Recurrent involuntary memories and mind wandering are related but distinct.

Spontaneous thought is common in daily life, and includes recurrent involuntary autobiographical memories (IAMs; memories retrieved unintentionally and repetitively) and mind wandering (MW). 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? Undergraduates (N = 2,701) completed self-report measures of recurrent IAMs, trait MW, and psychopathology (i.e., PTSD, depression, anxiety). Regressions indicated that recurrent IAMs were significantly associated with spontaneous MW, but not deliberate MW. Further, both spontaneous MW and recurrent IAMs had unique relationships with disorder symptoms. Results suggest that recurrent IAMs are related to MW to the extent that recurrent IAMs are spontaneous. Conversely, recurrent IAMs are distinct from MW to the extent that recurrent IAMs' associations with disorder symptoms could not be solely explained by trait MW (and vice versa). This work highlights related, but distinguishable, forms of spontaneous thought and their transdiagnostic links with psychopathology.

Disentangling boredom from depression using the phenomenology and content of involuntary autobiographical memories.

Recurrent involuntary autobiographical memories (IAMs) are memories retrieved unintentionally and repetitively. 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. Participants (n = 2484) described their most frequent IAM and rated its phenomenological properties (e.g., valence). Structural topic modeling, a method of unsupervised machine learning, identified coherent content within the described memories. Boredom proneness was positively correlated with depressive symptoms, and both boredom proneness and depressive symptoms were correlated with more negative recurrent IAMs. 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. Phenomenology and content in recurrent IAMs can effectively disambiguate boredom proneness from depressive symptoms in a large sample of undergraduate students from a racially diverse university.

Specific topics, specific symptoms: linking the content of recurrent involuntary memories to mental health using computational text analysis.

Researchers debate whether recurrent involuntary autobiographical memories (IAMs; memories of one's personal past retrieved unintentionally and repetitively) are pathological or ordinary. While some argue that these memories contribute to clinical disorders, recurrent IAMs are also common in everyday life. Here, we examined how the content of recurrent IAMs might distinguish between those that are maladaptive (related to worse mental health) versus benign (unrelated to mental health). Over two years, 6187 undergraduates completed online surveys about recurrent IAMs; those who experienced recurrent IAMs within the past year were asked to describe their memories, resulting in 3624 text descriptions. 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, we also found that 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. Our work shows that topics in recurrent IAMs-and their links to mental health-are identifiable, distinguishable, and quantifiable.

Understanding autobiographical memory content using computational text analysis.

Although research on autobiographical memory (AM) continues to grow, there remain few methods to analyze AM content. Past approaches are typically manual, and prohibitively time- and labour-intensive. These methodological limitations are concerning because content may provide insights into the nature and functions of AM. In particular, analyzing content in recurrent involuntary autobiographical memories (IAMs; those that spring to mind unintentionally and repetitively) could resolve controversies about whether these memories typically involve mundane or distressing events. Here, we present computational methods that can analyze content in thousands of participants' AMs, without needing to hand-code each memory. A sample of 6,187 undergraduates completed surveys about recurrent IAMs, resulting in 3,624 text descriptions. Using frequency analyses, we identified common (e.g., "time", "friend") and distinctive words in recurrent IAMs (e.g., "argument" as distinctive to negative recurrent IAMs). 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 large quantities of AM content with enhanced granularity and reproducibility. We present the means to enable future research on AM content at an unprecedented scope and scale.

Machine learning to detect invalid text responses: Validation and comparison to existing detection methods.

A crucial step in analysing text data is the detection and removal of invalid texts (e.g., texts with meaningless or irrelevant content). To date, research topics that rely heavily on analysis of text data, such as autobiographical memory, have lacked methods of detecting invalid texts that are both effective and practical. Although researchers have suggested many data quality indicators that might identify invalid responses (e.g., response time, character/word count), few of these methods have been empirically validated with text responses. In the current study, 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. Our approach (a) trains, validates, and tests on a subset of texts manually labelled as valid or invalid, (b) calculates performance metrics to help select the best model, and (c) predicts whether unlabelled texts are valid or invalid based on the text alone. Model validation and evaluation using autobiographical memory texts indicated that machine learning accurately detected invalid texts with performance near human coding, significantly outperforming existing data quality indicators. Our openly available code and instructions enable new methods of improving data quality for researchers using text as data.

Recurrent involuntary memories are modulated by age and linked to mental health.

Recurrent involuntary autobiographical memories (IAMs), or memories that spring to mind unintentionally and repetitively, are common among younger and older adults. Since older adults show enhanced emotion regulation, we investigated whether their recurrent IAMs were more positive than younger adults'. Additionally, we examined whether recurrent IAMs reflected mental health in both age groups. In our study, community-dwelling older (Mage = 75.6) and younger adults (Mage = 19.7; ns = 95) completed surveys assessing recurrent IAMs (e.g., their frequency, valence) and symptoms of mental health issues (e.g., depression, anxiety, posttraumatic stress). As hypothesized, age modulated recurrent IAM valence, despite the involuntary nature of these memories: younger adults' recurrent IAMs were disproportionately negative (74%), whereas older adults' were disproportionately positive (60%). Further, experiencing recurrent IAMs-especially negative ones-predicted worse mental health in both younger and older adults. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Divided attention at encoding or retrieval interferes with emotionally enhanced memory for words.

Emotional information is typically better remembered than neutral information. We asked whether emotional, compared to neutral, words were less vulnerable to the detrimental effects of divided attention. In two experiments, undergraduate students intentionally encoded words of intermixed valence (neutral, negative, or positive) and arousal (neutral, high, or low). Following a filled delay, memory was assessed with a free recall test. In Experiment 1, participants encoded visually-presented words under either full attention (FA; no distracting task) or divided attention (DA; concurrently making animacy decisions to auditorily-presented distractor words) in a counterbalanced, within-subjects design. As expected following FA at encoding, recall was significantly enhanced for negative compared to neutral words. Following DA at encoding, recall was significantly impaired across all valences. Critically, DA at encoding also eliminated the memory benefit for negative information: recall of negative words was no longer significantly different from neutral or positive words. In Experiment 2, we manipulated attention at retrieval rather than encoding. Remarkably, results from Experiment 1 were replicated: DA eliminated the well-known emotionality boost for negative words. In both experiments, memory for positive words did not significantly differ from neutral. Findings suggest that DA during either encoding or retrieval can interfere with the specific mechanisms by which negative emotion typically improves memory.

The influence of social anxiety-provoking contexts on context reinstatement effects.

The context reinstatement (CR) effect is the finding that target stimuli are better remembered when presented in the same context as during initial encoding, compared with a different context. It remains unclear, however, whether emotional features of the context affect this memory benefit. In two experiments, we investigated whether the anxiety-provoking nature of a context scene might influence the CR effect. During encoding, participants viewed target faces paired with scenes validated as either highly anxiety-provoking or not, half of which contained other faces embedded within the scene. During retrieval, target faces were presented again with either the same or a new context scene. In Experiment 1, the expected CR effect was observed when the contexts were low-anxiety scenes or high-anxiety scenes without embedded faces. In contrast, the CR effect was absent when the contexts were high-anxiety scenes containing embedded faces. In Experiment 2, to determine whether the presence of embedded faces or the anxiety level of scenes reduced the CR effect, we included an additional context type: low-anxiety scenes with embedded faces. Once again, the CR effect was absent only when the context scene was highly anxiety-provoking with embedded faces: reinstating this context type failed to benefit memory for targets. Results suggest that the benefit to target memory via reinstating a context depends critically on emotional characteristics of the reinstated context.

Recurrent involuntary autobiographical memories: characteristics and links to mental health status.

Memories of events from one's personal past that come to mind unintentionally and effortlessly are termed involuntary autobiographical memories (IAMs). Recurrent IAMs are known as relevant to many disorders within clinical literature. However, less is known about their links with mental health status in the general population. In the current study, 2184 undergraduate students completed surveys assessing occurrence of any recurrent IAMs. Participants also wrote a description of their most frequently recurring IAM and rated it on phenomenological characteristics, such as frequency, valence, vividness, and centrality. Results showed that the majority of our sample experienced recurrent IAMs, replicating previous findings, but most of these memories were emotionally negative, unlike past work. Importantly, negative recurrent IAMs were associated with significantly more mental health concerns, including symptoms of depression, anxiety, and posttraumatic stress. We also found that frequency of IAM recurrence was predicted by the memory's age, level of completeness/detail, emotional intensity, and centrality to one's life story. Further, descriptions of positive recurrent IAMs contained significantly more episodic detail compared to negative or neutral ones, suggesting that emotional regulation may play a role in how recurrent IAMs are recounted. Recurrent IAMs, and their characteristics, serve as a window into mental health status.

Altered working memory capacity for social threat words in high versus low social anxiety.

Background and objectives: Differences in working memory capacity (WMC) have been suggested in individuals with high levels of social anxiety (SA). Specifically, these individuals may preferentially maintain socially threatening material in working memory. Design and methods: We adapted the digit span task to a series of word span tasks. We assessed WMC for lists of words that varied in terms of their threat-relatedness, in individuals either high or low in SA. Results: Experiment 1 revealed reduced WMC for socially threatening words in those with high compared to low SA. Importantly, this relative reduction in WMC was driven by the low SA group showing expanded capacity for socially threatening words relative to neutral or generally threatening words. Furthermore, reductions in WMC for social threat were uniquely predicted by SA, and not by other theoretically related constructs such as state general anxiety, trait general anxiety, or depression. Experiment 2 showed that the semantic similarity of the words within each list was not responsible for the differences in WMC between list type or SA group. Conclusions: Our findings suggest that individuals high in SA may fail to upregulate WMC for social information due to the activation of, or rumination upon, socially threatening concepts.

Social anxiety enhances recognition of task-irrelevant threat words.

Past research is mixed regarding the conditions under which memory biases emerge in individuals with high levels of social anxiety. The current study examined whether high social anxiety would be associated with a memory bias for threatening, but task-irrelevant information, or whether it creates a memory bias for both threatening as well as neutral distractors. 60 undergraduate students were recruited, half classified as having high social anxiety and half as having low social anxiety according to the Social Phobia Inventory. Participants memorized a series of sequentially and visually presented target words that were either all neutral (e.g., patient) or all socially threatening (e.g., embarrassed). Simultaneously during encoding, participants also saw a distractor word on each trial that was either neutral or socially threatening. Memory for targets was then assessed using a recall and recognition test. Incidental recall and recognition tests for the distractors were also administered. There were no group differences in memory for threat versus neutral targets. However, recognition of socially threatening distractors was significantly enhanced in those with high relative to low levels of social anxiety, but only when targets were also socially threatening. Memory biases in high social anxiety were shown to be specific for threat-related distractors rather than general, for all distractors. This specific bias for threat emerged only when the to-be-remembered target information was also threatening. Findings suggest that when social anxiety is primed, attention to irrelevant, but socially threatening, information is heightened.