Participants

To estimate a-priori required sample size, we used G-power software with the following statistical assumptions: type 1 error of 5% and minimum statistical power of 95% [23]. Based on previous studies, moderate associations were expected between the study variables [4]. For this reason, minimum sample size was estimated at 266 respondents. The overall sample consisted of 572 participants from the USA and the UK. Participant’s ages ranged from 18 to 80 with mean age of 42.95 years (SD = 14.03). Approximately 50% of the sample (n = 285) identified as male, 49.5% identified as female (n = 283) and the rest identified as none or didn’t report their gender. Number of education years ranged between 10 to 35 with average of 15.41 years (SD = 3.46). 95.26% of the sample were Caucasian. As for relationship status, 71% reported they were in a relationship, 29% reported they were not. As for religiosity level, 53.5% reported they were not religious at all, while less than 1% reported they were very religious. Participants were compensated with a payment of 1.5 pounds sterling (about 1.8 USD), which equals to about 7 pounds sterling per hour.

Procedure

All data was collected between February 15–16, 2022. Participants were recruited through Prolific (online participant recruitment platform; www.Prolific.co) and received monetary compensation. Recently, online panels have become a common way to target and reach respondents in social science research [24, 25]. The prolific panel was found to have better quality than other recruitment platforms (e.g., Amazon Mechanical Turk) [26, 27]. All participants completed a series of online questionnaires. Prior to filling out the questionnaires, participants provided a signed informed consent, which specified the purpose of the research, its procedures, and the voluntary nature of participation. Participants were guaranteed anonymity, and no disclosure of personal details was required. The study was approved by the IRB in the first author’s academic institution (IRB number 2021–380).

Measures

Synchronicity Awareness was assessed with the Synchronicity Awareness and Meaning-Detecting (SAMD) Scale [4.] The SAMD scale is comprised of two subscales: (a) synchronicity awareness (SA), and (b) synchronicity meaning-detecting (MD). Since the first dimension refers to the frequency of specific events and the second dimension to the subjective perception of such events, a different response format (i.e., 6- and 7-point scales) and different number of items are adopted for each dimension.

The SA subscale refers to awareness of the occurrence of synchronicity events in daily lives. It involves 9 items using a 6-point scale (0 = never, 1 = once, 2 = twice or more, 3 = rarely, 4 = often, 5 = all the time). An example item is: "I ran into something or someone that I thought about in an unexpected place". Internal reliabilities in the current study were good: Cronbach’s α and McDonald’s ω coefficients were .81. As for the prevalence of synchronicity experiences, 92.13% to all participants reported they experienced at least one or more such encounters.

The MD subscale refers to the meaning detected in the synchronicity events or experiences. It involves 13 items using a 7-point scale (1 = not at all to 7 = to a high degree). An example item is: "I believe that unexplained events enable new discovery and development". Internal reliabilities in the current study were good: Cronbach’s α and McDonald’s ω coefficients were .91.

Dispositional trait mindfulness was assessed using two common instruments. One instrument was the shortened form of the five facets of mindfulness questionnaire (FFMQSF) [28]. The five facets of dispositional mindfulness are assessed by measuring: nonreactivity (the ability to withhold thoughts, emotional expressions, and physical actions), ability to observe (the direction of attention to the surroundings), acting with awareness (being aware of inner and sensations and outer stimuli), ability to describe (the ability to verbalize thoughts and feelings), and being non-judgmental (accepting the self and the others as they are). It’s 24 statements (e.g., "I notice the smells and aromas of things") were rated on a 6-point Likert scale (1 = "never or very rarely true", 5 = "very often or always true"). Items of two facets, awareness and being non-judgmental, were presented in reveres scales, such that high score corresponded with being less aware and more judgmental; these scales were transformed before the analysis of the data to correspond with the direction of the other scales. Regarding the internal reliabilities of the subscales: nonreactivity subscale had Cronbach’s α and McDonald’s ω coefficients of .85, ability to observe subscale had Cronbach’s α and McDonald’s ω coefficients of .85, acting with awareness subscale had Cronbach’s α and McDonald’s ω coefficients of .87, ability to describe subscale had Cronbach’s α and McDonald’s ω coefficients of .88, and being non-judgmental subscale had Cronbach’s α of .82 and McDonald’s ω coefficient of .83.

Another instrument employed to assess dispositional mindfulness, was the Mindfulness Attention and Awareness Scale (MAAS) [7]. The MAAS consists of 15 items measured on a 6-point Likert scale (1 –Almost always, to 6 –Almost never) that asks participants about how they normally go through activities in their daily lives (e.g., “I rush through activities without being really attentive to them”). Internal reliability was Cronbach’s α of .88 and McDonald’s ω coefficient of .89.

Trait socio-cognitive mindfulness was assessed with the Langer mindfulness Scale which assesses novelty seeking, novelty producing, and engagement (LMS) [29]. Novelty seeking is measured by items such as “I do not actively seek to learn new things”. The subscale novelty producing includes items such as “I find it easy to create new and effective ideas”, and the subscale engagement includes items such as “I ‘get involved’ in almost everything I do”. Participants rate their agreement with items on a 7-point scale ranging from "1 = strongly disagree" to "7 = strongly agree". In the present research, the subscales demonstrated adequate to good internal consistencies. Novelty seeking had Cronbach’s α and McDonald’s ω coefficients of .82, novelty producing had Cronbach’s α of .75 and McDonald’s ω coefficients of .77 and engagement had Cronbach’s α of .62 and McDonald’s ω coefficients of .63.

Encoding style was assessed with Encoding Style Questioner (ESQ) [30]. This scale consists of 9 items evaluating the level of internal encoding. Representative items include, "For a split second from a distance, I sometimes mistake strangers for people I know", and "Sometimes when I’m driving, I see a piece of paper or a leaf being moved by the wind, and for a split-second think that it might be an animal". Participants respond to each item using a 6-point Likert type scale, ranging from "1 = Never" to "7 = Often". A high score on the ESQ reflects an internal encoding style, whereas a low score reflects an external encoding style. In the current study the ESQ had Cronbach’s α of .84 and McDonald’s ω coefficients of .85.

Statistical plan

Data were cleaned using Microsoft Excel and analyzed with JASP version 0.17.1 [31]. The sample was randomly split into two datasets of approximately equal size and with approximately equal number of men and women: the Exploratory Factor Analysis (EFA, N = 290) was performed on one half, and the Confirmatory Factor Analysis (CFA, N = 282) was performed on the other half. Pearson correlations were analyzed to assess the correlations between total assessments’ scores (i.e., SA, MD, MAAS, FFMQ, ESQ).

EFA

The EFA was aimed to examine whether Synchronicity Awareness (SA) and Meaning Detection (MD) items are loaded onto two separate factors, that are distinguishable from the items and factors of mindfulness and encoding style. To this end, all items from the SA, MD, Five Facets of Mindfulness Questionnaire (FFMQ), Langer Mindfulness Scale (LMS), and Encoding Style Questionnaire (ESQ), were submitted to the EFA. Items of the Mindfulness Attention and Awareness Scale (MAAS) were excluded because they mainly overlap with the awareness facet of the FFMQ. First, Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity were conducted to confirm that our data are adequate for factor analysis. Indeed, the KMO revealed and overall MSA value of .85, and Bartlett’s Chi square was χ²(2346) = 9831.14, p < .001, thus indicating that the data are adequate for factor analysis.

Next, the EFA was conducted using a minimum residual estimation method and by applying an Oblimin rotation. The analysis yielded nine factors (factor loadings are presented in Table 1). The analysis revealed that overall, the items were loaded onto their designated factor, explaining 46% of the variance and presented a good fit (χ²(1761) = 2444.74, p < .001; RMSEA = .036 [90% CI: .033-.04], SRMR = .034, TLI = .875, CFI = .909). It seems, therefore, that the SA and MD items are distinguishable from the mindfulness and encoding style items, and they constitute two distinct constructs. Nevertheless, one item from each of the following scales, MD, SA, and ESQ, was not loaded onto its corresponding factor. For the LMS, three “engagement” items and one “novelty producing” item were not loaded onto their corresponding factors.

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Table 1. Factor loadings and uniqueness of the research items.

https://doi.org/10.1371/journal.pone.0307443.t001

CFA

The CFA was conducted to check the validity of the notion that SA and MS are two factors distinct from each other and from the well-established mindfulness and encoding style factors. To this end, 11 factors corresponding with SA, MD, ESQ, five factors of the FFMQ, and three factors of the LMS, were submitted to the CFA. FFMQ and LMS factors were submitted as eight first-order factors (i.e., without a latent factor) in order to better understand the interplay of SA and MD with mindfulness (factor loadings are presented in Table 2). Overall, the CFA indicated good fit, and provided the following goodness of fit indices: χ²(2222) = 5527.44, p < .001; RMSEA = .050 (90% CI [.047, .052]), SRMR = .069, CFI = .972, NFI = .948, GFI = .973, and TLI = .970, hence validating that SA and MD are distinguishable from the factors of mindfulness and encoding style.

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Table 2. CFA factor loadings and residual variance of the research items.

https://doi.org/10.1371/journal.pone.0307443.t002

Correlation analysis

Finally, after establishing that SA and MD are two standalone constructs, we turned to examine the correlations between the different constructs in our study. This analysis was carried on the entire sample (N = 572) and its coefficients are presented in Table 3. It was found that encoding style was mainly negatively associated with MAAS and FFMQ scores, indicating that mindfulness was associated with external encoding style. More important, Table 3 reveals that SA nor MD were correlated with age, but both were positively correlated with religiosity, indicating that participants reporting to be more religious also reported elevated rates of synchronicity awareness and meaning detection.

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Table 3. Pearson correlation coefficients between the study variables.

https://doi.org/10.1371/journal.pone.0307443.t003

As for the trait-like factors, SA exhibited a medium to strong positive association with MD, but medium to weak association with encoding style, all factors of Langer’s Mindfulness Scale, and the FFMQ’s facets of Observing and Describing. Similar associations were observed for MD, with the exception of MD being negatively associated with the FFMQ facet of Acting without judging. To sum, these associations indicate that both SA and MD may be characterized with participants’ tendency to interpret environmental cues as preexisting experiences (i.e., internal encoding style), with participants’ increased interoceptive awareness and with the ability to describe these internal feelings, as well as with increased mindful thinking. Additional analyses are presented in S1 Appendix.

Limitations and suggestions for future research

The present study has two main limitations that should be taken into consideration. First, our sample consisted of English-speaking Westerners, the majority of whom identified as Caucasians. Because the mindfulness questionnaires employed in this study were conceived by Western scholars and articulated in English, there may be a plausible confinement to the validity of our findings strictly to this demographic. Consequently, a cautious approach must be taken in extending these insights to a more universal human experience. Indeed, this caveat has been previously discussed [39], with the notion that mindfulness questionnaires may be culturally biased to some extent thus should be prudently interpreted. It should be noted, however, that our sample did not involve undergraduate students, but rather a community sample and hence more likely to represent the wide population. Furthermore, a comparison between Caucasians and non-Caucasians revealed no significant differences in any of the study variables, but in Age (Caucasians were 6 years older in average) and Religiosity (Caucasians reported to be somewhat less religious). Therefore although we cannot generalize the findings to different ethnicities than Caucasians, it seems that the experience of synchronicity may be an essential human experience and not limited to the current sample demographics. Nonetheless, Future studies should also include cultural variables in order to shed light on the question.

A second limitation lies in the correlational nature of our study. Because mindfulness and synchronicity were not cultivated but assessed, we cannot conclude that mindfulness increases synchronicity awareness. Nevertheless, in this study we sought to explore whether mindfulness and synchronicity awareness are distinct constructs as well as the interplay between them, hence investigating the impact of mindfulness on synchronicity awareness was not in the scope of the present study. It bears emphasizing that unveiling the potential causal linkage between mindfulness and synchronicity is important for better understanding the cognitive mechanisms of mindfulness and may entail some real-world implications, hence should be addressed in future studies.

Altogether, we suggest that mindfulness and synchronicity are distinct-yet-related constructs. Their intersection may reside in some bottom-up perceptual processes, as increased sensitivity to cues or broad perceptual span. Alternatively, their intersection may reside in similar top-down meta-cognitive processes occurring at the fringes of consciousness. Future studies may illuminate the underlying commonalities of mindfulness and synchronicity by comparing participants with high compared to low synchronicity awareness in perceptual capabilities or in tasks promoting processing at the fringes of consciousness. Diary or Ecological Momentary Assessment studies may also be employed to reveal the manner to which mindfulness and synchronicity awareness are intertwined. Understanding the conditions which facilitate or hinder synchronicity experiences may enrich not only the field of mindfulness, but also the related fields of spirituality, positive psychology, and psychotherapy. Future investigations in this research trajectory should prioritize encompassing a more diverse participant pool to foster inclusivity and global perspective, thereby nurturing a well-rounded comprehension of the phenomena in question.

Overall, despite its limitations, this study extends existing literature of clinical reports and case studies on the phenomenon of synchronicity by taking a step further to provide possible directions to better understand the cognitive mechanisms underlying the experience of synchronicity. This study also lay the ground for a new direction of research in the field of mindfulness and provides a new perspective on the manner to which mindfulness may shape our perception of daily experiences.