Beyond Judgment: Exploring Large Language Models as Non-Judgmental Support for Maternal Mental Health

TL;DR

This study explores how mothers use large language models as non-judgmental tools for emotional support and reassurance, revealing their preferences and social context influences in maternal mental health support.

Contribution

It provides empirical insights into the role of LLMs as low-risk, judgment-free resources for mothers seeking emotional and informational support.

Findings

Mothers use LLMs to seek reassurance about childcare decisions.

Many mothers prefer LLMs to avoid social judgment and consequences.

Over half value human warmth more, but some rely on LLMs to avoid judgment.

Abstract

In the age of Large Language Models (LLMs), much work has already been done on how LLMs support medication advice and serve as information providers; however, how mothers use these tools for emotional and informational support to avoid social judgment remains underexplored. This study conducted a 10-day mixed-methods exploratory survey ($N=107$) to investigate how mothers use LLMs as a non-judgmental resource for emotional support and regulation, and for situational reassurance. Our findings show that mothers are asking LLMs various questions about childcare to reassure themselves and avoid judgment, particularly around childcare decisions, maternal guilt, and late-night caregiving. Open-ended responses also show that mothers are comfortable with LLMs because they do not have to think about social consequences or judgment. Although mothers use LLMs for quick information or reassurance to avoid judgment, over half of the participants value human warmth more than LLMs; however, a significant minority, especially those in joint families, consider LLMs to avoid human judgment. These findings help understand how LLMs can be framed as low-risk interaction support rather than a replacement for human support, and highlight the role of social context in shaping emotional technology use.