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Religion, Brain & Behavior
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/rrbb20
A many-analysts approach to the relation between
religiosity and well-being
Suzanne Hoogeveen, Alexandra Sarafoglou, Balazs Aczel, Yonathan Aditya,
Alexandra J. Alayan, Peter J. Allen, Sacha Altay, Shilaan Alzahawi, Yulmaida
Amir, Francis-Vincent Anthony, Obed Kwame Appiah, Quentin D. Atkinson,
Adam Baimel, Merve Balkaya-Ince, Michela Balsamo, Sachin Banker,
František Bartoš, Mario Becerra, Bertrand Beffara, Julia Beitner, Theiss
Bendixen, Jana B. Berkessel, Renatas Berniūnas, Matthew I. Billet, Joseph
Billingsley, Tiago Bortolini, Heiko Breitsohl, Amélie Bret, Faith L. Brown,
Jennifer Brown, Claudia C. Brumbaugh, Jacek Buczny, Joseph Bulbulia,
Saúl Caballero, Leonardo Carlucci, Cheryl L. Carmichael, Marco E. G. V.
Cattaneo, Sarah J. Charles, Scott Claessens, Maxinne C. Panagopoulos,
Angelo Brandelli Costa, Damien L. Crone, Stefan Czoschke, Christian
Czymara, E. Damiano D'Urso, Örjan Dahlström, Anna Dalla Rosa, Henrik
Danielsson, Jill De Ron, Ymkje Anna de Vries, Kristy K. Dean, Bryan J. Dik,
David J. Disabato, Jaclyn K. Doherty, Tim Draws, Lucas Drouhot, Marin
Dujmovic, Yarrow Dunham, Tobias Ebert, Peter A. Edelsbrunner, Anita
Eerland, Christian T. Elbaek, Shole Farahmand, Hooman Farahmand,
Miguel Farias, Abrey A. Feliccia, Kyle Fischer, Ronald Fischer, Donna Fisher-
Thompson, Zoë Francis, Susanne Frick, Lisa K. Frisch, Diogo Geraldes, Emily
Gerdin, Linda Geven, Omid Ghasemi, Erwin Gielens, Vukašin Gligorić, Kristin
Hagel, Nandor Hajdu, Hannah R. Hamilton, Imaduddin Hamzah, Paul H. P.
Hanel, Christopher E. Hawk, Karel K. Himawan, Benjamin C. Holding, Lina
E. Homman, Moritz Ingendahl, Hilla Inkilä, Mary L. Inman, Chris-Gabriel
Islam, Ozan Isler, David Izydorczyk, Bastian Jaeger, Kathryn A. Johnson,
Jonathan Jong, Johannes A. Karl, Erikson Kaszubowski, Benjamin A. Katz,
Lucas A. Keefer, Stijn Kelchtermans, John M. Kelly, Richard A. Klein, Bennett
Kleinberg, Megan L. Knowles, Marta Kołczyńska, Dave Koller, Julia Krasko,
Sarah Kritzler, Angelos-Miltiadis Krypotos, Thanos Kyritsis, Todd L. Landes,
Ruben Laukenmann, Guy A. Lavender Forsyth, Aryeh Lazar, Barbara J.
Lehman, Neil Levy, Ronda F. Lo, Paul Lodder, Jennifer Lorenz, Paweł Łowicki,
Albert L. Ly, Esther Maassen, Gina M. Magyar-Russell, Maximilian Maier,
Dylan R. Marsh, Nuria Martinez, Marcellin Martinie, Ihan Martoyo, Susan E.
Mason, Anne Lundahl Mauritsen, Phil McAleer, Thomas McCauley, Michael
McCullough, Ryan McKay, Camilla M. McMahon, Amelia A. McNamara,
Kira K. Means, Brett Mercier, Panagiotis Mitkidis, Benoît Monin, Jordan W.
Moon, David Moreau, Jonathan Morgan, James Murphy, George Muscatt,
Christof Nägel, Tamás Nagy, Ladislas Nalborczyk, Gustav Nilsonne, Pamina
Noack, Ara Norenzayan, Michèle B. Nuijten, Anton Olsson-Collentine, Lluis
Oviedo, Yuri G. Pavlov, James O. Pawelski, Hannah I. Pearson, Hugo Pedder,
Hannah K. Peetz, Michael Pinus, Steven Pirutinsky, Vince Polito, Michaela
Porubanova, Michael J. Poulin, Jason M. Prenoveau, Mark A. Prince, John
Protzko, Campbell Pryor, Benjamin G. Purzycki, Lin Qiu, Julian Quevedo
Pütter, André Rabelo, Milen L. Radell, Jonathan E. Ramsay, Graham Reid,
Andrew J. Roberts, Lindsey M. Root Luna, Robert M. Ross, Piotr Roszak,
Nirmal Roy, Suvi-Maria K. Saarelainen, Joni Y. Sasaki, Catherine Schaumans,
Bruno Schivinski, Marcel C. Schmitt, Sarah A. Schnitker, Martin Schnuerch,
Marcel R. Schreiner, Victoria Schüttengruber, Simone Sebben, Suzanne
C. Segerstrom, Berenika Seryczyńska, Uffe Shjoedt, Müge Simsek, Willem
W. A. Sleegers, Eliot R. Smith, Walter J. Sowden, Marion Späth, Christoph
Spörlein, William Stedden, Andrea H. Stoevenbelt, Simon Stuber, Justin Sulik,
Christiany Suwartono, Stylianos Syropoulos, Barnabas Szaszi, Peter Szecsi,
Ben M. Tappin, Louis Tay, Robert T. Thibault, Burt Thompson, Christian
M. Thurn, Josefa Torralba, Shelby D. Tuthill, Ann-Marie Ullein, Robbie C.
M. Van Aert, Marcel A. L. M. van Assen, Patty Van Cappellen, Olmo R. van
den Akker, Ine Van der Cruyssen, Jolanda Van der Noll, Noah N. N. van
Dongen, Caspar J. Van Lissa, Valerie van Mulukom, Don van Ravenzwaaij,
Casper J. J. van Zyl, Leigh Ann Vaughn, Bojana Većkalov, Bruno Verschuere,
Michelangelo Vianello, Felipe Vilanova, Allon Vishkin, Vera Vogel, Leonie
V. D. E. Vogelsmeier, Shoko Watanabe, Cindel J. M. White, Kristina Wiebels,
Sera Wiechert, Zachary Z. Willett, Maciej Witkowiak, Charlotte V. O. Witvliet,
Dylan Wiwad, Robin Wuyts, Dimitris Xygalatas, Xin Yang, Darren J. Yeo,
Onurcan Yilmaz, Natalia Zarzeczna, Yitong Zhao, Josjan Zijlmans, Michiel van
Elk & Eric-Jan Wagenmakers
To cite this article: Suzanne Hoogeveen, Alexandra Sarafoglou, Balazs Aczel, Yonathan Aditya,
Alexandra J. Alayan, Peter J. Allen, Sacha Altay, Shilaan Alzahawi, Yulmaida Amir, Francis-Vincent
Anthony, Obed Kwame Appiah, Quentin D. Atkinson, Adam Baimel, Merve Balkaya-Ince, Michela
Balsamo, Sachin Banker, František Bartoš, Mario Becerra, Bertrand Beffara, Julia Beitner, Theiss
Bendixen, Jana B. Berkessel, Renatas Berniūnas, Matthew I. Billet, Joseph Billingsley, Tiago
Bortolini, Heiko Breitsohl, Amélie Bret, Faith L. Brown, Jennifer Brown, Claudia C. Brumbaugh,
Jacek Buczny, Joseph Bulbulia, Saúl Caballero, Leonardo Carlucci, Cheryl L. Carmichael,
Marco E. G. V. Cattaneo, Sarah J. Charles, Scott Claessens, Maxinne C. Panagopoulos, Angelo
Brandelli Costa, Damien L. Crone, Stefan Czoschke, Christian Czymara, E. Damiano D'Urso,
Örjan Dahlström, Anna Dalla Rosa, Henrik Danielsson, Jill De Ron, Ymkje Anna de Vries, Kristy
K. Dean, Bryan J. Dik, David J. Disabato, Jaclyn K. Doherty, Tim Draws, Lucas Drouhot, Marin
Dujmovic, Yarrow Dunham, Tobias Ebert, Peter A. Edelsbrunner, Anita Eerland, Christian T.
Elbaek, Shole Farahmand, Hooman Farahmand, Miguel Farias, Abrey A. Feliccia, Kyle Fischer,
Ronald Fischer, Donna Fisher-Thompson, Zoë Francis, Susanne Frick, Lisa K. Frisch, Diogo
Geraldes, Emily Gerdin, Linda Geven, Omid Ghasemi, Erwin Gielens, Vukašin Gligorić, Kristin
Hagel, Nandor Hajdu, Hannah R. Hamilton, Imaduddin Hamzah, Paul H. P. Hanel, Christopher E.
Hawk, Karel K. Himawan, Benjamin C. Holding, Lina E. Homman, Moritz Ingendahl, Hilla Inkilä,
Mary L. Inman, Chris-Gabriel Islam, Ozan Isler, David Izydorczyk, Bastian Jaeger, Kathryn A.
Johnson, Jonathan Jong, Johannes A. Karl, Erikson Kaszubowski, Benjamin A. Katz, Lucas A.
Keefer, Stijn Kelchtermans, John M. Kelly, Richard A. Klein, Bennett Kleinberg, Megan L. Knowles,
Marta Kołczyńska, Dave Koller, Julia Krasko, Sarah Kritzler, Angelos-Miltiadis Krypotos, Thanos
Kyritsis, Todd L. Landes, Ruben Laukenmann, Guy A. Lavender Forsyth, Aryeh Lazar, Barbara
J. Lehman, Neil Levy, Ronda F. Lo, Paul Lodder, Jennifer Lorenz, Paweł Łowicki, Albert L. Ly,
Esther Maassen, Gina M. Magyar-Russell, Maximilian Maier, Dylan R. Marsh, Nuria Martinez,
Marcellin Martinie, Ihan Martoyo, Susan E. Mason, Anne Lundahl Mauritsen, Phil McAleer, Thomas
McCauley, Michael McCullough, Ryan McKay, Camilla M. McMahon, Amelia A. McNamara, Kira K.
Means, Brett Mercier, Panagiotis Mitkidis, Benoît Monin, Jordan W. Moon, David Moreau, Jonathan
Morgan, James Murphy, George Muscatt, Christof Nägel, Tamás Nagy, Ladislas Nalborczyk,
Gustav Nilsonne, Pamina Noack, Ara Norenzayan, Michèle B. Nuijten, Anton Olsson-Collentine,
Lluis Oviedo, Yuri G. Pavlov, James O. Pawelski, Hannah I. Pearson, Hugo Pedder, Hannah K.
Peetz, Michael Pinus, Steven Pirutinsky, Vince Polito, Michaela Porubanova, Michael J. Poulin,
Jason M. Prenoveau, Mark A. Prince, John Protzko, Campbell Pryor, Benjamin G. Purzycki, Lin
Qiu, Julian Quevedo Pütter, André Rabelo, Milen L. Radell, Jonathan E. Ramsay, Graham Reid,
Andrew J. Roberts, Lindsey M. Root Luna, Robert M. Ross, Piotr Roszak, Nirmal Roy, Suvi-Maria
K. Saarelainen, Joni Y. Sasaki, Catherine Schaumans, Bruno Schivinski, Marcel C. Schmitt,
Sarah A. Schnitker, Martin Schnuerch, Marcel R. Schreiner, Victoria Schüttengruber, Simone
Sebben, Suzanne C. Segerstrom, Berenika Seryczyńska, Uffe Shjoedt, Müge Simsek, Willem W.
A. Sleegers, Eliot R. Smith, Walter J. Sowden, Marion Späth, Christoph Spörlein, William Stedden,
Full Terms & Conditions of access and use can be found at
https://www.tandfonline.com/action/journalInformation?journalCode=rrbb20
Andrea H. Stoevenbelt, Simon Stuber, Justin Sulik, Christiany Suwartono, Stylianos Syropoulos,
Barnabas Szaszi, Peter Szecsi, Ben M. Tappin, Louis Tay, Robert T. Thibault, Burt Thompson,
Christian M. Thurn, Josefa Torralba, Shelby D. Tuthill, Ann-Marie Ullein, Robbie C. M. Van Aert,
Marcel A. L. M. van Assen, Patty Van Cappellen, Olmo R. van den Akker, Ine Van der Cruyssen,
Jolanda Van der Noll, Noah N. N. van Dongen, Caspar J. Van Lissa, Valerie van Mulukom, Don
van Ravenzwaaij, Casper J. J. van Zyl, Leigh Ann Vaughn, Bojana Većkalov, Bruno Verschuere,
Michelangelo Vianello, Felipe Vilanova, Allon Vishkin, Vera Vogel, Leonie V. D. E. Vogelsmeier,
Shoko Watanabe, Cindel J. M. White, Kristina Wiebels, Sera Wiechert, Zachary Z. Willett, Maciej
Witkowiak, Charlotte V. O. Witvliet, Dylan Wiwad, Robin Wuyts, Dimitris Xygalatas, Xin Yang,
Darren J. Yeo, Onurcan Yilmaz, Natalia Zarzeczna, Yitong Zhao, Josjan Zijlmans, Michiel van Elk
& Eric-Jan Wagenmakers (2022): A many-analysts approach to the relation between religiosity and
well-being, Religion, Brain & Behavior, DOI: 10.1080/2153599X.2022.2070255
To link to this article: https://doi.org/10.1080/2153599X.2022.2070255
© 2022 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
View supplementary material
Published online: 06 Jul 2022.
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TARGET ARTICLE
A many-analysts approach to the relation between religiosity and
well-being
Suzanne Hoogeveen
a
, Alexandra Sarafoglou
a
, Balazs Aczel
b
, Yonathan Aditya
c
,
Alexandra J. Alayan
d
, Peter J. Allen
e
, Sacha Altay
f
, Shilaan Alzahawi
g
, Yulmaida Amir
h
,
Francis-Vincent Anthony
i
, Obed Kwame Appiah
a
, Quentin D. Atkinson
j
,Adam Baimel
k
,
Merve Balkaya-Ince
l
,Michela Balsamo
m
,Sachin Banker
n
,František Bartoš
o
,Mario Becerra
p
,
Bertrand Beffara
q
,Julia Beitner
r
,Theiss Bendixen
s
,Jana B. Berkessel
t
,Renatas Berniūnas
u
,
Matthew I. Billet
v
,Joseph Billingsley
w
,Tiago Bortolini
x
,Heiko Breitsohl
y
,Amélie Bret
z
,
Faith L. Brown
aa
,Jennifer Brown
ab
,Claudia C. Brumbaugh
ac
,Jacek Buczny
ad
,
Joseph Bulbulia
ae
,Saúl Caballero
af
,Leonardo Carlucci
ag
,Cheryl L. Carmichael
ah
,
Marco E. G. V. Cattaneo
ai
,Sarah J. Charles
ab
,Scott Claessens
j
,Maxinne C. Panagopoulos
aj
,
Angelo Brandelli Costa
ak
,Damien L. Crone
al
,Stefan Czoschke
r
,Christian Czymara
am
,
E. Damiano D’Urso
an
,Örjan Dahlström
ao,ap
,Anna Dalla Rosa
aq
,Henrik Danielsson
ao,ap
,
Jill De Ron
a
,Ymkje Anna de Vries
ar,as
,Kristy K. Dean
at
,Bryan J. Dik
d
,David J. Disabato
au
,
Jaclyn K. Doherty
av
,Tim Draws
aw
,Lucas Drouhot
ax
,Marin Dujmovic
e
,Yarrow Dunham
ay
,
Tobias Ebert
t
,Peter A. Edelsbrunner
az
,Anita Eerland
ba,bb
,Christian T. Elbaek
bc
,
Shole Farahmand
bd
,Hooman Farahmand
be
,Miguel Farias
ab
,Abrey A. Feliccia
bf
,
Kyle Fischer
j
,Ronald Fischer
x,ae
,Donna Fisher-Thompson
bg
,Zoë Francis
bh
,Susanne Frick
bi
,
Lisa K. Frisch
bj
,Diogo Geraldes
bk
,Emily Gerdin
ay
,Linda Geven
a,bl
,Omid Ghasemi
bm
,
Erwin Gielens
bn
,Vukašin Gligorić
bo
,Kristin Hagel
bp
,Nandor Hajdu
bq,b
,Hannah
R. Hamilton
br
,Imaduddin Hamzah
bs
,Paul H. P. Hanel
bt
,Christopher E. Hawk
bu
,
Karel K. Himawan
c
,Benjamin C. Holding
bv,bw
,Lina E. Homman
ao,ap
,Moritz Ingendahl
bi
,
Hilla Inkilä
bx
,Mary L. Inman
by
,Chris-Gabriel Islam
bz,ca
,Ozan Isler
cb,cc
,David Izydorczyk
bi
,
Bastian Jaeger
an
,Kathryn A. Johnson
cd
,Jonathan Jong
ce
,Johannes A. Karl
ae
,
Erikson Kaszubowski
cf
,Benjamin A. Katz
cg
,Lucas A. Keefer
aa
,Stijn Kelchtermans
p
,
John M. Kelly
ch
,Richard A. Klein
an
,Bennett Kleinberg
an,ci
,Megan L. Knowles
cj
,
Marta Kołczyńska
ck
,Dave Koller
a,cl
,Julia Krasko
cm
,Sarah Kritzler
cm
,Angelos-
Miltiadis Krypotos
p,ax
,Thanos Kyritsis
j
,Todd L. Landes
cn
,Ruben Laukenmann
bi
,
Guy A. Lavender Forsyth
j
,Aryeh Lazar
co
,Barbara J. Lehman
cp
,Neil Levy
cq
,Ronda F. Lo
cr
,
Paul Lodder
cs
,Jennifer Lorenz
bz
,PawełŁowicki
ct
,Albert L. Ly
cu
,Esther Maassen
an
,
Gina M. Magyar-Russell
cv
,Maximilian Maier
a,cw
,Dylan R. Marsh
d
,Nuria Martinez
cx
,
Marcellin Martinie
cn
,Ihan Martoyo
cy,cz
,Susan E. Mason
bg
,Anne Lundahl Mauritsen
s
,
Phil McAleer
aj
,Thomas McCauley
da
,Michael McCullough
da
,Ryan McKay
db
,
Camilla M. McMahon
dc
,Amelia A. McNamara
cp
,Kira K. Means
dd
,Brett Mercier
de
,
Panagiotis Mitkidis
bc,dh
,Benoît Monin
g
,Jordan W. Moon
cd
,David Moreau
df
,
Jonathan Morgan
dg,di
,James Murphy
cx
,George Muscatt
di
,Christof Nägel
dj
,Tamás Nagy
br
,
Ladislas Nalborczyk
dk,dl
,Gustav Nilsonne
bw,dm
,Pamina Noack
dn
,Ara Norenzayan
v
,
Michèle B. Nuijten
an
,Anton Olsson-Collentine
an
,Lluis Oviedo
do
,Yuri G. Pavlov
dp,dq
,
James O. Pawelski
al
,Hannah I. Pearson
dr
,Hugo Pedder
ds
,Hannah K. Peetz
bb
,
Michael Pinus
dt
,Steven Pirutinsky
du
,Vince Polito
dv
,Michaela Porubanova
dw
,
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://
creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the
original work is properly cited, and is not altered, transformed, or built upon in any way.
CONTACT Suzanne Hoogeveen suzanne.j.hoogeveen@gmail.com
Supplemental data for this article can be accessed at https://doi.org/10.1080/2153599X.2022.2070255.
RELIGION, BRAIN & BEHAVIOR
https://doi.org/10.1080/2153599X.2022.2070255
Michael J. Poulin
dx,dy
,Jason M. Prenoveau
dz
,Mark A. Prince
d
,John Protzko
ea
,
Campbell Pryor
cv
,Benjamin G. Purzycki
s
,Lin Qiu
eb
,Julian Quevedo Pütter
bi
,
André Rabelo
ec
,Milen L. Radell
bg
,Jonathan E. Ramsay
ed
,Graham Reid
ee,ef
,
Andrew J. Roberts
bm
,Lindsey M. Root Luna
by
,Robert M. Ross
eg
,Piotr Roszak
eh
,
Nirmal Roy
aw
,Suvi-Maria K. Saarelainen
bx
,Joni Y. Sasaki
dr
,Catherine Schaumans
ei
,
Bruno Schivinski
ej
,Marcel C. Schmitt
ek
,Sarah A. Schnitker
l
,Martin Schnuerch
bi
,
Marcel R. Schreiner
bi
,Victoria Schüttengruber
bj
,Simone Sebben
el
,Suzanne
C. Segerstrom
em
,Berenika Seryczyńska
en
,Uffe Shjoedt
s
,Müge Simsek
eo,a
,
Willem W. A. Sleegers
an
,Eliot R. Smith
ep
,Walter J. Sowden
eq
,Marion Späth
dn
,
Christoph Spörlein
er
,William Stedden
es
,Andrea H. Stoevenbelt
an,au
,Simon Stuber
et
,
Justin Sulik
eu
,Christiany Suwartono
ev
,Stylianos Syropoulos
ew
,Barnabas Szaszi
b
,
Peter Szecsi
bq,b
,Ben M. Tappin
ex
,Louis Tay
ex
,Robert T. Thibault
e,ey
,Burt Thompson
bg
,
Christian M. Thurn
az
,Josefa Torralba
ez
,Shelby D. Tuthill
d
,Ann-Marie Ullein
dn
,
Robbie C. M. Van Aert
an
,Marcel A. L. M. van Assen
an
,Patty Van Cappellen
fa
,
Olmo R. van den Akker
cs
,Ine Van der Cruyssen
a,fb
,Jolanda Van der Noll
fc
,
Noah N. N. van Dongen
fd
,Caspar J. Van Lissa
fe
,Valerie van Mulukom
ab
,
Don van Ravenzwaaij
ff
,Casper J. J. van Zyl
fg
,Leigh Ann Vaughn
bf
,Bojana Većkalov
bo
,
Bruno Verschuere
a
,Michelangelo Vianello
aq
,Felipe Vilanova
ak
,Allon Vishkin
fh
,
Vera Vogel
bi
,Leonie V. D. E. Vogelsmeier
an
,Shoko Watanabe
fi
,Cindel J. M. White
cr
,
Kristina Wiebels
df
,Sera Wiechert
a,fb
,Zachary Z. Willett
cp
,Maciej Witkowiak
fj
,
Charlotte V. O. Witvliet
by
,Dylan Wiwad
fk
,Robin Wuyts
a
,Dimitris Xygalatas
fl
,Xin Yang
ay
,
Darren J. Yeo
fm,fn
,Onurcan Yilmaz
fo
,Natalia Zarzeczna
a
,Yitong Zhao
fp
,Josjan Zijlmans
fq
,
Michiel van Elk
bl
, and Eric-Jan Wagenmakers
a
a
University of Amsterdam;
b
Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary;
c
Faculty of
Psychology, Universitas Pelita Harapan;
d
Colorado State University;
e
School of Psychological Science, University of
Bristol;
f
Institut Jean Nicod, Paris, France;
g
Stanford University, Graduate School of Business;
h
Universitas
Muhammadiyah Prof. Dr. HAMKA;
i
Salesian Pontifical University, Rome;
j
School of Psychology, University of
Auckland;
k
Centre for Psychological Research, Oxford Brookes University;
l
Department of Psychology and
Neuroscience, Baylor University;
m
Department of Psychological, Health and Territorial Sciences, University of Chieti,
Chieti, Italy;
n
University of Utah, Eccles School of Business;
o
Department of Psychological Methods, University of
Amsterdam;
p
KU Leuven;
q
The Walden III Slowpen Science Laboratory;
r
Institute of Psychology, Goethe University
Frankfurt, Germany;
s
Department of the Study of Religion, Aarhus University;
t
Mannheim Centre for European
Social Research, University of Mannheim;
u
Vilnius University, Lithuania;
v
University of British Columbia;
w
North
Carolina State University;
x
D’Or Institute for Research and Education (IDOR);
y
University of Klagenfurt, Austria;
z
University of Nantes;
aa
The University of Southern Mississippi;
ab
Coventry University;
ac
Queens College & Graduate
Center, City University of New York;
ad
Department of Experimental and Applied Psychology, VU Amsterdam;
ae
Victoria University of Wellington;
af
Instituto Tecnológico Autónomo de México;
ag
Department of Economics,
Management and Territory, University of Foggia, Italy;
ah
Brooklyn College & Graduate Center, City University of
New York;
ai
Department of Clinical Research, University of Basel, Switzerland;
aj
University of Glasgow;
ak
Pontifícia
Universidade Católica do Rio Grande do Sul;
al
University of Pennsylvania;
am
Department of Sociology with Focus on
Quantitative Methods for Social Research, Goethe University Frankfurt;
an
Tilburg University;
ao
Linköping University;
ap
The Swedish Institute for Disability Research;
aq
Department of Philosophy, Sociology, Education and Applied
Psychology, University of Padua;
ar
Department of Developmental Psychology, University of Groningen, Groningen,
NL;
as
Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen,
Groningen, NL;
at
Grand Valley State University;
au
Kent State University;
av
The Graduate Center, City University of
New York;
aw
Delft University of Technology;
ax
Department of Sociology, Utrecht University;
ay
Yale University;
az
ETH
Zurich;
ba
Department of Communication Science, Radboud University;
bb
Behavioural Science Institute, Radboud
University Nijmegen;
bc
Department of Management, Aarhus University;
bd
Faculty of Physical Education and Sport
Science, University of Tehran;
be
Clinical Psychology, Faculty of Education and Psychology, Shiraz University;
bf
Ithaca
College, Ithaca, NY, USA;
bg
Niagara University;
bh
University of the Fraser Valley;
bi
University of Mannheim;
bj
University of Zürich;
bk
Utrecht School of Economics, Utrecht University;
bl
Leiden University;
bm
School of
Psychological Sciences, Macquarie University;
bn
Tilburg Universty;
bo
Department of Psychology, University of
Amsterdam;
bp
Max Planck Institute for Evolutionary Anthropology, Germany;
bq
Doctoral School of Psychology,
ELTE Eötvös Loránd University, Budapest, Hungary;
br
Institute of Psychology, ELTE Eötvös Loránd University,
Budapest, Hungary;
bs
Politeknik Ilmu Pemasyarakatan;
bt
University of Essex;
bu
DigiPen Institute of Technology,
2S. HOOGEVEEN ET AL.
Department of Humanities and Social Sciences;
bv
Faculty of Social Science, Department of Sociology, University of
Copenhagen;
bw
Department of Clinical Neuroscience, Karolinska Institutet;
bx
University of Eastern Finland;
by
Hope
College;
bz
University of Göttingen;
ca
Federal Statistical Office of Germany;
cb
School of Economics and Finance,
Queensland University of Technology, Brisbane, Australia;
cc
Centre for Behavioural Economics, Society and
Technology, Brisbane, Australia;
cd
Department of Psychology, Arizona State University;
ce
Centre for Trust, Peace
and Social Relations, Coventry University;
cf
Universidade Federal de Santa Catarina;
cg
SUNY Stony Brook University;
ch
Department of Psychological Science, University of California, Irvine;
ci
University College London;
cj
Franklin &
Marshall College;
ck
Institute of Political Studies of the Polish Academy of Sciences;
cl
University of Zurich;
cm
Faculty
of Psychology, Ruhr University Bochum;
cn
University of Melbourne;
co
Ariel University, Israel;
cp
University of St
Thomas;
cq
Department of Philosophy, Macquarie University, Australia;
cr
York University;
cs
Department of
Methodology & Statistics, Tilburg University;
ct
Faculty of Psychology, Univeristy of Warsaw, Poland;
cu
Department
of Psychology, Loma Linda University;
cv
Department of Psychology, Loyola University Maryland;
cw
Department of
Experimental Psychology, University College London;
cx
Canterbury Christ Church University;
cy
Faculty of Science
and Technology, Universitas Pelita Harapan, Indonesia;
cz
Reformed Theological Seminary Indonesia;
da
University of
California, San Diego;
db
Royal Holloway, University of London, Egham, UK;
dc
Miami University;
dd
Western
Washington University;
de
Department of Psychology, University of Toronto;
df
School of Psychology & Centre for
Brain Research, The University of Auckland;
dg
University of Colorado at Colorado Springs;
dh
Center for Mind and
Culture;
di
School of Life Sciences, University of Warwick;
dj
German Police University;
dk
Aix Marseille Univ, CNRS, LPC,
Marseille, France;
dl
Aix Marseille Univ, CNRS, LNC, Marseille, France;
dm
Department of Psychology, Stockholm
University;
dn
Heinrich-Heine-University Duesseldorf;
do
Antonianum University, Rome;
dp
Ural Federal University,
Ekaterinburg, Russia;
dq
University of Tübingen, Germany;
dr
University of Hawai’iatMānoa;
ds
Department
Population Health Sciences, Bristol Medical School, University of Bristol;
dt
Department of Psychology, Hebrew
University, Israel;
du
Touro College, Graduate School of Social Work;
dv
School of Psychological Sciences, Macquarie
University, Australia;
dw
Microsoft Mixed Reality;
dx
University at Buffalo;
dy
University at Buffalo;
dz
Loyala University
Maryland;
ea
Central Connecticut State University;
eb
Nanyang Technological University, Singapore;
ec
Universidade
de Brasília, Brazil;
ed
School of Social and Health Sciences, James Cook University, Singapore;
ee
Department of
Experimental Psychology, Medical Sciences Division, University of Oxford;
ef
Heart & Brain Group, Wellcome Centre
for Integrative Neuroimaging (WIN), Department of Psychiatry, Medical Sciences Division, University of Oxford;
eg
Department of Psychology, Macquarie University, Australia;
eh
Copernicus University of Torun;
ei
Independent
Researcher;
ej
School of Media and Communication, RMIT University;
ek
Department of Psychology, University of
Koblenz-Landau;
el
University of Zurich;
em
Department of Psychology, University of Kentucky;
en
Copernicus
Univerversity of Torun;
eo
Netherlands Interdisciplinary Demographic Institute -KNAW, University of Groningen;
ep
Indiana University, Bloomington;
eq
Department of Behavioral Health, Tripler Army Medical Center, Honolulu,
Hawaii, USA;
er
Institut für Sozialwissenschaften, Heinrich-Heine Universität Düsseldorf;
es
None;
et
University of
Groningen;
et
Universität Koblenz Landau;
eu
Cognition, Values and Behaviour Lab, Ludwig Maximilian University,
Germany;
ev
Faculty of Psychology, Atma Jaya Catholic University of Indonesia, Indonesia;
ew
Department of
Psychological and Brain Sciences, University of Massachusetts Amherst;
ex
Purdue University;
ey
Meta-research
Innovation Center at Stanford (METRICS), Stanford University;
ez
University of Murcia;
fa
Duke University;
fb
Hebrew
University of Jerusalem;
fc
FernUniversität in Hagen;
fd
Department of Psychology, University of Amsterdam;
fe
Department of Methodology & Statistics, Utrecht University;
ff
University of Groningen, Groningen, The
Netherlands;
fg
University of Johannesburg;
fh
University of Michigan;
fi
University of Illinois at Urbana-Champaign;
fj
No Affiliation;
fk
Kellogg School of Management, Northwestern University;
fl
University of Connecticut, USA;
fm
Division of Psychology, School of Social Sciences, Nanyang Technological University, Singapore;
fn
Department of
Psychology & Human Development, Vanderbilt University, Nashville, TN, USA;
fo
Department of Psychology, Kadir
Has University, Istanbul, Turkey;
fp
Department of Psychology, Wake Forest University;
fq
Department of Child and
Adolescent Psychiatry, Amsterdam University Medical Center
ABSTRACT
The relation between religiosity and well-being is one of the most
researched topics in the psychology of religion, yet the directionality
and robustness of the effect remains debated. Here, we adopted a
many-analysts approach to assess the robustness of this relation based
on a new cross-cultural dataset (N=10, 535 participants from 24
countries). We recruited 120 analysis teams to investigate (1) whether
religious people self-report higher well-being, and (2) whether the
relation between religiosity and self-reported well-being depends on
perceived cultural norms of religion (i.e., whether it is considered
normal and desirable to be religious in a given country). In a two-stage
procedure, the teams first created an analysis plan and then executed
ARTICLE HISTORY
Received 25 January 2022
Accepted 7 March 2022
KEYWORDS
Health; many analysts; open
science; religion
RELIGION, BRAIN & BEHAVIOR 3
their planned analysis on the data. For the first research question, all but 3
teams reported positive effect sizes with credible/confidence intervals
excluding zero (median reported
b
=0.120). For the second research
question, this was the case for 65% of the teams (median reported
b
=0.039). While most teams applied (multilevel) linear regression
models, there was considerable variability in the choice of items used to
construct the independent variables, the dependent variable, and the
included covariates.
1. Introduction
The relation between religion and well-being has been a topic of debate for centuries. While Freud
considered religion a “universal obsessional neurosis”andNietzschecalledChristianity“the
greatest misfortune of humanity,”the recent scientific literature has painted a more positive pic-
ture of religion’seffect on (mental) health (e.g., Gebauer et al., 2017;Georgeetal.,2002;Koenig&
Larson, 2001; Plante & Sherman, 2001;Seybold&Hill,2001;Thoresen,1999;Zimmeretal.,
2016). Individual religiosity has, for instance, been related to less depression (Smith et al.,
2003), more happiness (Abdel-Khalek, 2006; Lewis & Cruise, 2006), higher life satisfaction
(Lim & Putnam, 2010), and even lower mortality (Ebert et al., 2020;Stavrova,2015). At the
same time, the robustness, universality, and methodological specificity of the religion—well-
being relation remains an outstanding question. In this project, we adopted a many-analysts
approach to investigate two research questions using a new large cross-cultural dataset featuring
N=10,535 participants from 24 countries. Specifically, we recruited 120 teams to conduct ana-
lyzes in order to answer the following two research questions: (1) “Do religious people self-report
greater well-being?,”and (2) “Does the relation between religiosity and self-reported well-being
depend on perceived cultural norms regarding religion?.”In the subsequent sections, we will first
introduce our theoretical framework, dataset, and the many-analysts approach, before describing
the key results with respect to the stated research questions and the varying approaches taken by
the many-analysts teams. A general discussion of the project and the results is included in the
closing article (Hoogeveen et al.,2022).
1.1. Theoretical background
Theliteratureonthepsychologyofreligionisreplete with positive correlations between (self-
rated) religiosity and mental health (Abdel-Khalek, 2006;Georgeetal.,2002; Koenig & Larson,
2001;Plante&Sherman,2001; Seybold & Hill, 2001;Smithetal.,2003;T
horesen,1999; Zimmer
et al., 2016; see Koenig, 2009 for a review). At the same time, meta-analyzes indicate that the
relation between religion and well-being is often small (around r=.1; Bergin,1983; Hackney &
Sanders, 2003;Koenig&Larson,2001). In addition, it has been argued that positive associations
are found only for particular measures and operationalizations of these constructs (Hackney &
Sanders, 2003; Poloma & Pendleton, 1989). A recent meta-analysis of longitudinal studies
reported that, out of eight religiosity/spirituality measures, only participation in public religious
activities and the importance of religion were statistically significantly related to self-rated mental
health, which was operationalized as distress, life satisfaction, well-being, and quality of life
(Garssen et al., 2020).
Furthermore, the type of religiosity (i.e., intrinsic vs. extrinsic; positive vs. negative religious cop-
ing) and religious status (religious vs. uncertain) appear to moderate the relationship between reli-
gion and mental well-being (Smith et al., 2003; Villani et al., 2019). For instance, extrinsic religious
orientation (i.e., when people primarily use their religious community as a social network, whereas
personal religious beliefs are secondary) and negative religious coping (i.e., when people have
internal religious guilt or doubts) have been shown to be negatively related to well-being (Abu-
4S. HOOGEVEEN ET AL.
Raiya, 2013; Weber & Pargament, 2014). Yet other research suggests that it is precisely the social
aspect of religious service attendance and congregational friendships that explains how religiosity
is positively associated with life satisfaction (Lim & Putnam, 2010). Moreover, the direction of the
religiosity—mental health relation remains unclear; while engaging in religious activities might
make people happier, people with better mental health might also be more likely to engage in pub-
lic, social events.
Additionally, there is large variability in the extent to which religion is ingrained in culture and
social identity across the globe (Kelley & de Graaf, 1997; Ruiter & van Tubergen, 2009). Accordingly,
when investigating the association between religiosity and well-being, it may be necessary to take into
account the cultural norms related to religiosity within a society. Being religious may contribute to
self-rated health and happiness when being religious is perceived to be a socially expected and desir-
able option (Diener et al., 2011; Ebert et al., 2020; Gebauer et al., 2017; Stavrova, 2015; Stavrova et al.,
2013). This makes sense from the literature on person-culturefit (Dressler et al., 2007): a high person-
culture fit indicates good agreement between one’s personal values and beliefs and the beliefs that are
shared by one’s surrounding culture. A fruitful way to measure cultural norms is through the shared,
intersubjective perception of the beliefs and attitudes that are prevalent in a society (Chiu et al., 2010;
Zou et al., 2009). Intersubjective norms of religiosity, for instance, refer to the shared perception of the
importance of religion within a society or culture. Rather than expressing the importance of religious
beliefs and behaviors in one’s own personal life, intersubjective norms of religiosity (henceforth: cul-
tural norms of religiosity) uncover the perceived importance of religious beliefs and behaviors for the
average person within a culture. Religious individuals may be more likely to benefit from being reli-
gious when their convictions and behaviors align with perceived cultural norms. For countries in
which religion is more trivial or even stigmatized, the relation between religiosity and well-being
may be absent or even reversed. Relatedly, in secular countries, religion might be practiced relatively
often by minority groups, which has been shown to attenuate the positive association between reli-
gious involvement and well-being (Hayward & Elliott, 2014; Huijts & Kraaykamp, 2011; May &
Smilde, 2016; Okulicz-Kozaryn, 2010).
1.2. A many-analysts approach
In the current project, we aim to shed light on the association between religion and well-being and
the extent to which different theoretically- or methodologically-motivated analytic choices affect the
results. To this end, we initiated a many-analysts project, in which several independent analysis
teams analyze the same dataset in order to answer a specific research question (e.g., Bastiaansen
et al., 2020; Boehm et al., 2018; Botvinik-Nezer et al., 2020; Silberzahn & Uhlmann, 2015; van Don-
gen et al., 2019). A many-analysts approach has been proposed as a way to mitigate the influence of
individual-researcher biases (e.g., confirmation bias by the proponent of a theory or disconfirma-
tion bias by the skeptic), especially since the analysis teams are not typically invested in the out-
come. More generally, a many-analysts study is arguable less vulnerable to publication bias
toward publishing only significant rather than null results, which may lower the (unconscious) ten-
dency toward p-hacking by individual analysts. A many-analysts approach can balance out the
effects of researcher bias while still allowing for expertize-based analytic decisions such as reason-
able preprocessing steps, variable exclusion, and model specification. As such, it enables one to
assess the robustness of outcomes and quantify variability based on theory-driven analysis decisions
and plausible statistical models. Specifically, we believe that the more consistent the results from
different analysis teams are, the more confident we can be in the conclusions we draw from the
results. A many-analysts approach may be preferable to an exhaustive multiverse analysis (Steegen
et al., 2016) that might simply include the full spectrum of options, including those that are theor-
etically and methodologically unrealistic.
The idea of inviting different analysis teams to answer the same research question using the
same data is relatively novel (Silberzahn & Uhlmann, 2015; see Aczel et al., 2021 for general
RELIGION, BRAIN & BEHAVIOR 5
guidelines); we are aware of three papers in neuroscience (Botvinik-Nezer et al., 2020; Fillard
et al., 2011; Maier-Hein et al., 2017), one in microeconomics (Huntington-Klein et al., 2021),
and eight in psychology, three of which pertain to cognitive modeling (Boehm et al., 2018;Dutilh
et al., 2019;Starnsetal.,2019) while the remaining five are from other fields of psychology (Bas-
tiaansen et al., 2020;Salganiketal.,2020;Schweinsbergetal.,2021;Silberzahnetal.,2018;van
Dongen et al., 2019). Most similar to the current work are the projects that applied a many-ana-
lysts approach to perform statistical inference ontherelationbetweentwovariables,suchasskin
color and red cards in soccer (Silberzahn et al., 2018), scientist gender and verbosity (Schweins-
berg et al., 2021), or amygdala activity and stress (van Dongen et al., 2019). While the exact focus
of previous many-analysts projects varied (e.g., experience sampling, fMRI preprocessing, predic-
tive modeling, proof of the many-analysts concept), the take-home messages were rather consist-
ent: all papers showed that different yet equally justifiable analytic choices result in very different
outcomes, sometimes with statistically significant effects in opposite directions (e.g., Schweins-
berg et al., 2021;Silberzahnetal.,2018). In addition, it has proved difficult to pinpoint the
exact sources of variability due to the fact that analytic approaches differed in many respects sim-
ultaneously (e.g., exclusion criteria, inclusion of covariates etc.). Nevertheless, the outcomes of
thesepreviousprojectssuggestthatchoicesofstatisticalmodel(Silberzahnetal.,2018), statistical
framework (van Dongen et al., 2019), (pre)processing software (Botvinik-Nezer et al., 2020), and
the variables themselves (Schweinsberg et al., 2021)exertsubstantialeffects on the results and
conclusions.
We believe a many-analysts approach is uniquely suited to address various concerns in the
study of religion and well-being. First, the relation between religion and health has been
researched for decades with hundreds of qualitative reports, cross-sectional and longitudinal
studies,andevenrandomizedcontrolledtrialswith religious/spiritual interventions for mental
health issues (Captari et al., 2018;Harrisetal.,2018;Koenigetal.,2020;Rosmarinetal.,
2010). Yet new studies keep emerging (e.g., Chang et al., 2021;Luo&Chen,2021;Simkin,
2020) and the debate seems far from settled (see for instance the recent special issue in the Inter-
national Journal for the Psychology of Religion; van Elk, 2021). Second, both “religion”and “well-
being”are broad and multifaceted constructs that are sensitive to different measures and opera-
tionalizations, which might result in both quantitatively and qualitatively different conclusions
(Hackney & Sanders, 2003; Poloma & Pendleton, 1989). Third, the standard way to assess robust-
ness of an effect or association is often through meta-analysis, but the fragmentation of the litera-
ture on the religion—health link and methodological heterogeneity between studies challenge the
use and validity of meta-analyzes in this domain (Koenig et al., 2021). In general, meta-analyzes
may suffer from several drawbacks such as publication bias and sensitivity to arbitrary methodo-
logical choices (e.g., different meta-analytic techniques can result in different conclusions; de
Vrieze, 2018;vanElketal.,2015). Moreover, the estimated effect sizes in meta-analyzes might
be as much as three times larger than in preregistered multiple-site replication studies (Kvarven
et al., 2020). Fourth, the discussion on the potential health-benefits of religion has been muddied
by concerns about researcher interests and biases. That is, it has been argued that scholars of reli-
gion might be biased by their own (religious) beliefs (Ladd & Messick, 2016;Swigartetal.,2020;
Wulff,1998) or by the fact that a substantial amount of research in the science of religion is
funded by religiously-oriented organizations such as the John Templeton Foundation (Bains,
2011; Wiebe, 2009).
1
Inviting independent analysts from various backgrounds including but
not restricted to religious studies attenuates this potential concern. Moreover, in addition to
quantifying variability, with a sufficiently large number of analysis teams one can also investigate
factors that might explain observed variability, such as those related to theoretical or methodo-
logical expertize and prior beliefs (Aczel et al., 2021).
2
In addition to the theoretical rationale for using a many-analysts approach to answer the
research questions at hand, we also consider the current dataset particularly appropriate for
such an approach. That is, the complexity of the data allows for many justifiable choices for
6S. HOOGEVEEN ET AL.
the operationalization of the variables and the statistical approach to be employed. While the
questions posed to the participants in the cross-cultural study could no longer be changed, the
specific method of derivation for the religiosity and well-being scores was at the discretion of
the many analysts. At the same time, the research questions and data structure (cross-sectional
correlational data) were sufficiently intuitive and manageable to inspire many researchers in
the fields of (social) psychology, religious studies, health science, and general methodology to
propose an analysis.
Finally, we believe that our project involves a combination of elements that extend existing
many-analysts work. First, we collected new data for this project with the aim to provide new evi-
dencefortheresearchquestionsofinterest,asopposed to using an existing dataset that has been
analyzed before. Second, we targeted both researchers interested in methodology and open
science, as well as researchers from the field of the scientific study of religion and health to encou-
rage both methodologically sound and theoretically relevant decisions (see the section “Analysis
teams”). Third, in comparison to previous many-analysts projects in psychology, the current pro-
jectincludesalotofteams(i.e.,120vs.4,12,14,17,27,29,and70teams,thoughnotethata
machine learning project included 160 analyst teams; Salganik et al., 2020). Fourth, we applied
a two-step procedure that ensured a purely confirmatory status of the analyzes: in stage 1, all
teams firsteithercompletedapreregistrationorspecified an analysis pipeline based on a blinded
version of the data. After submitting the plan to the OSF, teams received the real data and exe-
cuted their planned analyzes in stage 2 (see Sarafoglou et al., 2022 for more details on and an
empirical investigation of preregistration vs. data blinding based on the present data). Fifth,
the many-analysts approach itself was preregistered prior to cross-cultural data collection (see
osf.io/xg8y5), although the details of the processing and analysis of the many-analysts data
were not preregistered.
1.3. The dataset
The dataset provided to the analysts featured data from 10,535 participants from 24 countries col-
lected in 2019. The data were collected as part of the cross-cultural religious replication project (see
also Hoogeveen et al., 2021; Hoogeveen & van Elk, 2018). The dataset contained measures of reli-
giosity, well-being, perceived cultural norms of religion, as well as some demographic items. The
full dataset, the data documentation file, and original questionnaire can be found on the OSF pro-
ject page (osf.io/qbdce/).
1.3.1. Participants
Participants were recruited from university student samples, from personal networks, and from
(demographically representative) samples accessed by panel agencies and online platforms
(MTurk, Kieskompas, Sojump, TurkPrime, Lancers, Qualtrics panels, Crowdpanel, and
Prolific). Participants were compensated for participation by financial remuneration, the possi-
bility for a reward through a raffle, course credits, or received no compensation. Everyone aged
18 years or above could participate.
3
Participants were required to answer all multiple choice
questions, and hence there were no missing data (except for 36 people who did not provide a
numeric age and 995 people who chose not to answer the item on sexual satisfaction, as this
was the only item for which participants were not required to provide an answer.) The countries
were convenience-sampled (i.e., through personal networks), but were selected to cover six con-
tinents and include different ethnic and religious majorities. The final sample included individ-
uals who identified as Christian (31.2%), Muslim (6.1%), Hindu (2.9%), Buddhist (2.0%), Jewish
(1.0%), or were part of another religious group (2.9%). Finally, 53.9% of participants did not
identify with any religion. See Tables A1 and A2 in Appendix 1 for the full descriptive statistics
of the dataset.
RELIGION, BRAIN & BEHAVIOR 7
1.3.2. Measures
Personal religiosity was measured using nine standardized self-report items taken from the World
Values Survey (WVS; World Values Survey, 2010), covering religious behaviors (institutionalized
such as church attendance and private such as prayer/meditation), beliefs, identification, values, and
denomination. The well-being measure consisted of 18 self-report items from the validated short ver-
sionofQualityofLifescale,asusedbytheWorld Health Organization (WHOQOL-BREF; WHOQOL
Group, 1998). Included items cover general health and well-being, as well as the domains of physical
health, psychological health and social relationships. Specific items evaluated: the quality of life in gen-
eral, and satisfaction of overall health (general); pain, energy, sleep, mobility, activities, dependence on
medication, and work capability (physical domain); life enjoyment, concentration, self-esteem, body-
image, negative feelings, and meaningfulness (psychological domain); as well as personal relationships,
social support, and sexual satisfaction (social domain). In addition to the raw scores for each item, we
also provided an overall mean, as well as three means per subscale, following the calculation instruc-
tions in the WHOQOL-BREF manual. Cultural norms of religiosity were measured with two items
assessing participants’perception of the extent to which the average person in their country considers
a religious lifestyle and belief in God/Gods/spirits important (Wan et al., 2007). Finally, demographics
were measured at the individual level (i.e., age, gender, level of education, subjective socioeconomic
status (SES), and ethnicity) whereas GDP per capita (current US$, World Bank Group, 2017), sample
type (e.g., university students, online panels), and means of compensation (e.g., course credit, monetary
reward) were determined at the country/sample level. Items were reverse-coded when applicable. Per-
sonal religiosity items were additionally rescaled to the 0-1 range to make them contribute equally to an
averagereligiosityscoresincetheitemsweremeasuredondifferent scales (e.g., a 1–8 Likert scale or a
“yes/no”item, which was coded as “no”=0and“yes”=1).
4
GDP was provided as a raw value as well
as standardized at the country level.
2. Disclosures
2.1. Data, materials, and preregistration
At the start of this project we did not envision a particular statistical analysis to be executed across
the reported results from the individual teams, and therefore we did not preregister any statistical
inference procedure. However, at an earlier stage, we did preregister our own hypotheses regarding
the research questions that were posed to the analysis teams (see osf.io/zyu8c/). This preregistration
also anticipates the many-analysts approach, yet does not specify the exact details of the project. In
this preregistration document, we indicated that the analysis teams would first receive a blinded
version of the data, but we later decided that half of the teams would work with blinded data
and the other half would write their own preregistration (see Sarafoglou et al., 2022). Note that
we did not include our own estimated effect sizes in the results as shown below. Our results, how-
ever, do corroborate the overall pattern of results from the analysis teams. Interested readers can
access our preregistered analysis of the research questions on the OSF (osf.io/vy8z7/).
All documents provided to the analysis teams (dataset, documentation, questionnaire), as well
as the administered surveys, the anonymized raw and processed data (including relevant docu-
mentation), and the R code to conduct all analyzes (including all figures), can be found on the
project page on the OSF (osf.io/vy8z7/). Identifying information (such as names, email-addresses,
universities) was removed from all free-text answers. See also Table 2for an overview of all
resources.
2.2. Reporting
We report how we determined our sample size, all data exclusions, and all manipulations in the
study. However, it should be noted that this project also involved an empirical evaluation of analysis
8S. HOOGEVEEN ET AL.
blinding, which is reported in another paper (i.e., Sarafoglou et al., 2022). Here, we only describe
measures relevant to the theoretical research questions and the many-analysts approach. The
description of the remaining measures that were only used for the experimental analysis proposal
manipulation can be found in Sarafoglou et al. (2022).
2.3. Ethical approval
The study was approved by the local ethics board of the University of Amsterdam (registration
number: 2019-PML-12707). All participants were treated in accordance with the Declaration of
Helsinki. See Appendix 1 for details on the ethical approval for the cross-cultural data collection.
3. Methods
3.1. Analysis teams
The analysis teams were recruited through advertisements in various newsletters and email lists
(e.g., the International Association for the Psychology of Religion (IAPR), International Association
for the Cognitive Science of Religion (IACSR), Society for Personality and Social Psychology
(SPSP), and the Society for the Psychology of Religion and Spirituality (Div. 36 of the APA)), on
social media platforms (i.e., blogposts and Twitter), and through the authors’personal network.
We invited researchers of all career stages (i.e., from doctoral student to full professor). Teams
were allowed to include graduate and undergraduate students in their teams as long as each
team also included a PhD candidate or a more senior researcher. Initially, N= 173 teams signed
up to participate in the many-analysts project. From those teams, N= 127 submitted an analysis
plan and N= 120 completed the project. The members from each analysis team were offered co-
authorship on the main manuscript. No individual researcher or team was excluded from the study.
The number of analysts per team ranged from 1 to 7, with most teams consisting of 1 (41%) or 2
(33%) analysts (median = 2). The different career stages and domains of expertize featured in the
analysis teams are given in Table 1. In addition, Figure 1shows the self-rated collective knowledge
about the topic of religion and well-being and about methodology and statistics. As becomes evi-
dent, most of the analysis teams had more methodological and/or statistical expertize than substan-
tive expertize; 80% of the teams reported considerable expertize with regard to methods and
statistics compared to 31% with regard to religion and well-being, 19% compared to 17% was neu-
tral, and 3% compared to 50% reported little to no knowledge, respectively.
Table 1. Career stages and domains of expertize featured in the 120 analysis teams.
Percentage of teams
Career stages
Doctoral student 54 (45%)
Post-doc 45 (37.50%)
Assistant professor 32 (26.67%)
Associate professor 26 (21.67%)
Full professor 20 (16.67%)
Domains of expertize
Social psychology 43 (35.83%)
Cognition 28 (23.33%)
Methodology and statistics 25 (20.83%)
Religion and culture 25 (20.83%)
Psychology (other) 19 (15.83%)
Health 17 (14.17%)
Note: Teams may include multiple members of the same position and in the same
domain.
RELIGION, BRAIN & BEHAVIOR 9
3.2. Sampling plan
For a separate component of the project (see Sarafoglou et al., 2022), the preregistered sample size
target was set to a minimum of 20 participating teams, which was based on the recruited analysis
teams in the many-analysts project from Silberzahn et al. (2018). However, we did not set a maxi-
mum number of participating teams. The recruitment of analysis teams was ended on December 22,
2020.
3.3. Materials
3.3.1. Surveys
The analysts received three surveys, here referred to as the pre-survey, the mid-survey, and the post-
survey. In the pre-survey, participating teams indicated the career stages and domains of expertize
featured in their team, self-rated their (collective) theoretical and methodological knowledge (5-pt
Likert scale), and anticipated the likelihood of the effects of interest (7-pt Likert scale). In the mid-
survey, teams were asked about the experienced effort, frustration, workload in hours spent on the
project, and the extent to which this workload was lower or higher than expected for the analysis
planning phase (i.e., stage 1; 7-pt Likert scales). In the post-survey, the teams provided the results of
their analyzes and again indicated their experiences during the analysis executing phase (i.e., stage
2). Specifically, per research question, teams were asked about their statistical approach, the oper-
ationalization of the independent variable(s) and dependent variable(s), included covariates, ana-
lytic sample size, (unit of) effect size, p-value or Bayes factor, and additional steps they took for
the analysis. Furthermore, for both research questions, the teams gave a subjective conclusion
about the evidence for the effect (i.e., “good evidence for a relation,”“ambiguous evidence,”or
“good evidence against a relation”), about the practical meaningfulness/relevance of the effect
(based on the data; “yes”or “no”), and indicated again the likelihood of the effects of interest
(on a 7-pt Likert scale). Additionally, teams indicated the appropriateness of their statistical
approach (7-pt Likert scale), the suitability of the dataset for answering each research question
(7-pt Likert scale), and whether or not they deviated from their planned analysis. In case this
last question was answered affirmatively, they specified with regard to which aspects they deviated
(i.e., hypotheses, included variables, operationalization of the independent variable(s), operationa-
lization of the dependent variable(s), exclusion criteria, statistical test, statistical model, direction of
the effect). Finally, teams again reported the experienced effort, frustration, workload in hours and
Figure 1. Responses to the survey questions on self-rated topical and methodological knowledge. The top bar represents the
teams’answers about their knowledge regarding religion and well-being and the bottom bar represents the teams’answers
about their knowledge regarding methodology and statistics. For each item, the number to the left of the data bar (in
brown/orange) indicates the percentage of teams that reported little to no knowledge. The number in the center of the data
bar (in grey) indicates the percentage of teams that were neutral. The number to the right of the data bar (in green/blue) indi-
cates the percentage of teams that reported (some) expertize.
10 S. HOOGEVEEN ET AL.
the extent to which this workload was lower or higher than expected for stage 2 (on 7-pt Likert
scales).
3.4. Procedure
After signing up, participating teams received a document outlining the aim of the project, the time-
line, a short theoretical background with respect to the research questions, and a description of the
dataset. Then, after completing the pre-survey, teams could access the full data documentation, the
questionnaire as presented to the participants of the cross-cultural study, and either a blinded ver-
sion of the data or a preregistration template, depending on which condition they had been assigned
to. Teams could then design their analysis and upload their documents on their own team page on
the OSF (deadline: December 22nd, 2020). The project leaders “froze”the stage 1 documents and
sent the link to the mid-survey. Upon completion of this survey, teams automatically received
access to the real data. They could execute and upload their final analysis scripts on the OSF
until February 28th, 2021. Teams were encouraged to also upload a document summarizing
their results, but this was not mandatory. Finally, all teams completed the post-survey. See Table
2for an overview of the procedure.
4. Results
Here, we report the key results of the project. Specifically, we evaluate the teams’reported effect
sizes and their subjective conclusions about the research questions (i.e., the primary results). In
addition, we provide descriptive results about the many-analysts aspect (i.e., the secondary results:
variability in analytic approaches, included variables, and the teams’experiences across the two
different stages). Finally, we assessed whether or not the reported effect sizes are related to subjec-
tive beliefs about the likelihood of the research questions.
4.1. Primary results
Teams could report any effect size metric of their choosing, but we noted that we preferred a beta
coefficient (i.e., a fully standardized coefficient; z-scored predictors and outcomes) to allow for a
comparison between teams. As we correctly anticipated that (1) most teams would conduct linear
regression analyzes (see Table 3) and (2) both the (scale of the) independent and dependent vari-
ables might vary across teams, we considered a beta coefficient the most suitable effect size metric.
Note that our request for beta coefficients as effect size metrics may have affected the teams’choice
Table 2. Overview of project stages and resources.
Process Link
Stage 1
Recruitment and sign-up osf.io/hpd6b
Pre-survey osf.io/kgqze
Access to data documentation, questionnaire and either of:
(a) preregistration form osf.io/a5ent
(b) blinded data osf.io/ktvqw
Design analysis and upload plan OSF team pages
Mid-survey osf.io/kgqze
Stage 2
Access to data osf.io/6njsy
Execute analysis and upload script (optional: + report) OSF team pages
Post-survey osf.io/kgqze
Lead team: summarize and write-up key results
Invite analysis teams to write commentary
Note: See osf.io/vy8z7 for an overview of all team pages.
RELIGION, BRAIN & BEHAVIOR 11
of statistical model and encouraged them to use regression models that generate beta coefficients.
For teams that did not prov