Don’t worry, be happy: Protective factors to buffer against distress associated with psychotic
Please not that this is the final author version and it can differ in detail from the
Running title: Buffering secondary distress of psychotic experiences
Anna Kuranova1*, Sanne H. Booij1,2,3, Peter de Jonge4, Bertus Jeronimus4, Ashleigh Lin5, Klaas J.
Wardenaar1, Marieke Wichers1, Johanna T.W. Wigman1,2
1 University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP)
Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
2 Department of Research and Education, Friesland Mental Health Care Services, Leeuwarden, The
3 Center for Integrative Psychiatry, Lentis, Groningen, The Netherlands
4 University of Groningen, Department of Developmental Psychology, Groningen, The Netherlands
5 Telethon Kids Institute, The University of Western Australia, Australia
* Correspondence: Anna Kuranova
Interdisciplinary Center Psychopathology and Emotion regulation (ICPE)
University Medical Center Groningen,
HPC: CC72, PO Box 30.001
9700 RB Groningen,
E-Mail: email@example.com Phone +31 6 82 74 98 95
Background: Around 6-7% of the general population report psychotic experiences (PEs). Positive PEs
(e.g. hearing voices) may increase the risk of development of psychotic disorder. An important predictor
of the transition to a psychotic disorder is secondary distress associated with PEs. We examined the
moderating effect of potential protective factors on this secondary distress.
Methods: Data come from 2,870 individuals of the HowNutsAreTheDutch study. PEs were assessed with
the Community Assessment of Psychic Experience (CAPE) questionnaire and were divided into three
subdomains ("Bizarre experiences", "Delusional ideations", and "Perceptual anomalies"). Protective
factors explored were having a partner, having a pet, benevolent types of humor, optimism and the high
levels of personality traits emotional stability (reversed neuroticism), extraversion, openness to
experience, conscientiousness, and agreeableness. We examined whether these protective factors
moderated (lowered) the association between frequency of PEs and PE-associated distress.
Results: Due to low prevalence of perceptual anomalies in the sample, this domain was excluded from
analysis. No moderating effects were observed of protective factors on the association between bizarre
experiences and distress. Having a partner and high levels of optimism, self-enhancing humor, openness,
extraversion and emotional stability moderated the association between delusional ideations and
secondary distress, leading to lower levels of distress.
Conclusions: Several protective factors were found to moderate the association between frequency and
secondary distress of delusional ideations, with high levels of the protective factors being associated
with lower levels of distress. A focus on protective factors could be relevant for interventions and
prevention strategies regarding psychotic phenomena.
Keywords: psychotic experiences, protective factors, secondary distress, CAPE, HowNutsAreTheDutch,
Compared to psychotic disorders, mild, subclinical psychotic experiences (PE) are relatively common,
with on average around 6-7% of the general population reporting any PE at least once in their life (John
J McGrath et al., 2015; Van Os and Reininghaus, 2016), although large differences between cultures have
been reported (McGrath et al., 2015; Sun et al., 2017, 2015). Most of these PEs are transient, with 80%
of such experiences estimated to occur only once in an individual’s lifetime (Linscott and Van Os, 2013).
Yet, PEs have been shown to increase the risk of developing clinical psychosis (Kline et al., 2012; Van Os
and Reininghaus, 2016) and other mental illness in the future (Fisher et al., 2013; Kaymaz et al., 2012;
Trotta et al., 2019; Werbeloff et al., 2012; Yoshizumi et al., 2004). For example, according to the meta-
analysis by Linscott and van Os, 7.4% of people with baseline PE will develop a psychotic disorder later
in life (Linscott and Van Os, 2013).
Therefore, factors that might affect the development of subclinical PEs into clinical psychotic
phenomena have received extensive attention. Among the factors with the greatest influence on this
development are the frequency and persistence of PEs and the level of associated or secondary distress
(Connell et al., 2016; Garralda, 2015; Hanssen et al., 2005; Janssens et al., 2016; Linscott and Van Os,
2013; Murphy et al., 2017; Van Os and Reininghaus, 2016; Wusten et al., 2018). Associated distress may
be the most important factor for future increase in the symptoms and need for care. Individuals who
hallucinate and hear “voices” but appraise these experiences as positive tend to report fewer complaints
and help-seeking behavior, even when the PEs are persistent and frequent (Baumeister et al., 2017;
Powers et al., 2017). Additionally, individuals with a higher need for clinical care tend to appraise
induced PEs as being more distressing than did individuals without need for care (Peters et al., 2017).
Consequently, some people may experience some PEs as positive and without much distress (Brett et
al., 2009; Mohr and Claridge, 2015; Moreira-Almeida and Cardeña, 2011; Powers et al., 2017) and
individual differences in such appraisals can underlie variation in the level of secondary distress and
clinical outcomes (Kline and Schiffman, 2014; O’Connor, 2009).
Although the absence of distress and the positive appraisal of PEs have been associated with better
outcomes (Baumeister et al., 2017; Brett et al., 2009; Moreira-Almeida and Cardeña, 2011; Osborne et
al., 2017; Powers et al., 2017), little attention has been given to potential protective factors that may
lower the secondary distress. Some studies showed that non-help-seeking individuals with PE reported
lower levels of social and environmental adversity, normal cognitive functioning, high spirituality, and
higher psychological and emotional well-being and social support compared to the individuals with PEs
who experience need for help (Brett et al., 2014; Peters et al., 2016). This results are also in line with
longitudinal studies on high-risk adolescents suggesting that high having a relatively high IQ, more
positive atmosphere at home, and higher levels of social support reduced the prevalence of psychotic
symptoms later in life (Crush et al., 2019, 2018a; Newbury et al., 2016; Riches et al., 2019). However,
other protective factors may also buffer against common mental illness, but received little attention in
the context of secondary distress by PEs. Such factors include having a partner (Lim et al., 2014), having
a pet (McConnell et al., 2011; Shubert, 2012), benevolent types of humor (Fritz et al., 2017; Martin et
al., 2003), optimism (Conversano et al., 2010; Dolphin et al., 2015), and certain levels of personality trait
scores (high emotional stability, high extraversion, high openness to experience, high conscientiousness
and high agreeableness)(Bos et al., 2016a; Boyette et al., 2014; Chowdhury et al., 2018; Hengartner et
al., 2017; Levy et al., 2007; Zhan et al., 2018)
The aim of this study was to investigate whether the above-mentioned protective factors were
associated with lower levels of PE-associated distress in adults from the general population. We
hypothesize that protective factors will moderate the association between the frequency of PEs and PE-
associated distress, so that higher levels of protective factors will be associated with a weaker
associations between PE frequency and distress. Moreover, previous studies have shown that not all
PEs are equally associated with distress (Capra et al., 2015; Peters et al., 2016; Unterrassner et al., 2017a;
Wigman et al., 2011). Therefore, we examined our hypotheses separately for three domains of PEs
("Bizarre experiences", "Delusional ideations", and "Perceptual anomalies"), which were recently
identified in a meta-analysis of the Community Assessment of Psychic Experience (CAPE) questionnaire
(Konings et al., 2006; Mark and Toulopoulou, 2016).
2.1 Study design
2.1.1 Study Sample
Data came from a large national crowdsourcing study in the Netherlands (www.HoeGekIs.nl), which
consists of an online platform for collecting self-reported data on mental health of the general
population in the Netherlands. Participants were included after registration on the project website
(launched December 19th 2013) and could take part in both cross-sectional and longitudinal
studies(Krieke et al., 2016). In these analyses, only data from the cross-sectional study were used.
Measurements for the cross-sectional study was done in modules that consisted of one or more
questionnaires on a speciﬁc domain (e.g., Mood, Well-being, Personality). Participants could choose the
modules that they wanted to complete, but always had to start with a module assessing their socio-
demographic proﬁle. In this study, data on psychotic experiences from the Community Assessment of
Psychic Experiences (CAPE) module and on protective factors from the ‘Start’, ‘Optimism’, ‘Humor’, and
‘Personality’ modules were used. The date of the data extraction for the current study was December
31, 2015. Participants who were 18 years or older and provided informed consent for the use of their
data for research were included in the study. The study protocol was reviewed and exempted by the
Medical Ethical Committee of the University Medical Center Groningen (registration number
M13.147422 and M14.160855)(Krieke et al., 2016).
188.8.131.52 Subclinical psychotic experiences
Lifetime subclinical psychotic experiences were assessed with the Community Assessment of Psychic
Experiences (CAPE(Konings et al., 2006)). The CAPE is a 42-item questionnaire with three subscales:
positive psychotic experiences (20 items), negative psychotic experiences (14 items) and depressive
feelings (8 items; not assessed). For this work, only positive PEs were used, as studies suggest that
positive experiences are specifically predictive for a development of clinical (psychotic) disorder and
need for care (Chapman et al., 1994; Pedrero and Debbané, 2017; Welham et al., 2010, 2009), whereas
negative/cognitive symptoms seem to be more predictive of poorer psychosocial functioning (Kwapil et
al., 2013; Wunderink, 2017). Each item assessed both symptom frequency (CAPE a) on 4-point scale,
ranging from “never” to “nearly always”, and associated secondary distress (CAPE b) on a 4-point scale,
ranging from “not distressed” to “very distressed”. Following a recent meta-analysis on the CAPE(Mark
and Toulopoulou, 2016) the positive psychotic experiences were grouped into three domains: "Bizarre
experiences" (7 items), "Delusional ideations" (9 items), and "Perceptual anomalies" (4 items). The
domain affiliation of items is presented in Table 1. The frequency scores of all experiences were summed
per domain (CAPE a) and the secondary distress scores were summed and dichotomized into no distress
(0) and any distress (1) because of the highly skewed distribution. For the analyses, only those items that
were endorsed were included, as items can only be experienced as distressing where they are present
Table 1. CAPE Subdomains of positive PEs, from Mark and Toulopoulou, 2016
Do you ever feel as if things in magazines or on TV were written especially for you?
Do you ever feel as if electrical devices such as computers can influence the way you
Do you ever feel as if the thoughts in your head are being taken away from you?
Do you ever feel as if the thoughts in your head are not your own?
Have your thoughts ever been so vivid that you were worried other people would hear
Do you ever hear your own thoughts being echoed back to you?
Do you ever feel as if you are under the control of some force or power other than
Do you ever feel as if people seem to drop hints about you or say things with a double
Do you ever feel as if some people are not what they seem to be?
Do you ever feel as if you are being persecuted in some way?
Do you ever feel as if there is a conspiracy against you?
Do you ever feel as if you are destined to be someone very important?
Do you ever feel that you are a very special or unusual person?
Do you ever think that people can communicate telepathically?
Do you believe in the power of witchcraft, voodoo or the occult?
Do you ever feel that people look at you oddly because of your appearance?
Do you ever hear voices when you are alone?
Do you ever hear voices talking to each other when you are alone?
Do you ever feel as if a double has taken the place of a family member, friend or
Do you ever see objects, people or animals that other people cannot see?
184.108.40.206 Protective factors
Available demographic factors included having a partner (yes/no) and/or a pet (yes/no). Optimism was
assessed with The Life Orientation Test – Revised (LOT-R) (Scheier et al., 1994) using 10 items scored on
a 5-point Likert scale. The ‘optimism’ sum score was calculated using optimism-related items and
reversed pessimism related items, and higher scores represent higher optimism levels. Humor styles
were assessed with Humor Style Questionnaire (HSQ)(Martin et al., 2003) using 32 items scored on a 7-
point Likert scale. Separate sum scores for benign styles of humor (‘self-enhancing humor’ and ‘affiliative
humor’) were calculated, with higher scores indicating higher levels of this type of humor.
Personality traits were assessed with the 60-item NEO Five Factor Inventory (NEO-FFI-3)(Costa and
McCrae, 1992) or 12 items per domain scored on 5-point Likert scales. Domain scores for the traits
‘extraversion’, ‘openness to experience’, ’agreeableness’, ‘conscientiousness’ and ‘emotional stability’
(the inverse of neuroticism thus low neuroticism) were studied as protective factors, with higher scores
representing higher trait levels.
For each of the three studied PE domains, we first tested the main effect of the frequency of PEs on the
secondary distress of these PEs with binominal logistic regression. Effects are expressed in Odds Ratio
After that, the correlations between PE frequency scores and levels of protective factors was examined,
to check the presence of an association between these variables for the main analysis. For that,
Spearman's rank correlation coefficient was used due to a skewed distribution of the frequency items
and potential non-linear association between variables.
Next, potential moderation effects of the protective factors on the association between frequency of
PEs and distress caused by these experiences were investigated by entering the interaction between the
protective factors and PE frequency scores into the model and testing if this interaction was significant.
Multiplicative interactions were tested, as we assumed relationship between the frequency of a PE and
associated distress to differ conditionally on the presence and level of protective factors, and this effect
to be multiplicative (different OR's depending on the presence and level of protective factors). The
models were constructed for each subdomain of psychotic experiences and for each protective factor
separately. All tests were corrected for age and gender (Brañas et al., 2017; Kelleher et al., 2012). To
correct for multiple testing, the False discovery rate (FDR) correction was applied following the
Benjamini–Hochberg procedure (Benjamini and Hochberg, 1995) with an alpha level set at 0.05, thus
allowing for 5% of obtained significant results to be false positive.
Significant interactions were visualized, thus PE frequency*distress was stratified for low and high values
of the protective factors to further investigate the size and shape of the moderating effect. For
continuous protective factors, the frequency-distress associations were plotted for groups with mean
+/- 1 standard deviation (Aiken and West, 1991) and for dichotomous variables, we plotted the
associations for the two categories.
All analyses were conducted in R, version 3.6.0.
3.1 Sample and PEs
From the 12.503 participants who completed one instrument (Mage = 45.0 (SD= 15.0), 65.2% female) we
selected the subsample of 2870 participants who completed the CAPE (Mage=48.73 (SD=13.88), 66.72%
female). CAPE-completers were slightly more often female (67% versus 65%, P < 0.05) and older (mean
= 48.7 years [SD = 13.9] vs. 44.2 years [SD = 14.7]; P < 0.001) than non-completers. More details can be
found in the previous publication on the HowNutsAreTheDutch sample (Wigman et al., 2017). Bizarre
experiences were reported by 1127 participants (39.27% of total sample; PE mean= 1.79, SD=1.4) of
whom 40% reported secondary distress (n=449). Delusional ideations were reported by 2735
participants (95.30 % of total sample; mean=4.22, SD= 2.61) of whom 71% reported secondary distress
(n=1932). Perception Anomalies were reported by 353 participants (12.30% of total sample; mean=1.43,
SD=0.89) of whom 28% reported secondary distress (n=99). These three domains showed substantial
overlap (Spearman correlations; ‘Bizarre experiences’-‘Delusional ideations’: ρ=0.45, p<.001; ’Bizarre
experiences’ – ‘Perception anomalies’: ρ= 0.27, p<.001; ‘Delusional ideations–‘Perceptional Anomalies’:
ρ= 0.31, p<.001).
3.2 Protective factors
The distributions of the protective factors are presented in Table 2 for the total sample and per PE
domain. Because not all participants completed all modules, each model was based on different
numbers of people (see Table s1). There were no differences in the distribution of non-responders across
these subsamples (see Table s1).
Table 2. Distribution of the protective factors (%, n, mean and SD) in total sample and per subsamples of
Total sample (n
subsample (n =
subsample (n =
subsample (n =
Having a partner
Having a pet
Affiliative humor style
3.3 Associations between protective factors and frequency of PEs
The associations between protective factors and frequency of PEs are presented in table s2. Most of the
protective factors were significantly associated with the frequency of PEs, however the effect sizes of
these associations were very low (rho ~0.07 on average), with the exception of factors openness (rho =
0,23 with the frequency of Delusional Ideations) and emotional stability (rho = -0,23 with the frequency
of Bizarre Experiences and rho = -0,25 with the frequency of Delusional ideations)
3.4 Associations between frequency of PEs and associated secondary distress
PE frequency score was positively associated with distress for each domain (Bizarre Experiences:
OR=2.62, p<0.001; Delusional Ideations: OR=1.47, p<0.001; Perceptional Anomalies: OR=1.74, p=0.001).
Because of the low frequency of Perceptual anomalies, subsequent analyses were only performed for
of the Bizarre experiences and Delusional ideations domains.
The protective factors showed no significant interaction effects with PE frequency in predicting distress
for Bizarre experiences. For Delusional ideations, the protective factors having a partner, optimism, self-
enhancing humor, extraversion, openness, and emotional stability showed significant interaction effects
on the association between frequency of PEs and PEs distress. More specifically, having a partner,
optimism, self-enhancing humor, extraversion, openness, and emotional stability reduced the
association between frequency of PEs and the level of secondary PE distress (Figure 1). The odds ratios
(ORs) for the interaction terms of the logistic regression analyses are presented in Table 3, however it
must be noted that these ORs cannot be directly interpreted as effect sizes. The interpretation of effect
sizes presented in Figure as follows: for example, for the trait emotional stability, a person with low
emotional stability (-1 SD) and 5 frequency of Delusional ideations will have ~95% chance to experience
distress, and a person with high emotional stability (+1 SD) and also 5 frequency score will have ~60%
change of experiencing distress.
Table 3. ORs for the protective factor * frequency of PEs (CAPE A) interactions, per domains of PEs.
Having a partner
Having a pet
Affiliative humor style
Self-enhancing humor style
* corresponds to the significant interaction effects after the FDR correction. Note that the 95%
confidence intervals were not corrected for multiple testing
Figure 1. Visualization of the effect sizes: plots of association between frequency of PEs (x-axis) and
probability of associated distress (y-axis) per +/- 1 SD and mean values of protective factors (yes/no
for ‘having a partner’).
Footnote: In these graphs, X-axes correspond to the frequency of PEs (CAPE a sumscores), and y-axes
– to the probability of the distress associated with PEs. For the first graph, ‘the effect of having a
partner’, red upper line corresponds to the absence of partner, and green lower line – to the presence
of partner. For other graphs, the upper red line corresponds to the low level of protective factor (-1
SD), middle blue line – to the mean level of protective factor, and lower green line – to the high level
of protective factor (+1 SD). The interpretation of the effects is as follows: for example, for emotional
stability, a person with low emotional stability (-1 SD) and 5 frequency of Delusional ideations will
have ~95% chance to experience distress, and a person with high emotional stability (+1 SD) and also
5 frequency score will have ~60% change of experiencing distress.
The aim of this study was to investigate whether several protective factors reduced the level of distress
associated with different types of subclinical psychotic experiences (PEs) in adults from the general
population. First, in all three PE domains higher PE frequency was associated with higher probability of
distress. This effect was most pronounced for Bizarre Experiences. Second, the protective factors
showed different moderating effects on Bizarre Experiences than on Delusional Ideations. For Bizarre
Experiences, there were no significant interactions between studied protective factors and PE associated
distress. For Delusional Ideations, the following factors significantly moderated the association between
the frequency of PEs and the distress associated with them: having a partner, higher levels of optimism,
higher levels of a self-enhancing humor style, higher extraversion, higher openness, and higher
It is difficult to explain why these protective factors only appeared in the context of Delusional Ideation
and not for Bizarre Experiences. One possible explanation of the absence of significant results for the
domain ‘Bizarre experiences’ may lie in the smaller sub-sample size, as ‘Delusional ideations’ were
reported almost twice as often than ‘Bizarre experiences’. Moreover, in our sample, Bizarre experiences
were associated with higher level of distress than Delusional ideations. Therefore, it could be speculated
that the buffering effect of protective factors is less strong in case of more intensely distressing
experiences. In our sample 71% reported having any distress by Delusional ideations, whereas for Bizarre
experiences any distress reported only 40% of participants. These results may be explained by the intra-
item distribution of frequency and distress: in particular, in Bizarre experiences, more frequent items
were also highly distressing, whereas in Delusion ideations more frequent items were generally less
distressing. Our observation that Bizarre experiences are more distressing than Delusional ideations is
not consistent with previous findings (Capra et al., 2015). This inconsistency may be explained by the
discrepancies in PE classification: because we followed the model of Mark and Toulopoulou (Mark and
Toulopoulou, 2016), we included grandiose and persecutory items in the delusional ideations,. However,
grandiose items are known to be less distressing (Ronald et al., 2014; Wigman et al., 2011) or even
beneficial for mental health (Unterrassner et al., 2017b). Additionally, some delusional items were very
frequently endorsed (e.g. “Do you ever feel as if some people are not what they seem to be?”),
potentially tapping into more normal experiences and thus being less distressing.
Another speculative explanation for the differential effects of Delusional ideations and Bizarre
experiences may lie in the different nature of these domains. Bizarre experiences may be felt as more
real and external (i.e. coming from outside) and be perceived as less controllable and less verifiable than
Delusional ideations. For example, in our sample the most distressing item from the domain of
Delusional ideations was “feeling as being persecuted in some way”. This feeling may be to a certain
extend verified, whereas for the most distressing Bizarre experiences item, “feeling as if the thoughts in
your head are being taken away from you”, verification is more difficult. Such reasoning is in the line
with recent cognitive model of psychosis which highlights the importance of the externalizing appraisal
of psychotic experiences (Garety et al., 2001). Therefore, there may be more options for cognitive and
emotional reappraisals for Delusional ideations than for Bizarre Experiences. Following this argument, it
can be imagined that, after a discussion with a partner, the level of distress from “feeling being
persecuted in some way” may decrease because a partner can provide some contradictory evidence (or
potentially help in case of persecution, and awareness of this can reduce distress). In the case of “feeling
as if the thoughts in your head are being taken away from you”, such ’reality testing’ or expected help
is more difficult.
Within the domain of Delusional ideations, several factors were found to moderate (i.e. lower)
the effect of PE frequency on lower secondary distress. Three personality traits had significant effects
(high extraversion, high openness and high emotional stability), consistent with the literature and our
expectations. Higher levels of openness and extraversion and emotional stability were associated with
more adaptive emotional regulation and beneficial coping strategies (Connor-Smith and Flachsbart,
2007; Purnamaningsih, 2017), which may in turn lead to more positive reappraisal of psychotic
experiences. Similar reasoning may be applicable to the effects of optimism and self-enhancing humor
(Jenaabadi et al., 2015; Perchtold et al., 2019). A possible reason for the absence of an effect for
affiliative humor may be that this humor style is more connected with relationships with others(Martin
et al., 2003), and therefore may be less relevant for the positive appraisal of subjective PEs.
For socio-demographic protective factors, having a partner was associated with lower distress for
Delusional ideations, which is consistent with findings of a general protective effect of social support
(Beetz et al., 2012; Brett et al., 2014; Lim et al., 2014; Ogechi et al., 2016). Although having a pet has
been shown to have some psychological and physical benefits (McConnell et al., 2011), the evidence is
somewhat contradictory(Mueller et al., 2018). In addition, the type of pet, which we did not assess,
seems important (Westgarth et al., 2010). Furthermore, although pets could also be seen as (proxies of)
social support (Bos et al., 2016a), as it was discussed earlier, part of the beneficial effect of social support
may occur due to the opportunity for reality testing, which is less the case through interactions with
It is also necessary to note that these results possibly may be explained by a mediating rather than a
moderating effect of the protective factors. In this case, the association of higher level of protective
factors with lower probability of distress may be explained by the fact the protective factors are
associated also with the lower frequency of PEs, and because of that, also with lower probability of
distress. However, based on the low correlations between frequency and protective factors, this
explanation seems unlikely. Among protective factors with significant interaction effects, only openness
and emotional stability were relatively highly associated with PE frequency. Moreover, for openness this
association is positive, meaning that higher levels of openness are associated with higher frequency of
PEs, and so for this factor the moderation may exist despite this association. Therefore, the only one
factor for which it is not possible to state the absence of mediation is emotional stability.
Our study has several other limitations. First, the PEs of different domains were unequally distributed in
our sample. In particular, Perceptional Anomalies were not often reported in this general population
sample, and their secondary distress was reported even less often, leading us to exclude this domain
from interaction analyses. Therefore, the results of our study are not generalizable to populations
experiencing Perceptional Anomalies and are not fully comparable to the studies using the full CAPE.
Moreover, most of the people who reported Bizarre experiences also reported Delusional Ideations, and
therefore they cannot be treated as belonging to separate individual samples. Therefore, no definite
statements can be made about moderation effects on Bizarre experiences, as mostly all of these
individuals also reported delusional ideations. Second, the distribution of distress was highly skewed.
As other data transformations and use of ordinal regression models was not possible due to violation of
proportional odds assumption, we decided to dichotomize the distress variables, which led to
considerable loss of data and potential omission of important information. Third, the exact time
between and order of assessments varied largely between participants and therefore the time between
assessment of PEs and of protective factors was often different. However, all measures were assessed
within the timespan of one year. Nevertheless, these differences may potentially lead to discrepant
results (e.g. the status of relationships with a partner has changed between the moment of filling in the
first module and the CAPE). In line with this, the CAPE asks for lifetime experiences and the actual PE
may have taken place at a different time than the assessed risk factor is assessed, which might have
added noise to the analysis. Fourth, due to the way the PEs were assessed, frequency scores represent
a combination of the presence of PEs and their frequency, some people with the same scores might have
had a very different combinations of PEs: e.g. frequency score of three might have meant both three
different items which are experienced “sometimes”, or one which is experiences “nearly always”. This
discrepancy might have added more noise to the analysis as well. Fifth, the used sample is not
representative of the general population, because of its crowdsourced nature (Krieke et al., 2016) with
people with high education and females being overrepresented. Therefore, generalizing our findings to
the general population is not possible. Sixth, as our study is cross-sectional, we cannot establish the
direction of the underlying processes; for example, it may still be that PEs actually influence personality
rather than vice versa. This consideration complicated the interpretation of results, which must be
considered preliminary until replicated on longitudinal cohort. Finally, other potential protective factors
may explain the low level of distress despite high frequent PEs. Among these factors may be sleep quality
(Andorko et al., 2017), empathy (Bonfils et al., 2017), physical activity (Crush et al., 2018b), green space
(Bos et al., 2016b), as well as other, higher-level factors (i.e. family and community dynamics) (Coughlan
et al., 2019; Crush et al., 2018b; Riches et al., 2019). Moreover, it is likely that these protective factors
are correlated with each other. There may exist meaningful clusters of protective factors, which may
differ in regard of their buffering effect. Therefore, the next step is to establish such protective processes
longitudinally and at the individual level (Fisher et al., 2018); future studies will benefit from including
both clinical and non-clinical cohorts and data-driving clustering of the protective factors.
It must be noted that our study is closely connected to the concept of resilience. Psychological resilience
is defined in different ways, and often is understood as an outcome of a dynamic process of successful
adaptation to adversity, i.e. good (or stable) mental health despite stressful events and risk factors
(Kalisch et al., 2017). In this framework of resilience, the protective factors studied in this paper can be
seen as resilience-increasing factors that facilitate the process of adaptation in terms of a favorable
outcome despite adversity. Future resilience studies could investigate the process of response
responding to psychotic experiences in more detail in people with different levels of these protective
In conclusion, our results indicate that several protective factors may influence the probability of PEs to
be distressing and that this protective effect may differ between subdomains of PEs. However, due to
the cross-sectional nature of the study, no conclusions on causality can be drawn. In the future, if
replicated in longitudinal studies with more generalizable samples and including a wider selection of
protective factors, these findings could be used to help identify individuals at higher risk of poorer
outcome, and potentially to create tailored intervention and prevention approaches, focusing on
enhancing individuals’ protective factors (Falkenberg et al., 2011; Hudson and Chris Fraley, 2015;
Karnieli-Miller et al., 2017; Malouff and Schutte, 2017; Roberts, B.W., Luo, J., Briley, D.A., Chow, P.I., Su,
R., Hill, 2017), such as school-based mental health trainings. Focusing on distress associated with PEs
and on protective factors may enrich our understanding of the nature of PEs, and explain why despite
having frequent PEs, some people are more resilient to psychopathology (Brett et al., 2009; Mohr and
Claridge, 2015; Moreira-Almeida and Cardeña, 2011; Powers et al., 2017).
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6. Supplementary tables
Table s1. Distribution of filled in modules and percent of missings in total sample and across subsamples
Having a partner
Having a pet
Humor Style Questionnaire
NEO Five Factor Inventory
Table s2. Spearman's rank correlation test for Distribution of the associations between protective
factors and frequency of PEs (CAPE A) per subsamples of PEs.
Affiliative humor style
Self-enhancing humor style
Note that the p-values were not corrected for multiple testing
7. Supplementary script:
The supplementary script can be accessed at Open Science Framework by DOI 10.17605/OSF.IO/ESM74
Role of the Funding Source: MW was supported by funding from the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovative programme (ERC-CoG-2015; No
681466); The Netherlands Organization for Scientific Research (NWO) supported JW (Veni grant no.
016.156.019) and BJ (Veni 016.195.405). AL is supported by an NHMRC Career Development Fellowship
(#1148793). The funding agencies have played no role in the design or execution of this study. All authors
declare no conflict of interest.
Authors’ contributions: AK, JW, SB and MW were involved in the formulation of the research hypothesis
and questions. PJ, BJ, KW, and JW participated in data collection and study design. PJ and BJ contributed
to data management. JW and AK managed literature searches and statistical analyses and wrote the first
version of the manuscript. SB and MW participated in editing and finalizing the manuscript. All authors
have contributed to and have approved the final manuscript. We thank drs. Hans Burgerhof, who kindly
gave advice on some aspects of statistical analysis