求助决策研究的认知计算框架

doi:10.3724/SP.J.1042.2026.1606

摘要/Abstract

摘要： 面对难以解决的问题时, 个体需要权衡利弊决定是否或向谁主动求助以获得他人帮助。这一求助决策是人类合作和适应的重要基础。然而, 以往碎片化、非定量化的研究视角与方法不利于系统性知识体系的构建, 亦难以定量解析核心认知成分的权衡和整合过程, 因此求助决策的认知计算与神经机制至今仍不清晰。本文应用整合与量化的视角, 提出求助决策研究的认知计算框架: (1)梳理理论与实证研究, 提炼核心认知成分, 提出决策的产生、动态调整和互动双方特征的调节这三个求助决策研究的关键环节; (2)将理性和有限理性决策理论深化拓展并应用于求助决策研究, 构建一套系统的候选认知计算模型假设; (3)提出未来求助决策机制研究的关键科学问题与研究方法展望。

关键词: 求助决策, 认知计算框架, 决策产生, 动态调整, 互动双方特征

Abstract: When faced with challenging problems, individuals need to weigh the pros and cons to decide whether and from whom to seek help in order to obtain assistance from others. Such 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 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.
First, this review synthesizes previous theoretical and empirical studies to address the fragmentation of existing research on help-seeking. Although previous studies have identified a variety of factors related to help seeking, these factors have often been examined separately, making it difficult to construct a systematic account of help-seeking decision-making. To address this issue, the present review summarizes three stages of the help-seeking process—need perception, interpersonal request, and reciprocal exchange—and distills three corresponding core cognitive components: perceived help-seeking benefit, anticipated social rejection cost, and anticipated reciprocity anxiety cost. On this basis, the review further proposes three key aspects for studying help-seeking decision-making: decision generation, dynamic adjustment, and the moderating role of dyadic interaction features.
Second, this review further extends and applies rational and bounded rationality decision theories to the study of help-seeking decision-making, thereby constructing a systematic set of candidate cognitive-computational model hypotheses based on the three key aspects. These model hypotheses include rational models, bounded rational heuristic models, and hybrid models combining the two. Rational models assume that individuals weigh and integrate different cognitive components, including perceived benefits and anticipated costs, in a relatively systematic manner, so that help-seeking decisions are generated and dynamically adjusted through value-based trade-offs, integration, and social learning. In contrast, bounded rational heuristic models assume that, under conditions such as uncertainty, limited information, and cognitive constraints, individuals may actively ignore part of the available information and rely on simpler decision rules or more limited processing strategies, thereby making decisions more quickly and with lower cognitive demands, and in some cases even more accurately. In addition, this review proposes hybrid models that combine rational and bounded rational heuristic strategies, thereby extending existing accounts of how help-seeking strategies may shift between these two modes and suggesting that rational and bounded rational heuristic processes are better understood not as a static dichotomy, but as dynamically interacting processes within individuals.
Third, based on the proposed cognitive-computational model hypotheses, this review outlines key scientific questions and methodological prospects for future research on the cognitive-computational and neural mechanisms underlying help-seeking decision-making. Future research needs to clarify when individuals rely on rational or bounded rational heuristic strategies, how core cognitive components are represented, weighed, and integrated to generate and adjust help-seeking decisions, and how dyadic interaction features and other individual difference factors shape these processes. Methodologically, future studies should develop interactive paradigms that can repeatedly elicit and quantitatively measure help-seeking decisions, while collecting behavioral data to test, compare, and refine rational models, bounded rational heuristic models, and hybrid models, and to combine computational modeling with neuroimaging methods such as fMRI, EEG, and MEG to reveal the cognitive-computational and neural mechanisms underlying help-seeking decision-making. In addition, future studies could incorporate relevant individual-difference indicators, thereby providing a quantitative basis for the precise identification of related problems and for targeted intervention.
Overall, this review addresses the fragmentation and non-quantitative nature of previous help-seeking research by proposing an integrated cognitive-computational framework. It summarizes three stages of the help-seeking process, distills the corresponding core cognitive components, constructs a systematic set of candidate cognitive-computational model hypotheses, and outlines key scientific questions and methodological prospects for future research. Together, these contributions provide a foundation for future research on the cognitive-computational and neural mechanisms underlying help-seeking decision-making and related domains.

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

中图分类号:

B849: C91

罗浩诚, 杜伟, 魏琏厅, 周晓林, 高晓雪. (2026). 求助决策研究的认知计算框架. 心理科学进展 , 34(9), 1606-1628.

LUO Haocheng, DU Wei, WEI Lianting, ZHOU Xiaolin, GAO Xiaoxue. (2026). A cognitive-computational framework for studying help-seeking decision-making. Advances in Psychological Science, 34(9), 1606-1628.

参考文献

[1] 江光荣, 王铭. (2003). 大学生心理求助行为研究.中国临床心理学杂志, 11(3), 180-184.
[2] Adams J. S.(1965). Inequity in social exchange. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 2, pp. 267-299). New York: Academic Press.
[3] Anvari F., Alsalti T., Oehler L. A., Hussey I., Elson M., & Arslan R. C. (2025). Defragmenting psychology.Nature Human Behaviour, 9(5), 836-839.
[4] Bang D., Moran R., Daw N. D., & Fleming S. M. (2022). Neurocomputational mechanisms of confidence in self and others.Nature Communications, 13(1), 4238.
[5] Bierhoff H.-W. (2002). Prosocial behavior. Psychology Press..
[6] Brehm J. W.(1966). A theory of psychological reactance. Academic Press..
[7] Brehm, J. W. (1989). Psychological reactance: Theory and applications.Advances in Consumer Research, 16(1), 72-75.
[8] Brooks A. W., Gino F., & Schweitzer M. E. (2015). Smart people ask for (my) advice: Seeking advice boosts perceptions of competence.Management Science, 61(6), 1421-1435.
[9] Carnevale J. B., Huang L., Vincent L. C., Farmer S., & Wang L. (2021). Better to give than to receive (or seek) help? The interpersonal dynamics of maintaining a reputation for creativity.Organizational Behavior and Human Decision Processes, 167, 144-156.
[10] Cassidy, J. (2000). Adult romantic attachments: A developmental perspective on individual differences.Review of General Psychology, 4(2), 111-131.
[11] Cleavenger D., Gardner W. L., & Mhatre K. (2007). Help-seeking: Testing the effects of task interdependence and normativeness on employees’ propensity to seek help.Journal of Business and Psychology, 21(3), 331-359.
[12] Cleavenger, D. J., & Munyon, T. P. (2015). Overcoming the help-seeker’s dilemma: How computer-mediated systems encourage employee help-seeking initiation.Organization Studies, 36(2), 221-240.
[13] Clement S., Schauman O., Graham T., Maggioni F., Evans- Lacko S., Bezborodovs N., … Thornicroft G. (2015). What is the impact of mental health-related stigma on help- seeking? A systematic review of quantitative and qualitative studies.Psychological Medicine, 45(1), 11-27.
[14] Cohen J. D., Daw N., Engelhardt B., Hasson U., Li K., Niv Y., … Willke T. L. (2017). Computational approaches to fMRI analysis.Nature Neuroscience, 20(3), 304-313.
[15] Cox J. A., Trapp M. M., & McLean S. (2025). Gender differences in adolescents’ help-seeking behaviours and intentions for psychosocial problems in led outdoor activities.Journal of Adventure Education and Outdoor Learning, 25(3), 668-678.
[16] Crocker J., Canevello A., & Brown A. A. (2017). Social motivation: Costs and benefits of selfishness and otherishness.Annual Review of Psychology, 68, 299-325.
[17] Crockett, M. J. (2016). How formal models can illuminate mechanisms of moral judgment and decision making.Current Directions in Psychological Science, 25(2), 85-90.
[18] Cushman, F. (2024). Computational social psychology.Annual Review of Psychology, 75, 625-652.
[19] Davidai, S. (2025). Going at it alone: Zero-sum beliefs inhibit help-seeking.Journal of Experimental Social Psychology, 117, 104714.
[20] Davison K., Malmberg L. -E., & Sylva K. (2023). Academic help-seeking interactions in the classroom: A microlongitudinal study.British Journal of Educational Psychology, 93(1), 33-55.
[21] Daw N. D., Niv Y., & Dayan P. (2005). Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control.Nature Neuroscience, 8(12), 1704-1711.
[22] DePaulo, B. M., & Fisher, J. D. (1980). The costs of asking for help.Basic and Applied Social Psychology, 1(1), 23-35.
[23] Doll C. M., Michel C., Rosen M., Osman N., Schimmelmann B. G., & Schultze-Lutter F. (2021). Predictors of help-seeking behaviour in people with mental health problems: A 3-year prospective community study.BMC Psychiatry, 21(1), 432.
[24] Fan, Y. -H., & Lin, T. -J. (2023). Identifying university students’ online academic help-seeking patterns and their role in Internet self-efficacy.The Internet and Higher Education, 56, 100893.
[25] Feher da Silva C., Lombardi G., Edelson M., & Hare T. A. (2023). Rethinking model-based and model-free influences on mental effort and striatal prediction errors.Nature Human Behaviour, 7(6), 956-969.
[26] Fehr, E., & Fischbacher, U. (2003). The nature of human altruism.Nature, 425(6960), 785-791.
[27] Fisher J. D., Nadler A., & Whitcher-Alagna S. (1982). Recipient reactions to aid.Psychological Bulletin, 91(1), 27-54.
[28] Flynn, F., & Lake, V. (2008). If you need help, just ask: Underestimating compliance with direct requests for help.Journal of Personality and Social Psychology, 95(1), 128-143.
[29] Flynn F. J., Reagans R. E., Amanatullah E. T., & Ames D. R. (2006). Helping one's way to the top: Self-monitors achieve status by helping others and knowing who helps whom.Journal of Personality and Social Psychology, 91(6), 1123-1137.
[30] Fong C. J., Gonzales C., Hill-Troglin Cox C., & Shinn H. B. (2023). Academic help-seeking and achievement of postsecondary students: A meta-analytic investigation.Journal of Educational Psychology, 115(1), 1-21.
[31] Fornari L., Ioumpa K., Nostro A. D., Evans N. J., De Angelis L., Speer S. P. H., … Gazzola V. (2023). Neuro-computational mechanisms and individual biases in action-outcome learning under moral conflict.Nature Communications, 14(1), 1218.
[32] Friedman A., Carmeli A., & Dutton J. E. (2018). When does respectful engagement with one's supervisor foster help-seeking behaviors and performance?Journal of Vocational Behavior, 104, 184-198.
[33] Frolichs K. M. M., Rosenblau G., & Korn C. W. (2022). Incorporating social knowledge structures into computational models.Nature Communications, 13(1), 6205.
[34] Gao X., Jolly E., Yu H., Liu H., Zhou X., & Chang L. J. (2024). The psychological, computational, and neural foundations of indebtedness.Nature Communications, 15(1), 68.
[35] Gao X., Yu H., Sáez I., Blue P. R., Zhu L., Hsu M., & Zhou X. (2018). Distinguishing neural correlates of context- dependent advantageous- and disadvantageous-inequity aversion.Proceedings of the National Academy of Sciences, 115(33), 7680-7689.
[36] García-Arch J., Korn C. W., & Fuentemilla L. (2025). Self- utility distance as a computational approach to understanding self-concept clarity.Communications Psychology, 3(1), 50.
[37] Gigerenzer, G. (2002). Rationality: Why social context matters. In Adaptive thinking: Rationality in the real world (pp. 201-210). Oxford University Press.
[38] Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making.Annual Review of Psychology, 62, 451-482.
[39] Gigerenzer G., Reb J., & Luan S. (2022). Smart heuristics for individuals, teams, and organizations.Annual Review of Organizational Psychology and Organizational Behavior, 9, 171-198.
[40] Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement.American Sociological Review, 25(2), 161-178.
[41] Greenberg, M. S. (1980). A theory of indebtedness. In K. J. Gergen, M. S. Greenberg, & R. H. Willis (Eds.), Social exchange: Advances in theory and research(pp. 3-26). Springer.
[42] Greenberg, M. S., & Shapiro, S. P. (1971). Indebtedness: An adverse aspect of asking for and receiving help.Sociometry, 34(2), 290-301.
[43] Guest, O., & Martin, A. E. (2021). How computational modeling can force theory building in psychological science.Perspectives on Psychological Science, 16(4), 789-802.
[44] Hackel, L. M., & Amodio, D. M. (2018). Computational neuroscience approaches to social cognition.Current Opinion in Psychology, 24, 92-97.
[45] Hertwig R., Hoffrage U., & ABC Research Group. (Eds). (2012). Simple heuristics in a social world. Oxford University Press..
[46] Hofmann D. A., Lei Z., & Grant A. M. (2009). Seeking help in the shadow of doubt: The sensemaking processes underlying how nurses decide whom to ask for advice.Journal of applied psychology, 94(5), 1261-1274.
[47] Hu J., Hu Y., Li Y., & Zhou X. (2021). Computational and neurobiological substrates of cost-benefit integration in altruistic helping decision.The Journal of Neuroscience, 41(15), 3545-3561.
[48] Hu J., Konovalov A., & Ruff C. C. (2023). A unified neural account of contextual and individual differences in altruism.eLife, 12, e80667.
[49] Hu Y., Gao X., Yu H., He Z., & Zhou X. (2022). Neuroscience of moral decision making. In S. Della Sala (Ed.), Encyclopedia of behavioral neuroscience (2nd ed., pp. 481-495). Elsevier.
[50] Jin T., Zhang S., Lockwood P., Vilares I., Wu H., Liu C., & Ma Y. (2022). Learning whom to cooperate with: Neurocomputational mechanisms for choosing cooperative partners.Cerebral Cortex, 33(8), 4612-4625.
[51] Jones E. E.,& Davis, K. E. (1965). From acts to dispositions the attribution process in person perception. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 2, pp. 219-266). Academic Press.
[52] Juhl J., Wildschut T., Sedikides C., Xiong X., & Zhou X. (2021). Nostalgia promotes help seeking by fostering social connectedness.Emotion, 21(3), 631-643.
[53] Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
[54] Kearns M., Muldoon O. T., Msetfi R. M., & Surgenor, P. W. G. (2015). Understanding help-seeking amongst university students: The role of group identity, stigma, and exposure to suicide and help-seeking.Frontiers in Psychology, 6, 1462.
[55] Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research.Annual Review of Psychology, 31, 457-501.
[56] Koban L., Andrews-Hanna J. R., Ives L., Wager T. D., & Arch J. J. (2023). Brain mediators of biased social learning of self-perception in social anxiety disorder.Translational Psychiatry, 13(1), 292.
[57] Konovalov A., Hu J., & Ruff C. C. (2018). Neurocomputational approaches to social behavior.Current Opinion in Psychology, 24, 41-47.
[58] Kriegeskorte N., Mur M., & Bandettini P. A. (2008). Representational similarity analysis - connecting the branches of systems neuroscience.Frontiers in Systems Neuroscience, 2, 4.
[59] Law M. K. H., Thompson V. A., Stankov L., & Kleitman S. (2026). Systematic adaptive and maladaptive giving-up strategies in cognitive problem-solving.Thinking & Reasoning, 32(1), 27-69.
[60] Lee, F. (1997). When the going gets tough, do the tough ask for help? Help seeking and power motivation in organizations.Organizational Behavior and Human Decision Processes, 72(3), 336-363.
[61] Lee, F. (2002). The social costs of seeking help.The Journal of Applied Behavioral Science, 38(1), 17-35.
[62] Levine, S. M., & Schwarzbach, J. V. (2021). Individualizing representational similarity analysis.Frontiers in Psychiatry, 12, 729457.
[63] Li Y., Hu J., Ruff C. C., & Zhou X. (2022). Neurocomputational evidence that conflicting prosocial motives guide distributive justice.Proceedings of the National Academy of Sciences, 119(49), e2209078119.
[64] Ligneul, R. (2019). Sequential exploration in the Iowa gambling task: Validation of a new computational model in a large dataset of young and old healthy participants.PLOS Computational Biology, 15(6), e1006989.
[65] Lim J. H., Tai K., Bamberger P. A., & Morrison E. W. (2020). Soliciting resources from others: An integrative review.Academy of Management Annals, 14(1), 122-159.
[66] Lockwood P. L., Apps M. A. J., & Chang, S. W. C. (2020). Is there a ‘social’ brain? Implementations and algorithms.Trends in Cognitive Sciences, 24(10), 802-813.
[67] Lua V. Y. Q., Majeed N. M., Hartanto A., & Leung, A. K. -y. (2022). Help-seeking tendencies and subjective well-being: A cross-cultural comparison of the United States and Japan.Social Psychology Quarterly, 85(2), 164-186.
[68] Luo H., Du W., Shen B., Li X., Dai H., Hu J., Zhou X., & Gao X. (2024). From whom should I seek help? The temporal competition dynamics of rejection and repayment cost concerns behind help-seeking decisions.PsyArXiv.
[69] Mackenzie C. S., Heath P. J., Vogel D. L., & Chekay R. (2019). Age differences in public stigma, self-stigma, and attitudes toward seeking help: A moderated mediation model.Journal of Clinical Psychology, 75(12), 2259-2272.
[70] Marr, D. (2010). Vision: A computational investigation into the human representation and processing of visual information. The MIT Press.
[71] Matas L., Arend R. A., & Sroufe L. A. (1978). Continuity of adaptation in the second year: The relationship between quality of attachment and later competence.Child Development, 49(3), 547-556.
[72] McLaren T., Peter L. -J., Tomczyk S., Muehlan H., Schomerus G., & Schmidt S. (2023). The seeking mental health care model: Prediction of help-seeking for depressive symptoms by stigma and mental illness representations.BMC Public Health, 23(1), 69.
[73] McLaren T., Peter L. -J., Tomczyk S., Muehlan H., Schomerus G., & Schmidt S. (2024). The differential influence of self-construal on the effect of self-efficacy on the help-seeking process: A quasi-experimental online study among people with untreated depressive symptoms.Acta Psychologica, 242, 104119.
[74] Melis, A. P., & Raihani, N. J. (2023). The cognitive challenges of cooperation in human and nonhuman animals.Nature Reviews Psychology, 2(9), 523-536.
[75] Nadler, A. (1987). Determinants of help seeking behaviour: The effects of helper's similarity, task centrality and recipient's self esteem.European Journal of Social Psychology, 17(1), 57-67.
[76] Nadler, A. (1997). Personality and help seeking: Autonomous versus dependent seeking of help. In G. R. Pierce, B. Lakey, I. G. Sarason, & B. R. Sarason (Eds.), Sourcebook of social support and personality. (pp. 379-407). Plenum Press.
[77] Nadler, A. (2002). Inter-group helping relations as power relations: Maintaining or challenging social dominance between groups through helping.Journal of Social Issues, 58(3), 487-502.
[78] Nadler, A. (2015). The other side of helping: Seeking and receiving help. In D. A. Schroeder & W. G. Graziano (Eds.), The Oxford Handbook of Prosocial Behavior (pp. 307-328). Oxford University Press.
[79] Nadler A.,& Jeffrey, D. (1986). The role of threat to self-esteem and perceived control in recipient reaction to help: Theory development and empirical validation. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 19, pp. 81-122). Academic Press.
[80] Nadler A., Peri N., & Chemerinski A. (1985). Effects of opportunity to reciprocate and self-esteem on help-seeking behavior.Journal of Personality, 53(1), 23-35.
[81] Nadler, A., & Porat, I. (1978). When names do not help: Effects of anonymity and locus of need attribution on help-seeking behavior.Personality and Social Psychology Bulletin, 4(4), 624-626.
[82] Newark D. A., Bohns V. K., & Flynn F. J. (2017). A helping hand is hard at work: Help-seekers’ underestimation of helpers’ effort.Organizational Behavior and Human Decision Processes, 139, 18-29.
[83] Niv Y., Edlund J. A., Dayan P., & O'Doherty J. P. (2012). Neural prediction errors reveal a risk-sensitive reinforcement- learning process in the human brain.The Journal of Neuroscience, 32(2), 551-562.
[84] Olsson A., FeldmanHall O., Haaker J., & Hensler T. (2018). Social regulation of survival circuits through learning.Current Opinion in Behavioral Sciences, 24, 161-167.
[85] Olsson A., Knapska E., & Lindström B. (2020). The neural and computational systems of social learning.Nature Reviews Neuroscience, 21(4), 197-212.
[86] Pan Y., Vinding M. C., Zhang L., Lundqvist D., & Olsson A. (2023). A brain-to-brain mechanism for social transmission of threat learning.Advanced Science, 10(28), 2304037.
[87] Philippe R., Janet R., Khalvati K., Rao R. P. N., Lee D., & Dreher J. -C. (2024). Neurocomputational mechanisms involved in adaptation to fluctuating intentions of others.Nature Communications, 15(1), 3189.
[88] Pisauro M. A., Fouragnan E. F., Arabadzhiyska D. H., Apps M. A. J., & Philiastides M. G. (2022). Neural implementation of computational mechanisms underlying the continuous trade-off between cooperation and competition.Nature Communications, 13(1), 6873.
[89] Qu C., Bénistant J., & Dreher J. -C. (2022). Neurocomputational mechanisms engaged in moral choices and moral learning.Neuroscience & Biobehavioral Reviews, 132, 50-60.
[90] Rescorla, R. A., & Wagner, A. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In A. H. Black, & W. F. Prokasy (Eds.), Clasical Conditioning II: Current Research and Theory (Vol. 2, pp. 64-99). New York: Appleton-Century- Crofts.
[91] Ruff, C. C., & Fehr, E. (2014). The neurobiology of rewards and values in social decision making.Nature Reviews Neuroscience, 15(8), 549-562.
[92] Ruihua L., Che Hassan N., & Saharuddin N. (2025). Understanding academic help-seeking among first-generation college students: A phenomenological approach.Humanities and Social Sciences Communications, 12(1), 56.
[93] Schultner D., Molleman L., & Lindström B. (2025). Feature-based reward learning shapes human social learning strategies.Nature Human Behaviour, 9, 2183-2198.
[94] Shaffer P. A., Vogel D. L., & Wei M. (2006). The mediating roles of anticipated risks, anticipated benefits, and attitudes on the decision to seek professional help: An attachment perspective.Journal of Counseling Psychology, 53(4), 442-452.
[95] Shapiro, E. G. (1980). Is seeking help from a friend like seeking help from a stranger?Social Psychology Quarterly, 43(2), 259-263.
[96] Shute V. J., Wang L., Greiff S., Zhao W., & Moore G. (2016). Measuring problem solving skills via stealth assessment in an engaging video game.Computers in Human Behavior, 63, 106-117.
[97] Sijben J., Huibertse L. J., Rainey L., Broeders M. J. M., Peters Y., & Siersema P. D. (2024). Oesophageal cancer awareness and anticipated time to help-seeking: Results from a population-based survey.British Journal of Cancer, 130(11), 1795-1802.
[98] Simon, H. A. (1955). A behavioral model of rational choice.The Quarterly Journal of Economics, 69(1), 99-118.
[99] Song X., Anderson T., Himawan L., McClintock A., Jiang Y., & McCarrick S. (2019). An investigation of a cultural help-seeking model for professional psychological services with U.S. and Chinese samples.Journal of Cross-Cultural Psychology, 50(9), 1027-1049.
[100] Stanovich, K. E. (1999). Who is rational? Studies of individual differences in reasoning. Lawrence Erlbaum Associates Publishers.
[101] Stokes, S. J., & Bickman, L. (1974). The effect of the physical attractiveness and role of the helper on help seeking.Journal of Applied Social Psychology, 4(3), 286-294.
[102] Teng F., Wang X., Lei Q., & Poon K. T. (2024). Love me, because I rely on you: Dependency-oriented help-seeking as a strategy for human mating.Journal of Personality and Social Psychology, 127(6), 1215-1236.
[103] Terenzi D., Liu L., Bellucci G., & Park S. Q. (2021). Determinants and modulators of human social decisions.Neuroscience & Biobehavioral Reviews, 128, 383-393.
[104] Tessler, R. C., & Schwartz, S. H. (1972). Help seeking, self-esteem, and achievement motivation: An attributional analysis.Journal of Personality and Social Psychology, 21(3), 318-326.
[105] Vahed S., Galván E. P., & Sanfey A. G. (2024). Computational modeling of social decision-making.Current Opinion in Psychology, 60, 101884.
[106] van Dijk, E., & De Dreu, C. K. W. (2021). Experimental games and social decision making.Annual Review of Psychology, 72(1), 415-438.
[107] Will G. -J., Rutledge R. B., Moutoussis M., & Dolan R. J. (2017). Neural and computational processes underlying dynamic changes in self-esteem.eLife, 6, e28098.
[108] Wilson, R. C., & Collins, A. G. E. (2019). Ten simple rules for the computational modeling of behavioral data.eLife, 8, e49547.
[109] Worthy D. A., Hawthorne M. J., & Otto A. R. (2013). Heterogeneity of strategy use in the Iowa gambling task: A comparison of win-stay/lose-shift and reinforcement learning models.Psychonomic Bulletin & Review, 20(2), 364-371.
[110] Wu X., Ren X., Liu C., & Zhang H. (2024). The motive cocktail in altruistic behaviors.Nature Computational Science, 4(9), 659-676.
[111] Xiong X., Guo S., Gu L., Huang R., & Zhou X. (2018). Reciprocity anxiety: Individual differences in feeling discomfort in reciprocity situations.Journal of Economic Psychology, 67, 149-161.
[112] Yang Y., Luo S., Wang W., Gao X., Yao X., & Wu T. (2024). From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications.NeuroImage: Clinical, 42, 103608.
[113] Yu H., Gao X., Shen B., Hu Y., & Zhou X. (2024). A levels-of-analysis framework for studying social emotions.Nature Reviews Psychology, 3, 198-213.
[114] Yu H., Lu C., Gao X., Shen B., Liu K., Li W., … Zhou X. (2022). Explaining individual differences in advantageous inequity aversion by social-affective trait dimensions and family environment.Social Psychological and Personality Science, 13(2), 626-637.
[115] Zajkowski W., Badman R. P., Haruno M., & Akaishi R. (2024). A neurocognitive mechanism for increased cooperation during group formation.Communications Psychology, 2(1), 127.
[116] Zhang, Y., & Chen, Z. S. (2025). Harnessing electroencephalography connectomes for cognitive and clinical neuroscience.Nature Biomedical Engineering, 9, 1186-1201.
[117] Zhao, X., & Epley, N. (2022). Surprisingly happy to have helped: Underestimating prosociality creates a misplaced barrier to asking for help.Psychological Science, 33(10), 1708-1731.
[118] Zhong S., Ma C., Huang Y., Zhang T., Hou X., Tai T. C., … Zhou L. (2025). Patterns, delays, and associated factors of help-seeking behaviour for lifetime mood disorders and anxiety disorders: A national representative survey.Journal of Affective Disorders, 372, 386-393.