Transdiagnostic compulsivity is associated with reduced reminder setting, only partially attributable to overconfidence

Reviewer #1 (Public review):

Summary:

Boldt et al test several possible relationships between trandiagnostically-defined compulsivity and cognitive offloading in a large online sample. To do so, they develop a new and useful cognitive task to jointly estimate biases in confidence and reminder-setting. In doing so, they find that over-confidence is related to less utilization of reminder-setting, which partially mediates the negative relationship between compulsivity and lower reminder-setting. The paper thus establishes that, contrary to the over-use of checking behaviors in patients with OCD, greater levels of transdiagnostically-defined compulsivity predicts less deployment of cognitive offloading. The authors offer speculative reasons as to why (perhaps it's perfectionism in less clinically-severe presentations that lowers the cost of expending memory resources), and sets an agenda to understand the divergence in cognitive between clinical and nonclinical samples. Because only a partial mediation had robust evidence, multiple effects may be at play, whereby compulsivity impacts cognitive offloading via overconfidence and also by other causal pathways.

Strengths:

The study develops an easy-to-implement task to jointly measure confidence and replicates several major findings on confidence and cognitive offloading. The study uses a useful measure of cognitive offloading - the tendency to set reminders to augment accuracy in the presence of experimentally manipulated costs. Moreover, the utilizes multiple measures of presumed biases -- overall tendency to set reminders, the empirically estimated indifference point at which people engage reminders, and a bias measure that compares optimal indifference points to engage reminders relative to the empirically observed indifference points. That the study observes convergenence along all these measures strengthens the inferences made relating compulsivity to the under-use of reminder-setting. Lastly, the study does find evidence for one of several a priori hypotheses and sets a compelling agenda to try to explain why such a finding diverges from an ostensible opposing finding in clinical OCD samples and the over-use of cognitive offloading.

Weaknesses:

Although I think this design and study are very helpful for the field, I felt that a feature of the design might reduce the tasks's sensitivity to measuring dispositional tendencies to engage cognitive offloading. In particular, the design introduces prediction errors, that could induce learning and interfere with natural tendencies to deploy reminder-setting behavior. These PEs comprise whether a given selected strategy will be or not be allowed to be engaged. We know individuals with compulsivity can learn even when instructed not to learn (e.g., Sharp, Dolan and Eldar, 2021, Psychological Medicine), and that more generally, they have trouble with structure knowledge (eg Seow et al; Fradkin et al), and thus might be sensitive to these PEs. Thus, a dispositional tendency to set reminders might be differentially impacted for those with compulsivity after an NPE, where they want to set a reminder, but aren't allowed to. After such an NPE, they may avoid moreso the tendency to set reminders. Those with compulsivity likely have superstitious beliefs about how checking behaviors lead to a resolution of catastrophes, that might in part originate from inferring structure in the presence of noise or from purely irrelevant sources of information for a given decision problem.
It would be good to know if such learning effects exist, if they're modulated by PE (you can imagine PEs are higher if you are more incentivized - e.g., 9 points as opposed to only 3 points - to use reminders, and you are told you cannot use them), and if this learning effect confounds the relationship between compulsivity and reminder-setting.

A more subtle point, I think this study can be more said to be an exploration than a deductive of test of a particular model -> hypothesis -> experiment. Typically, when we test a hypothesis, we contrast it with competing models. Here, the tests were two-sided because multiple models, with mutually exclusive predictions (over-use or under-use of reminders) were tested. Moreover, it's unclear exactly how to make sense of what is called the direct mechanism, which is supported by the partial (as opposed to complete) mediation.

Reviewer #2 (Public review):

Summary:

Boldt et al., investigated whether previously established relationships between transdiagnostic psychiatric symptom dimensions and confidence distortions would result in downstream influences on the confidence-related behaviour of reminder setting. 600 individuals from the general population completed a battery of psychiatric symptom questionnaires and an online reminder-setting task. In line with previous studies, individuals high in compulsivity (CIT) showed over-confidence in their task performance, whereas individuals high in anxious-depression (AD) tended to be under-confident. Crucially, the over-confidence associated with CIT partially mediated a decreased tendency to use external reminders during task performance, whereas the under-confidence associated with AD did not result in any alteration in external reminder setting. The authors suggest that metacognitive monitoring is impaired in CIT which has a knock-on effect on reminder setting behaviour, but that a direct link also exists between CIT and reduced reminder setting independently of confidence.

Strengths:

The study combines the latest advances in transdiagnostic approaches to psychopathology with a cleverly designed external reminder-setting task. The approach allows for investigation of what some of the downstream consequences associated with impaired metacognition in sub-clinical psychopathology may be.

The experimental design and hypotheses were pre-registered prior to data collection.

The manuscript is well written and rigorous analysis approaches are used throughout.

Weaknesses:

Participants only performed a single task so it remains unclear if the observed effects would generalise to reminder setting in other cognitive domains.

The sample consisted of participants recruited from the general population. Future studies should investigate whether the effects observed extend to individuals with the highest levels of symptoms (including clinical samples).

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1:

(1) You claim transdiagnostic phenotypes are temporally stable -- since they're relatively new constructs, do we know how stable? In what order?

This is an important question. We have added two recent references to support this claim on page 1 and cite these studies in the references on pages 25 and 28:

“Using factor analysis, temporally stable (see Fox et al., 2023a; Sookud, Martin, Gillan, & Wise, 2024), transdiagnostic phenotypes can be extracted from extensive symptom datasets (Wise, Robinson, & Gillan, 2023).”

Fox, C. A., McDonogh, A., Donegan, K. R., Teckentrup, V., Crossen, R. J., Hanlon, A. K., … Gillan, C. M. (2024). Reliable, rapid, and remote measurement of metacognitive bias. Scientific Reports, 14(1), 14941. https://doi.org/10.1038/s41598-024-64900-0

Sookud, S., Martin, I., Gillan, C., & Wise, T. (2024, September 5). Impaired goal-directed planning in transdiagnostic compulsivity is explained by uncertainty about learned task structure. https://doi.org/10.31234/osf.io/zp6vk

More specifically, Sookud and colleagues found the intraclass correlation coefficient (ICC) for both factors to be high after a 3- or 12 month period (ICC_{AD_3} = 0.87; ICC_{AD_12} = 0.87; ICC_{CIT_3} = 0.81; ICC_{CIT_3}= 0.76; see Tables S41 and S50 in Sookud et al., 2024).

(2) On hypotheses of the study:

I didn't understand the logic behind the hypothesis relating TDx Compulsivity -> Metacognition > Reminder-setting

It seems that (a) Compulsivity relates to overconfidence which should predict less remindersetting

Compulsivity has an impaired link between metacognition and action, breaking the B->C link in the mediation described above in (a). What would this then imply about how Compulsivity is related to reminder-setting?

"In the context of our study, a Metacognitive Control Mechanism would be reflected in a disrupted relationship between confidence levels and their tendency to set reminders." What exactly does this predict - a lack of a correlation between confidence and remindersetting, specifically in high-compulsive subjects?

Lastly, there could be a direct link between compulsivity and reminder-usage, independent of any metacognitive influence. We refer to this as the Direct Mechanism Why though theoretically would this be the case?

"We initially hypothesised to find support for the Metacognitive Control Mechanism and that highly compulsive individuals would offload more".

The latter part here, "highly compulsive individuals would offload more" is I think the exact opposite prediction of the Metacognitive control mechanism hypothesis (compulsive individuals offload less). How could you possibly have tried to find support, then, for both?

Is the hypothesis that compulsivity positively predicts reminder setting the "direct mechanism" - if so, please clarify that, and if not, it should be added as a distinct mechanism, and additionally, the direct mechanism should be specified.

There's more delineation of specific hypotheses (8 with caveats) in Methods.

"We furthermore also tested this hypothesis but predicted raw confidence (percentage of circles participants predicted they would remember; H6b and H8b respectively)," What is the reference of "this hypothesis" given that right before this sentence two hypotheses are mentioned? To keep this all organized, it would be good to simply have a table with hypotheses listed clearly.

We agree with the reviewer that there is room to improve the clarity of how our hypotheses are presented. The confusion likely arises from the fact that, since we first planned and preregistered our study, several new pieces of work have emerged, which might have led us to question some of our initial hypotheses. We have taken great care to present the hypotheses as they were preregistered, while also considering the current state of the literature and organizing them in a logical flow to make them more digestible for the reader. We have clarified this point on page 4:

“Back when we preregistered our hypotheses only a limited number of studies about confidence and transdiagnostic CIT were available. This resulted in us hypothesising to find support for the Metacognitive Control Mechanism and that highly compulsive individuals would offload more due to an increased need for checkpoints.”

The biggest improvement we believe comes from our new Table 1, which we have included in the Methods section in response to the reviewer’s suggestion (pp. 21-22):

“We preregistered 8 hypotheses (see Table 1), half of which were sanity checks (H1-H4) aimed to establish whether our task would generally lead to the same patterns as previous studies using a similar task (as reviewed in Gilbert et al., 2023).”

We furthermore foreshadowed more explicitly how we would test the Metacognitive Control Mechanism in the Introduction section on page 4, as requested by the reviewer:

“In the context of our study, a Metacognitive Control Mechanism would be reflected in a disrupted relationship between confidence levels and their tendency to set reminders (i.e., the interaction between the bias to be over- or underconfident and transdiagnostic CIT in a regression model predicting a bias to set reminders).”

To avoid any confusion regarding the term ‘direct’ in the ‘Direct Mechanism’, we now explicitly clarify on page 4 that it refers to any non-metacognitive influences. Additionally, we had already emphasized in the Discussion section the need for future studies to specify these influences more directly.

Page 4: “We refer to this as the Direct Mechanism and it constitutes any possible influences that affect reminder setting in highly-compulsive CIT participants outside of metacognitive mechanisms, such as perfectionism and the wish to control the task without external aids.”

The reviewer was correct in pointing out that, in the Methods section, we incorrectly referred to ‘this hypothesis’ when we actually meant both of the previously mentioned hypotheses. We have corrected this on page 23:

“We furthermore also tested these hypotheses but predicted raw confidence (percentage of circles participants predicted they would remember; H6b and H8b respectively), as well as extending the main model with the scores from the cognitive ability test (ICAR5) as an additional covariate (H6c and H8c respectively).”

Finally, upon revisiting our Results section, we noticed that we had not made it sufficiently clear that hypothesis H6a was preregistered as non-directional. We have now clarified this on page 9:

“We predicted that the metacognitive bias would correlate negatively with AD (Hypothesis 8a; more anxious-depressed individuals tend to be underconfident). For CIT, we preregistered a non-directional, significant link with metacognitive bias (Hypothesis H6a). We found support for both hypotheses, both for AD, β = -0.22, SE = 0.04, t = -5.00, p < 0.001, as well as CIT, β = 0.15, SE = 0.05, t = 3.30, p = 0.001, controlling for age, gender, and educational attainment (Figure 3; see also Table S1). Note that for CIT this effect was positive, more compulsive individuals tend to be overconfident.”

(3) You say special circles are red, blue, or pink. Then, in the figure, the colors are cyan, orange, and magenta. These should be homogenized.

Apologies, this was not clear on our screens. We have corrected this now but used the labels “blue”, “orange” and “magenta” as our shade of blue is much darker than cyan:

Page 16: “These circles flashed in a colour (blue, orange, or magenta) when they first appear on screen before fading to yellow.”

(4) The task is not clearly described with respect to forced choice. From my understanding, "forced choice" was implicitly delivered by a "computer choosing for them". You should indicate in the graphic that this is what forced choice means in the graphic and description more clearly.

This is an excellent point. On pages 17 and 18 we now include a slightly changed Figure 6, which includes improved table row names and cell shading to indicate the choice people gave. Hopefully this clarifies what “forced choice” means.

(5) If I have point (4) right, then a potential issue arises in your design. Namely, if a participant has a bias to use or not use reminders, they will experience more or less prediction errors during their forced choice. This kind of prediction error could introduce different mood impacts on subsequent performance, altering their accuracy. This will have an asymmetric effect on the different forced phases (ie forced reminders or not). For this reason, I think it would be worthwhile to run a version of the experiment, if feasible, where you simply remove choice prior to revealing the condition. For example, have a block of choices where people can "see how well you do with reminders" -- this removes expectation and PE effects.

[See also this point from the weaknesses listed in the public comments:]

Although I think this design and study are very helpful for the field, I felt that a feature of the design might reduce the tasks's sensitivity to measuring dispositional tendencies to engage cognitive offloading. In particular, the design introduces prediction errors, that could induce learning and interfere with natural tendencies to deploy reminder-setting behavior. These PEs comprise whether a given selected strategy will be or not be allowed to be engaged. We know individuals with compulsivity can learn even when instructed not to learn (e.g., Sharp, Dolan, and Eldar, 2021, Psychological Medicine), and that more generally, they have trouble with structure knowledge (eg Seow et al; Fradkin et al), and thus might be sensitive to these PEs. Thus, a dispositional tendency to set reminders might be differentially impacted for those with compulsivity after an NPE, where they want to set a reminder, but aren't allowed to. After such an NPE, they may avoid more so the tendency to set reminders. Those with compulsivity likely have superstitious beliefs about how checking behaviors leads to a resolution of catastrophes, which might in part originate from inferring structure in the presence of noise or from purely irrelevant sources of information for a given decision problem.

It would be good to know if such learning effects exist if they're modulated by PE (you can imagine PEs are higher if you are more incentivized - e.g., 9 points as opposed to only 3 points - to use reminders, and you are told you cannot use them), and if this learning effect confounds the relationship between compulsivity and reminder-setting.

We would like to thank the reviewer for providing this interesting perspective on our task. If we understand correctly, the situation most at risk for such effects occurs when participants choose to use a reminder. Not receiving a reminder in the following trial can be seen as a negative prediction error (PE), whereas receiving one would represent the control condition (zero PE). Therefore, we focused on these two conditions in our analysis.

We indeed found that participants had a slightly higher tendency to choose reminders again after trials where they successfully requested them compared to after trials where they were not allowed reminders (difference = 4.4%). This effect was statistically significant, t(465) = 2.3, p = 0.024. However, it is important to note that other studies from our lab have reported a general, non-specific response ‘stickiness,’ where participants often simply repeat the same strategy in the next trial (Scarampi & Gilbert, 2020), which could have contributed to this pattern.

When we used CIT to predict this effect in a simple linear regression model, we did not find a significant effect (β = -0.05, SE = 0.05, t = -1.13, p = 0.26).

To further investigate this and potentially uncover an effect masked by the influence of the points participants could win in a given trial, we re-ran the model using a logistic mixed-effects regression model. This model predicted the upcoming trial’s choice (reminder or no reminder) from the presence of a negative prediction error in the current trial (dummy variable), the ztransformed number of points on offer, and the z-transformed CIT score (between-subject covariate), as well as the interaction of CIT and negative PE. In this model, we replicated the previous ‘stickiness’ effect, with a negative influence of a negative PE on the upcoming choice, β = -0.24, SE = 0.07, z = -3.44, p < 0.001. In other words, when a negative PE was encountered in the current trial, participants were less likely to choose reminders in the next trial. Additionally, there was a significant negative influence of points offered on the upcoming choice, β = -0.28, SE = 0.03, z = -8.82, p < 0.001. While this might seem counterintuitive, it could be due to a contrast effect: after being offered high rewards with reminders, participants might be deterred from using the reminder strategy in consecutive trials where lower rewards are likely to be offered, simply due to the bounded reward scale. CIT showed a small negative effect on upcoming reminder choice, β = -0.06, SE = 0.04, z = -1.69, p = 0.09, indicating that participants scoring higher on the CIT factor tended to be less likely to choose reminders, thus replicating one of the central findings of our study. It is unclear why this effect was not statistically significant, but this is likely due to the limited data on which the model was based (see below). Finally, and most importantly, the interaction between the current trial’s condition (negative PE or zero PE) and CIT was not significant, contrary to the reviewer’s hypothesis, β = 0.04, SE = 0.07, z = 0.57, p = 0.57.

It should also be noted that this exploratory analysis is based on a limited number of data points: on average, participants had 2.5 trials (min = 0; max = 4) with a negative PE and 6.7 trials (min = 0; max = 12) with zero PE. There were more zero PE trials simply because to maximise the number of trials included in this analysis, each participant’s 8 choice-only trials were included and on those trials the participant always got what they requested (the trial then ended prematurely). Due to the fact that not all cells in the analysed design were filled, only 466 out of 600 participants could be included in the analysis. This may have caused the fit of the mixed model to be singular.

In summary, given that these results are based on a limited number of data points, some models did not fit without issues, and no evidence was found to support the hypotheses, we suggest not including this exploratory analysis in the manuscript. However, if we have misunderstood the reviewer and should conduct a different analysis, we are happy to reconsider.

Unfortunately, conducting an additional study without the forced-choice element is not feasible, as this would create imbalances in trial numbers for the design. The advantage of the current, condensed task is the result of several careful pilot studies that have optimized the task’s psychometric properties.

Scarampi, C., & Gilbert, S. J. (2020). The effect of recent reminder setting on subsequent strategy and performance in a prospective memory task. Memory, 28(5), 677–691. https://doi.org/10.1080/09658211.2020.1764974

(6) One can imagine that a process goes on in this task where a person must estimate their own efficacy in each condition. Thus, individuals with more forced-choice experience prior to choosing for themselves might have more informed choice. Presumably, this is handled by your large N and randomization, but could be worth looking into.

We would like to thank the reviewer for pointing this out, as we had not previously considered this aspect of our task. However, we believe it is not the experience with forced trials per se, but rather the frequency with which participants experience both strategies (reminder vs. no reminder), that could influence their ability to make more informed choices. To address this, we calculated the proportion of reminder trials during the first half of the task (excluding choiceonly trials, where the reminder strategy was not actually experienced). We hypothesized that the absolute distance of this ‘informedness’ parameter should correlate positively with the absolute reminder bias at the end of the task, with participants who experienced both conditions equally by the midpoint of the task being less biased towards or away from reminders. However, this was not the case, r = 0.05, p = 0.21.

Given the lengthy and complex nature of our preregistered analysis, we prefer not to include this exploratory analysis in the manuscript.

(7) Is the Actual indifference calculated from all choices? I believe so, given they don't know only till after their choice whether it's forced or not, but good to make this clear.

Indeed, we use all available choice data to calculate the AIP. We now make this clear in two places in the main text:

Page 5: “The ‘actual indifference point’ was the point at which they were actually indifferent, based on all of their decisions.”

Page 6: “Please note that all choices were used to calculate the AIP, as participants only found out whether or not they would use a reminder after the decision was made.”

(8) Related to 7, I believe this implies that the objective and actual indifference points are not entirely independent, given the latter contains the former.

Yes, the OIP and AIP were indeed calculated in part from events that happened within the same trials. However, since these events are non-overlapping (e.g., the choice from trial 6 contributes to the AIP but the accuracy measured several seconds later from that trial contributes to the OIP) and since our design dictates whether or not reminders can be used on those trials in question (by randomly assigning them to the forced internal/forced external condition) this could not induce circularity.

(9) I thought perfectionism might be a trait that could explain findings and it was nice to see convergence in thinking once I reached the conclusion. Along these lines, I was thinking that perhaps perfectionism has a curvilinear relationship with compulsivity (this is an intuition I'm not sure if it's backed up empirically). If it's really perfectionism, do you see that, at the extreme end of compulsivity, there's more reminder-setting? Ie did you try to model this relationship using a nonlinear function? You might clues simply by visual inspection.

It is interesting to note that the reviewer reached a similar interpretation of our results. We considered this question during our analysis and conducted an additional exploratory analysis to examine how CIT quantile relates to reminder bias (see Author response image 1). Each circle reflects a participant. As shown, no clear nonlinearities are evident, which challenges this interpretation. We believe that adding this to the already lengthy manuscript may not be necessary, but we are of course happy to reconsider if Reviewer 1 disagrees.

Author response image 1.

(10) [From the weaknesses listed in the public comments.] A more subtle point, I think this study can be more said to be an exploration than a deductive test of a particular model -> hypothesis > experiment. Typically, when we test a hypothesis, we contrast it with competing models. Here, the tests were two-sided because multiple models, with mutually exclusive predictions (over-use or under-use of reminders) were tested. Moreover, it's unclear exactly how to make sense of what is called the direct mechanism, which is supported by partial (as opposed to complete) mediation.

The reviewer’s observation is accurate; some aspects of our study did take on a more exploratory nature, despite having preregistered hypotheses. This was partly due to the novelty of our research questions. We appreciate this feedback and will use it to refine our approach in future studies, aiming for more deductive testing.

Reviewer #2:

(1) Regarding the lack of relationship between AD and reminder setting, this result is in line with a recent study by Mohr et al (2023:https://osf.io/preprints/psyarxiv/vc7ye) investigating relationships between the same transdiagnostic symptom dimensions, confidence bias and another confidence-related behaviour: information seeking. Despite showing trial-by-trial under-confidence on a perceptual decision task, participants high in AD did not seek information any more than low AD participants. Hence, the under-confidence in AD had no knock-on effect on downstream information-seeking behaviour. I think it is interesting that converging evidence from your study and the Moher et al (2023) study suggest that high AD participants do not use the opportunity to increase their confidence (i.e., through reminder setting or information seeking). This may be because they do not believe that doing so will be effective or because they lack the motivation (i.e., through anhedonia and/or apathy) to do so.

This is indeed an interesting parallel and we would like to thank the reviewer for pointing out this recently published study, which we unfortunately have missed. We included it in the Discussion section, extending our sub-section on the missing downstream effects of the AD factor, as well as listing it in the references on page 27.

Page 14: “Our findings align with those reported in a recent study by Mohr, Ince, and Benwell (2024). The authors observed that while high-AD participants were underconfident in a perceptual task, this underconfidence did not lead to increased information-seeking behaviour. Future research should explore whether this is due to their pessimism regarding the effectiveness of confidence-modulated strategies (i.e., setting reminders or seeking information) or whether it stems from apathy. Another possibility is that the relevant downstream effects of anxiety were not measured in our study and instead may lie in reminder-checking behaviours.”

Mohr, G., Ince, R.A.A. & Benwell, C.S.Y. Information search under uncertainty across transdiagnostic psychopathology and healthy ageing. Transl Psychiatry 14, 353 (2024). https://doi.org/10.1038/s41398-024-03065-w

(2) Fox et al 2023 are cited twice at the same point in the second paragraph of the intro. Not sure if this is a typo or if these are two separate studies?

Those are indeed two different studies and should have been formatted as such. We have corrected this mistake in the following places and furthermore also corrected one of the references as the study has recently been published:

P. 2 (top): “Previous research links transdiagnostic compulsivity to impairments in metacognition, defined as thinking about one’s own thoughts, encompassing a broad spectrum of self-reflective signals, such as feelings of confidence (e.g., Rouault, Seow, Gillan & Fleming, 2018; Seow & Gillan, 2020; Benwell, Mohr, Wallberg, Kouadio, & Ince, 2022; Fox et al., 2023a;

Fox et al., 2023b; Hoven, Luigjes, Denys, Rouault, van Holst, 2023a).”

P. 2 (bottom): “More specifically, individuals characterized by transdiagnostic compulsivity have been consistently found to exhibit overconfidence (Rouault, Seow, Gillan & Fleming, 2018; Seow & Gillan, 2020; Benwell, Mohr, Wallberg, Kouadio, & Ince, 2022; Fox et al., 2023a; Fox et al., 2023b; Hoven et al., 2023a).”

P. 4: “Prior evidence exists for overconfidence in compulsivity (Rouault et al., 2018; Seow & Gillan, 2020; Benwell et al., 2022; Fox et al., 2023a; Fox et al., 2023b; Hoven et al., 2023a), which would therefore result in fewer reminders.”

P. 23: “Though we did not preregister a direction for this effect, in the light of recent findings it has now become clear that compulsivity would most likely be linked to overconfidence (Rouault et al., 2018; Seow & Gillan, 2020; Benwell et al., 2022; Fox et al., 2023a; Fox et al., 2023b; Hoven et al., 2023a).”

P. 24: “Fox, C. A., Lee, C. T., Hanlon, A. K., Seow, T. X. F., Lynch, K., Harty, S., … Gillan, C. M. (2023a). An observational treatment study of metacognition in anxious-depression. ELife, 12, 1–17. https://doi.org/10.7554/eLife.87193”

P. 24: “Fox, C. A., McDonogh, A., Donegan, K. R., Teckentrup, V., Crossen, R. J., Hanlon, A. K., … Gillan, C. M. (2024). Reliable, rapid, and remote measurement of metacognitive bias. Scientific Reports, 14(1), 14941. https://doi.org/10.1038/s41598-024-64900-0”

(3) Typo in the Figure 1 caption: "The preregistered exclusion criteria for the for the accuracies with....".

Thank you so much for pointing this out. We haved changed the sentence in the caption of Figure 1 to read “The preregistered exclusion criteria for the accuracies with or without reminder are indicated as horizontal dotted lines (10% and 70% respectively).”

Typo in the Figure 5 caption: "Standardised regression coefficients are given for each pat".

Thank you so much for pointing this out to us, we have corrected the typo and the sentence in the caption of Figure 5 now reads “Standardised regression coefficients are given for each path.”

[From the weaknesses listed in the public comments.] Participants only performed a single task so it remains unclear if the observed effects would generalise to reminder-setting in other cognitive domains.

We appreciate the reviewer’s concern regarding the use of a single cognitive task in our study, which is indeed a common limitation in many cognitive neuroscience studies. The cognitive factors underlying offloading decisions are still under active debate. Notably, a previous study found that intention fulfilment in an earlier version of our task correlates with real-world behaviour, lending validity to our paradigm by linking it to realistic outcomes (Gilbert, 2015). Additionally, recent unpublished work (Grinschgl, 2024) has shown a correlation between offloading across two lab tasks, though a null effect was reported in another study with a smaller sample size by the same team (Meyerhoff et al., 2021), likely due to insufficient power. In summary, we agree that future research should replicate these findings with alternative tasks to enhance robustness.

Gilbert, S. J. (2015). Strategic offloading of delayed intentions into the external environment. Quarterly Journal of Experimental Psychology, 68(5), 971–992. https://doi.org/10.1080/17470218.2014.972963

Grinschgl, S. (2024). Cognitive Offloading in the lab and in daily life. 2nd Cognitive Offloading Meeting. [Talk]

Meyerhoff, H. S., Grinschgl, S., Papenmeier, F., & Gilbert, S. J. (2021). Individual differences in cognitive offloading: a comparison of intention offloading, pattern copy, and short-term memory capacity. Cognitive Research: Principles and Implications, 6(1), 34. https://doi.org/10.1186/s41235-021-00298-x

(6) [From the weaknesses listed in the public comments.] The sample consisted of participants recruited from the general population. Future studies should investigate whether the effects observed extend to individuals with the highest levels of symptoms (including clinical samples).

We agree that transdiagnostic research should ideally include clinical samples to determine, for instance, whether the subclinical variation commonly studied in transdiagnostic work differs qualitatively from clinical presentations. However, this approach poses challenges, as transdiagnostic studies typically require large sample sizes, and recruiting clinical participants can be more difficult. With advancements in online sampling platforms, such as Prolific, achieving better availability and targeting may make this more feasible in the future. We intend to monitor these developments closely and contribute to such studies whenever possible.