Reducing Self-Stigma Among Individuals with History of Childhood Maltreatment: a Cross-Cultural Lens

Overview

Individuals who report experiencing any kind of abuse during childhood report shame and self-blame, often leading to self-stigma and a reluctance to reveal their experiences and seek help. Such stigma may aggravate the mental health consequences of child maltreatment (CM). The investigators hypothesize that: 1. The brief video-based intervention will have the immediate and repeated effect of reducing self-stigma among CM survivors compared with the control condition. 2. The brief video-based intervention will increase seeking treatment compared with the control condition. 3. The brief video-based intervention will show similar effects in reducing self-stigma across multiple countries.

Prior research suggests that social contact-based interventions are the most efficient way of reducing stigma. This study aims to address self-stigma and empower individuals who self-reported experiencing any kind of abuse during childhood and increase their openness to seeking help, if needed. Four hundred participants with self-reported experience of any kind of childhood abuse will be recruited to participate in a Randomized Controlled Trial (RCT) testing the efficacy of the intervention. Participants will be randomized into one of two arms: 1) A 2-minute video intervention in which a CM survivor (presented by an actor) shares their personal CM experience and describes how they were able to overcome feelings of shame and self-blame to seek mental health care; or 2) A 2-minute control video using the same actor, but without a personal narrative of CM experience. Both videos will be preceded by and immediately followed by questionnaires assessing self-stigma and openness to seeking treatment. An additional assessment of emotional engagement will be added immediately following intervention delivery. Following the intervention, there will be a 30- day follow-up to examine potential long-term effects. The results will be analyzed alongside results from parallel protocols being conducted by partner sites in other countries (Switzerland, Sweden, Japan, Peru, India, Australia, Turkey, South Africa, and Israel). Each site will conduct the study under their own university's purview and with their own protocol, and only deidentified data will be shared for analysis. All study procedures will be conducted remotely via CloudReseach and Mechanical Turk, which is a crowdsourcing platform. The study survey will be hosted by Qualtrics.