based study

P.G. van der Velden*, Marije Oudejans, J.W.M. Das, M.W.G. Bosmans, Andreas Maercker

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    2 Citations (Scopus)

    Abstract

    A specific type of social support after potentially traumatic events is called “social recognition”. It is the acknowledgement or validation of event‐related thoughts, behavior, and feelings by the individual or others. It consists of positive individual or societal reactions that recognize and acknowledge victims’ traumatic experiences and difficulties. Current studies suggest that social recognition protects against the development of PTSD symptomatology, but there is a lack of population-based studies assessing the longitudinal interplay between PTSD symptomatology and social recognition. For this purpose, we conducted a longitudinal study using the Dutch LISS panel, based on a random sample of the Dutch population. Structural equation modeling showed that among recently affected adults (0–2 months ago), those with relatively higher levels of social recognition had lower levels of PTSD symptomatology 6 months later. Victims with high levels of PTSD symptomatology at baseline received less social recognition 6 months later. On the intermediate term (affected 5–12 months ago), baseline social recognition was no longer predictive of PTSD symptoms 6 months later, in contrast to PTSD symptomatology predicting lack of social recognition. In sum, PTSD symptom levels eroded social recognition on the short and intermediate term, while the protective role of social recognition was limited to the short term.
    Original languageEnglish
    Pages (from-to)287-294
    JournalPsychiatry Research
    Volume279
    Publication statusPublished - 2019

    Keywords

    • PTSD
    • Social recognition
    • Acknowledgement
    • Violence
    • Accidents
    • Theft
    • Structural equation modeling

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