Factor structure of the Self-Regulation Questionnaire among adult learners from Poland, Serbia, Slovakia, and the Czech Republic

Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 h ps://doi.o g/10.1186/s41155-022-00241-z RESEARCH © The Au ho (s) 2022. Open Access This a icle is licensed unde a C ea i e Commons A ibu ion 4.0 In e na ional License, which pe mi s use, sha ing, adap a ion, dis ibu ion and ep oduc ion in any medium o o ma , as long as you gi e app op ia e c edi o he o iginal au ho (s) and he sou ce, p o ide a link o he C ea i e Commons licence, and indica e i changes we e made. The images o o he hi d pa y ma e ial in his a icle a e included in he a icle’s C ea i e Commons licence, unless indica ed o he wise in a c edi line o he ma e ial. I ma e ial is no included in he a icle’s C ea i e Commons licence and you in ended use is no pe mi ed by s a u o y egula ion o exceeds he pe mi ed use, you will need o ob ain pe mission di ec ly om he copy igh holde . To iew a copy o his licence, isi h p:// c ea i eco mmons. o g/ licen ses/ by/4. 0/. Open Access Psicologia: Re lexão e C í ica Fac o s uc u e o  heSel -Regula ion Ques ionnai e amongadul lea ne s omPoland, Se bia, Slo akia, and heCzech Republic Ji ka Vaculíko á1* , Ilona Koč a o á1, Jan Kalenda1, Zuzana Neupaue 2, Ma ija C ije ić Vukče ić3 and Anna Włoch4 Abs ac Backg ound: One o he mos signi ican human quali ies is he abili y o de elop, implemen , and lexibly main ain planned beha iou in o de o achie e one’s goals. Sel - egula ion has become a ela i ely well- esea ched a ea in he ield o psychology and pedagogy. Howe e , empi ically alid and eliable ins umen is s ill missing ac oss Eu opean con ex . The p ima y goal o his esea ch was o analyze he psychome ic p ope ies o he Czech e sion o he Sel - Regula ion Ques ionnai e (SRQ-CZ) among adul lea ne s om Poland, Se bia, Slo akia, and he Czech Republic. Objec i e: The aim o he p esen s udy was o examine he ac o s uc u e and psychome ic p ope ies o he SRQ-CZ alida ed in he Czech educa ional con ex in a mul i-cul u al sample. Me hods: A o al o 1711 adul lea ne s om Eu opean coun ies including Poland, Se bia, Slo akia, and he Czech Republic comple ed he SRQ-CZ. The i s s ep o e iewing he alidi y o he SRQ-CZ included es ing ace alidi y. Fu he mo e, explo a o y ac o analysis (EFA) was pe o med on hal he sample and con i ma o y ac o analysis (CFA) on he o he hal . Measu emen in a iance was conduc ed ac oss gende , age, and coun y ollowed by he e alua ion o he eliabili y o he inal ins umen . Resul s: EFA showed ha a h ee- ac o s uc u e bes i he da a. The o iginally p oposed Impulse Con ol and Sel - Di ec ion a e me ged in o one dis inc ac o , while Decision Making and Goal O ien a ion comp ise he o he wo. Goodness-o - i s a is ics yielded om CFA showed a good i o he model, in oducing a eliable and measu emen in a ian ins umen . Conclusion: The p esen s udy used a di e se mul i-cul u al sample o explo e he ac o ial s uc u e and psycho- me ic p ope ies o he SRQ-CZ. A h ee- ac o model was ob ained as he esul o he explo a o y and con i ma- o y ac o analyses. Fu he analysis aiming a measu emen in a iance, compa ing he sample acco ding o gende , age, and coun y, led o sa is ac o y esul s. The only excep ion was a lack o model i in he case o Se bia. Al hough u he psychome ic e alua ion o he SRQ-CZ is s ill needed, he p esen ed esul s cons i u e signi ican indings, con i ming ins umen alidi y and u ili y as a measu e o gene alized sel - egula ion capaci y ac oss adul lea ne s in Eu opean educa ional con ex . *Co espondence: [email p o ec ed] 1 Resea ch Cen e o FHS, Tomas Ba a Uni e si y in Zlín, Zlín, Czech Republic Full lis o au ho in o ma ion is a ailable a he end o he a icle Page 2 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 Keywo ds: Sel - egula ion, Adul lea ne s, Explo a o y ac o analysis (EFA), Con i ma o y ac o analysis (CFA), Measu emen in a iance Backg ound Al hough sel - egula ion is conside ed a c ucial p econ- di ion o any lea ning, he COVID-19 wo ld inc eased he equi emen s on adul s’ abili y o sel -di ec and sel - egula e lea ning. Lea ne s in bo h o mal and non o mal educa ion mo e equen ly ha e o gain hei knowledge and skills h ough digi al lea ning en i onmen s, whe e hey ecei e less di ec ion and o ma i e assessmen om eache s and educa o s (Di Pe o & Ka piński, 2021; S anis ee e  al., 2021; Walle e  al., 2020). The e o e, hey end o be mo e dependen on hei own abili y o de elop, implemen , and lexibly main ain planned beha - iou in o de o achie e one’s goals (B own e al., 1999). Mo eo e , an unp edic able si ua ion in he labou ma - ke , accompanied by he speed o social and echnological changes, leads o he obsolescence o adul s’ cu en skills and demand o new ones (ILO, 2021; OECD, 2019). Con- sequen ly, he need o li elong lea ning and he abili y o sel - egula e lea ning ac i i ies and ela ed beha iou has inc eased immensely (UNESCO, 2019, 2021; WEF, 2020). These ends a e no ypical only o he Wes e n wo ld bu also in Eas e n Eu ope, which aces many new chal- lenges in li elong lea ning. These include he ageing o he popula ion, he ising numbe o mig an s ha need o lea n a new language and job- ela ed skills, as well as a ans o ma ion o he indus ial sec o (Kalenda e al., 2022). Howe e , mos Eu opean coun ies lack a alid and eliable ins umen o assessing he sel - egula ion o adul lea ne s. Resea che s and p o essionals canno e alua e his c ucial p econdi ion o success ul lea ning wi hou such an ins umen . Fo his eason, he p i- ma y pu pose o his s udy is o cul u ally adap a alid and eliable esea ch ins umen o measu ing he sel - egula ion o adul s in ou Eu opean coun ies: Poland, Se bia, Slo akia, and he Czech Republic. A numbe o heo ies explaining sel - egula ion p o- cesses ha e been de eloped o heo e ically unde line and empi ically cap u e sel - egula ion ac i i y ac oss all con inen s and di e se ields o s udy (Boekae s e al., 2005; Baumeis e & Hea he on, 2009; Senécal & Valle- and, 1995; Veens a e al., 2010). The concep ualisa ion o sel - egula ion has e ol ed om a igid s imulus- esponse unde s anding o one’s capaci y o beha e inde- penden ly bu ollowing an o iginal ex e nal command (Diaz & F uhau , 1991) o a mo e complex concep u- alisa ion including pe sonali y and social de e minan s (B own e  al., 1999). In he ollowing pa ag aphs, we b ie ly elabo a e he mos impo an ones ha a e c ucial o he heo e ical backg ound o he selec ed esea ch ins umen . The i s o hese is a social cogni i e pe spec i e on sel - egula ion (Bandu a, 1986, 1991) ha highligh s he in e ac ion o pe sonal, beha iou al, and en i on- men al p ocesses. In his amewo k, sel - egula ion includes no only beha iou al skills in managing en i- onmen al con ingencies, bu also con ains a sense o pe sonal agency o enac hese skills in ele an con- ex s. This iadic model assumes ha people sel - eg- ula e hei beha iou h ough he use o hei inne hough s, eelings, and ac ions ha a e planned, moni- o ed, and cyclically adap ed acco ding o acqui ed eedback conce ning he e ec i eness o s a egies in mee ing hei easonable goals. A pe son’s pe cep ion o sel -e icacy plays a majo ole in mo i a ing hem o sel - egula e hei beha iou . The second one is Ca e and Scheie ’s (1982; 1998) cybe ne ic sel - egula ion model o beha iou as a eed- back loop. This concep ion ocusses on a eedback cycle ha is cha ac e ized by ou phases summa ized as TOTE (‘Tes -Ope a e-Tes -Exi ’). In his cycle, a goal is i s planned. Subsequen ly, a ‘Tes ’ is pe o med o iden- i y whe he he goal has been achie ed. I no , ‘Ope a- ions’ a e pe o med o achie e he goal. Finally, he Tes is pe o med again. I he e a e no disc epancies be ween cu en and desi ed s a es, he indi idual en e s he ‘Exi ’ phase. O he wise, he p ocess epea s in a loop. Syn hesizing ideas om he p e ious wo heo e ical s eams and elabo a ed on in Kan e (1970) h ee-phase heo y, Mille and B own (1991) de eloped hei own concep ion, including sel -moni o ing, sel -e alua ion, and sel - ein o cemen and ex ended he numbe o sel - egula ion p ocesses o se en. Based on his heo e ical amewo k, he au ho s de eloped he 63-i em Sel -Reg- ula ion Ques ionnai e (SRQ) o ini ially assess hese sel - egula o y p ocesses (B own e al., 1999). In addi ion o his esea ch ins umen , wo o he s we e de eloped in he same di ec ion. Ca ey e al. (2004) p o ided a single- dimension solu ion ha was adap ed in o he 31-i em Sho Sel -Regula ion Ques ionnai e (SSRQ), while Neal and Ca ey (2005a, b) p oposed a wo- ac o solu ion as he measu e o someone’s capaci y o sel - egula ion. Since he o iginal SRQ (B own e al., 1999) has been widely used and es ed o psychome ic p ope ies in a a ie y o li e domains, we belie e ha i is a use ul esea ch ins umen o in es iga ing he sel - egu- la ion abili ies o adul lea ne s. Howe e , p e ious Page 3 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 s udies ha e es ablished se e al ac o ial solu ions. Ou o h ee Ame ican s udies (Bandu a e al., 2003; B own e al., 1999; Ca ey e al., 2004; Neal and Ca ey, 2005a, b), none me CFA goodness-o - i indices o he es ed se en- ac o model. Simila ly, in Sou h A i- can esea ch (Po gie e & Bo ha, 2009), B own e al. (1999) p oposed model equi ed modi ica ions in o de o mee analysis equi emen s. As a esul , hey o - mula ed a six- ac o solu ion wi h 24 i ems. Likewise, Picha do e al. (2014; 2018) and Ga o a e al. (2015) sugges ed a mo e pa simonious model wi h ou ac- o s. In summa y, he SRQ lacks s able ac o ial s uc- u e and su icien da a i , as p edominan ly measu ed on s uden s’ samples. Fo his eason, we emedy his gap wi h an empi ical e alua ion o he SRQ’s eliabili y and cons uc alid- i y on a cul u ally di e se sample o adul lea ne s while ollowing applica ions and guidelines o c oss-cul u al psychology (Be y e al., 2013; McLean, 2022). Mo e- o e , conside ing he cul u e-sensi i e na u e o sel - egula ion (Ja amillo e  al., 2017; LeCuye & Zhang, 2015), measu emen in a iance was conduc ed ac oss each coun y o o igin. Fu he , new insigh s a e p e- sen ed wi h espec o gende di e ences in sel - egu- la ion as widely epo ed om bo h he psychological ( an Te e ing e al., 2020; Velayu ham e al., 2012) and neu ological (Hosseini-Kamka & Mo on, 2014) pe - spec i es. The s udy also in es iga es he inding ha age ep esen s an impo an ac o in de e mining indi idual di e ences in sel - egula ion (Ra aelli e al., 2005). Mo e speci ically, we in es iga ed whe he he SRQ’s model s uc u e o equi alency ac oss g oups o gende , age, and coun y by a se ies o measu emen in a iance es s. The aim o his s udy is o desc ibe he alida ion o he Czech e sion o he Sel -Regula ion Ques ionnai e (SRQ-CZ; Ga o a e al., 2015) using c oss-cul u al da a om adul lea ne s wi h simila cul u al backg ounds in ou Eu opean coun ies: Poland, Se bia, Slo akia, and he Czech Republic. Thus, he main objec i e is o examine and asce ain whe he he SRQ-CZ shows he same ep esen a ion o sel - egula ion as p e i- ously epo ed by esea che s (Ga o a e al., 2015). On his basis, we p esen an e alua ion o he ace alid- i y and cons uc alidi y o he ins umen . To in es i- ga e he ac o ial s uc u e o he ins umen , EFA and CFA we e used, ollowed by an e alua ion o measu e- men in a iance ac oss gende , age, and coun y and hen an e alua ion o he eliabili y o he inal ins u- men . The main con ibu ion o his s udy is o b oaden ou unde s anding o sel - egula ion o beha iou among adul lea ne s om an unde s udied Eu opean pe spec i e. Me hod Pa icipan s The esea ch sample consis ed o 1,711 adul lea ne s om ou Eu opean coun ies: Poland (n = 276), Se bia (n = 410), Slo akia (n = 511), and he Czech Republic (n = 514). Da a collec ion was based on a con enien sample o lea ne s en olled in o mal educa ion, aged be ween 18 and 64 yea s. The ques ionnai e was admin- is a ed by a na ional esea ch eam in he i s qua e o 2022 using an in e ne su eying echnique o by a spe- cialized agency using he Compu e Assis ed Web In e - iewing me hod (CAWI). The da a collec ion and da a analysis in his s udy ha e ollowed e hical p inciples o esea ch, espec ing he ICC/ESOMAR In e na ional Code (ESOMAR, 2016). The p inciple o anonymi y was applied o main ain he anonymi y o he pa icipan s, and he esea che s emphasized in o med consen h oughou he s udy. Pa - icipan s we e in o med abou he aims o he esea ch and ha he gi en in o ma ion would be ea ed con i- den ially. Fu he mo e, g an -p ojec e iewe s e alua ed he g an p oposals wi h espec o hei e hical implica- ions, ensu ing he sa e y and igh s o pa icipan s. The whole sample consis ed o 355 (20.7%) males wi h an a e age age o 26.36 yea s (SD = 7.9) and 1356 (79.3%) emales wi h an a e age age o 25.1 yea s (SD = 7), wi h an o e all mean age o 25.4 yea s ( anging om 18 o 61 yea s; SD = 7.3). Da a on he highes a ained educa ional le el showed ha he majo i y had a ained a leas h ee yea s o highe educa ion and he e o e ea ned he Bach- elo deg ee (i.e. In e na ional S anda d Classi ica ion o Educa ion ISCED 6). De ailed demog aphic in o ma ion abou he samples can be seen in Table1. Measu e The o iginal SRQ (B own e al., 1999) is a 63-i em, sel - epo ing ins umen designed o assess he abili y o beha iou al sel - egula ion in se en phases. These phases e lec he abili y o indi iduals o ecei e el- e an in o ma ion, e alua e and compa e i o no ms, igge change, sea ch o op ions, o mula e a plan, implemen he plan, and assess he plan’s e ec i eness. Howe e , we decided o use he Czech e sion o he SRQ (SRQ-CZ; Ga o a e al., 2015), based on cul u al app op ia eness o he a ge popula ion o Eu opean lea ne s. Fac o analysis o he SRQ-CZ discon i med he o iginal se en-phase heo y and ins ead yielded a model wi h ou ac o s: Impulse Con ol (8 i ems), Goal O ien a ion (5 i ems), Sel -Di ec ion (7 i ems), and Decision Making (7 i ems). In his s udy, he Czech e sion o SRQ included 27 i ems wi h esponse op ions on i e-poin Like scale anging om “s ongly disa- g ee” o “s ongly ag ee” along equal in e als. Page 4 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 Pa icipan s o his s udy we e in o med ha he e a e no igh o w ong answe s and hey should espond o he i ems quickly wi hou hinking oo long. The esul s a e calcula ed as he a i hme ic mean o exp ess he o al aw sco e and he sco es o indi idual dimen- sions. Despi e he ac ha he ool has al eady been alida ed, we decided o i s apply explo a o y and only hen con i ma o y ac o analysis. The eason o his p ocedu e is ha he ool exis s in se e al pe mu- a ions wi h di e en numbe s o ac o s and i ems, so i s cu en o m is no in e na ionally s able. Fou necessa y s eps we e in ol ed in he ins u- men ’s p epa a ion (AERA e al., 1999; Hamble on e al., 2005; ITC, 2017). Fi s , SRQ-CZ i ems we e ansla ed by skilled ansla o s o p oduce he language modi i- ca ions o he ins umen o Polish, Se bian, and Slo- ak. Be o e he ansla ion o he ins umen , an online semina was o ganised, whe ein he esea ch pa ne s discussed and ag eed on he basic s anda ds o he ansla ion p ocess. Second, backwa d and o wa d ansla ions we e applied o p oduce he p ima y lan- guage modi ica ions. These modi ica ions we e analysed by expe ienced esea che s o he cong uence o i ems wi h cul u al adi ions and c i ically assessed wi hin he na ional esea ch eam. Las ly, each language e - sion was ield es ed on a sample o he a ge popula- ion o judge he ace alidi y. While esea che s had a deep unde s anding o he backg ound o he ins u- men , a ge pa icipan s p o ided aluable insigh s ha o he wise migh be missed. Focus was placed on he con en and logical cohesion o he ins umen . De ailed o e iew o he i ems is p esen ed in Addi ional ile1. P ocedu e andda a analyses All analy ical p ocedu es we e applied, along wi h judg- men c i e ia which ook in o accoun he heo e i- cal amewo k as well as he p ac ical use ulness o he ins umen . Indi idual s eps assessing ace and con- s uc alidi y we e e alua ed simul aneously based on s a is ical as well as judgmen al c i e ia ocused on indi- idual i ems and ac o s as well as he ques ionnai e as a whole. In his con ex , we empi ically e i ied whe he he SRQ-CZ had an iden ical s uc u e, as indica ed by p e ious esea ch (Ga o a e al., 2015), o whe he ano he ac o ial solu ion can be iden i ied, as sugges ed by p edominan ly non-Eu opean s udies (B own e  al., 1999; Ca ey e al., 2004; Neal and Ca ey, 2005a, b; Po gi- e e & Bo ha, 2009). Fu he mo e, we e alua ed measu e- men in a iance acco ding o gende , age, and coun y, any o which may play he ole o a seconda y ac o in luencing sel - egula ion capaci y. Fi s , he inspec ion o he means, s anda d de ia ions, skewness, and ku osis o each i em was accomplished h ough i em analysis. The ac o s uc u e o he SRQ- CZ was u he c oss- alida ed (James e al., 2013) using a sample andomly di ided in o wo sepa a e g oups. Based on he hypo hesized consis ency o he co e- la ed ac o s, EFA using P incipal Componen Analysis was applied o he i em co ela ion ma ix. Following he ecommenda ions o Tabachninick and Fidell (2014), oblique p omax o a ion was applied as a sui able com- p omise (Russell, 2002). To e ain sa is ac o y a iables, he .40–.30–.20 ule was adop ed (Howa d, 2016). In addi ion o conside a- ion o he in e p e able ac o s uc u e, we inspec ed Ca ell’s sc ee plo (Ca ell, 1966) and pe o med pa - allel analysis (Ho n, 1965), as well as Wayne Velice ’s minimum a e age pa ial (MAP) analysis (Velice , 1976). To e alua e he in e nal consis ency o he ull and subscale sco es ob ained om he EFA, C onbach’s α, McDonald’s ω, and Gu mann’s λ6 we e compa ed wi h subscales expec ed o be eliable i he in e nal eliabili y coe icien is a leas ≥ .70 (DeVellis, 2016; Gid on, 2013), while also aking in o accoun he num- be o scale i ems. Pea son co ela ion wi h Bon e oni co ec ion was used o con ol o mul iple es ing. To in e p e he sizes o co ela ion coe icien s, we use e ec -size labels acco ding o Cohen’s (1988, p. 79–81) Table 1 Demog aphic de ails o he samples Va iables Poland (n = 276) Se bia (n = 410) Slo akia (n = 511) Czech Republic (n = 514) To al (n =1711) n (%) Gende Male 23 (8.3) 105 (25.6) 98 (19.2) 129 (25.1) 355 (20.7) Female 253 (91.7) 305 (74.4) 413 (80.8) 385 (74.9) 1356 (79.3) Age 18–20 yea s 94 (34.1) 65 (15.9) 177 (34.6) 48 (9.3) 384 (22.4) 21+ yea s 182 (65.9) 345 (84.1) 334 (65.4) 466 (90.7) 1327 (77.6) Educa ion ISCED 3-5 123 (44.6) 152 (37.1) 0.0 (0.0) 204 (39.7) 479 (28.0) ISCED 6 87 (31.5) 134 (32.7) 350 (68.5) 236 (45.9) 807 (47.2) ISCED 7 62 (22.5) 95 (23.2) 120 (23.5) 73 (14.2) 350 (20.5) ISCED 8 4 (1.4) 29 (7.1) 41 (8) 1 (.20) 75 (4.4) Page 5 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 con en ions o = .10 (small); = .30 (medium); and = .50 (la ge) co ela ion. Second, a se ies o CFAs o he ac o s uc u e o he SRQ-CZ ob ained in he p e ious s age was pe o med on he o he hal o he sample. The inal model was also e i ied on sepa a e samples di ided by he gende , age, and coun y. Thi d, a se ies o measu emen in a i- ance es s using mul iple g oup CFA we e ca ied ou o de e mine whe he he model s uc u e was equi alen ac oss g oups o gende , age, and coun y. Con igu al, me ic, and scala le els o in a iance we e e alua ed. Based on he common ecommenda ions o in es iga e he model’s goodness o i (Hoope e al., 2008), a numbe o s a is ics we e used: compa a i e i index (CFI; Ben le , 1990), Tucke –Lewis index (TLI; Tucke & Lewis, 1973), and oo mean squa e e o o app oxima ion (RMSEA; S eige , 1990). In addi ion, we epo ed he Chi-Squa e (x2) s a is ic, deg ees o eedom, and i s p alue. The desc ip i e i em analysis, EFA, and he awpa . sps and map.sps sc ip s (O´Conno , 2000; Velice , 1976) we e unde aken in IBM SPSS 27.0. IBM SPSS AMOS 27.0 was used o pe o m CFA and MI. We also used JASP 0.16.2.0 o calcula e C onbach’s α, McDonald’s ω, and Gu mann’s λ6. Only esponses wi h no missing al- ues we e included in he analysis. Resul s Desc ip i e s a is ics o he SRQ-CZ can be seen in Addi ional ile 1. The means o all 27 i ems anged be ween 2.39 and 4.12 ou o 5, wi h a mean sco e o 3.28. The alues o he s anda d de ia ions (SD) o all i ems anged be ween .89 o 1.28, wi h a mean o 1.08. Values o he skewness and ku osis o all i ems did no exceed he alue o ≥ 2 o skewness and ≥ 7 o ku - osis (Cu an e al., 1996; T ochim & Donnelly, 2006), sugges ing no se ious iola ion o he da a dispe sion. In he nex s ep, he esea ch sample was andomly di ided in o wo independen samples o he EFA and CFA, espec i ely. The 27 i ems o sel - egula ion we e subjec ed o EFA wi h he aim o ga he ing in o ma ion abou he in e ela ionships among he se o a iables. Explo ing he ac o s uc u e o  heSRQ‑CZ The Kaise -Meye -Olkin measu e o sampling adequacy (KMO) was .89, indica ing ha he sample was adequa e, and Ba le ’s es o sphe ici y eached signi icance (x2(351) = 6739.62, p < .001), suppo ing he ac o abili y o he co ela ion ma ix. A sc ee plo o eigen alues (no shown) was s ongly in a ou o he h ee- ac o s uc u e. This esul was suppo ed by he pa allel analysis, indica ing he p es- ence o h ee componen s wi h eigen alues exceeding he co esponding c i e ion alues o a andomly gene a ed da a ma ix. Fu he mo e, Wayne Velice ’s o iginal MAP es (Velice , 1976) p esen ed a h ee- ac o s uc u e. The numbe o componen s was also h ee acco ding o he e ised es e sion (O’Conno , 2000). Compa ing hese indings and he heo y-based ini ia i e wi h he da a-d i en solu ion, a h ee- ac o s uc u e o he SRQ- CZ was selec ed. A o al o 22 i ems we e shown o emain by he esul s o EFA, om which h ee scales we e c ea ed, accoun ing o app oxima ely 41% o he a iance, wi h eigen alues o 6.63, 2.88, and 1.56 espec i ely. The mean o he inal i ems on a spli sample used o EFA (n = 855) anged be ween 2.42 and 4.05 (SD = .90 o 1.30). The i em ha bes explained he a iance measu ed in he pa icipan ’s sel - egula ion was GO19 (I ha e ules ha I s ick by no ma e wha ), om he hi d ac o . On he o he hand, i em GO10 (I can s ick o a plan ha ’s wo king well) om he same ac o had he lowes ac o loading, communali ies, and a lowe a e age co ela ion han he es o he i ems. Based on he heo- e ical amewo k o SRQ, i em GO10 well ep esen ed he meaning o he ac o . Mo eo e , we es ed a model wi h- ou his i em; howe e , i did no each be e i . The e o e, we decided o e ain he i em wi hin he ac o and suppo mul iple- ac o indica o s (a leas ou o six pe ac o ), pe o ming analysis wi h la gely de e mined ac o s (Fab i- ga e al., 1999). The ac o loadings o each i em as well as eliabili y a e p esen ed in Table2. The i s subscale, i led Sel -Con ol, consis ed o ele en i ems assessing in e nal sel -con ol skills, including i ems ini ially alling unde he ac o s Impulse Con ol (7 i ems, e.g. I ha e ouble ollowing h ough wi h hings once I’ e made up my mind o do some hing) and Sel -Di ec ion (4 i ems, e.g. I don’ no ice he e ec s o my ac ions un il i ’s oo la e). The second subscale ep esen ed a ac o meas- u ing pe sonal Decision Making (7 i ems, e.g. I’m good a inding di e en ways o ge wha I wan ). The hi d sub- scale comp ised ou goal o ien a ion- ela ed i ems (e.g. I ha e ules ha I s ick by no ma e wha ). The h ee subscales showed a medium co ela ion wi h each o he , eaching expec ed di ec ions. The co - ela ions o he h ee subscales wi h he o e all cons uc anged om medium o la ge, which sugges s he possi- bili y o connec ing all he subscales in o one o e all con- s uc , as well as suppo ing a h ee- ac o s uc u e (see Addi ional ile2). A his poin , we decided o u he e alua e he connec ion o subscales in o h ee ac o s. E alua ing he ac o s uc u e o  heSRQ‑CZ In o de o e alua e he da a-d i en ounda ion o he SRQ-CZ, we e i ied he cons uc alidi y o indi id- ual ac o s as well as hei connec ion wi h he de aul Page 6 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 model (see Addi ional ile 3) on he o he andomly di ided sample (n = 856). The esul s o he CFA model i a e displayed in Table3. As can be seen in Table3, all es ed independen ac o s ul illed he s a is ical as well as he judgmen c i e ia o he ool cons uc ion. This means ha he ac o s wo k independen ly well and can be applied sepa a ely. Mo eo- e , he connec ion o he ac o s unde he umb ella o one de aul model also p o ed o be unc ional: x2(206) = 665.179, CFI = .920, TLI = .911, RMSEA = .051. Measu emen in a iance o  heSRQ‑CZ ac ossgende , age, andcoun y Acco ding o Cheung and Rens old’s (2002) ecommen- da ion o he di e ences among he alues o ΔCFI (wi h alues lowe han .01 conside ed a sign o in a iance), he ac o means o males and emales can be compa ed up o he scala le el. Simila ly, he di e ence be ween he age g oups is measu emen in a ian up o he sca- la le el. Ne e heless, based on he esul s shown in Table4, he ins umen does no seem o be in a ian ac oss coun ies. We addi ionally checked he CFA goodness-o - i s a- is ics o he de aul model independen ly ac oss coun- y samples (see Addi ional ile 4). All he coun ies eached accep able pa ame e s excep Se bia, o which he indices (CFI = .871, TLI = .856) emained below he ecommended alue o .90 (Ben le , 1990). Fo his eason, we u he compa ed measu emen in a iance ac oss coun ies wi hou he sample om Se bia (see Table 2 Pa e n ma ix o he SRQ-CZ (n = 855) No e: The ex ac ion me hod was p incipal componen analysis; he o a ion me hod was p omax wi h Kaise No maliza ion. Fac o loadings in bold ep esen i ems’ loadings on o hei p ima y ac o . F1–3 = ac o , h2 = communali ies, α-i = C onbach’s α i he i em is dele ed. SC Sel -Con ol, DM Decision Making, GO Goal O ien a ion I em desc ip ion F1 F2 F3 h2α-i IC7: I ha e ouble ollowing h ough wi h hings once I’ e made up my mind o do some hing. .790 −.036 .067 .611 .831 IC3: I ge easily dis ac ed om my plans. .708 .244 −.139 .497 .841 IC9: I can come up wi h lo s o ways o change, bu i ’s ha d o me o decide which one o use. .698 .159 −.017 .440 .842 IC27: I gi e up quickly. .685 −.121 .046 .517 .838 SD4: I don’ no ice he e ec s o my ac ions un il i ’s oo la e. .658 .002 −.047 .456 .841 IC8: I don’ seem o lea n om my mis akes. .634 −.022 −.010 .417 .844 IC6: When i comes o deciding abou a change, I eel o e whelmed by he choices. .610 −.003 .110 .338 .848 SD5: I ’s ha d o me o see any hing help ul abou changing my ways. .603 −.078 .115 .359 .847 SD15: I ha e a ha d ime se ing goals o mysel . .588 −.101 −.051 .427 .844 SD2: I ha e ouble making up my mind abou hings. .571 .147 .015 .284 .854 IC21: O en I don’ no ice wha I’m doing un il someone calls i o my a en ion. .571 .070 .058 .286 .838 DM23: I’m good a inding di e en ways o ge wha I wan . .017 .742 −.088 .490 .706 DM14: As soon as I see a p oblem o challenge, I s a looking o possible solu ions. −.138 .684 −.049 .521 .704 DM20: I can usually ind se e al di e en possibili ies when I wan o change. .007 .669 .004 .447 .712 DM18: The e is usually mo e han one way o accomplish some hing. .096 .650 .017 .396 .724 DM16: When I’m ying o change some hing, I pay a lo o a en ion o how I’m doing. .193 .649 −.041 .353 .737 DM17: As soon as I see hings a en’ going igh I wan o do some hing abou i . −.147 .583 .038 .448 .716 DM22: Usually I see he need o change be o e o he s do. .188 .489 .036 .221 .759 GO19: I ha e ules ha I s ick by no ma e wha . .080 −.148 .903 .680 .631 GO13: I am se in my ways. .048 −.033 .841 .658 .612 GO12: I ha e pe sonal s anda ds, and y o li e up o hem. .085 .092 .756 .599 .652 GO10: I can s ick o a plan ha ’s wo king well. −.186 .109 .390 .303 .782 Fac o label SC DM GO Toge he No. o i ems 11 7 4 22 M2.70 3.60 3.72 3.34 SD .78 .63 .77 .73 Explained a iance in % 24.56 10.68 5.76 41 McDonald’s ω.858 .858 .758 .436 C onbach’s α.856 .856 .737 .676 Gu mann’s λ6 .853 .853 .696 .758 Page 7 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 Addi ional ile5). The de aul model was in a ian up o he con igu al model, which ep esen s he es ing o he ac o s uc u e. In a ian ac o loadings (me ic model) and he in e cep s cons ained o be equal (scala model) showed poo i . Reliabili y o  heSRQ‑CZ In addi ion o he p esen ed esul s o cons uc alidi y, he eliabili y coe icien s we e calcula ed. Besides C on- bach’s α eliabili y coe icien , which while commonly used is no longe su icien ly wa an ed as a sole index o eliabili y (Agbo, 2010), McDonald’s ω and Gu mann’s λ6 we e calcula ed. As can be seen in Addi ional ile6, he h ee ac o s o he de aul model a e expec ed o be eliable in all moni o ed g oups. In o he wo ds, all indi- ces showed good eliabili y (≥ .70) o he h ee ac o s ac oss samples wi h he excep ion o he in e nal con- sis ency o he Goal O ien a ion ac o (λ6 = .663) in he case o Se bia sample. Wi h ega d o Se bia, howe e , his ac o did each sa is ac o y esul s in he case o C onbach’s α = .705, and McDonald’s ω = .722. Discussion The main objec i e o he p esen s udy was o desc ibe he cons uc alidi y o he Czech e sion o he Sel - Regula ion Ques ionnai e (SRQ-CZ), aimed a measu - ing he sel - egula ion o beha iou in ou phases. Based on indings om he sample o adul lea ne s in Poland, Se bia, Slo akia, and he Czech Republic, his s udy ep- esen s a unique c oss-cul u al app oach in unde s and- ing he pe sonal abili y o ac acco ding o an in e nal plan o achie e pe sonal goals, wi hou ex e nal suppo o ewa d. In line wi h p e ious esea ch (Ga o a e al., 2015), we p o ide empi ical suppo o he exis ence o Impulse Con ol and Sel -Di ec ion wi hin he Sel -Con ol ac- o , and Decision Making and Goal O ien a ion wi hin sepa a e ac o s, e alua ed on a cul u ally di e se sample. The signi icance o his esea ch is he inding ha he ins umen holds he same cons uc s o beha iou sel - egula ion as epo ed in he pionee ing wo k o Ga o a e al. (2015). The only excep ion is he model’s modi ica- ion in he case o i em pu i ica ion ( om 22 o 27 i ems) and ac o educ ion ( om h ee o ou ac o s). On his basis, Impulse Con ol and Sel -Di ec ion, measu ing he inhibi ion o emo i e esponse endencies, c ea ed one common ac o called Sel -Con ol. I ems included in his sha ed ac o we e simila in he na u e o hei meanings, as well as in hei e e sed pola i y, which could signi ican ly in luence esponden s’ pa e n o esponses. When compa ing his ac o o he emaining cons uc s (Decision Making and Goal O ien a ion), ac- o sco es need o be e-coded o epo on he nega i e unc ion o sel - egula ion. O e all, we ha e ound ha he inal model o he ins umen is obus in i s applica ion as a whole, as well Table 3 CFA goodness-o - i s a is ics o he indi idual ac o s and de aul model (n = 856) No e: Sel -Con ol includes he Impulse Con ol and Sel -Di ec ion i ems. No = numbe o i ems; p < .001 Model No x2d CFI TLI RMSEA F1 (Sel -Con ol) 11 140.035 44 .967 .959 .050 F2 (Decision Making) 7 44.512 14 .977 .965 .050 F3 (Goal O ien a ion) 4 9.294 2 .992 .975 .065 De aul model 22 665.179 206 .920 .911 .051 Table 4 Measu emen in a iance o he de aul model o p ede ined g oups (n = 856) No e: p < .001 G ouping a iable Le el o in a iance x2d CFI ΔCFI TLI RMSEA Gende Con igu al 900.514 412 .916 .905 .053 Me ic 916.414 431 .916 0 .910 .051 Scala 961.789 450 .912 -.004 .909 .052 Age Con igu al 899.548 412 .916 .906 .053 Me ic 920.445 431 .916 0 .909 .052 Scala 938.434 450 .916 0 .913 .050 Coun y Con igu al 1560.571 824 .881 .867 .065 Me ic 1681.58 881 .871 -.01 .865 .065 Scala 2215.514 938 .794 -.077 .797 .080 Page 8 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 as in he sepa a e usage o all indi idual ac o s. Ano he impo an inding o ou s udy is he sui abili y o he ins umen o he speci ic g oups o esponden s di ided by gende and age. In p ac ise, i suppo s he s a is i- cal ele ance o mean compa ison o sel - egula ion o beha iou be ween males and emales and g oups di ided by age. The ob ained model was u he es ed o measu e- men in a iance acco ding o coun y o o igin. In he case o Se bia, he esul s showed ha he inal model o he ins umen migh be weak. Sc eening he da a, dis i- bu ional p ope ies and demog aphic in o ma ion abou he Se bian sample did no a y om he speci ied pop- ula ion o in e es , i.e. did no a y om o he na ional samples used in his s udy. Thus he ques ion emains as o how speci ic he Se bian pe cep ion o sel - egula ed beha iou is as compa ed o o he Cen al and Eas e n Eu opean coun ies, as well as how Se bian pe cep ions o sel - egula ion di e om ha o he neighbou ing coun ies o Poland, Slo akia, and he Czech Republic, all o which a e simila cul u ally and demog aphically. Due o his disc epancy, applica ion o he ins umen wi h- ou u he in es iga ion would be inapp op ia e a his s age o he esea ch. We also es ed measu emen in a i- ance on he es o he coun ies in he analysis (wi hou Se bia), showing ha he same s uc u e o he model holds o all g oups (in a ian on he con igu al le el). Fu he modi ica ions o he model would be needed o inc ease he in e na ional compa abili y o he ins u- men . Howe e , i should be no ed ha he ins umen was e alua ed as in e nally consis en ac oss all he c e- a ed samples, including he accep able alues (C onbach’s α and McDonald’s ω) o Se bia Picha do-Ma ínez e  al. (2014) epo ed he imple- men a ion o a esea ch s a egy simila o his s udy. In hei s udy, 63 i ems om he SRQ we e adminis a ed o a sample o 834 s uden s andomly di ided in o wo se s o explo a o y and con i ma o y samples. The esul s show e idence o he alidi y and in e nal consis ency o he Sho Sel -Regula ion Ques ionnai e (SSRQ) in he Spanish con ex , sugges ing a ou - ac o model wi h 17 i ems. Likewise, da a om 845 Spanish ea ly and middle adolescen s showed goodness o i wi h he ou - ac o model and he same numbe o i ems (Picha do e al., 2018). Howe e , he socio-demog aphic and cul u al di e si y o he sample s ill needs esea ch. The p esen s udy has s eng hs, as well as some limi a- ions, which should be add essed in u u e esea ch. The ela i ely la ge sample size made i possible o andomly di ide he da a in hal so ha bo h EFA and CFA could be unde aken. The ac ha he sample consis ed o ou na ional samples may be seen bo h as a s eng h and as a weakness. Due o he low esponse a e mos likely jus i ied by he onse o COVID-19 pandemic, i was no possible o conduc ep esen a i e quo a samples. The e- o e, he p esen ed esul s should no be assumed o be gene alizable o he a ge popula ion. On he o he hand, his s udy ep esen s one o he ew a emp s o esea ch sel - egula ion om an in e na ional poin o iew and mee he ecommenda ions o sample size when con- duc ing CFA. I should be no ed ha ou sample as a whole ep esen s a highly educa ed popula ion, based on hei highe - han-a e age le el o comple ed educa ion. Mo e han 70% o he pa icipan s epo ed ha ing a leas 3 yea s o uni e si y educa ion (up o ISCED 6) and a e now con inuing o pa icipa e a a highe le el. This s udy included cul u al and linguis ic di e si y ha poses signi ican challenges o he p ocess o s anda di- za ion o measu es (Hamble on & Zenisky, 2011; Si eci, 2011). Taking measu emen equi alence ac oss cul- u es and languages in o ull accoun , he biases o esul in e p e a ion we e ca e ully e alua ed using guidelines o adap ing educa ional and psychological measu es (Hamble on e al., 2005; ITC, 2017). Ano he ques ion is ela ed o he gene al cha ac e o he SRQ. I cap u es gene ic a he han speci ic asks. We belie e, howe e , ha while illing in he ques ionnai e, esponden s always ela e hei answe s o a speci ic ac ion in a li e si ua- ion. Fo example, he esul s o a esponden who illed in he ques ionnai e ela ed o sel - egula ion in spo s may yield a di e en pic u e o sel - egula ion han ha o a esponden who ela ed hei sel - egula ion o s udy ac i i ies. This ques ions he cons uc alidi y o he ques ionnai e. As o u u e esea ch, a ch onology o he sel - eg- ula ed beha iou , deli e ed om he se en-phase sel - egula ion heo y (Mille & B own, 1991), indica ing whe he a pe son sys ema ically p oceeds one s ep a a ime and whe he hey use all ac i i ies in each phase, can be an icipa ed in a ollow-up in es iga ion. Based on he p esen ed esul s, he SRQ-CZ can be u he modi ied, ex ended, o used o supplemen da a om o he su eys ac oss di e se na ional o in e na ional samples. Mo eo- e , i can be adminis a ed by adul lea ning esea ch- e s, manage s, lec u e s, employe s, consul an s, o o he p o essionals in o mal educa ional se ings o adul lea ne s in Eu opean and non-Eu opean cul u es (Aub ey e al., 1994; Ca ey e al., 2004; Neal and Ca ey, 2005a, b). Conclusions The p esen s udy used a di e se mul icul u al sample o explo e he ac o ial s uc u e o he SRQ o iginally de el- oped by B own e  al. (1999). This ins umen assesses indi iduals’ abili y o sel - egula ion in se en phases. Despi e p e ious wo k on he ins umen ’s alida ion in Page 9 o 11 Vaculíko áe al. Psicologia: Re lexão e C í ica (2022) 35:40 he Czech con ex , we we e unable o ind a good model i o a p e iously alida ed ou - ac o model (Ga o a e al., 2015) using a mul iple-me hods design. The same ac o s appea ed in ou da a bu me ged in o a h ee- ac o solu- ion, wi h Impulse Con ol and Sel -Di ec ion in a sepa a e ac o called Sel -Con ol, and Decision Making and Goal O ien a ion as he o he wo. Since p e ious s udies ha e also ailed o each conclusi e esul s on he op imal ac- o s uc u e o he SRQ, u he esea ch is needed in o de o disen angle he possible e ec s o gende , age, and na ionali y on sel - egula ion o beha iou . Un il his e i- dence exis s, i would be wise o conduc ac o analysis in o de o explo e and e alua e whe he he o al sco e, and a h ee- ac o s uc u e, is applicable o hei samples. Abb e ia ions CFA: Con i ma o y ac o analysis; CFI: Compa a i e i index; d : Deg ee o eedom; DM: Decision Making; EFA: Explo a o y ac o analysis; GO: Goal O ien a ion; h2: Communali ies; ISCED: In e na ional S anda d Classi ica ion o Educa ion; KMO: Kaise -Meye -Olkin measu e; M: Mean; MAP: Minimum a e - age pa ial analysis; RMSEA: Roo mean squa e e o o app oxima ion; SC: Sel - Con ol; SD: S anda d de ia ion; SRQ: Sel -Regula ion Ques ionnai e; SRQ-CZ: Czech Sel -Regula ion Ques ionnai e; TLI: Tucke –Lewis index; x2: Chi-squa e; α-i: C onbach’s α i he i em is dele ed. Supplemen a y In o ma ion The online e sion con ains supplemen a y ma e ial a ailable a h ps:// doi. o g/ 10. 1186/ s41155- 022- 00241-z. Addi ional ile1. O e iew o he SRQ-CZ i ems including desc ip i e s a is ics (n = 1,711). Addi ional ile2. Co ela ion be ween SRQ-CZ subscales and he ull scale (n = 855). Addi ional ile3. E alua ed ac o s uc u es o a co ela ed h ee- ac o model (n = 856). Addi ional ile4. CFA goodness-o - i s a is ics o he de aul model ac oss coun ies. Addi ional ile5. Measu emen in a iance o he de aul model o coun y. Addi ional ile6. Reliabili y o he de aul model ac oss samples. Acknowledgemen s No applicable. Au ho s’ con ibu ions JV con ibu ed in he e iew esea ch, da a analysis, and inal w i ing. IK con ibu ed in he da a analysis. JK con ibu ed in he concep ion and design o he wo k. ZN con ibu ed in he da a collec ion. MCV con ibu ed in he da a collec ion. AW con ibu ed in he da a collec ion. All au ho s ead and app o ed he inal manusc ip . Funding This a icle was esea ched and w i en wi h he kind inancial suppo o he DANUBE p ojec : De elopmen o new and agogical diagnos ic app oaches and in e en ions o he adul docili y phenomenon. P ojec numbe : 2020-1-SK01-KA204-078313. A ailabili y o da a and ma e ials The da ase s used and analysed du ing he cu en s udy a e a ailable om he co esponding au ho on easonable eques . Decla a ions E hics app o al and consen o pa icipa e Da a collec ion and da a analysis ollow e hical p inciples o esea ch, espec ing he ICC/ESOMAR In e na ional Code (ESOMAR, 2016). The p inciple o anonymi y keeps pa icipan s anonymous and he esea che s emphasized olun a y pa icipa ion and in o med consen h oughou he s udy. Pa icipan s we e in o med abou he aims o he esea ch and ha he gi en in o ma ion would be ea ed con iden ially. Fu he mo e, g an -p ojec e iewe s e alua ed he g an p oposals wi h espec o hei e hical implica ions and assu ed he sa e y and igh s o pa icipan s. Consen o publica ion Au ho s decla e ha hey ha e consen o publish p esen ed pape . Au ho s ha e pe mission om he o iginal au ho s o he SRQ-CZ o use and adap hei wo k in his esea ch. Compe ing in e es s The au ho s decla e ha he esea ch was conduc ed in he absence o any comme cial o inancial ela ionships ha could be cons ued as a po en ial con lic o in e es . The au ho s decla e no ac ual o po en ial con lic s o in e es wi h espec o he esea ch, au ho ship, o publica ion o his a icle. Au ho de ails 1 Resea ch Cen e o FHS, Tomas Ba a Uni e si y in Zlín, Zlín, Czech Republic. 2 Ma ej Bel Uni e si y, Facul y o Educa ion, Banská Bys ica, Slo akia. 3 Uni e - si y o No i Sad, Facul y o Educa ion, Sombo , Se bia. 4 Pedagogical Uni e si y o C acow, C acow, Poland. Recei ed: 17 Sep embe 2022 Accep ed: 5 Decembe 2022 Re e ences Agbo, A. A. (2010). C onbach’s Alpha: Re iew o Limi a ions and Associa ed Recommenda ions. 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