Publications
12 publications in peer-reviewed academic journals, with 11 published as first author.
Both recurrent IAMs and MW are often unintentional or unconstrained, and both predict symptoms of mental health disorders. However, not all MW is unintentional, and not all IAMs are unconstrained. To what extent do recurrent IAMs and MW converge versus diverge? Results suggest that recurrent IAMs are related to MW in that recurrent IAMs are spontaneous. Conversely, recurrent IAMs are distinct from MW in that recurrent IAMs’ associations with disorder symptoms could not be solely explained by trait MW (and vice versa).
Yeung, R. C., & Fernandes, M. A. (2024). Recurrent involuntary memories and mind wandering are related but distinct. Psychological Research
We examined whether the phenomenology and content of recurrent IAMs could differentiate boredom and depression, both of which are characterized by affective dysregulation and spontaneous thought. Boredom proneness predicted less vivid recurrent IAMs, whereas depressive symptoms predicted more vivid, negative, and emotionally intense ones. Memory content also diverged: topics such as relationship conflicts were positively predicted by depressive symptoms, but negatively predicted by boredom proneness.
Yeung, R. C., Danckert, J., van Tilburg, W. A. P., & Fernandes, M. A. (2024). Disentangling boredom from depression using the phenomenology and content of involuntary autobiographical memories. Scientific Reports, 14, 1–15. https://doi.org/10.1038/s41598-024-52495-5
Using a previously validated computational approach (structural topic modeling), we identified coherent topics (e.g., “Conversations”, “Experiences with family members”) in recurrent IAMs. Specific topics (e.g., “Negative past relationships”, “Abuse and trauma”) were uniquely related to symptoms of mental health disorders (e.g., depression, PTSD), above and beyond the self-reported valence of these memories. Importantly, content in recurrent IAMs was distinct across symptom types (e.g., “Communication and miscommunication” was related to social anxiety, but not symptoms of other disorders), suggesting that while negative recurrent IAMs are transdiagnostic, their content remains unique across different types of mental health concerns.
Yeung, R. C., & Fernandes, M. A. (2023). Specific topics, specific symptoms: Linking the content of recurrent involuntary memories to mental health using computational text analysis. npj Mental Health Research, 2(22), 1–16. https://doi.org/10.1038/s44184-023-00042-x
Over the last two decades, Canadian higher education has largely addressed students’ mental health concerns through extra-curricular means. To instead embed education into the curriculum, CZ developed and taught an undergraduate course on mental health literacy. We conducted a pre-post study, finding that students made significant gains from T1 to T2, with a large effect size, in terms of attitudes toward seeking mental health services.
Zaza, C., & Yeung, R. C. (2023). It’s time to bring mental health literacy education into the postsecondary curriculum. Canadian Journal for the Scholarship of Teaching and Learning., 14(1), 1-15. https://doi.org/10.5206/cjsotlrcacea.2023.1.13663
Although there is scholarly interest in autobiographical memory (AM) content, past manual approaches are prohibitively time- and labour-intensive. Using structural topic modelling, we identified coherent topics (e.g., “Negative past relationships”, “Conversations”, “Experiences with family members”) within recurrent IAMs and found that topic use significantly differed depending on the valence of these memories. Computational methods allowed us to analyze AM content at an unprecedented scope and scale.
Yeung, R. C., Stastna, M., & Fernandes, M. A. (2022). Understanding autobiographical memory content using computational text analysis. Memory, 30(10), 1267–1287. https://doi.org/10.1080/09658211.2022.2104317
We propose and implement a supervised machine learning approach that can mimic the accuracy of human coding, but without the need to hand-code entire text datasets. Using autobiographical memory texts, we accurately detected invalid texts with performance near human coding, significantly outperforming existing data quality indicators.
Yeung, R. C., & Fernandes, M. A. (2022). Machine learning to detect invalid text responses: Validation and comparison to existing detection methods. Behavior Research Methods, 1–16. https://doi.org/10.3758/s13428-022-01801-y
Age modulated recurrent IAM valence, despite the involuntary nature of these memories: younger adults’ recurrent IAMs were disproportionately negative, whereas older adults‘ were disproportionately positive. Negative valence predicted worse mental health in both younger and older adults.
Yeung, R. C., & Fernandes, M. A. (2021). Recurrent involuntary memories are modulated by age and linked to mental health. Psychology and Aging, 36(7), 883–890. https://doi.org/10.1037/pag0000630
Findings suggest that divided attention during either encoding or retrieval can interfere with the specific mechanisms by which negative emotion typically improves memory.
Yeung, R. C., & Fernandes, M. A. (2021). Divided attention at encoding or retrieval interferes with emotionally enhanced memory for words. Memory, 29(3), 284–297. https://doi.org/10.1080/09658211.2021.1887896
Results suggest that the benefit to target memory via reinstating a context depends critically on emotional characteristics of the reinstated context, particularly when the context scene was highly anxiety-provoking with embedded faces.
Yeung, R. C., Lee, C. M., & Fernandes, M. A. (2021). The influence of social anxiety-provoking contexts on context reinstatement effects. Quarterly Journal of Experimental Psychology, 74(7), 1170–1184. https://doi.org/10.1177/1747021821998489
Negative recurrent IAMs were associated with significantly more mental health concerns, including symptoms of depression, anxiety, and posttraumatic stress.
Yeung, R. C., & Fernandes, M. A. (2020). Recurrent involuntary autobiographical memories: Characteristics and links to mental health status. Memory, 28(6), 753–765. https://doi.org/10.1080/09658211.2020.1777312
Our findings suggest that individuals high in social anxiety may fail to upregulate working memory capacity for social information due to the activation of socially threatening concepts.
Yeung, R. C., & Fernandes, M. A. (2019). Altered working memory capacity for social threat words in high versus low social anxiety. Anxiety, Stress, & Coping, 32(5), 505–521. https://doi.org/10.1080/10615806.2019.1626838
Memory biases in high social anxiety were shown to be specific for threat-related distractors rather than general, for all distractors, and emerged only when the to-be-remembered target information was also threatening.
Yeung, R. C., & Fernandes, M. A. (2019). Social anxiety enhances recognition of task-irrelevant threat words. Acta Psychologica, 194, 69–76. https://doi.org/10.1016/j.actpsy.2019.01.015
