Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review

Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the que...
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Autor*in:	Hanák, R. [verfasserIn] Pitel, L.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Anmerkung:	© Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022.

Übergeordnetes Werk:	Enthalten in: Advances in Gerontology - Moscow : MAIK Nauka, Interperiodica Publ., 2011, 12(2022), 3 vom: Sept., Seite 236-241
Übergeordnetes Werk:	volume:12 ; year:2022 ; number:3 ; month:09 ; pages:236-241

Links:	Volltext

DOI / URN:	10.1134/S2079057022030067

Katalog-ID:	SPR050983776

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allfields	10.1134/S2079057022030067 doi (DE-627)SPR050983776 (SPR)S2079057022030067-e DE-627 ger DE-627 rakwb eng Hanák, R. verfasserin aut Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022. Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. Pitel, L. aut Enthalten in Advances in Gerontology Moscow : MAIK Nauka, Interperiodica Publ., 2011 12(2022), 3 vom: Sept., Seite 236-241 (DE-627)647653923 (DE-600)2595689-9 2079-0589 nnns volume:12 year:2022 number:3 month:09 pages:236-241 https://dx.doi.org/10.1134/S2079057022030067 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2022 3 09 236-241
spelling	10.1134/S2079057022030067 doi (DE-627)SPR050983776 (SPR)S2079057022030067-e DE-627 ger DE-627 rakwb eng Hanák, R. verfasserin aut Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022. Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. Pitel, L. aut Enthalten in Advances in Gerontology Moscow : MAIK Nauka, Interperiodica Publ., 2011 12(2022), 3 vom: Sept., Seite 236-241 (DE-627)647653923 (DE-600)2595689-9 2079-0589 nnns volume:12 year:2022 number:3 month:09 pages:236-241 https://dx.doi.org/10.1134/S2079057022030067 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2022 3 09 236-241
allfields_unstemmed	10.1134/S2079057022030067 doi (DE-627)SPR050983776 (SPR)S2079057022030067-e DE-627 ger DE-627 rakwb eng Hanák, R. verfasserin aut Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022. Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. Pitel, L. aut Enthalten in Advances in Gerontology Moscow : MAIK Nauka, Interperiodica Publ., 2011 12(2022), 3 vom: Sept., Seite 236-241 (DE-627)647653923 (DE-600)2595689-9 2079-0589 nnns volume:12 year:2022 number:3 month:09 pages:236-241 https://dx.doi.org/10.1134/S2079057022030067 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2022 3 09 236-241
allfieldsGer	10.1134/S2079057022030067 doi (DE-627)SPR050983776 (SPR)S2079057022030067-e DE-627 ger DE-627 rakwb eng Hanák, R. verfasserin aut Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022. Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. Pitel, L. aut Enthalten in Advances in Gerontology Moscow : MAIK Nauka, Interperiodica Publ., 2011 12(2022), 3 vom: Sept., Seite 236-241 (DE-627)647653923 (DE-600)2595689-9 2079-0589 nnns volume:12 year:2022 number:3 month:09 pages:236-241 https://dx.doi.org/10.1134/S2079057022030067 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2022 3 09 236-241
allfieldsSound	10.1134/S2079057022030067 doi (DE-627)SPR050983776 (SPR)S2079057022030067-e DE-627 ger DE-627 rakwb eng Hanák, R. verfasserin aut Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022. Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. Pitel, L. aut Enthalten in Advances in Gerontology Moscow : MAIK Nauka, Interperiodica Publ., 2011 12(2022), 3 vom: Sept., Seite 236-241 (DE-627)647653923 (DE-600)2595689-9 2079-0589 nnns volume:12 year:2022 number:3 month:09 pages:236-241 https://dx.doi.org/10.1134/S2079057022030067 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2022 3 09 236-241
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source	Enthalten in Advances in Gerontology 12(2022), 3 vom: Sept., Seite 236-241 volume:12 year:2022 number:3 month:09 pages:236-241
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author	Hanák, R.
spellingShingle	Hanák, R. Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review
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title	Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review
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title_full	Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review
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title_sort	retirement resources inventory—scale assessment, relationship to retirement satisfaction, adjustment and a meta-analytical review
title_auth	Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review
abstract	Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022.
abstractGer	Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022.
abstract_unstemmed	Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. Before the RRI is used to measure retirement resources, it should be validated on large samples and adjusted to national specifications to confirm/reject it as a psychometrically valid measure. © Pleiades Publishing, Ltd. 2022. ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022.
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title_short	Retirement Resources Inventory—Scale Assessment, Relationship to Retirement Satisfaction, Adjustment and a Meta-Analytical Review
url	https://dx.doi.org/10.1134/S2079057022030067
remote_bool	true
author2	Pitel, L.
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doi_str	10.1134/S2079057022030067
up_date	2024-07-03T19:02:44.297Z
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ISSN 2079-0570, Advances in Gerontology, 2022, Vol. 12, No. 3, pp. 236–241. © Pleiades Publishing, Ltd., 2022.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The Retirement Resources Inventory (RRI) created by C.S. Leung and L.K. Earl is a frequently used self-reported scale for measuring retirement resources. Since it was introduced, 10 scientific papers have been published using the full set of questions and 3 papers using only some of the questions. These have produced ambiguous and inconsistent results with considerable differences in almost all the parameters measured between countries. This paper aims to conduct a systematic review of the scale’s psychometric characteristics and examine the meta-analytic relationship to retirement adjustment, satisfaction and validation for the Slovak population. Instead of the proposed 6-factor structure, we found that different scholars had identified from 3 to 10 factors, and using a Slovak sample we found 4 factors. Internal reliability measured by Cronbach’s alpha showed high levels in all the studies (0.85–0.93). Meta-analytical relationships with RAI showed a strong random effect, r = 0.6 CI [0.35, 0.85], with the RSI, r = 0.509 CI [0.46, 0.56]. But the mean score for the specific subscales differed significantly from the original study in each of the countries it was tested in. 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