Abstract: When faced with challenging problems, individuals need to weigh the pros and cons to decide whether and from whom to seek help actively in order to obtain assistance from others. This help-seeking decision-making constitutes a crucial foundation for human cooperation and adaptation. However, fragmented and non-quantitative research perspectives and methods in previous studies have hindered the construction of a systematic knowledge framework and limited the quantitative analysis of the trade-offs and integration processes of core cognitive components. Consequently, the cognitive-computational and neural mechanisms underlying help-seeking decisions remain poorly understood. From an integrated and quantitative perspective, this review proposes a cognitive-computational framework for studying help-seeking decision-making: (1) reviewing theoretical and empirical studies to distill core cognitive components, and identifying three key stages in help-seeking decision-making: decision generation, dynamic adjustment, and the moderating role of dyadic interaction features; (2) extending and applying rational and bounded rationality decision theories to help-seeking decision-making study, thereby constructing a systematic set of candidate cognitive-computational model hypotheses; (3) outlining critical scientific questions and methodological prospects for future study on the mechanisms of help-seeking decision-making.

Key words: help-seeking decision-making, cognitive-computational framework, decision generation, dynamic adjustment, dyadic interaction features