Understanding WhatsApp Disengagement: A Communication Privacy Management Perspective on Group Exit
Abstract
This study investigated why individuals leave WhatsApp groups, drawing on Communication Privacy Management (CPM) Theory through a quantitative research design. Using questionnaires and SPSS Version 31, data were analysed via chi-square tests, independent samples t-tests, and logistic regression. The most frequently cited reasons for leaving groups were information overload (68%), excessive voice messages (54%), and motivational or quotation content (49%). Communication style also played a notable role, with harsh, offensive, or emotionally hurtful language reported as damaging to participants' well-being and a contributing factor to group exit. Statistical analyses revealed several significant findings. Chi-square results demonstrated a significant association between age and privacy concerns (χ² = 12.34, p < .01), while independent samples t-tests showed that females reported greater privacy concerns than males (t = 2.15, p < .05). Logistic regression confirmed that both privacy concerns (β = 0.42, p < .01) and interpersonal conflict (β = 0.37, p < .05) meaningfully increased the likelihood of departure. Overall, the study found that privacy boundary violations, intensified conflict, personal attacks, and inappropriate language were strong drivers of disengagement. The findings underscore the importance of respectful communication, clearly defined group purposes, and effective moderation. Platform-level features supporting user autonomy were also highlighted as essential. Future research directions include cross-platform comparisons, intervention strategies to minimise unnecessary exits, and exploration of cultural differences in digital privacy management. The study contributes valuable insights into the social and psychological dynamics shaping participation in digital group communication.
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References
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