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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
39057185_p1
|
39057185
|
sec[0]/sec[0]/p[1]
|
1.1. Religiosity and Intelligence
| 1.525391 |
other
|
Other
|
[
0.005413055419921875,
0.0004315376281738281,
0.994140625
] |
[
0.224365234375,
0.63525390625,
0.13671875,
0.0035247802734375
] |
It has been suggested that the negative association between religiosity and intelligence may be rooted in one or a combined effect of three broad causal categories . First, more intelligent persons tend to prefer an analytic cognitive style over an intuitive cognitive style . Adopting an analytic thinking style can lead to a decrease in religiosity . Second, religiosity is believed to fulfill psychological needs and desires , which, in turn, could be obtained by intelligence as well. For instance, both religion and intelligence are positively associated with self-regulation and self-control, which, in turn, could lead to positive outcomes, including well-being and academic achievement . Furthermore, both religiosity and intelligence have been linked to higher beliefs in compensatory control and self-enhancement. In addition, both religiosity and intelligence can help in lowering feelings of loneliness . Such common characteristics of religion and intelligence support the notion that these constructs are functionally equivalent to a certain extent . This would reduce the need for religiosity in more intelligent individuals. Third, whilst religiosity can strengthen bonds between people sharing similar views and promote sociability , intelligence is negatively correlated with conformity , which may be attributable to more intelligent people being less likely to adopt belief systems from their surroundings.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p2
|
39057185
|
sec[0]/sec[1]/p[0]
|
1.2. Effect-Strength Differentiation
| 1.356445 |
other
|
Study
|
[
0.0435791015625,
0.0006566047668457031,
0.95556640625
] |
[
0.57275390625,
0.3974609375,
0.0278167724609375,
0.0019216537475585938
] |
Although the empirical evidence for a negative association between religiosity and intelligence is overwhelming , causes of unobserved between-study variability in terms of effect strength have not yet been conclusively clarified. In particular, different religiosity and cognitive measurement types have been suspected to play a role in the accuracy of effect size estimations.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p3
|
39057185
|
sec[0]/sec[1]/p[1]
|
1.2. Effect-Strength Differentiation
| 1.051758 |
other
|
Other
|
[
0.004604339599609375,
0.0004074573516845703,
0.9951171875
] |
[
0.339111328125,
0.60595703125,
0.051361083984375,
0.0034332275390625
] |
For instance, associations between religiosity and intelligence are typically less pronounced in studies assessing proxies of intelligence, like Grade Point Average (GPA), in contrast to those with psychometric assessments of intelligence. This is most likely due to school grades being a rather noisy measure of intelligence . In addition, studies differ widely with regard to the (psychometric) operationalization of intelligence. For instance, religious beliefs have been shown to correlate more substantially with the performance on matrix tests than with the performance on vocabulary tests .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p4
|
39057185
|
sec[0]/sec[1]/p[2]
|
1.2. Effect-Strength Differentiation
| 1.541016 |
other
|
Study
|
[
0.031768798828125,
0.0006623268127441406,
0.9677734375
] |
[
0.8505859375,
0.11187744140625,
0.036041259765625,
0.0014600753784179688
] |
Likewise, correlations between religiosity and intelligence are smaller in strength when religious involvement (like going to church or group membership), as opposed to self-reported religious beliefs, is assessed. This has been assumed to be due to religious involvement being motivated by factors other than religiosity, like social involvement or acceptance . Therefore, they can be considered to represent a less salient indicator of the religious beliefs of an individual than self-reported religious beliefs. Considerable variations in the operationalization of religious beliefs could have further contributed to the observed heterogeneity of reported effect sizes between studies.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
39057185_p5
|
39057185
|
sec[0]/sec[1]/p[3]
|
1.2. Effect-Strength Differentiation
| 1.665039 |
other
|
Other
|
[
0.1357421875,
0.0008764266967773438,
0.86328125
] |
[
0.2120361328125,
0.7763671875,
0.01059722900390625,
0.0011644363403320312
] |
In some cases, associations with intelligence have been shown to be more pronounced with measures of religious beliefs comprising a single item or just a few items compared to validated instruments like the Centrality of Religiosity Scale .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p6
|
39057185
|
sec[0]/sec[1]/p[4]
|
1.2. Effect-Strength Differentiation
| 1.860352 |
biomedical
|
Other
|
[
0.51318359375,
0.0011463165283203125,
0.48583984375
] |
[
0.260498046875,
0.72998046875,
0.0084686279296875,
0.0009045600891113281
] |
Large-scale cohort-studies may, thus, be useful to assess the stability of the cross-temporal religiosity and intelligence link.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p7
|
39057185
|
sec[0]/sec[2]/p[0]
|
1.3. Spirituality and Intelligence
| 1.09082 |
other
|
Other
|
[
0.005706787109375,
0.0003905296325683594,
0.994140625
] |
[
0.01708984375,
0.98046875,
0.0016345977783203125,
0.0007338523864746094
] |
While institutionalized religiosity is on a decline in many Western countries, such as the United States, the number of people describing themselves as spiritual, but not religious, has been increasing . In 2012, about 65% of the adult population in the US described themselves as religious (either in addition to being spiritual or not), and only approximately 18% indicated that they were spiritual but not religious. A mere five years later, in 2017, about a quarter of US adults said they think of themselves as spiritual but not religious, representing an eight-percentage-point increase in five years, whilst only 54% of US-American adults described themselves as religious, representing a decrease of eleven percent.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
39057185_p8
|
39057185
|
sec[0]/sec[2]/p[1]
|
1.3. Spirituality and Intelligence
| 1.144531 |
other
|
Study
|
[
0.014434814453125,
0.0005831718444824219,
0.98486328125
] |
[
0.84326171875,
0.09112548828125,
0.0633544921875,
0.0021076202392578125
] |
In contrast to the extensive literature about religiosity and intelligence associations, relationships of spirituality with intelligence have been comparatively little investigated. To the best of our knowledge, only three studies have so far reported associations between spirituality and intelligence, either reporting effect size strengths that resemble the ones established in previous meta-analytical examinations for religiosity and intelligence , some “of somewhat lower magnitude”, but “nonetheless consistent with earlier work” , or trivial effects .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
39057185_p9
|
39057185
|
sec[0]/sec[2]/p[2]
|
1.3. Spirituality and Intelligence
| 1.132813 |
other
|
Other
|
[
0.00826263427734375,
0.0008420944213867188,
0.99072265625
] |
[
0.0019369125366210938,
0.99560546875,
0.0019521713256835938,
0.00051116943359375
] |
It is difficult to clearly distinguish between the “overlapping circles” of religiosity and spirituality. However, they undoubtedly differ in the degree of their formalization. While religiosity is based on an institutionalized system of beliefs, attitudes, and rituals and has been typically assumed to comprise important social and societal aspects, spirituality “involves a personal quest for meaning in life” .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p10
|
39057185
|
sec[0]/sec[2]/p[3]
|
1.3. Spirituality and Intelligence
| 1.285156 |
other
|
Other
|
[
0.0341796875,
0.0005793571472167969,
0.96533203125
] |
[
0.0716552734375,
0.9228515625,
0.004543304443359375,
0.0009703636169433594
] |
As a consequence, explanatory mechanisms of negative relationships between religiosity and intelligence cannot be assumed to be identical to those for potential associations between spirituality and intelligence.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p11
|
39057185
|
sec[0]/sec[2]/p[4]
|
1.3. Spirituality and Intelligence
| 1.862305 |
other
|
Other
|
[
0.260009765625,
0.0018405914306640625,
0.73828125
] |
[
0.05865478515625,
0.9150390625,
0.0257720947265625,
0.0007433891296386719
] |
On one hand, spirituality might be functionally as equivalent, to a certain extent, with religiosity and with intelligence. For instance, it has been shown that spirituality can have beneficial effects on mental health, which is mediated by enhanced self-control or reduced feelings of loneliness and can empower patients to have a sense of control . Moreover, the preference for an analytic cognitive style is negatively associated with reporting embracing a spiritual epistemology .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p12
|
39057185
|
sec[0]/sec[2]/p[5]
|
1.3. Spirituality and Intelligence
| 1.046875 |
other
|
Other
|
[
0.0101776123046875,
0.000514984130859375,
0.9892578125
] |
[
0.00823211669921875,
0.98974609375,
0.0012979507446289062,
0.0005693435668945312
] |
On the other hand, a smaller likelihood of more intelligent individuals conforming to religious dogma should not play a decisive role in being spiritual or not. Consequently, it may be reasonable to assume negative associations between spirituality and intelligence but less pronounced associations of spirituality than religiosity with intelligence.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p13
|
39057185
|
sec[0]/sec[3]/p[0]
|
1.4. The Present Study
| 1.874023 |
other
|
Study
|
[
0.0401611328125,
0.0006384849548339844,
0.958984375
] |
[
0.99365234375,
0.0048980712890625,
0.0010862350463867188,
0.0002868175506591797
] |
Here, we examine associations between different religiosity and spirituality assessments and crystallized intelligence in the General Social Survey data (GSS), a large representative cohort-based survey of US-American citizens. We assess whether there are associations between (i) religiosity and crystallized intelligence and (ii) spirituality and crystallized intelligence, as well as (iii) whether they generalize over different age groups, cohorts, and religiosity measurement modalities. We, therefore, initially provide direct comparisons between the effect size strength of religiosity and crystallized intelligence associations with spirituality and crystallized intelligence associations for various times of data assessment. Moreover, we assess if the respective correlations change in magnitude over time.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p14
|
39057185
|
sec[0]/sec[3]/p[1]
|
1.4. The Present Study
| 1.714844 |
biomedical
|
Study
|
[
0.97265625,
0.0019369125366210938,
0.025634765625
] |
[
0.77880859375,
0.218505859375,
0.00171661376953125,
0.0010576248168945312
] |
Our study protocol, including all hypotheses and planned confirmatory analyses, was preregistered prior to all data analyses on the Open Science Framework at https://osf.io/jwsd6 on 22 October 2023 (see Supplementary S1 at https://osf.io/k4nqc for deviations from the preregistered protocol).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p15
|
39057185
|
sec[0]/sec[4]/p[0]
|
1.5. Hypotheses
| 1.811523 |
other
|
Study
|
[
0.0288543701171875,
0.0003821849822998047,
0.970703125
] |
[
0.9541015625,
0.043792724609375,
0.0015096664428710938,
0.0005116462707519531
] |
First, we expected religiosity and spirituality to be positively correlated because of conceptual overlaps. Second, we hypothesized that religious and spiritual beliefs are both negatively associated with crystallized intelligence. Negative associations of spirituality and crystallized intelligence were expected because we considered some explanatory mechanisms for negative religiosity and intelligence associations to be valid for potential spirituality and intelligence associations as well. We expected these associations to generalize across age groups within, as well as across, cohorts. Third, we expected correlations between religious involvement and crystallized intelligence to be less pronounced than correlations between religious beliefs and crystallized intelligence. However, during times of declining institutionalized religiosity, ongoing participation in religious organizations, religious gatherings, and similar events may conceivably function as a stronger indicator for the actual beliefs of a person than in more religious societies. This assumption is reasonable because social pressure to attend formal religious events can be expected to be lower in less religious societies. Consequently, in this case, attendance can be considered to be a more genuine expression of actual beliefs instead of a social obligation. Therefore, we hypothesized that associations between religious involvement and crystallized intelligence have become more pronounced in more recent years.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p16
|
39057185
|
sec[1]/sec[0]/p[0]
|
2.1. Sample
| 2.527344 |
biomedical
|
Study
|
[
0.57568359375,
0.0010786056518554688,
0.423583984375
] |
[
0.99755859375,
0.0020160675048828125,
0.00019943714141845703,
0.00008296966552734375
] |
We tested our hypotheses based on US-American individual-level data from 14 cohorts over 34 years via the General Social Survey . The GSS is a population representative cohort-based survey of noninstitutionalized US adults that has been conducted annually or biannually since 1972. Between-cohort data are independent because no participant takes part more than once. We included information from 14 cohorts: 1988, 1991, 1993, 1994, 1998, 2000, 2006, 2008, 2010, 2012, 2014, 2016, 2018, and 2022. Participants’ ( N = 35,093) age averaged at 47.39 years ( SD = 17.6), and recruited samples were balanced in terms of sex (19,588 women; 56%; for cohort characteristics, see Table 1 ).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999994 |
39057185_p17
|
39057185
|
sec[1]/sec[1]/sec[0]/p[0]
|
2.2.1. Cognitive Abilities
| 2.548828 |
other
|
Study
|
[
0.148681640625,
0.0005116462707519531,
0.8505859375
] |
[
0.7216796875,
0.27392578125,
0.0036640167236328125,
0.0006775856018066406
] |
The GSS data include an assessment of vocabulary knowledge that has been administered at most data collection times, namely the WORDSUM vocabulary test. In this ten-item, single-choice task, respondents are asked to find a synonym out of five response options for each of the ten presented stimulus words. Correct responses are awarded one point, thus yielding possible scores ranging from 0 to 10. Verbal ability assessments are education-dependent , thus representing a measure of crystallized intelligence . Because such tests have been shown to exhibit substantial g -loadings as correlations with full-scale IQ reach up to r = 0.93 , they can be used as a proxy measure for general intelligence. The WORDSUM vocabulary test has been used in several widely cited studies as an intelligence measure .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p18
|
39057185
|
sec[1]/sec[1]/sec[1]/p[0]
|
2.2.2. Religiosity
| 1.480469 |
other
|
Study
|
[
0.1016845703125,
0.0007367134094238281,
0.8974609375
] |
[
0.61962890625,
0.3779296875,
0.0016031265258789062,
0.0010309219360351562
] |
Religiosity and spirituality were assessed via two questions in nine cohorts : “To what extent do you consider yourself a religious person? Are you…” (not religious at all/slightly religious/moderately religious/very religious) and “To what extent do you consider yourself a spiritual person? Are you…” (not spiritual at all/slightly spiritual/moderately spiritual/very spiritual). Items of this type are among the most valid items to assess religious beliefs and may be, thus, expected to measure spirituality similarly well.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p19
|
39057185
|
sec[1]/sec[1]/sec[2]/p[0]
|
2.2.3. Religious Beliefs
| 1.415039 |
other
|
Study
|
[
0.05072021484375,
0.0006856918334960938,
0.94873046875
] |
[
0.853515625,
0.1444091796875,
0.0011043548583984375,
0.0008716583251953125
] |
Religious beliefs were assessed by means of a single item in 14 cohorts : “Please look at this card and tell me which statement comes closest to expressing what you believe about God” (I do not believe in God/I do not know whether there is a God and I do not believe there is any way to find out/I do not believe in a personal God, but I do believe in a Higher Power of some kind/I find myself believing in God some of the time, but not at others/while I have doubts, I feel that I do believe in God/I know God really exists and I have no doubts about it). We only used responses yielding values of 1 (“I don’t believe in God” = not religious) and 6 (“I know God really exists and I have no doubts about it” = religious) in our analyses.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p20
|
39057185
|
sec[1]/sec[1]/sec[3]/p[0]
|
2.2.4. Religious Involvement
| 1.369141 |
other
|
Other
|
[
0.078857421875,
0.0009436607360839844,
0.92041015625
] |
[
0.424560546875,
0.572265625,
0.0015468597412109375,
0.0013380050659179688
] |
In 10 cohorts , religious involvement was assessed via the following question: “How often do you take part in the activities and organizations of a church or place of worship other than attending services?” (never/less than once a year/about once or twice a year/several times a year/about once a month/2–3 times a month/nearly every week/every week/several times a week/once a day/several times a day).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p21
|
39057185
|
sec[1]/sec[1]/sec[3]/p[1]
|
2.2.4. Religious Involvement
| 2.429688 |
other
|
Study
|
[
0.29345703125,
0.001129150390625,
0.70556640625
] |
[
0.99462890625,
0.004604339599609375,
0.0004570484161376953,
0.00011944770812988281
] |
For our main analyses, the original ordinal scaling of our items of self-reported overall religiosity and religious involvement was maintained. We supplemented these calculations with extreme group analyses in our examination of self-reported religiosity and spirituality associations to enhance the power to detect a potential effect. Therefore, we only included religious (very religious) vs. non-religious (not religious at all) and spiritual (very spiritual) vs. non-spiritual individuals (not spiritual at all). Concerning religious involvement, we did not conduct extreme-group comparisons due to the small amount of people who had reported strong involvement. Instead, religious involvement was dichotomized into religiously involved (less than once a year/about once or twice a year/several times a year/about once a month/2–3 times a month/nearly every week/every week/several times a week/once a day/several times a day) vs. not religiously involved individuals (never). All analyses with dichotomized religiosity (religious = very religious/moderately religious/slightly religious vs. not religious = not religious at all) and spirituality (spiritual = very spiritual/moderately spiritual/slightly spiritual vs. not spiritual = not spiritual at all) items are reported in Supplementary S2 at https://osf.io/wpxfy .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p22
|
39057185
|
sec[1]/sec[2]/p[0]
|
2.3. Analyses
| 3.207031 |
biomedical
|
Study
|
[
0.7841796875,
0.0010471343994140625,
0.214599609375
] |
[
0.99755859375,
0.001262664794921875,
0.0010709762573242188,
0.00009894371032714844
] |
We used both primary data analyses and meta-analytical approaches to assess cross-sectional associations of religiosity or spirituality with crystallized intelligence, as well as potential cross-temporal changes in effect size strength.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p23
|
39057185
|
sec[1]/sec[2]/sec[0]/p[0]
|
2.3.1. Primary Data Analyses
| 3.232422 |
other
|
Study
|
[
0.427734375,
0.001056671142578125,
0.5712890625
] |
[
0.998046875,
0.001399993896484375,
0.0006513595581054688,
0.0000985860824584961
] |
To examine associations of religious or spiritual beliefs with crystallized intelligence and their potential differences with respect to age groups and cohorts, we conducted multiple linear regressions across all cohorts. Specifically, we regressed scores on the vocabulary test for two dummy-coded variables (religiosity: slightly religious, moderately religious, very religious; reference = not religious at all; spirituality: slightly spiritual, moderately spiritual, very spiritual; reference = not spiritual at all): the age and sex of participants. Moreover, we included interaction terms of age and religiosity, as well as age and spirituality, to assess potential moderations by age. Analogous to our above approach, we repeated these analyses in extreme-group calculations using two dichotomous predictors for religiosity (i.e., very religious vs. not religious at all) and spirituality (i.e., very spiritual vs. not spiritual at all).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p24
|
39057185
|
sec[1]/sec[2]/sec[0]/p[1]
|
2.3.1. Primary Data Analyses
| 3.271484 |
other
|
Study
|
[
0.388427734375,
0.00118255615234375,
0.6103515625
] |
[
0.998046875,
0.0013151168823242188,
0.0006642341613769531,
0.00010073184967041016
] |
Because measures of religious beliefs have been shown to correlate more strongly (negatively) with intelligence than religious involvement , we examined whether results differed depending on the type of religiosity assessment. In a hierarchical theory-guided stepwise forward regression, we first entered a dichotomous indicator of religious beliefs (I do not believe in God vs. I know God really exists and I have no doubts about it), sex, and participant age to predict crystallized intelligence. We also included an interaction term for religious beliefs and age. In a subsequent step, dummy-coded variables indicating religious involvement (less than once a year, about once or twice a year, several times a year, about once a month, 2–3 times a month, nearly every week, every week, several times a week, once a day, several times a day; reference = never) were added as predictors in the model. Interactions of religious involvement with age were used to assess potential moderating effects of age.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p25
|
39057185
|
sec[1]/sec[2]/sec[0]/p[2]
|
2.3.1. Primary Data Analyses
| 3.017578 |
biomedical
|
Study
|
[
0.9208984375,
0.0010271072387695312,
0.07818603515625
] |
[
0.998046875,
0.0011587142944335938,
0.0005288124084472656,
0.0000890493392944336
] |
Model fits were compared by examining changes in R -squared values. Subsequently, an identical model was calculated with a dichotomous indicator of religious involvement. For all regression models including interaction terms, we first reported results of the respective model with main effects only. We did so to show potential changes in effect size strength after including interactions. In supplementary analyses, we added the year of data collection as a predictor in our stepwise regression to examine potential changes due to cross-temporal effects.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p26
|
39057185
|
sec[1]/sec[2]/sec[1]/p[0]
|
2.3.2. Meta-Analytical Approach
| 3.0625 |
other
|
Study
|
[
0.35546875,
0.0009675025939941406,
0.6435546875
] |
[
0.99658203125,
0.0026683807373046875,
0.0007772445678710938,
0.00011068582534790039
] |
Due to the ordinal scaling of the religiosity and spirituality assessments, we first obtained the Spearman correlation coefficients of (i) religiosity and crystallized intelligence, (ii) spirituality and crystallized intelligence, and (iii) religious involvement and crystallized intelligence within each cohort. In order to investigate time-trends, these precision-weighted (i.e., larger samples being assigned larger weights) coefficients were then meta-regressed on the time of data assessment in three separate models. Analyses were repeated for biserial correlations based on dichotomous indicators of religiosity (very religious vs. not religious at all), spirituality (very spiritual vs. not spiritual at all), and religious involvement (religiously involved vs. not religiously involved).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p27
|
39057185
|
sec[1]/sec[2]/sec[1]/p[1]
|
2.3.2. Meta-Analytical Approach
| 1.460938 |
other
|
Study
|
[
0.07037353515625,
0.0007476806640625,
0.9287109375
] |
[
0.92138671875,
0.0760498046875,
0.001926422119140625,
0.0008416175842285156
] |
In addition, we assessed differences in the strength of religiosity with crystallized intelligence and spirituality with crystallized intelligence associations, as well as religious beliefs with crystallized intelligence and religious involvement with crystallized intelligence associations .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p28
|
39057185
|
sec[1]/sec[2]/sec[1]/p[2]
|
2.3.2. Meta-Analytical Approach
| 4.003906 |
biomedical
|
Study
|
[
0.998046875,
0.00018203258514404297,
0.0019321441650390625
] |
[
0.9990234375,
0.0005574226379394531,
0.0003345012664794922,
0.00003802776336669922
] |
Considering the sample sizes at hand, we focused on the interpretation of effect sizes rather than nominal null hypothesis significance testing in our results. We interpret the Pearson correlation coefficients according to Cohen’s well-established classification , where absolute r = 0.10, 0.30, and 0.50 and η 2 = 0.01, 0.06, and 0.13 values are considered to represent lower thresholds of small, medium, and large effects, respectively (effects smaller than r = 0.10 and η 2 = 0.01 are considered to be trivial and not meaningful). Those guidelines have previously been challenged by Gignac and Szodorai , who collated 708 meta-analytically derived (absolute) Pearson correlations and found that only 2.7% were ≥0.50, whereas about 55% were ≤0.21. Consequently, it has been suggested that r = 0.10, 0.20 and 0.30 may represent better bottom thresholds for small, medium, and large effects, respectively. All analyses were performed in the open-source software R.4.3.2 using the packages “sjstats” , “sensemakr” , and “rms” . Our entire analytic code is available at https://osf.io/tyb9e .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p29
|
39057185
|
sec[2]/sec[0]/p[0]
|
3.1. Primary Data Analyses
| 1.439453 |
other
|
Study
|
[
0.05316162109375,
0.0006732940673828125,
0.9462890625
] |
[
0.9765625,
0.022003173828125,
0.0009608268737792969,
0.0004487037658691406
] |
Table 2 shows the Pearson correlations between indicators of religiosity and spirituality across all cohorts. As expected, crystallized intelligence was negatively and non-trivially associated with religiosity and religious beliefs and virtually unrelated to religious involvement. Also in line with our expectations, religiosity and spirituality, as well as religiosity and religious involvement, were positively associated.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
39057185_p30
|
39057185
|
sec[2]/sec[0]/p[1]
|
3.1. Primary Data Analyses
| 2.683594 |
other
|
Study
|
[
0.2470703125,
0.0009937286376953125,
0.751953125
] |
[
0.99658203125,
0.002349853515625,
0.0007562637329101562,
0.000133514404296875
] |
In cross-cohort regressions ( Table 3 ), we observed the negative, albeit small, effects of religiosity (assessed with an ordinal response format) on crystallized intelligence. In contrast, spirituality (assessed with an ordinal response format) yielded a positive sign, although effects were trivial in strength. Age showed a small association with crystallized intelligence, thus conforming to the well-known positive age and crystallized IQ link. Interactions with age only reached nominal significance for religiosity, indicating smaller negative effects of religiosity on crystallized intelligence in older ages, although effects were merely trivial. Sex did not yield any meaningful effects on crystallized intelligence.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p31
|
39057185
|
sec[2]/sec[0]/p[2]
|
3.1. Primary Data Analyses
| 3.556641 |
other
|
Study
|
[
0.3056640625,
0.0008955001831054688,
0.693359375
] |
[
0.99560546875,
0.0027561187744140625,
0.00142669677734375,
0.00012981891632080078
] |
Regressing crystallized intelligence on extreme groups (very religious vs. not religious at all; very spiritual vs. not spiritual at all) showed a significant negative small effect of religiosity ( β = −0.945, p < 0.001, η 2 = 0.02) and a significant positive but trivial effect of spirituality on crystallized intelligence ( β = 0.271, p < 0.05, η 2 = 0.003). When interactions were included, the main effects changed in terms of signs, although effects did not reach nominal significance (religiosity: β = 0.315, p = 0.341, η 2 = 0.02; spirituality: β = −0.232, p = 0.485, η 2 = 0.003). The interaction between age and religiosity was significant ( β = −0.026, p < 0.001, η 2 = 0.006), indicating nominally weaker negative effects of religiosity on crystallized intelligence in older ages, although they were trivial in strength.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p32
|
39057185
|
sec[2]/sec[0]/p[3]
|
3.1. Primary Data Analyses
| 2.822266 |
other
|
Study
|
[
0.1580810546875,
0.001033782958984375,
0.8408203125
] |
[
0.9970703125,
0.0018205642700195312,
0.0007700920104980469,
0.00015616416931152344
] |
Effects of religious beliefs and religious involvement on crystallized intelligence are detailed in Table 4 . Religious beliefs were negatively associated with crystallized intelligence in both models with and without indicators of religious involvement. Interestingly, compared with the reference category (never), indicators of religious involvement yielded mostly positive signs, which became nominally significant for seven categories (less than once a year, about once or twice a year, several times a year, about once a month, 2–3 times a month, nearly every week, every week) in the model without interactions, although all of them were trivial in strength. Effect strengths of interaction terms were not meaningful, providing no evidence for moderating effects of participants’ age. Although Model 2 ( R 2 = 0.031) explained significantly ( F = 4.505, p < 0.001) more variance than Model 1 ( R 2 = 0.023), the effects of the added variables were merely trivial, thus indicating beliefs as the strongest predictor for crystallized intelligence. Variance inflation factors yielded no evidence for multicollinearity (all VIF s < 1.23 in models without interactions).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p33
|
39057185
|
sec[2]/sec[0]/p[4]
|
3.1. Primary Data Analyses
| 1.804688 |
other
|
Study
|
[
0.3564453125,
0.0010318756103515625,
0.642578125
] |
[
0.9658203125,
0.033111572265625,
0.0008978843688964844,
0.0002903938293457031
] |
Originally, we had preregistered these analyses with an inverse order of included predictors (i.e., we first intended to include indicators of religious involvement and, subsequently, indicators of religious beliefs) and consequently provide corresponding results in Supplementary S3 ( https://osf.io/fkjdr ), which were in line with the findings of our main analyses.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p34
|
39057185
|
sec[2]/sec[0]/p[5]
|
3.1. Primary Data Analyses
| 1.849609 |
other
|
Study
|
[
0.07830810546875,
0.0006814002990722656,
0.9208984375
] |
[
0.98974609375,
0.009429931640625,
0.0006771087646484375,
0.0002646446228027344
] |
Table 5 shows the effects of dichotomized religious involvement on crystallized intelligence. Again, religious beliefs had a negative impact on crystallized intelligence, whereas religious involvement had a positive effect. After including religious involvement, the adjusted R 2 increased significantly from 0.023 to 0.029 ( F = 24.261; p < 0.001), but again the effects of religious involvement were trivial and beliefs were the strongest predictor for crystallized intelligence.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p35
|
39057185
|
sec[2]/sec[0]/p[6]
|
3.1. Primary Data Analyses
| 1.740234 |
other
|
Study
|
[
0.350341796875,
0.0014886856079101562,
0.64794921875
] |
[
0.98681640625,
0.012054443359375,
0.0006661415100097656,
0.0002524852752685547
] |
The data collection year did not show any significant influences when it was added as a predictor in our supplementary analyses of both dummy-coded and dichotomized religious involvement. The meaningfulness of the other predictors remained virtually unchanged, thus suggesting that our results were generalized over data collection years (for numerical detail, see Supplementary S4 at https://osf.io/9crp5 ).
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p36
|
39057185
|
sec[2]/sec[1]/p[0]
|
3.2. Meta-Analytical Results
| 3.296875 |
other
|
Study
|
[
0.256103515625,
0.0008616447448730469,
0.7431640625
] |
[
0.9970703125,
0.0017747879028320312,
0.00102996826171875,
0.00010120868682861328
] |
In line with the results of our stepwise regressions, cohort-specific correlations between religiosity and crystallized intelligence were consistently negative, whereas associations between spirituality and crystallized intelligence showed positive signs but trivial correlation strengths in all cohorts (left columns in Table 6 ). Formal analyses indicated that the strength of the religiosity and crystallized intelligence association differed significantly from that of the spirituality and crystallized intelligence correlation in all cohorts (all p s < 0.01; Table 6 ). Correlations of religiosity and crystallized intelligence ( ß = −0.007, p = 0.041, R 2 = 0.451 η 2 = 0.53) were consistently negative but increased in magnitude in more recent years, while those of spirituality and crystallized intelligence ( ß = −0.006, p = 0.042, R 2 = 0.445 η 2 = 0.08) changed signs and became negative in later cohorts, but they remained trivial in terms of effect strength.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p37
|
39057185
|
sec[2]/sec[1]/p[1]
|
3.2. Meta-Analytical Results
| 1.871094 |
other
|
Study
|
[
0.12030029296875,
0.0010862350463867188,
0.87841796875
] |
[
0.99462890625,
0.004489898681640625,
0.0008034706115722656,
0.00021374225616455078
] |
We repeated these analyses with extreme groups (very religious vs. not religious at all, very spiritual vs. not spiritual at all), yielding broadly conforming results compared to ordinal analyses. For all cohorts, we found negative correlations of religiosity and crystallized intelligence, whereas spirituality and crystallized intelligence correlations were mostly positive in terms of sign but trivial in terms of strength (rightmost columns in Table 6 ). Again, within all cohorts, religiosity and crystallized intelligence correlation coefficients differed significantly in terms of strength compared to those of spirituality and crystallized intelligence.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p38
|
39057185
|
sec[2]/sec[1]/p[2]
|
3.2. Meta-Analytical Results
| 2.291016 |
other
|
Study
|
[
0.152099609375,
0.0007200241088867188,
0.84716796875
] |
[
0.994140625,
0.00528717041015625,
0.0005035400390625,
0.00014150142669677734
] |
Point-biserial correlations between religiosity and crystallized intelligence ( ß = −0.004, p = 0.213, R 2 = 0.118 η 2 = 0.24) did not change significantly across cohorts, while those of spirituality and crystallized intelligence ( ß = −0.007, p = 0.026, R 2 = 0.520 η 2 = 0.59) decreased across the cohorts. The observed negative associations between religiosity and crystallized intelligence were in line with our expectations; however, in contrast to our expectations, spirituality was virtually unrelated to crystallized intelligence.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p39
|
39057185
|
sec[2]/sec[1]/p[3]
|
3.2. Meta-Analytical Results
| 3.404297 |
other
|
Study
|
[
0.317138671875,
0.0011014938354492188,
0.681640625
] |
[
0.99755859375,
0.001255035400390625,
0.0008487701416015625,
0.0000966787338256836
] |
We obtained correlation coefficients of religious involvement and crystallized intelligence for each cohort ( Table 7 ). Religious involvement was virtually unrelated to crystallized intelligence. No meaningful significant changes in effect size strengths over time were observed ( ß = −0.003, p = 0.285, R 2 = 0.051, η 2 = 0.19). A similar pattern was observed after dichotomizing religious involvement, showing no meaningful changes in effect strength over time ( ß = −0.001, p = 0.449, R 2 = −0.052, η 2 = 0.10). Associations of religious beliefs with crystallized intelligence were consistently negative and mostly non-trivial in terms of strength. Interestingly, negative associations between religious beliefs and crystallized intelligence increased in strength across cohorts, yielding a strong effect ( ß = −0.008, p = 0.005, R 2 = 0.711 η 2 = 0.75). Our findings supported our hypothesis of less pronounced correlations of religious involvement with crystallized intelligence compared to correlations of religious beliefs with crystallized intelligence. However, we did not observe any changes in the effect strengths of religious involvement and crystallized intelligence associations over time.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p40
|
39057185
|
sec[3]/p[0]
|
4. Discussion
| 1.375 |
other
|
Study
|
[
0.04766845703125,
0.0006718635559082031,
0.95166015625
] |
[
0.974609375,
0.0241241455078125,
0.0009059906005859375,
0.000545501708984375
] |
Here, we provide evidence for religiosity and crystallized intelligence, as well as spirituality and crystallized intelligence, associations in 14 population-representative US-based cohorts from 1988 to 2022. We show that crystallized intelligence is negatively related to religiosity but unrelated to spirituality. Our results present several points of interest, as discussed below.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p41
|
39057185
|
sec[3]/p[1]
|
4. Discussion
| 2.644531 |
other
|
Study
|
[
0.437255859375,
0.0009369850158691406,
0.56201171875
] |
[
0.99462890625,
0.004150390625,
0.0008912086486816406,
0.00012814998626708984
] |
First, as expected, we found small but meaningful negative associations of religious beliefs with crystallized intelligence as well as negative associations of self-reported religiosity with crystallized intelligence. We found tentative evidence for less pronounced associations between self-reported religiosity and crystallized intelligence associations in older ages. These findings are consistent with the idea of protective effects of religiosity on age-related cognitive decline, which have been demonstrated for American samples , but failed to be replicated in (Western) Europe . Such effects were mainly attributed to religiosity leading to an increase in activities that are likely to stimulate cognitive functions .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p42
|
39057185
|
sec[3]/p[2]
|
4. Discussion
| 1.811523 |
other
|
Study
|
[
0.056732177734375,
0.000522613525390625,
0.94287109375
] |
[
0.97705078125,
0.0214385986328125,
0.00135040283203125,
0.00035858154296875
] |
Interestingly, associations in earlier cohorts showed significantly smaller associations between religiosity and crystallized intelligence compared to subsequent cohorts, thus indicating cross-temporally increasing effect size strengths. When explicitly examining associations between belief in God and crystallized intelligence, we also found an increase in effect size strength across cohorts, but no effects of age. This pattern suggests stronger influences of social changes over time than of participant ages on religiosity and crystallized intelligence associations. It may be speculated that this may be due to individuals having become more comfortable with describing themselves as not being religious due to society having become less conservative and more permissive. Conceivably, an increasing polarization of the political landscape in the USA could be another reason that may drive individuals to express their religiosity as an expression of party affiliation .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p43
|
39057185
|
sec[3]/p[3]
|
4. Discussion
| 1.476563 |
other
|
Study
|
[
0.0389404296875,
0.0005373954772949219,
0.96044921875
] |
[
0.94091796875,
0.0565185546875,
0.0015850067138671875,
0.0007457733154296875
] |
Second, religious involvement was unrelated to crystallized intelligence in our data. Less pronounced associations of crystallized intelligence with religious involvement than with religious beliefs were to be expected and are in line with previous findings , although the presently observed virtually nil effect was somewhat unexpected. Lower associations are expectable because taking part in a religious organization or ceremony constitutes a weaker indicator for the actual beliefs of a person than self-reports of being religious. The virtual null associations of religious involvement and crystallized intelligence, however, are noteworthy and may indicate that religious involvement might not be motivated by the same causes as personal beliefs.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p44
|
39057185
|
sec[3]/p[4]
|
4. Discussion
| 2.351563 |
other
|
Study
|
[
0.1201171875,
0.0007257461547851562,
0.87890625
] |
[
0.99267578125,
0.005977630615234375,
0.0009546279907226562,
0.0001996755599975586
] |
We did not observe any effects of age regarding religious involvement. Moreover, in contrast to associations between religious beliefs and crystallized intelligence, associations of religious involvement with crystallized intelligence did not change across cohorts. It is reasonable to expect cross-temporal changes in the involvement and crystallized intelligence association only, because when institutionalized religiosity becomes less prevalent in a society, being part of a religious organization may be considered to represent a better indicator for the actual beliefs of a person. This can be attributed to attendance at religious events being likely a more genuine expression of actual beliefs instead of a social obligation in less religious societies. In more religious societies, attendance in religious events and organizations may often be a consequence of extrinsic motivators such as societal pressure. This is also indicated by a decline in religious involvement in societies becoming more liberal and pluralistic with regard to religiosity . The effect-strength increases in religiosity and crystallized intelligence associations across different cohorts seem to be consistent with smaller negative associations between self-reported religiosity and crystallized intelligence in older participants. Both might be attributed to a decreasing societal value of religiosity in the US-American population .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p45
|
39057185
|
sec[3]/p[5]
|
4. Discussion
| 1.783203 |
other
|
Study
|
[
0.0419921875,
0.00046825408935546875,
0.95751953125
] |
[
0.97021484375,
0.0269927978515625,
0.002300262451171875,
0.0004229545593261719
] |
Finally, we did not observe any meaningful associations of self-reported spirituality with crystallized intelligence. These findings contrast previous reports of negative spirituality and intelligence associations . Although we expected associations with crystallized intelligence to be less pronounced for spirituality than for religiosity, it seems surprising that spirituality was practically unrelated to crystallized intelligence. The conceptual overlaps between the religiosity and spiritually constructs may lead researchers to expect that well-established correlational patterns like those of religiosity with intelligence may generalize, to a certain extent, to spirituality associations. Whilst our findings may support the idea that religiosity and intelligence could be functionally equivalent to a certain extent, spirituality and intelligence do not appear to be functionally overlapping at all.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
39057185_p46
|
39057185
|
sec[3]/p[6]
|
4. Discussion
| 1.167969 |
other
|
Other
|
[
0.024749755859375,
0.0005083084106445312,
0.974609375
] |
[
0.388427734375,
0.60400390625,
0.00568389892578125,
0.001926422119140625
] |
This is further supported by evidence for systematic differences between religious and spiritual individuals. For instance, it has been shown that high openness values predict spirituality positively but religious fundamentalism negatively . Considering the well-established positive openness to experience with intelligence association , these results appear to be in line with our findings.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p47
|
39057185
|
sec[3]/p[7]
|
4. Discussion
| 1.270508 |
other
|
Other
|
[
0.03375244140625,
0.0005879402160644531,
0.9658203125
] |
[
0.046783447265625,
0.94873046875,
0.0036029815673828125,
0.000858306884765625
] |
Importantly, it needs to be emphasized that the presently observed negative associations between IQ and religious beliefs indicate effects at the population level. We do not mean to suggest that, on an individual level, religious believers are necessarily less intelligent than non-believers.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p48
|
39057185
|
sec[3]/sec[0]/p[0]
|
Limitations
| 1.750977 |
other
|
Study
|
[
0.040618896484375,
0.0004856586456298828,
0.958984375
] |
[
0.95947265625,
0.037811279296875,
0.0020580291748046875,
0.000560760498046875
] |
In terms of limitations, it needs to be acknowledged that in our archival data analyses, religiosity and spirituality were each assessed with a single item. Single items have sometimes been criticized due to their inferior or sometimes unknown reliability and validity compared to multi-item scales . However, it has been demonstrated in the context of educational research that single items may provide useful and psychometrically sound alternatives when scale scores are unavailable . Moreover, the strength of the presently observed religiosity and crystallized intelligence link closely resembles those from earlier accounts that used self-report scales to assess religiosity , thus providing indirect evidence of the reliability and validity of our items. In fact, religiosity has repeatedly been assessed by means of single items .
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p49
|
39057185
|
sec[3]/sec[0]/p[1]
|
Limitations
| 1.273438 |
other
|
Study
|
[
0.0109710693359375,
0.00039768218994140625,
0.98876953125
] |
[
0.89697265625,
0.09942626953125,
0.0026397705078125,
0.00106048583984375
] |
Single items of religiosity have been shown to be good indicators of intrinsic proreligious positions , and recent findings demonstrate the usefulness and predictive validity of such assessments in general . The usefulness of single items in the context of religiosity is further supported by the short form of the Centrality of Religiosity Scale, the CRS-5 . The CRS-5 comprises five single-item religiosity subscales such as public practice (“How often do you take part in religious services?”) or ideology (“To what extent do you believe that God or something divine exists?”). In a recent study, both of these items have been shown to yield the strongest factor loadings on personal religiosity , thus demonstrably representing valid religiosity assessments. Because these two items had been administered in the GSS, we used them as appropriate indicators of religiosity in the present analyses.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
39057185_p50
|
39057185
|
sec[3]/sec[0]/p[2]
|
Limitations
| 1.728516 |
other
|
Study
|
[
0.3994140625,
0.001285552978515625,
0.59912109375
] |
[
0.9736328125,
0.0253143310546875,
0.0007233619689941406,
0.000339508056640625
] |
In addition, relatively few people have reported that they do not belief in God. In most cohorts, around 60 participants, and in 1988, even as few as 22, chose this answer option. We only conducted extreme group comparisons here because we considered other answer options to be too vague to conduct meaningful analyses. Because this low case number could have underestimated the strength of correlations with other variables, reported effect sizes may be seen as the lower threshold of true effect strengths. The consistency of our results in terms of effect strength and size, however, support our interpretations.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
39057185_p51
|
39057185
|
sec[4]/p[0]
|
5. Conclusions
| 2.302734 |
other
|
Study
|
[
0.1595458984375,
0.0006837844848632812,
0.83984375
] |
[
0.99365234375,
0.00536346435546875,
0.0008597373962402344,
0.0001646280288696289
] |
In conclusion, we show here negative associations of religiosity but none for spirituality with crystallized intelligence in fourteen population-representative cohorts of US citizens from 1988 to 2022. These results were broadly generalized across age groups, cohorts, and analytical approaches, thus suggesting that religiosity and intelligence may possibly be functionally equivalent to some extent, whilst spirituality represents a distinct construct that is not. Increasing associations of religious beliefs with crystallized intelligence across cohorts may conceivably be attributed to the decreasing societal value of religiosity in the USA.
|
[
"Florian Dürlinger",
"Thomas Goetz",
"Jakob Pietschnig"
] |
https://doi.org/10.3390/jintelligence12070065
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p0
|
PMC11277988
|
sec[0]/p[0]
|
Background
| 3.990234 |
biomedical
|
Study
|
[
0.99951171875,
0.0001615285873413086,
0.00023186206817626953
] |
[
0.87060546875,
0.0247802734375,
0.10406494140625,
0.0005097389221191406
] |
Giardia duodenalis ( G. duodenalis ) is a protozoan flagellate infecting the intestinal tract of human and animals with a worldwide distribution . The fecal–oral route, including direct (i.e., person-to-person, animal-to-animal or zoonotic) or indirect (i.e., waterborne or foodborne) are the main transmission mode of G. duodenalis by consumption of infective cyst . Spreading of G. duodenalis in different communities is related to sanitation level, Human Development Index (HDI), income level, and drinking water quality . Therefore, the occurrence of G. duodenalis is much lower in developed countries than in less-developed countries . Some populations, including children, pregnant women, and immunocompromised people are at higher risk of G. duodenalis infection .
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p1
|
PMC11277988
|
sec[0]/p[1]
|
Background
| 3.902344 |
biomedical
|
Review
|
[
0.99853515625,
0.0006899833679199219,
0.0006380081176757812
] |
[
0.06207275390625,
0.0328369140625,
0.904296875,
0.000850677490234375
] |
The common clinical symptoms/signs of giardiasis include fatty stools (steatorrhea), nausea, vomiting, abdominal discomfort, abdominal bloating, cramps, malabsorption, and weight loss . Among clinical manifestations, diarrhea is the cause of mortality of about 480,000 young children worldwide, responsible for 9% of all deaths among children under 5 years of age in 2019 ( https://data.unicef.org/topic/child-health/diarrhoeal-disease/ .). Based on the World Health Organization (WHO) reports in 2010, giardiasis is assessed to cause ∼28.2 million cases of diarrhea . Moreover, chronic giardiasis is related with food allergies , irritable bowel syndrome (IBS) , chronic fatigue syndrome , arthritis , as well as growth deficiency in children .
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p2
|
PMC11277988
|
sec[0]/p[2]
|
Background
| 3.878906 |
biomedical
|
Review
|
[
0.99853515625,
0.000629425048828125,
0.000835418701171875
] |
[
0.26513671875,
0.002422332763671875,
0.73193359375,
0.0004949569702148438
] |
Children are more exposed to different environmental sources (e.g., playing with soil) and also have immature immune systems to fight infections . Therefore, children have a higher probability of contracting infectious agents. Determination of the epidemiological patterns of G. duodenalis infection is necessary to design future control programs and preventive measures to reduce the incidence of the infection. To address this gap, we designed a systematic review and meta-analysis to assess the prevalence of G. duodenalis and associated risk factors in African children.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p3
|
PMC11277988
|
sec[1]/sec[0]/p[0]
|
Information sources and systematic search
| 3.919922 |
biomedical
|
Review
|
[
0.9892578125,
0.0038509368896484375,
0.0067596435546875
] |
[
0.0166168212890625,
0.0019407272338867188,
0.98095703125,
0.0003685951232910156
] |
The present systematic review and meta-analysis was conducted based on the Preferred Reporting
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p4
|
PMC11277988
|
sec[1]/sec[0]/p[1]
|
Information sources and systematic search
| 3.978516 |
biomedical
|
Study
|
[
0.99951171875,
0.000308990478515625,
0.00021266937255859375
] |
[
0.94970703125,
0.0022029876708984375,
0.04791259765625,
0.00028228759765625
] |
Items for Systematic Reviews and Meta-analyses (PRISMA) protocol . Published articles on the prevalence of G. duodenalis in African children was gathered through three international databases (i.e. PubMed, Scopus, and Web of Science) and Google Scholar search engine between 1 January 2000 and 15 March 2022. The search process was accomplished using Medical Subject Headings (MeSH) terms alone or in combination: (“Intestinal protozoa” OR “ Giardia ” OR “Giardiasis”) AND (“Prevalence” OR “Epidemiology”) AND (“Children”). Moreover, the references list of all selected articles was hand-searched to find other relevant articles or their citations by searching in Google Scholar.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p5
|
PMC11277988
|
sec[1]/sec[1]/p[0]
|
Inclusion criteria, study selection and data extraction
| 4.023438 |
biomedical
|
Review
|
[
0.998046875,
0.001308441162109375,
0.0008172988891601562
] |
[
0.1363525390625,
0.0014505386352539062,
0.86181640625,
0.0006070137023925781
] |
To assess the article eligibility based on determined inclusion criteria, all papers were reviewed by two independent reviewers and possible contradictions among studies were removed by discussion and consensus. The inclusion criteria for this systematic review were as follows: (1) full-texts or abstracts published in English from Africa continent; (2) peer-reviewed original research papers or short reports; (3) cross-sectional studies that estimated the prevalence of Giardia in children population (≤18 years); (4) utilizing fecal microscopy, coproantigen or molecular diagnostic methods; (5) reports with information on the total sample size and positive samples; and (6) published online from 1 January 2000 and 15 March 2022. Those papers without full-text accessibility or papers that did not meet the above criteria were excluded. Next, the desired data were gathered precisely using a data extraction form including, the first author's last name, the year the study was conducted and the publication year, countries, provinces and cities, types of method used, total sample sizes, number of positive samples, types of children, gender and age of children.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p6
|
PMC11277988
|
sec[1]/sec[2]/p[0]
|
Study quality assessment
| 3.878906 |
biomedical
|
Study
|
[
0.99853515625,
0.0003228187561035156,
0.0010404586791992188
] |
[
0.99169921875,
0.00360870361328125,
0.00449371337890625,
0.00008380413055419922
] |
The Joanna Briggs Institute (JBI) checklist was applied for the risk of bias (internal validity) assessment of the included articles . This checklist comprises ten questions with four options including Yes, No, Unclear, and Not applicable. Summary, a study can be awarded a maximum of one star for each numbered item. The papers with a total score of 4–6 and 7–10 points were specified as the moderate and high quality, respectively. Based on the obtained score, the authors have decided to include (4–10 points) and exclude (≤3 points) the papers.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p7
|
PMC11277988
|
sec[1]/sec[3]/p[0]
|
Meta-analysis
| 4.085938 |
biomedical
|
Study
|
[
0.99951171875,
0.0003218650817871094,
0.0002720355987548828
] |
[
0.9990234375,
0.00025534629821777344,
0.0008325576782226562,
0.0000641942024230957
] |
For each included study, the point estimates and their respective 95% confidence intervals (CI) using a random effect model (REM) were calculated. The REM allows for a distribution of true effect sizes between articles. To visualize possible heterogeneity among included studies the forest plot analysis was used. The heterogeneity index among the included studies was defined using the I 2 index and Tau squared to reveal the variation in study outcomes between individual studies . The univariate and multivariable meta-regression analysis was used to estimate the effects of probable factors in heterogeneity . To investigate the effect of each study on the pooled estimation of prevalence, the sensitivity analysis method was used by removing studies one by one. The robustness of each model was evaluated and finally, the most favorable model was chosen.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p8
|
PMC11277988
|
sec[1]/sec[3]/p[1]
|
Meta-analysis
| 4.046875 |
biomedical
|
Study
|
[
0.99951171875,
0.0002225637435913086,
0.0001773834228515625
] |
[
0.9990234375,
0.00023126602172851562,
0.0006718635559082031,
0.000057756900787353516
] |
Using sub-group analyses, the pooled prevalence of Giardia infection was estimated according to countries, types of diagnostic methods, types of children, and periods of studies. An odds ratio (OR) (and the corresponding 95% (CI)) was calculated for each study to assess the association between Giardia spp. prevalence and risk factors such as sex (male and female) and place of living (rural and urban).
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p9
|
PMC11277988
|
sec[1]/sec[3]/p[2]
|
Meta-analysis
| 3.970703 |
biomedical
|
Study
|
[
0.99951171875,
0.00015056133270263672,
0.0005578994750976562
] |
[
0.99853515625,
0.0009531974792480469,
0.0006399154663085938,
0.000050187110900878906
] |
The publication bias was evaluated with Egger's regression test and interpretation of the funnel plot in this meta-analysis and the trim-and-fill method was used to estimate the number of censored studies and correct the overall estimate .
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p10
|
PMC11277988
|
sec[1]/sec[3]/p[3]
|
Meta-analysis
| 3.867188 |
biomedical
|
Study
|
[
0.99951171875,
0.0001722574234008789,
0.0003287792205810547
] |
[
0.9990234375,
0.0005979537963867188,
0.00023818016052246094,
0.00005161762237548828
] |
Moreover, due to different sensitivities and specificities of diagnostic methods, we assumed that our results would be “apparent” prevalence rates, and did not represent true prevalence rates. The prevalence of G. duodenalis in children in different countries from Africa was demonstrated as a world map using ArcGIS 10.3 software ( https://www.arcgis.com ). Source of vector map is from ESRI ( www.esri.com/en-us/home ). This meta-analysis was conducted with the Stata version 16 software and the trial version of Comprehensive Meta-Analysis software vs. 3. A P -value of <0.05 was considered significant.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p11
|
PMC11277988
|
sec[2]/sec[0]/p[0]
|
Characteristics of the eligible studies
| 3.958984 |
biomedical
|
Study
|
[
0.99853515625,
0.0006103515625,
0.0006742477416992188
] |
[
0.86279296875,
0.00127410888671875,
0.1358642578125,
0.00035381317138671875
] |
A flowchart depicting the identification process of qualifying studies is presented in Fig. 1 . In brief, the systematic search identified 4702 potentially relevant articles. After removing duplicates and/or non-eligible papers, 114 articles from 29 countries across Africa met the inclusion criteria in the systematic review and meta-analysis. The countries with the highest number of studies were Ethiopia (17.54%; 20/114 studies) and Egypt (16.66%; 19/114 studies). The main characteristics of each study are shown in the Supplementary Table 1. The results of quality assessment according to JBI with references for eligible studies are depicted in Supplementary Table 1. The included articles in the present meta-analysis showed an acceptable quality. Fig. 1 PRISMA flow diagram describing included/excluded studies. Fig. 1
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p12
|
PMC11277988
|
sec[2]/sec[1]/p[0]
|
The pooled prevalence of G. Duodenalis in children
| 4.105469 |
biomedical
|
Study
|
[
0.99951171875,
0.00028514862060546875,
0.0002658367156982422
] |
[
0.99951171875,
0.0001951456069946289,
0.0003707408905029297,
0.000050902366638183594
] |
A total of 63,165 children were evaluated in 114 studies regarding the prevalence of G. duodenalis in African children, of which 10,202 were diagnosed as infected based on diagnostic criteria. After performing sensitivity analysis by removing one-by-one studies and selecting the robustness model, the overall prevalence of G. duodenalis infection in African children was estimated at 18.3% (95% CI,16.5–20.2) using the REM .
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p13
|
PMC11277988
|
sec[2]/sec[1]/p[1]
|
The pooled prevalence of G. Duodenalis in children
| 4.160156 |
biomedical
|
Study
|
[
0.99951171875,
0.000274658203125,
0.0004036426544189453
] |
[
0.9990234375,
0.0001825094223022461,
0.0007257461547851562,
0.000056684017181396484
] |
According to the heterogeneous assessment indicators between studies , it was shown that there is a high heterogeneity between the studies included in this meta-analysis. In the next step, multivariable and univariate meta-regression models were used to find the origin of heterogeneity ( Table 1 ). Multivariable meta-regression analysis showed that the type of population studied in children it may be the source of heterogeneity ( p = 0.037), however, this analysis did not show significant heterogeneity in the quality of the studies included in the meta-analysis, study location, sample size, diagnostic methods, and age groups ( P > 0.05) ( Table 1 ). In addition, the univariate meta-regression model showed that the location of the study (country) ( p = 0.006) and the type of population under study ( p = 0.004) may be the causes of heterogeneity ( Table 1 ). Table 1 Result of multivariable and univariate meta-regression model to identify possible sources of heterogeneity. Table 1 The probable source of heterogeneity Multivariable Univariate Coefficient (95%CI) P-value Adj R-squared Coefficient (95%CI) P-value Adj R-squared Years of publication −0.00101 0.745 9.76% (Multivariable) −0.00040 0.893 −0.91% Risk of bias −0.02642 0.148 −0.03138 0.057 2.42% Country 0.00705 0.117 0.01821 0.006 ⁎ 12.18% Sample size −0.00001 0.556 −0.00002 0.248 0.32% Detection method −0.01604 0.443 −0.01613 0.431 −0.35% Population under study −0.00365 0.037 ⁎ −0.00318 0.004 ⁎ 10.14% Age group −0.00007 0.998 −0.00267 0.913 −0.91% ⁎ Statistically significant (P-value≤0.05)
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p14
|
PMC11277988
|
sec[2]/sec[1]/p[2]
|
The pooled prevalence of G. Duodenalis in children
| 4.207031 |
biomedical
|
Study
|
[
0.99951171875,
0.00030040740966796875,
0.00030517578125
] |
[
0.99853515625,
0.00023615360260009766,
0.0011081695556640625,
0.00006246566772460938
] |
The subgroup meta-analysis using the REM was used to estimate the overall prevalence in groups including country, type of study population, year of publication, detection method, and age group ( Table 2 ). According to the location of the study, the highest prevalence of G. duodenalis was in African children in Niger 65.1% (55–75.2), Algeria 54.5% (1.04–98.07), Senegal 45.2% (40.4–50.1), and Guinea-Bissau 40.6% (30.9–50.2), respectively. On the other hand, the lowest prevalence was related to Cameroon 0.08% (0.02–1.05), and the Central African Republic 0.09% (0.001–1.09) . Table 2 The overall Prevalence G. duodenalis in African children. Table 2 No. studies No. examined No. positive Prevalence (95%CI) Heterogeneity χ 2 P-value I 2 (%) Tau-squared Country Algeria 2 294 111 54.5% (1.04–98.07) 82.97 <0.001 98.8% 0.1451 Angola 1 328 66 20.1% (15.8–24.5) NA NA NA NA Botswana 1 200 33 16.5% (11.4–21.6) NA NA NA NA Burkina Faso 2 694 143 19.6% (3.02–36) 32.94 <0.001 97.0% 0.0136 Cameroon 1 831 7 0.08% (0.02–1.05) NA NA NA NA Central African Republic 1 333 3 0.09% (0.001–1.09) NA NA NA NA Chad 1 200 21 10.5% (6.03–14.7) NA NA NA NA Côte d'Ivoire 2 1704 259 17.1% (10.3–23.9) 7.75 0.005 87.1% 0.0021 Egypt 19 7592 1642 22.1% (14.6–29.6) 1746.61 <0.001 99.0% 0.0270 Ethiopia 20 6493 1063 13.9% (9.03–18.5) 947.43 <0.001 98.0% 0.0107 Ghana 4 5073 866 16.4% (6.07–26.1) 276.07 <0.001 98.9% 0.0097 Guinea 1 392 20 5.01% (2.09–7.03) NA NA NA NA Guinea-Bissau 3 588 224 40.6% (30.9–50.2) 7.54 0.023 73.5% 0.0051 Kenya 5 5924 357 6.04% (3.09–9.0) 70.63 <0.001 94.3% 0.0008 Libya 7 3273 387 11.6% (5.01–18) 357.73 <0.001 98.3% 0.0072 Malawi 2 228 33 17.2% (4.07–29.7) 2.93 0.087 65.8% 0.0058 Morocco 3 1419 200 14% (11.1–16.8) 4.61 0.100 56.6% 0.0004 Mozambique 6 7028 1813 19.8% (9.08–29.9) 499.67 <0.001 99.0% 0.0155 Nigeria 10 12,719 757 9.06% (6.09–12.2) 607.48 <0.001 98.5% 0.0016 Niger 1 86 56 65.1% (55–75.2) NA NA NA NA Rwanda 4 1985 855 38.7% (10.5–66.9) 740.96 <0.001 99.6% 0.0822 Sudan 8 2191 475 21.7% (14.9–28.4) 114.13 <0.001 93.9% 0.0086 Tanzania 3 1524 295 17.8% (5.03–41.1) 286.46 <0.001 99.3% 0.0413 Zambia 2 1115 261 19.5% (0.09–38.1) 67.15 <0.001 98.5% 0.0177 Sahrawi 1 120 41 34.2% (25.7–42.7) NA NA NA NA São Tomé and Prín 1 134 10 7.05% (3–11.9) NA NA NA NA Several countries in Africa 1 135 7 5.02% (1.04–8.09) NA NA NA NA South Africa 1 162 16 9.09% (5.03–14.5) NA NA NA NA Senegal 1 400 181 45.2% (40.4–50.1) NA NA NA NA Type of study population Children 51 27,701 5116 19.3% (16.2–22.4) 5085.47 <0.001 99.0% 0.0124 Children with diarrhea 16 6070 1038 17% (12–21.9) 516.57 <0.001 97.1% 0.0095 Displaced children 1 450 91 20.2% (16.5–23.9) NA NA NA NA Handicapped children 1 56 17 30.4% (18.3–42.4) NA NA NA NA HIV Infected Children 1 35 9 25.7% (11.2–40.2) NA NA NA NA Iron-deficient children 1 575 375 65.2% (61.3–69.1) NA NA NA NA Preschool children 4 1205 143 11.3% (7.08–14.7) 10.85 0.013 72.4% 0.0009 Primary school children 11 8105 790 13% (8.09–17) 786.69 <0.001 98.7% 0.0044 School Children 27 19,391 2712 18.5% (14.6–22.9) 3443.14 <0.001 99.2% 0.0107 Children with allergy 1 27 3 7.04% (2.05–17.03) NA NA NA NA Diagnostic method ELISA 1 274 25 9.01% (5.07–12.5) NA NA NA NA Microscopic examination 94 52,103 7363 16.3% (14.5–18.1) 8430.46 <0.001 98.9% 0.0079 Molecular examination 6 1558 381 22.7% (8.03–37.1) 384.88 <0.001 98.7% 0.0311 Real-time PCR 10 7296 2098 36.6% (24.9–48.4) 1412.18 <0.001 99.4% 0.0349 Immunoassays 1 983 25 9.07% (7.08–11.5) NA NA NA NA Immunofluorescent microscopy 1 120 41 34.2% (25.7–42.7) NA NA NA NA Rapid immunochromatographic test 1 831 199 23.9% (21–26.8) NA NA NA NA Year 2000–2005 10 11,353 876 17.4% (11.8–23.0) 1696.47 <0.001 99.5% 0.0078 2006–2011 23 10,834 2511 22.1% (17.0–27.33) 1175.61 <0.001 98.1% 0.0153 2012–2017 52 25,865 3985 17.1% (14.5–19.7) 4633.68 <0.001 98.9% 0.0085 2018–2022 29 15,113 2830 18% (13.7–22.2) 2318.93 <0.001 98.8% 0.0131 Age group <5 years 47 24,378 4382 17.9% (14.7–21.1) 4779.66 <0.001 99.0% 0.0120 5–12 years 55 25,572 4333 19.5% (16.6–22.5) 5576.79 <0.001 99.0% 0.0120 12–19 years 12 13,215 1487 14.9% (10.4–19.4) 1035.52 <0.001 98.9% 0.0059 NA: Not applicable, ELISA: enzyme-linked immunosorbent assay; PCR: polymerase chain reaction. Fig. 2 Prevalence of G. duodenalis in children on the African continent. Fig. 2
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11277988_p15
|
PMC11277988
|
sec[2]/sec[1]/p[3]
|
The pooled prevalence of G. Duodenalis in children
| 4.003906 |
biomedical
|
Study
|
[
0.99951171875,
0.0002624988555908203,
0.00043892860412597656
] |
[
0.99951171875,
0.0002033710479736328,
0.00021398067474365234,
0.00004202127456665039
] |
Based on the type of studied groups of children, the highest prevalence was related to, iron-deficient children 65.2% (61.3–69.1), handicapped children 30.4% (18.3–42.4), HIV infected children 25.7% (11.2–40.2) and displaced children 20.2% (16.5–23.9), respectively ( Table 2 ). Based on the age groups of the studied children, the prevalence of G. duodenalis in African children was estimated at under 5 years 17.9% (14.7–21.1), 5–12 years 19.5% (16.6–22.5) and 12–19 years 14.9% (10.4–19.4), respectively.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p16
|
PMC11277988
|
sec[2]/sec[1]/p[4]
|
The pooled prevalence of G. Duodenalis in children
| 3.992188 |
biomedical
|
Study
|
[
0.99951171875,
0.0002963542938232422,
0.00038361549377441406
] |
[
0.99951171875,
0.0003666877746582031,
0.0002396106719970703,
0.000049233436584472656
] |
The prevalence of G. duodenalis in children on the African continent was estimated at 17.4% (11.8–23.0) in 2000–2005, 22.1% (17.0–27.33) in 2006–2011, 17.1% (14.5–19.7) in 2012–2017, and 18% (13.7–22.2) in 2018–2022 ( Table 2 ).
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p17
|
PMC11277988
|
sec[2]/sec[2]/p[0]
|
Risk factors
| 4.09375 |
biomedical
|
Study
|
[
0.99951171875,
0.00026988983154296875,
0.0003943443298339844
] |
[
0.99951171875,
0.0001844167709350586,
0.00023496150970458984,
0.00004297494888305664
] |
Based on children's sex, boys had a higher risk for G. duodenalis than girls (OR = 1.26; 95% CI: 1.13–1.40, p < 0.001) (Q value = 52.84, d.f. = 26, p = 0.001, I 2 = 50.79%, Tau squared = 0.082), . Additionally, living in a rural area compared to an urban area increased the chance of contracting G. duodenalis by 1.24 times, but this increase was not statistically significant (OR = 1.24;95% CI:0.76–2.00, P = 0.375) (Q statistic = 20.35, d.f. = 5, p = 0.001, I 2 = 75.43%, Tau squared = 0.254) . Fig. 3 Relationship between gender and G. duodenalis in children of Africa. Fig. 3 Fig. 4 Relationship between the living area and G. duodenalis in children of Africa. Fig. 4
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p18
|
PMC11277988
|
sec[2]/sec[3]/p[0]
|
Publication bias
| 4.140625 |
biomedical
|
Study
|
[
0.99951171875,
0.0002758502960205078,
0.0002536773681640625
] |
[
0.99951171875,
0.0002123117446899414,
0.00038242340087890625,
0.000057578086853027344
] |
Egger's regression test and asymmetry in the funnel plot displays that there is significant publication bias for included studies in this meta-analysis (bias = 10.018, 95%CI: 7 7.941–12.096, P < 0.001) . Therefore, the trim-and-fill model using non-parametric methods was used for correction the meta-analysis. This model showed that 54 hypothetical studies about the prevalence of G. duodenalis in African children were censored in this meta-analysis. Consequently, the pooled prevalence of G. duodenalis corrected by the REM based on the trim-and-fill model was estimated to be 4.09% (95%CI: 2.09–7.0). Fig. 5 Funnel plot with 95% confidence interval for assessing the publication bias. Fig. 5
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p19
|
PMC11277988
|
sec[3]/p[0]
|
Discussion
| 4.09375 |
biomedical
|
Study
|
[
0.99951171875,
0.0002627372741699219,
0.0001863241195678711
] |
[
0.9990234375,
0.0001970529556274414,
0.0004737377166748047,
0.00006335973739624023
] |
This is the first study to estimate the prevalence of G. duodenalis among African children. The prevalence obtained for G. duodenalis in the meta-analysis were relatively high, especially in studies that have used the Real-time PCR method ( Table 2 ). Conventionally, microscopy detection method using staining procedures is considered as the gold standard method for the detection of cysts and/or trophozoites of G. duodenalis . However, molecular methods are preferred for conducting research activities because they have higher sensitivity and specificity and the interpretation of results is easier . Accordingly, the pooled prevalence provided by molecular methods could be closer to the true prevalence. For a deeper understanding of this issue, it is necessary for researchers to use molecular methods in addition to microscopy methods.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p20
|
PMC11277988
|
sec[3]/p[1]
|
Discussion
| 4 |
biomedical
|
Study
|
[
0.99951171875,
0.00015532970428466797,
0.00031685829162597656
] |
[
0.9892578125,
0.0009546279907226562,
0.0098419189453125,
0.00009769201278686523
] |
By considering the prevalence of G. duodenalis in different African countries, the highest infection rates were found in Niger (one study with pooled prevalence of 65.1%) and Algeria (two studies with pooled prevalence of 54.5%). By contrast, infection rates in Cameroon (one study with pooled prevalence of 0.08%) and Central African Republic (one study with pooled prevalence of 0.09%) countries were low. Several environmental and sociodemographic parameters are complicated in the different prevalence rates obtained, including climatic condition, parasite control measures, HDI , and the use of diverse diagnostic methods in different regions . In addition to all these factors, it is necessary to conduct more studies in African countries and some countries that have not done any research on this issue should consider it; finally, a deeper understanding of its prevalence in children in different parts of Africa can be obtained.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p21
|
PMC11277988
|
sec[3]/p[2]
|
Discussion
| 3.298828 |
biomedical
|
Study
|
[
0.998046875,
0.0002799034118652344,
0.001445770263671875
] |
[
0.998046875,
0.0008840560913085938,
0.0008387565612792969,
0.00006961822509765625
] |
Considering the year of publication ( Table 2 ), the prevalences in different time periods from 2000 to 2022 were almost similar. Therefore, the results of this meta-analysis study, especially the pooled prevalence rates based on the year of publication, should be interpreted with caution. Hence, factors such as the number of published articles and the sample size of studies each year may play a role in causing heterogeneity.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p22
|
PMC11277988
|
sec[3]/p[3]
|
Discussion
| 3.232422 |
biomedical
|
Study
|
[
0.9990234375,
0.0003383159637451172,
0.0007638931274414062
] |
[
0.99658203125,
0.0027828216552734375,
0.0003979206085205078,
0.00011849403381347656
] |
Living in a rural area compared to an urban area, and boys compared to girls increased the chance of contracting G. duodenalis by 1.24 and 1.26 times, respectively, which might be explained by lower personal hygiene scores and more contact with G. duodenalis cysts-contaminated water and vegetables.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11277988_p23
|
PMC11277988
|
sec[3]/p[4]
|
Discussion
| 3.9375 |
biomedical
|
Study
|
[
0.9990234375,
0.0003039836883544922,
0.000827789306640625
] |
[
0.9990234375,
0.00017654895782470703,
0.0009288787841796875,
0.000056862831115722656
] |
The present study has a number of limitations. First, despite our comprehensive search, there was a paucity or absence of data for a number of countries, and many of the available studies had limited sample sizes and a lack of data on socio-demographic and/or risk factors. Moreover, in some countries only one or two eligible studies was identified, which could compromise somewhat the interpretation of present estimates. Second, studies included were undertaken during different time periods, with an absence of recent data for some countries, limiting the accuracy of inter-regional comparisons. Third, there was a high heterogeneity in this meta-analysis. Although we investigated its possible source by performing meta-regression analysis.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11277988_p24
|
PMC11277988
|
sec[4]/p[0]
|
Conclusions
| 2.929688 |
biomedical
|
Other
|
[
0.994140625,
0.0031147003173828125,
0.002925872802734375
] |
[
0.00540924072265625,
0.9833984375,
0.0103912353515625,
0.0006971359252929688
] |
In summary, prevention and control scheme of G. duodenalis in children should receive greater attention by health officials and health policymakers, especially in African countries where prevalence is highest. Also, we recommend that periodic screenings for G. duodenalis in such countries should be incorporated into the routine clinical care of iron-deficient children, handicapped children, HIV infected children, and displaced children.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p25
|
PMC11277988
|
sec[5]/p[0]
|
Funding
| 0.817383 |
other
|
Other
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[
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This study was supported by Zoonoses Research Center , Jahrom University of Medical Sciences, Jahrom, Iran .
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
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PMC11277988_p26
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PMC11277988
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Ethics approval and consent to participate
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biomedical
|
Other
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This study was approved by Jahrom University of Medical Sciences Ethics Committee .
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11277988_p27
|
PMC11277988
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sec[7]/p[0]
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Consent for publication
| 1.026367 |
other
|
Other
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[
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Not applicable.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
fr
| 0.857141 |
PMC11277988_p28
|
PMC11277988
|
sec[8]/p[0]
|
CRediT authorship contribution statement
| 0.974121 |
other
|
Other
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Sara Matin: Supervision, Methodology, Conceptualization. Vahid Rahmanian: Software, Formal analysis. Ahmad Meshkin: Investigation. Bahareh Bahadori Mazidi: Methodology. Ali Taghipour: Writing – review & editing, Writing – original draft, Supervision, Methodology, Conceptualization. Amir Abdoli: Writing – original draft.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11277988_p29
|
PMC11277988
|
sec[9]/p[0]
|
Declaration of competing interest
| 0.981934 |
other
|
Other
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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
|
[
"Sara Kalavani",
"Sara Matin",
"Vahid Rahmanian",
"Ahmad Meshkin",
"Bahareh Bahadori Mazidi",
"Ali Taghipour",
"Amir Abdoli"
] |
https://doi.org/10.1016/j.parepi.2024.e00365
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11278003_p0
|
PMC11278003
|
sec[0]/p[0]
|
1. Introduction
| 4.378906 |
biomedical
|
Study
|
[
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0.00039577484130859375,
0.00046539306640625
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[
0.88916015625,
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The cerebellum, an integral component of the central nervous system, is pivotal for motor coordination and balance . Its intricate somatotopic organization establishes direct connectivity with the primary motor and sensory cortices, thereby orchestrating a sophisticated network for sensorimotor integration. In addition to its fundamental role in motor and sensory processing, the cerebellum is actively involved in various perceptual tasks, including the interpretation of visual, auditory, tactile, and nociceptive stimuli. Furthermore, the cerebellum plays a critical role in cognitive and emotional functions, forming connections with the prefrontal cortex and limbic system, and thus significantly contributing to numerous mental and emotional processes . Heavy alcohol intake exerts deleterious effects on the cerebellum, leading to cellular apoptosis, tissue atrophy, and cognitive dysfunction . Alcohol addiction (AA) is a significant health risk, contributing notably to liver cirrhosis and ranking as the third leading cause of premature mortality in European countries. Moreover, AA is implicated in 60 different illnesses and pathological conditions, with approximately 2.3 million deaths annually attributed to alcohol consumption . The binge ethanol model for studying alcohol dependence has been extensively explored in preclinical research. Faingold et al. determined that administering ethanol every 8 h over a four-day period effectively induces maximal signs of ethanol intoxication. Nixon et al. also found that administering ethanol over four days induces alcohol addiction in rats. In a study by Crews et al. , rats received intragastric ethanol three times daily for four days, resulting in blood alcohol levels ranging from 250 to 400 mg, causing significant intoxication.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999994 |
PMC11278003_p1
|
PMC11278003
|
sec[0]/p[1]
|
1. Introduction
| 4.457031 |
biomedical
|
Study
|
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Numerous studies have shown that binge ethanol consumption leads to brain damage . This damage begins in the frontal olfactory bulb after two days and progressively affects additional brain regions over time. Research consistently demonstrates that peak brain damage occurs shortly after the final dose on the fourth day . Although the exact mechanism of AA is unclear, several factors contribute to its etiology. AA causes alcohol toxicity in organs, leading to cellular tissue damage and death . Researchers have shown a relationship between proinflammatory cytokines and alcohol addiction. An experimental study revealed that long-term alcohol consumption exacerbates the inflammation process and elevates TNF-α (tumor necrosis factor-alpha) levels in rats’ serum, leading to tissue damage . A clinical study found an association between alcohol consumption and serum TNF-α levels in 30 male alcohol-addicted patients. The authors suggested that a high level of TNF-α indicates the longevity and severity of alcohol addiction . Additionally, alcohol consumption plays an important role in the activation of mitochondrial-dependent apoptosis through APAF-1 (apoptotic protease activating factor-1) . Wang et al. showed that high-dose alcohol consumption led to the production of reactive oxygen species (ROS), eventually causing apoptosis in mouse primary cardiomyocytes. Similarly, Hajnóczky et al. found that prolonged alcohol consumption disrupted the membrane permeabilization of mitochondria, allowing for the induction of apoptosis in cardiac cells.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11278003_p2
|
PMC11278003
|
sec[0]/p[2]
|
1. Introduction
| 4.304688 |
biomedical
|
Review
|
[
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[
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Anticonvulsants, initially developed for managing epilepsy, have emerged as a promising avenue in the treatment of alcohol addiction and dependency . Recent investigations underscore the efficacy of antiepileptic agents in mitigating alcohol intake, as evidenced by clinical trials . Zonisamide, an anticonvulsant sharing mechanistic similarities with topiramate , has been proposed as a potential therapeutic intervention for AA. Its mechanism of action involves the reinforcement of gamma-aminobutyric acid (GABA)-mediated neurotransmission. GABA, a neurotransmitter intricately involved in the regulation of anxiety, sleep, and muscle tone , plays a pivotal role in attenuating alcohol cravings and the concomitant anxiety associated with alcohol withdrawal. Arias et al. studied the role of zonisamide in alcohol dependence and found that it could be used to treat alcohol dependence . A clinical study indicated that zonisamide reduced the stimulatory impacts of AA in patients . Previous studies have used various dosages of zonisamide across different species (rabbits at 3–30 mg/kg , mice at 0, 25, 50 mg/kg , and rats at 25–50 mg/kg ), indicating its effectiveness against neurological complications. Kumar et al. studied a higher dose of zonisamide (100 mg/kg) in rats and demonstrated significant neuroprotective potential against seizures by mitigating oxidative stress, inflammation, and neuronal death, indicating its promise as a neuroprotective agent for epilepsy and other neurodegenerative diseases.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11278003_p3
|
PMC11278003
|
sec[0]/p[3]
|
1. Introduction
| 4.082031 |
biomedical
|
Study
|
[
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Although the impacts of zonisamide on AA have been previously investigated, there is no study on the effects of zonisamide on cerebellar pathology in induced AA animal models. This study aimed to elucidate the impact of zonisamide in mitigating cerebellar cellular inflammation and apoptosis subsequent to AA by assessing the expression levels of APAF-1 and TNF-α via immunostaining and bioinformatic methods.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11278003_p4
|
PMC11278003
|
sec[1]/sec[0]/p[0]
|
2.1. Animal Housing and Experimental Design
| 4.046875 |
biomedical
|
Study
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Thirty male Wistar albino rats were allowed access to water and food ad libitum and housed in cages (12/12 dark/light period, 23 ± 1 °C). Zonisamide (100 mg in each capsule) was purchased from Gerenica ® company. Generica (Genveon Drug Company, Sarıyer, Istanbul, Turkey). The experimental design was modified according to the study by Faingold et al. . Thirty rats were categorized into three groups (ten rats per group): Sham group: 6 cc of physiological saline was given orally to rats 3 times a day for 4 days at 8 h intervals. Ethanol (EtOH) group: 6 cc of EtOH was administered orally to rats 3 times a day for 4 days at 8 h intervals. EtOH + zonisamide group: Rats were given 6 cc of EtOH orally 3 times a day for 4 days at 8 h intervals. One hour before each EtOH administration, 100 mg/kg of zonisamide was administered to the rats once a day for 4 days.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11278003_p5
|
PMC11278003
|
sec[1]/sec[1]/p[0]
|
2.2. Open Field Maze
| 4.035156 |
biomedical
|
Study
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This test was conducted according to the procedures previously described by Seibenhener et al. . A white, high-density, non-porous plastic chamber with dimensions of 50 × 50 × 38 cm was used, equipped with a video camera positioned above it. The rats were initially placed in the center of the chamber, and their movements were recorded using tracking software (EthoVision XT (version 17.5, Noldus Inc., Leesburg, VA, USA)). The rats were allowed to move freely throughout the maze for 10 min while the software tracked their movements. The total ambulatory distance (cm) was evaluated to measure the locomotor ability of the rats.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p6
|
PMC11278003
|
sec[1]/sec[2]/p[0]
|
2.3. Measurement of Serum TNF-α
| 4.046875 |
biomedical
|
Study
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All animals were euthanized with an intramuscular injection of 90 mg/kg ketamine and 8 mg/kg xylazine (Rompun; Bayer, Germany) after the maze test. Intracardiac blood samples were collected from rats and analyzed for serum TNF-α content via ELISA kit . Blood samples from each rat were centrifuged at 2000 rpm for 10 min, and the supernatant was collected. Serum TNF-α (pg/mL) content was measured according to the manufacturer’s instructions.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p7
|
PMC11278003
|
sec[1]/sec[3]/p[0]
|
2.4. Tissue Preparation
| 3.929688 |
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|
Study
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Cerebellar tissues were removed for histological examination. The dissected samples were further placed in zinc formalin, dehydrated using a series of alcohol solutions, and then embedded in paraffin wax. In total, 5 µm sections were stained with hematoxylin eosin and Luxol fast blue dye.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11278003_p8
|
PMC11278003
|
sec[1]/sec[4]/p[0]
|
2.5. Immunohistochemical Examination
| 4.15625 |
biomedical
|
Study
|
[
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[
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Cerebellar sections were subjected to dewaxing, hydration in graded alcohol solutions, and rinsing with distilled water. To inhibit endogenous peroxidase activity, 3% hydrogen peroxide (H 2 O 2 ) was applied to the slides. Following washing in phosphate-buffered saline (PBS), the sections were incubated overnight at a temperature of 4 °C with primary antibodies APAF-1 and TNF-α . Sections were biotinylated and reacted with peroxidase solution for 15 min. After PBS rinsing, diaminobenzidine (DAB) chromogen was used to observe color changes. The reactions were stopped using a PBS solution, and the sections were counterstained with hematoxylin dye. Subsequently, the slides were mounted and imaged using a Zeiss Imager A2 light microscope .
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11278003_p9
|
PMC11278003
|
sec[1]/sec[5]/p[0]
|
2.6. Semi-Quantitative Histological Scoring
| 4.054688 |
biomedical
|
Study
|
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All images underwent processing and quantification using the ImageJ software (version 1.53, http://imagej.nih.gov/ij . The APAF-1 and TNF-α staining intensity was measured by following the method described by Crowe et al. . The quantitative analysis involved examining ten fields from each specimen within the respective groups . In specimens, a brown color indicated positive expression of the antibody of interest, while a blue color signified negative expression. The signal intensity (expression) in a field was determined by dividing the intensity of the antibody of interest by the entire specimen area. The staining area/whole area ratio was computed for each specimen across ten fields. An average value was calculated for groups and subjected to semi-quantitative immunohistochemistry scoring.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p10
|
PMC11278003
|
sec[1]/sec[6]/p[0]
|
2.7. Functional Enrichment Analysis
| 4.128906 |
biomedical
|
Study
|
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Functional enrichment analyses were conducted to elucidate the mechanisms of action of zonisamide in AA through APAF-1 and TNF-α proteins. Initially, the protein−protein interaction (PPI) networks of target proteins were intersected with the AA-PPI network through Cytoscape software v3.10.1 using STRING data (maximum additional interactors: 100 and cut-off: 0.4). The numbers of shared proteins were visualized using the Venny 2.1 tool . Subsequently, the Kyoto Encyclopedia of Genes and Genomes (KEGGs) pathway enrichment and gene ontology (GO) function annotation analyses were performed using common proteins in the PPI network through ShinyGO 0.80 . Pathways exhibiting a false discovery rate (FDR) below 0.05 were categorized using fold enrichment. Consequently, KEGGs and GO molecular function (MF) box plots were generated.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11278003_p11
|
PMC11278003
|
sec[1]/sec[7]/p[0]
|
2.8. Statistical Analysis
| 3.707031 |
biomedical
|
Study
|
[
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Statistical analysis was performed using the IBM SPSS 25.0 software (IBM, Armonk, New York, NY, USA) (All graphs were constructed via IBM software.). Data distribution was assessed using the Shapiro–Wilk test and recorded as median (interquartile range—IQR) since data were not distributed normally. The non-parametric Kruskal−Wallis test compared more than two groups, with the post hoc Dunn test applied due to the limited number of animals in each group. Statistical significance was determined for values with p < 0.05.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p12
|
PMC11278003
|
sec[2]/sec[0]/p[0]
|
3.1. Zonisamide Elevated Locomotor Activities of Rats
| 4.082031 |
biomedical
|
Study
|
[
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Rats were tested for locomotor abilities in an open field maze. The total ambulatory distance of the rats in the maze is shown in Table 1 . The rats in the EtOH group covered significantly less distance compared to the sham group , indicating a clear negative impact of ethanol on locomotor activity. After zonisamide treatment, rats traveled significantly more distance compared to the EtOH group . These results suggest that zonisamide may mitigate the locomotor impairments induced by ethanol exposure, highlighting its potential therapeutic benefit.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p13
|
PMC11278003
|
sec[2]/sec[1]/p[0]
|
3.2. Zonisamide Decreased the Serum TNF-α Levels
| 3.998047 |
biomedical
|
Study
|
[
0.99951171875,
0.0002789497375488281,
0.00025963783264160156
] |
[
0.9990234375,
0.0004801750183105469,
0.00028324127197265625,
0.000072479248046875
] |
Serum TNF-α levels were significantly increased in the EtOH group compared to the sham group . After zonisamide treatment, serum TNF-α levels were significantly decreased in the EtOH + zonisamide group compared to the EtOH group , suggesting that zonisamide effectively alleviated ethanol-induced inflammation .
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p14
|
PMC11278003
|
sec[2]/sec[2]/p[0]
|
3.3. Zonisamide Improved Histopathology of Cerebellar Tissue
| 4.144531 |
biomedical
|
Study
|
[
0.99951171875,
0.0003426074981689453,
0.00017702579498291016
] |
[
0.9990234375,
0.0003666877746582031,
0.0003249645233154297,
0.00010102987289428711
] |
Histochemical staining of cerebellar tissue sections is shown in Figure 2 . In the cerebellar sections of the sham group, neurons in the molecular, ganglionic, and granular layers appeared normal . In the EtOH group, vascular dilatation and congestion in the meninges, loss of tissue integrity, neuronal degeneration in the molecular layer, and apoptosis in Purkinje cells were observed . In the zonisamide-treated group, vascular congestion in the meninges persisted, but pathologies in the molecular and ganglionic layers improved .
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p15
|
PMC11278003
|
sec[2]/sec[2]/p[1]
|
3.3. Zonisamide Improved Histopathology of Cerebellar Tissue
| 4.128906 |
biomedical
|
Study
|
[
0.99951171875,
0.00022602081298828125,
0.00018918514251708984
] |
[
0.9990234375,
0.0006604194641113281,
0.0003478527069091797,
0.00009524822235107422
] |
In cerebellar sections stained with Luxol fast blue dye, densely myelinated axons in the gray and white matter were stained blue. Neuropils in the white matter were intensely stained with eosin in the sham group . In the EtOH group, myelin density in the gray matter and neuropils in the white matter decreased compared to the sham group . Zonisamide treatment promoted myelination in the white and gray matter and enhanced neuropil formation in the white matter .
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11278003_p16
|
PMC11278003
|
sec[2]/sec[3]/p[0]
|
3.4. Zonisamide Prevented Apoptosis and Neuroinflammation in Cerebellum
| 4.1875 |
biomedical
|
Study
|
[
0.99951171875,
0.0003218650817871094,
0.00023448467254638672
] |
[
0.99951171875,
0.0002073049545288086,
0.00029468536376953125,
0.00007408857345581055
] |
Immunostaining of cerebellar tissue sections is shown in Figure 3 . The effects of AA on cell survival were monitored by APAF-1 expression. In the sham group, APAF-1 expression was generally negative in the molecular, ganglionic, and granular layers of the cerebellar cortex and white matter . Alcohol toxicity induced cell death and increased APAF-1 expression in the EtOH group. The APAF-1 expression was intense in the basket and star cells of the molecular layer, Purkinje cells, and granular cells. The APAF-1 expression was also increased in neuroglia cells in the white matter . In the EtOH + zonisamide group, APAF-1 expression was decreased in the cerebellar cortex and white matter, suggesting that zonisamide treatment promoted cell survival in the cortical layers . The neuroinflammatory effect of AA was analyzed by TNF-α expression. In the sham group, TNF-α expression was negative . In the EtOH group, TNF-α expression increased due to inflammation, especially in neurons in the molecular layer and Purkinje cells . After zonisamide treatment, TNF-α expression in the EtOH + zonisamide group became mostly negative in ganglionic and granular layers and neuroglia in the white matter .
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11278003_p17
|
PMC11278003
|
sec[2]/sec[4]/p[0]
|
3.5. Zonisamide Downregulated Expression of APAF-1 and TNF-α
| 4 |
biomedical
|
Study
|
[
0.99951171875,
0.00020456314086914062,
0.0003452301025390625
] |
[
0.99951171875,
0.0003638267517089844,
0.00020813941955566406,
0.00005882978439331055
] |
A semi-quantitative analysis of APAF-1 and TNF-α expressions is shown in Figure 4 . AA induced the upregulation of APAF-1 and TNF-α expression in the cerebellar cortex; however, zonisamide treatment significantly lowered their expression in cerebellar tissues.
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11278003_p18
|
PMC11278003
|
sec[2]/sec[5]/p[0]
|
3.6. AA Is Molecularly Associated with APAF-1 and TNF-α Pathways
| 4.335938 |
biomedical
|
Study
|
[
0.99951171875,
0.0002999305725097656,
0.0002758502960205078
] |
[
0.9990234375,
0.00019812583923339844,
0.0006666183471679688,
0.00007534027099609375
] |
The results of the analyses revealed the pathways and cellular events influenced by zonisamide-suppressed Apaf-1 and TNF-α in relation to AA. In the Apaf-1 protein–protein interaction (PPI) network, there were three shared proteins (GAPDH, TNF, IL1B) with the AD PPI network, whereas the TNF-α network included eight overlapping proteins (IL6, TLR4, INS, TNF, IL10, CD4, CRP, IL1B). TNF and IL-1B are proteins commonly obtained in both APAF-1- and TNF-α-associated interaction networks of AA. From a general perspective, both genes are commonly annotated with cytokine mechanisms, including cytokine activity, cytokine receptor binding, cytokine−cytokine receptor interaction, and molecular signaling activities, such as receptor−ligand activity signaling receptor activator/regulator activity. In the KEGGs analysis, APAF-1 revealed a remarkably significant annotation regarding antifolate resistance for AA. In the GO analysis results, APAF-1 was particularly associated with aspartic-type endopeptidase inhibitor activity and IL-1 receptor binding. On the other hand, concerning the relationship between TNF-α and AA, there were notably significant enrichments observed, specifically in choline binding and infections, including pathways related to Malaria and African trypanosomiasis .
|
[
"Fırat Aşır",
"Fikri Erdemci",
"Zuhal Çankırı",
"Tuğcan Korak",
"Süreyya Özdemir Başaran",
"Özge Kaplan",
"Özkan Yükselmiş",
"Nilüfer Dönmezdil",
"Hayat Ayaz",
"Şehmus Kaplan",
"Selçuk Tunik"
] |
https://doi.org/10.3390/life14070795
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
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