The Infuence Of Focused Attention And Open Monitoring Mindfulness Meditation States On True And False Memory Part 2

The Deese‑Roediger‑McDermott (DRM) Task

The DRM is a word-learning task designed to provoke and test the formation of semantic-associative false memories (Roediger & McDermott, 1995). The current work employed a modified DRM paradigm. Although the typical DRM paradigm consists of 12–15 word-learning lists, 6 lists (see Table 1) were utilized for the current experiment (Roediger & McDermott, 1995). 

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Each list consisted of 15 words (study items) and 1 critical lure item which was not presented (Roediger & McDermott, 1995). Based on standard DRM protocols (e.g. Gallo & Roediger, 2002; Pardilla-Delgado & Payne, 2017; Roediger & McDermott, 1995), words from each list were ordered in decreasing relatedness to the critical lure.

Whilst previous work addressing mindfulness meditation influences on false memory has employed memory retrieval tasks involving recognition (Baranski & Was, 2017) or recognition and recall (Ayache et al., 2022; Rosenstreich, 2016; Sherman & Grange, 2020; Wilson et al., 2015) tests, in the present work, we assessed true and false memory retrieval based on recall and recognition tests as false memory in the DRM task is robust under recall and recognition retrieval conditions (Coburn et al., 2021).

Procedure
Due to the COVID-19 pandemic and associated social distancing health requirements and state-wide lockdowns precluding in-person contact, the experiment was conducted remotely. Experiment scripts were generated in E-Prime 3 and packaged in E-Prime Go (Psychological Software Tools Inc., Sharpsburg, PA). Four versions of the experiment were created — 2 including FAM and 2 with OMM but with counterbalanced orders for DRM word list sets in pre- and post-meditation phases. Individuals who were interested in participating contacted the researcher via email. Eligible participants were required to electronically sign and return the consent form before being randomly allocated to the FAM or OMM group. The participant was then emailed the link to the online survey, the experiment instructions, and the link for the script corresponding to their group allocation.

Online Survey

Participants followed a link to LimeSurvey where they answered demographic questions, including their age and gender, history of sleep difficulties, drug or alcohol dependence, cognitive, attention, or psychiatric diagnosis, and intellectual impairments. Participants then completed the MAAS. After completing the 5-min survey, participants followed a separate emailed link to download the E-prime Go experiment script, which ran on the participant’s computer. The procedure for the remote experiment is presented in Fig. 1.

Pre‑meditation Learning Phase

The experiment began with the first, pre-meditation, learning phase of the DRM paradigm. During the learning phase, 3 lists comprising 15 words each were presented on the screen sequentially for 1500 ms with a 10-s rest interval between lists (see Fig. 2). Participants were exposed to 3 DRM lists from Roediger et al. (2001) at pre-meditation (Table 1, set A) and 3 lists post-meditation (Table 1, set B), depending on their allocated world list set order. The presentation of sets A and B were counterbalanced to account for order effects. Participants were instructed to commit words to memory as best they could.

Pre‑meditation Recall Phase

Immediately following the learning phase, participants began the pre-meditation recall phase of the experiment which required participants to recall as many words from the learning phase as they could. Participants were instructed to type, one at a time and in any order, all the words that they recalled studying (see Fig. 2).

Mindfulness Induction

Following the pre-meditation learning and recall phase, participants completed an 8-min session of either FAM or OMM. The meditation was described to participants as an auditory cognitive task. In both conditions, a pre-recorded audio, presented as part of the E-Prime Go experiment script, was presented in English through headphones connected to the participant’s personal computer. Participants were instructed to remain seated for the task, to close their eyes, to refrain from moving and sleeping, and to follow the instructions of the audio-guided exercise as best as possible. 

The instructions for FAM and OMM were based on transcripts that were previously used by Immink et al. (2017) and have been found to influence cognitive control (Colzato et al., 2015a). In both conditions, an accredited male meditation teacher voice-guided participants through the meditation. Following the completion of their respective meditation session, participants completed ratings on their meditation experience related to perceived effort, motivation for, and success in completing the mindfulness technique. Ratings were obtained based on a sliding scale on a 100-point visual analog scale (VAS), with the left anchor text, “None”, and the right anchor text, “Maximum”. 

For meditation Effort, participants were asked to rate, “How much effort was required to complete the cognitive auditory task?”. For meditation Motivation, participants were asked to rate, “How motivated were you to complete the cognitive auditory task?”. For meditation Success, participants were asked to rate, “How successful were you in completing the cognitive auditory task?”.

Participants in the FAM group were guided step by step to focus and sustain attention on their breathing. If mind wandering occurred, participants were instructed to return attention to their breath. In the OMM group, participants were guided step-by-step to monitor their awareness of their breathing, thoughts, feelings, and bodily sensations from moment to moment without judgment or emotional reactivity.

Post‑meditation Learning Phase

Immediately after, participants began another, alternate learning phase of the DRM paradigm. Other than the presentation of a separate set of word lists, the second learning phase was identical to the pre-meditation learning phase.

Post‑meditation Recall Phase

This phase involved the same conditions as the pre-meditation recall phase. In total, the online experiment took approximately 20 min.

Recognition Test

The recognition tests consisted of 120 trials where a true memory, false memory, or distractor word was presented individually, and participants had a two-choice forced response to indicate if the word was previously studied in pre- and post-meditation lists or not. The trials consisted of 90 studied words (true memory) from pre and post-meditation word lists, 6 critical item words (false memory) from pre- and post-meditation word list sets, and 24 distractor words, which were non-studied words from lists described by Roediger et al. (2001). 

Recognition test performance was based on accuracy and reaction time. A correct response was when the participant responded to a true memory word as being previously studied or responded to a false memory word or a distractor word as not being previously studied. Reaction time was calculated as the latency between word appearance and response entry. The rationale for the inclusion of recognition reaction time performance was to assess if recognition accuracy was influenced by a potential trade-off between the latency of responding and the accuracy of the response. No feedback was provided after responses and a 1-s interval intervened in word presentations.

Data Analysis

Data analysis was conducted in IBM SPSS Statistics for Windows, Version 27. Separate independent samples t-tests were conducted to assess if the mindfulness meditation groups significantly differed in terms of participant age and mindfulness disposition, the latter based on MAAS scores. Age and MAAS data were not provided by one participant in the OMM group. Chi-square tests were conducted to test for group differences in gender distribution and the distribution of DRM word list order between pre- and post-meditation. Additional independent samples t-tests were conducted to test for group differences in ratings of meditation sessions related to effort, motivation, and perceived success. Pearson correlation coefficients were calculated between participant MAAS scores and meditation ratings.

For each participant and recall test (i.e. pre- and post-meditation), the recall percentage was calculated for true memory (studied items) and false memory (critical items). Participant recall percentages underwent outlier detection. Although outlier detection identified two high values (100%) in the FAM group and two high values (100%) in the OMM group for false memory recall percentage at premeditation and two high values (62.2%, 71.1%) in the FAM group for true memory recall at post-meditation, these values were considered to reasonably refect recall percentage performance and thus, meaningful for the present purpose. Therefore, these values were not excluded from inferential analysis. 

Data were then analyzed for normality. The Shapiro–Wilk test was used as it is deemed appropriate for small sample sizes (Le Boedec, 2016). All data were normally distributed except for the false memory recall percentage variable which violated normality (p=0.003). However, skew and kurtosis for false memory recall percentage did not breach the cut-off score of 2 and thus were considered within acceptable limits of robustness for an analysis of variance (ANOVA; Field, 2009). 

Therefore, all recall percentage data underwent parametric inferential analysis. Recall percentage was submitted a 2 (Group: FAM, OMM)×2 (List Order: A-B, B-A)×2 (Memory Type: True, False)×2 (Test Time Point: Pre- and Post-meditation) ANOVA with repeated measures on the latter two factors. The List Order factor reflected whether participants studied word list sets A or B at pre-meditation recall and then the other word list at post-meditation recall (i.e. Orders AB or BA) (see Table 1 for word lists under sets A and B). 

If participant age, MAAS scores, or meditation rating VAS scores significantly differ between groups, these were to be included as covariates in an analysis of covariance using the factors outlined above. The locus of any significant interactions was evaluated with post hoc simple main effect analysis using the least significant difference (LSD).

To test if heightened true and false memory recall was associated with trait mindfulness (Ayache et al., 2022; Yeh & Lu, 2017), Pearson correlation coefficients were calculated between MAAS scores and pre- and post-meditation true and false memory recall. We also included meditation effort, success, and motivation ratings in Pearson correlation coefficient calculations, based on the notion that perceived effort and self-efficacy, or success, in completion of the meditation technique, might indirectly influence true and false memory recall. 

For example, higher effort ratings associated with completing FAM have been associated with higher mindfulness state effects on inhibitory control (Yamaya et al., 2023), whilst higher effort ratings for OMM have been associated with greater state effects on motor sequence learning (Immink et al., 2017). We correlated self-reported meditation motivation with true and false memory because motivation has been reported to reflect the quality of the meditation state (Spanos et al., 1980). Pre- and post-meditation counts of recalled words not appearing in the studied lists or representing word list critical items were compared between FAM and OMM groups using generalized linear regression modeling with a Poisson distribution and Wald chi-square test.

For each participant, the recognition test percent accuracy and mean reaction time were calculated according to word type (true memory, false memory, distractor) and word list study phase (pre-meditation, post-meditation). 

The word list factor was included in the analysis to test if recognition accuracy or reaction time was dependent on the word being presented before or after the single-session meditation. Recognition accuracy and mean reaction time for true and false memory words were separately submitted to 2 (Group: FAM, OMM) × 2 (List Order: A-B, B-A) × 2 (Memory Type: True, False) × 2 (Test Time Point: Pre- and Postmeditation) ANOVA with repeated measures on the latter two factors. Recognition accuracy and mean reaction time for distractor words were separately submitted to 2 (Group: FAM, OMM)×2 (List Order: A-B, B-A) ANOVA. MAAS scores or meditation rating VAS scores were to be included as covariates in the event of significant meditation group differences in these measures. The locus of any significant interactions was evaluated with post hoc simple main effect analysis using the least significant difference (LSD). Pearson correlation coefficients were calculated between MAAS scores, meditation VAS ratings, pre- and post-meditation true and false memory, and distractor word recognition accuracy and reaction time. The motivation for conducting these correlation analyses was similar to that described for true and false memory recall.

Results

Tests for Group Differences: Participant Characteristics, Meditation Ratings, and DRM List Order

Mindfulness meditation style groups did not significantly differ in terms of gender distribution (p=0.54), participant age (p = 0.52), or MAAS score (p = 0.24) (see Table 2). MAAS scores in the present sample, 3.75, are comparable to the mean score of 3.97 reported by Brown and Ryan (2003) for non-meditating community adults. The present sample is below the mean score of 4.38 reported for active (Brown & Ryan, 2003), supporting the notion that the current sample was naïve mindfulness meditators. Meditation VAS scores for Efort (p=0.60), Motivation (p=0.42) and Success (p=0.38) did not significantly differ between FAM and OMM (see Table 2). MAAS scores were not significantly correlated with meditation VAS ratings for Efort (p=0.08) or Motivation (p=0.14) but were significantly correlated with meditation Success ratings, r(33)=0.44, p=0.01. Groups did not significantly differ concerning the distribution of DRM word list order between pre- and post-meditation (p=0.49) (see Table 2).

Analysis of True and False Memory Recall

Analysis of recall percentage revealed significant main effects of Memory Type (F[1, 30] = 14.08, p < 0.001, η2 partial=. 32) and List Order (F[1, 30]=6.10, p=0.019, η2 partial= 0.17. There was a significant 2-way interaction of Memory Type and Test Time Point (F[1, 30]=18.00, p < 0.001, η2 partial = 0.382) but this was superseded by a significant Memory Type × Test Time Point × List Order interaction, F(1, 30) = 6.91, p = 0.013, η2 partial = 0.19. All other main effects and interactions were not significant. 

Simple main effects analysis for the significant 3-way interaction revealed that for true memory type, there was no significant difference in recall percentage between pre- (Mean = 32.75%, SE = 3.72) and post-meditation (Mean = 33.04%, SE = 3.20, p = 0.94) for the AB list order group. For the BA list order group, true memory recall at pre-meditation (Mean = 31.57%, SE = 3.77) was significantly higher than at post-meditation (Mean=22.84%, SE=3.24, p=0.041). True memory recall for the AB group was significantly higher than the BA group at post-meditation (p=0.033) but not pre-meditation (p = 0.83). For false memory recall, the AB list order group did not exhibit significant differences between pre- (Mean = 37.73%, SE = 7.19) and post-meditation (Mean = 50.93%, SE = 8.10, p = 0.18) tests. 

The BA list order group demonstrated significantly higher true memory recall at post-meditation (Mean=47.88%, SE=8.22) than pre-meditation (Mean=1.67%, SE=7.30, p<0.001) tests. The AB list order group demonstrated significantly higher false memory recall at pre-meditation (p<0.001). No significant list order group differences were observed for post-meditation false memory recall (p = 0.79). True and false memory mean recall percentages for FAM and OMM groups at pre- and post-meditation retrieval tests are presented in Table 3 and illustrated in Fig. 3.

Correlation of MAAS Scores and Meditation Ratings with True and False Memory Recall

MAAS scores were not significantly correlated with recall percentages for true and false memory at pre- and post-meditation tests (all p>0.091). Meditation Effort and Motivation VAS scores were not significantly correlated with true or false memory recall at pre- and post-meditation tests (all p>0.06). Meditation Success VAS scores were not significantly correlated with false memory recall (all p>0.22) or true memory recall at the pre-meditation test (p=0.52). However, there was a significant positive correlation between meditation Success VAS scores and true memory recall percentage at post-meditation, r(34)=0.43, p=0.011.

Analysis of Non‑studied or Critical Item Words
Groups did not significantly differ concerning the count of recalled words not appearing on studied lists or representing critical items at the pre-meditation recall test (Mean=1.09, 95% CI: 0.79, 1.50, p=0.85) or post-meditation recall test (Mean=1.32, 95% CI: 0.67, 1.98, p=0.192).

Analysis of True and False Memory Recognition

Analysis of recognition accuracy for true and false memory words revealed a significant main effect of Memory Type, F(1,30) = 51.31, p < 0.001, η2 partial= 0.63. Recognition accuracy for true memory words (M = 63.14%, SE=2.83) was significantly higher than for false memory words (M=20.87%, SE=3.88). No other significant main effects or interactions were found for the recognition accuracy of true and false memory words (all p>0.17). Analysis of recognition mean reaction time for true and false memory words revealed no significant main effects or interactions (all p>0.19). No significant main effects or interactions for Group or List Order were observed in the analysis of distractor word accuracy and mean reaction time (all p>0.31).

Correlation of MAAS Scores and Meditation Ratings with True and False Memory Recognition

Correlation analysis of MAAS scores and meditation Effort, Motivation and Success VAS ratings with recognition accuracy and mean reaction time revealed no significant correlations between MAAS scores or meditation Motivation VAS scores and recognition test performances (all p > 0.069). Meditation Effort VAS scores exhibited a significant positive correlation with recognition accuracy for post-meditation false memory words (critical items of post-meditation studies lists), r(34) = 0.36, p = 0.021. Meditation Success VAS scores had a significant positive correlation with recognition accuracy for post-meditation true memory words (r[34] = 0.42, p = 0.014) and a significant negative correlation with post-meditation false memory word recognition accuracy (r[34] = − 0.38, p = 0.027).

Discussion

Disparate findings exist in the literature regarding the influence of mindfulness meditation on true and false memory formation. Previous research has not accounted for distinct cognitive control states that arise from different mindfulness meditation styles (Lippelt et al., 2014). Thus, the present aim was to investigate if FAM and OMM states provide distinct influences on true and false memory. Based on the metacontrol state model (Hommel, 2015; Hommel & Colzato, 2017), it was predicted that increased cognitive control associated with FAM states would result in reduced false memory and increased true memory retrieval. As OMM states are thought to weaken cognitive control (Hommel & Colzato, 2017; Lippelt et al., 2014), it was first hypothesized that OMM would lead to an increased incidence of false memory.
FAM and OMM Mindfulness States Might Increase False Memory

Contrary to the predictions, FAM and OMM did not differ in false memory recall at post-meditation. However, a significant increase in false memory recall percentage between pre and post-meditation tests suggests that both styles of mindfulness meditation might provide comparable influences on false memory formation. Single sessions of FAM and OMM might afford more generalized memory representations of encoded information (Schacter et al., 2011) either by heightening the activation of semantically related information (Gallo, 2010; Gallo & Roediger, 2002; Roediger & McDermott, 1995) or strengthening gist representation (Brainerd & Reyna, 2002). Augmenting generalized memory through mindfulness states might explain the wider benefits of mindfulness meditation on semantic memory tests, such as the verbal fluency task (Heeren et al., 2009; Zeidan et al., 2010).

Increased false memory recall following FAM and OMM mindfulness styles demonstrated in the present work is consistent with some of the previous studies investigating mindfulness meditation influences on false memory (Rosenstreich, 2016; Wilson et al., 2015). For instance, Wilson and colleagues (2015) reported a significant increase in false memories in a single session of breath-focused mindfulness meditation, which is very similar to the FAM technique employed in the present work. Increased false memory following OMM extends previous literature by demonstrating that mindfulness meditation influences on false memory might not be limited to FAM styles of meditation. 

To our awareness, this is the first demonstration of increased false memory following meditation states based on the OMM style alone. Previous demonstration of increased false memory following OMM has been when this style is combined with the FAM style in the meditation session (Calvillo et al., 2018; Meeks et al., 2019; Rosenstreich, 2016). The present findings illustrate that the inclusion of the FAM style is not necessary to elicit false memory formation following single-session meditation. This can be elicited by the OMM style in itself.

As with previous demonstrations, increased false memory following FAM and OMM styles was based on a single session of meditation. Meditation training might be necessary to elicit distinct influences of FAM and OMM styles on true and false memory formation in line with what might be predicted from the meta control state model (Hommel & Colzato, 2017) and empirical evidence of distinct cognitive control states established by these styles (Lippelt et al., 2014). Comparable effects of FAM and OMM styles on false memory demonstrated in the present experiment might be accounted for by meditation naïve participants’ reduced ability to achieve an OMM state and consequently, defaulting to a FAM state.

The present findings are in contrast with previous demonstrations of decreased false memory from mindfulness meditation or a lack of effect of mindfulness on false memory (Ayache et al., 2022; Baranski & Was, 2017; Sherman & Grange, 2020). Baranski & Was, (2017) explained that variable results could indicate that the effects of mindfulness meditation on false memory are not robust and susceptible to several factors, such as the participant’s degree of meditation training/exposure, mindfulness disposition, meditation session duration, and the number of studied word lists. Studies reporting either a decrease in false memories (Baranski & Was, 2017) or no change in false memory recall or recognition at post-meditation (Sherman & Grange, 2020) did not control for prior meditation experience or cognitive training. 

Ayache et al. (2022), Rosenstreich & Ruderman (2017), and Rosenstreich (2016) previously controlled for prior meditation experience in their demonstrations of mindfulness meditation state effects on false memory. The rationale for this control is that formal meditation experience can increase dispositional mindfulness, which presents a potential confound in the investigation of mindfulness state effects on false memory. We did not observe any significant correlation between mindfulness disposition and false memory recall indicating that such controls might not be necessary, and more widely, that mindfulness disposition is not a confounding factor in previous work. We also set out to account for potential individual differences in mindfulness state effects based on self-reported effort (Immink et al., 2017; Yamaya et al., 2023), success (Brandmeyer et al., 2019) and motivation (Spanos et al., 1980). 

We did not find any correlation between self-reported effort, success, or motivation with false memory recall following mindfulness meditation. The present findings thus suggest that mindfulness meditation state effects on false memory recall do not depend on individual differences in perceived meditation efficacy or meditation motivation. However, it should be noted that recognition accuracy was dependent on individual differences in self-reported meditation effort and success. Meditation effort ratings were positively correlated with the accurate rejection of false words as previously studied following the meditation state. Ratings of meditation success were positively correlated with accurate recognition of list words presented after the meditation state. 

Thus, it is apparent that higher self-reported effort and success, which might reflect perceived efficacy in completing the mindfulness technique, are associated with a heightened ability to distinguish true and false memory words in the recognition test. However, this explanation is complicated by the observation that higher self-reported success was also associated with poorer performance in rejecting false memory words associated with lists encoded after the meditation state. Further research is needed to address unclear relationships between self-reported meditation effort and success and recognition accuracy. Work is also needed to address why self-reported meditation measures were correlated with recognition accuracy but not memory recall. The present findings highlight that individual differences in perceived meditation effort and success need to be considered in research investigating meditation state effects on memory.

Mindfulness meditation's influence on increased false memory reported here must be considered with some caution. First, the present demonstration does not include a control condition. Therefore, it remains plausible that the increased false memory recall observed at post-meditation is due to repeated encoding and retrieval tests, and not due to exposure to mindfulness meditation in the second round of encoding and retrieval. Previous work has demonstrated that practice effects are high for repeated memory tests (Benedict & Zgaljardic, 1998). 

Although alternate DRM lists were used at the pre- and post-meditation phases, participants may have experienced increased false memory formation as a function of test-specific practice. That is, participants may have learned during the pre-meditation DRM phase that the lists followed a specific theme or gist (e.g. sleep) and applied this knowledge to the post-meditation learning phase. The absence of a control group prevents confident conclusions regarding the source of increased false memory, as these could be attributed to practice effects associated with the pre-/post-design. However, if the current findings were a consequence of practice, then an increase in true memory recall would also be expected. The current study did not detect such an increase, raising some doubt about practice effects as an explanation for the present results. Nevertheless, future studies should compare FAM and OMM to a no-meditation, control group to ensure that increases in false memory formation are a function of mindfulness meditation.

A second reason to treat the present demonstration of increased false memory following mindfulness meditation with caution lies in the possibility that the main effect of the test time point might have been influenced by the order of word lists used in pre- and post-meditation conditions as illustrated in the complex three-way interaction based on list order, test time point, and memory type factors. Indeed, it should be noted that, similarly to the lack of control regarding previous meditation experience, research to date has also typically not controlled for previously established variables related to associative processing and the DRM lists in particular, including forward (Brainerd & Wright, 2005) and backward associative strength (Cann et al., 2011; Howe, Wimmer & Blease, 2009), and other constructs such as mean gist strength (Brainerd et al., 2020). 

Future work would be able to more thoroughly understand how meditation may influence false memory, and more important, which aspects and memory processes are related to false memory if such constructs are measured and accounted for. This is highlighted in the work of Howe, Wimmer, and Blease (2009), who note that there exist differences in how false memories may be created between children and adults, potentially due to differences in inhibitory control and automaticity; this has implications for our understanding of false memory and links the process to attentional control mechanisms potentially tagged by meditation. Thus, analyses such as the ones noted here may be important next steps in this literature.

FAM and OMM Mindfulness States Do Not Influence True Memory

As FAM is thought to increase the cognitive control state, the second hypothesis predicted that this technique would lead to a greater increase in true memories than OMM relative to a pre-meditation control. This hypothesis was not supported, as FAM and OMM states did not differ concerning true memory recall. Additionally, an increase in true memory formation from pre- to post-meditation was not detected for either group, indicating that whilst the cognitive control states induced by single sessions of FAM and OMM increase false memories, they do not influence true memory formation.

The current findings contradict previous reports of increased true memory following mindfulness meditation (Baranski & Was, 2017; Rosenstreich, 2016). This can be accounted for by differences in the meditation experience provided before establishing the meditation state before memory encoding. For example, Rosenstreich (2016) trained participants in mindfulness meditation for 5 weeks as part of demonstrating increased true memory from mindfulness meditation. Basso et al., (2019) found that increases in true memory formation were evident after 8 but not 4 weeks of meditation training. 

Thus, in contrast to false memory, deriving increased true memory from single-session mindfulness meditation appears to rely on previous meditation training (Brown et al., 2016; Heeren et al., 2009; Lykins et al., 2012; Nyhus et al., 2019). The absence of increased true memory following mindfulness meditation demonstrated in the present work might be accounted for by the absence of meditation training in this sample.

That true memory, but not false memory, relies on previous mindfulness training and can be explained by a hierarchy of memory processing where generalized memories are more readily retrieved than perceptually or contextually detailed memories (Haque & Conway, 2010). Thus, smaller increments in attention control from single-session FAM and OMM in meditation novices might be sufficient to demonstrate immediate increases in low-level, semantically organized memory associated with false memory. Improvements in higher-order memory processes contributing to true memory, on the other hand, might require a higher degree of attention control, which in turn requires more long-term structural or functional neural adaptations that rely on mindfulness meditation training (Lardone et al., 2018).

Limitations and Future Directions

There are several potential reasons why the present study did not detect a significant difference between FAM and OMM on true and false memory formation. First, these techniques are not mutually exclusive, as OMM is recognized to involve aspects of FAM (Lee et al., 2018). Additionally, FAM is deemed suitable for beginners, whilst OMM is considered a more advanced technique (Lippelt et al., 2014). 

Consequently, the OMM group may have been influenced by a cognitive state more closely resembling that of FAM. Although FAM does not necessarily entail aspects of OMM techniques, participants in the FAM group may not have adhered to the specific instructions of their allocated meditation. Therefore, it cannot be confidently concluded that FAM and OMM groups achieved the distinct cognitive control states necessary to exert opposing influences on attention and subsequently memory. Due to differences in difficulty between FAM and OMM, future studies should consider training meditation-naïve participants in these techniques. 

Additionally, as FAM and OMM states have demonstrated differing patterns of neural activity (Yordanova et al., 2020), electroencephalography (EEG) may prove a useful tool for future research to objectively measure the extent to which participants are achieving these distinct states. In line with previous mindfulness meditation and false memory studies (Ayache et al., 2022; Sherman & Grange, 2020), future work should include manipulation checks to ensure that participants establish the intended distinct FAM and OMM states following encoding.

Secondly, the current project is limited by its small sample size which reduced the ability to detect a significant difference between groups. A post hoc power analysis revealed that the current study lacked sufficient power (0.41) to detect a significant difference between FAM and OMM groups at an alpha level of 0.05 and a moderate effect size (Faul et al., 2007). However, it should be noted that significant effects are argued to be reliable even under low statistical power conditions (Gelman & Carlin, 2014). Future research must recruit a much larger sample to ensure sufficient power to detect any potential differences between these techniques on true and false memory formation.

The current sample did include participants reporting insomnia, drug or alcohol dependence, and diagnoses related to attention or cognitive impairments and psychiatric conditions. We intended to be inclusive of these participant characteristics given their presence in the general population. Nevertheless, the presence of these in the sample could have potentially influenced the results differently from what might be expected in a sample free from any cognitive, sleep, psychiatric, or substance dependence conditions.

Another limitation of the present study was the lack of a controlled laboratory environment which prevented participant supervision and control over distracting input. Due to the COVID-19 pandemic, participants completed the experiment conditions in their homes. Consequently, participants may have more readily disengaged from the meditation due to distraction, pervasive mind-wandering, or boredom. As mind-wandering has been found to adversely affect cognitive performance (Zeidan et al., 2010), it is possible that participant disengagement, or lack of adherence to study protocol, may have influenced the results. 

The sample included participants who self-reported poor sleep quality, substance dependence, cognitive impairments, or psychiatric conditions. Participants reporting these histories were not excluded to allow for an inclusive sample within the age range. Nevertheless, there is potential that these participants might have differed concerning how they completed the mindfulness techniques, as well as the DRM and retrieval tests.

Another limitation is that our analysis of recall percentage did not account for the potential influence of recall duration. The present recall tests did not control the amount of time available to recall items. Therefore, it is possible that whilst recall percentages did not differ between mindfulness meditation styles, the amount of time used to recall each item might have differed. Finally, the provocation of semantic-associative false memories using the DRM paradigm may not generalize to real-world false memories (Pardilla-Delgado & Payne, 2017; Zhu et al., 2013). Therefore, future research should investigate the influence of FAM and OMM states on different memory tasks that may better reflect real-world scenarios. 

In 2017, Ayache et al., (2022) alone have undertaken the most ecologically salient evaluation of mindfulness meditation influences on false memory using a virtual environment-based DRM task. The misinformation paradigm, whereby participants are exposed to an event, given misleading post-event information, and are subsequently asked to recall the details, maybe more generalizable to real-world forms of false memory (Nichols & Loftus, 2019). Thus, may help to elucidate the effects of FAM and OMM on everyday memory generalization. 

Additionally, individual differences in attention have been linked to differences in the production of misinformation (Rivardo et al., 2011). Therefore, alternative false memory measures may engage separate attentional processes and thus may help to detect any potential differences between FAM and OMM states on true and false memory recall. Future work should continue to address whether individual differences in mindfulness disposition, which has been shown to moderate meditation influences on false memory (Ayache et al., 2022; Yeh & Lu, 2017) influence how FAM and OMM states influence false memory formation.

Acknowledgments

We thank two anonymous reviewers for their insightful and constructive comments on previous versions of this publication manuscript. This work and preparation of this publication were undertaken on the traditional land of the Kaurna people. We respect the cultural relationships the Kaurna people have with their country and acknowledge them as the traditional owners and occupants of the Adelaide Plains.

Author Contribution

SB, AC, and MI designed the experiment and contributed to data analysis and manuscript preparation. MI produced the mindfulness meditation audio recordings and generated the scripts for remote data collection. SB was responsible for remote data collection as well as data management.

Funding

Open Access funding enabled and organized by CAUL and its Member Institutions

Data Availability

Data is available on request from the authors.

Declarations

Ethics Approval All procedures performed in this experiment were approved by the University of South Australia Human Research Ethics Committee.

Consent to Participate 

By the 1964 Declaration of Helsinki, electronic informed consent was obtained from all participants.

Conflict of Interest 

The authors declare no competing interests.

Open Access

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third-party material in this article are included in the article's Creative Commons license unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

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