Evidence map›Paper›PMID 41960784›Full record

ArticleJournal of medical Internet research2026

Digital Discourse, Secondary Victimization, and Psychological Harm: Mixed-Methods Analysis of System Justification in the #MeToo Movement.

Harsh Parekh, Shriya Thakkar, Paras Bhatt, Patricia Akello

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Harsh Parekh *Paul H. Chook Department of Information Systems and Statistics, Zicklin School of Business, Baruch College, City University of New York, New York, NY, United States.ORCID http://orcid.org/0000-0002-3956-2401
Shriya Thakkar *Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, 950 New Hampshire Avenue, Washington DC, DC, 20052, United States, +1 (202) 994-7400.ORCID http://orcid.org/0000-0003-0446-6513
Paras BhattDepartment of Information Systems, Supply Chain & Analytics, College of Business, The University of Alabama in Huntsville, Huntsville, AL, United States.ORCID http://orcid.org/0000-0001-8225-7157
Patricia AkelloDepartment of MIS and Cybersecurity, College of Business, University of Montana, Missoula, MT, United States.ORCID http://orcid.org/0000-0002-0149-2225

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The #MeToo movement, initiated in 2006 and amplified on social media in 2017, mobilized women worldwide to share experiences of sexual harassment and assault online. While the movement increased awareness, it also revealed deep social divisions in digital spaces. Supportive discussions promoted solidarity and healing, whereas antagonistic responses reinforced backlash and secondary victimization. In India, the Indian Entertainment Industry (IEI) became a focal point where survivors' disclosures highlighted structural gender inequalities. These polarized reactions function as digital-health signals, reflecting stigma, psychosocial distress, and conditions that shape women's safety and mental well-being. Examining these narratives as indicators of public health risk helps identify patterns of structural inequity and secondary mental health burdens among survivors. Objective: This study examined online discourse surrounding #MeToo to identify forms of system-justifying narratives on social media and to assess how #MeTooIndia exposed institutional inequities within the IEI. Methods: This mixed-methods study comprised 2 components. In study 1, natural language processing was applied to analyze global #MeToo Twitter (subsequently rebranded X) discourse. From an initial corpus of 350,000 tweets, 205,082 were preprocessed, and sentiment and stance detection analysis identified 18,416 tweets expressing negative attitudes toward the movement. Latent Dirichlet allocation topic modeling extracted 22 topics, 12 of which aligned with system-justification categories, revealing distinct lexical and semantic patterns related to gender, institutional, and power dynamics. Two trained coders manually annotated a subsample to ensure conceptual clarity and interrater reliability. Study 2 involved qualitative, semistructured interviews with 20 academic experts in film, gender, and media studies to gather opinions on how #MeTooIndia influenced institutional discourse in the IEI and how these dynamics translate into digital and mental health risks. Results: Analysis of #MeToo Twitter discourse in study 1 identified 4 primary forms of system justification: by gender, by the institutional system, by backlash, and by victim-blaming. Gender and institutional system justifications were the most prevalent. Study 2 reinforced these findings, revealing how experts perceived #MeTooIndia as both empowering and constrained by entrenched institutional and cultural barriers. Together, our findings highlight the dual function of social media in promoting collective advocacy while reproducing conditions linked to gender-based violence, psychological stress, and reduced help-seeking-key digital and mental health concerns. Conclusions: This mixed-methods study reveals that digital discourse surrounding #MeToo often sustains existing gender and institutional hierarchies rather than dismantling them. Across Twitter data and expert interviews, gender and institutional system justifications emerged as dominant narratives, highlighting how online spaces can reinforce structural inequities while appearing progressive. Although #MeToo amplified visibility and awareness, its potential for lasting institutional change remains limited. These findings underscore the need for trauma-informed digital governance, public health recognition of online hostility as a psychosocial risk, and frameworks that situate digital activism to institutional reforms that support safety and mental well-being.

Indexed as

Crime VictimsSexual HarassmentSocial MediaDigital MediaFemaleHumansIndiaMedia Exposuregenderharassmentinequitiesmental healthmixed methods

Identifiers

PMID41960784
PMCPMC13067243

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.