Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021
Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Elsa‐Lynn Nassar [verfasserIn] Brooke Levis [verfasserIn] Marieke A. Neyer [verfasserIn] Danielle B. Rice [verfasserIn] Linda Booij [verfasserIn] Andrea Benedetti [verfasserIn] Brett D. Thombs [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: International Journal of Methods in Psychiatric Research - Wiley, 2020, 31(2022), 2, Seite n/a-n/a |
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| Übergeordnetes Werk: |
volume:31 ; year:2022 ; number:2 ; pages:n/a-n/a |
| Links: |
Link aufrufen |
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| DOI / URN: |
10.1002/mpr.1910 |
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| Katalog-ID: |
DOAJ021274576 |
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| 520 | |a Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. | ||
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10.1002/mpr.1910 doi (DE-627)DOAJ021274576 (DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a DE-627 ger DE-627 rakwb eng RC321-571 Elsa‐Lynn Nassar verfasserin aut Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. bias depression diagnostic test accuracy sample size screening Neurosciences. Biological psychiatry. Neuropsychiatry Brooke Levis verfasserin aut Marieke A. Neyer verfasserin aut Danielle B. Rice verfasserin aut Linda Booij verfasserin aut Andrea Benedetti verfasserin aut Brett D. Thombs verfasserin aut In International Journal of Methods in Psychiatric Research Wiley, 2020 31(2022), 2, Seite n/a-n/a (DE-627)379051672 (DE-600)2135760-2 15570657 nnns volume:31 year:2022 number:2 pages:n/a-n/a https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/article/92a6ff28a1474ea1b1cdcbcf8f36c50a kostenfrei https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/toc/1049-8931 Journal toc kostenfrei https://doaj.org/toc/1557-0657 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 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_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_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 31 2022 2 n/a-n/a |
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10.1002/mpr.1910 doi (DE-627)DOAJ021274576 (DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a DE-627 ger DE-627 rakwb eng RC321-571 Elsa‐Lynn Nassar verfasserin aut Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. bias depression diagnostic test accuracy sample size screening Neurosciences. Biological psychiatry. Neuropsychiatry Brooke Levis verfasserin aut Marieke A. Neyer verfasserin aut Danielle B. Rice verfasserin aut Linda Booij verfasserin aut Andrea Benedetti verfasserin aut Brett D. Thombs verfasserin aut In International Journal of Methods in Psychiatric Research Wiley, 2020 31(2022), 2, Seite n/a-n/a (DE-627)379051672 (DE-600)2135760-2 15570657 nnns volume:31 year:2022 number:2 pages:n/a-n/a https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/article/92a6ff28a1474ea1b1cdcbcf8f36c50a kostenfrei https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/toc/1049-8931 Journal toc kostenfrei https://doaj.org/toc/1557-0657 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 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_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_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 31 2022 2 n/a-n/a |
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10.1002/mpr.1910 doi (DE-627)DOAJ021274576 (DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a DE-627 ger DE-627 rakwb eng RC321-571 Elsa‐Lynn Nassar verfasserin aut Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. bias depression diagnostic test accuracy sample size screening Neurosciences. Biological psychiatry. Neuropsychiatry Brooke Levis verfasserin aut Marieke A. Neyer verfasserin aut Danielle B. Rice verfasserin aut Linda Booij verfasserin aut Andrea Benedetti verfasserin aut Brett D. Thombs verfasserin aut In International Journal of Methods in Psychiatric Research Wiley, 2020 31(2022), 2, Seite n/a-n/a (DE-627)379051672 (DE-600)2135760-2 15570657 nnns volume:31 year:2022 number:2 pages:n/a-n/a https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/article/92a6ff28a1474ea1b1cdcbcf8f36c50a kostenfrei https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/toc/1049-8931 Journal toc kostenfrei https://doaj.org/toc/1557-0657 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 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_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_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 31 2022 2 n/a-n/a |
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10.1002/mpr.1910 doi (DE-627)DOAJ021274576 (DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a DE-627 ger DE-627 rakwb eng RC321-571 Elsa‐Lynn Nassar verfasserin aut Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. bias depression diagnostic test accuracy sample size screening Neurosciences. Biological psychiatry. Neuropsychiatry Brooke Levis verfasserin aut Marieke A. Neyer verfasserin aut Danielle B. Rice verfasserin aut Linda Booij verfasserin aut Andrea Benedetti verfasserin aut Brett D. Thombs verfasserin aut In International Journal of Methods in Psychiatric Research Wiley, 2020 31(2022), 2, Seite n/a-n/a (DE-627)379051672 (DE-600)2135760-2 15570657 nnns volume:31 year:2022 number:2 pages:n/a-n/a https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/article/92a6ff28a1474ea1b1cdcbcf8f36c50a kostenfrei https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/toc/1049-8931 Journal toc kostenfrei https://doaj.org/toc/1557-0657 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 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_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_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 31 2022 2 n/a-n/a |
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10.1002/mpr.1910 doi (DE-627)DOAJ021274576 (DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a DE-627 ger DE-627 rakwb eng RC321-571 Elsa‐Lynn Nassar verfasserin aut Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. bias depression diagnostic test accuracy sample size screening Neurosciences. Biological psychiatry. Neuropsychiatry Brooke Levis verfasserin aut Marieke A. Neyer verfasserin aut Danielle B. Rice verfasserin aut Linda Booij verfasserin aut Andrea Benedetti verfasserin aut Brett D. Thombs verfasserin aut In International Journal of Methods in Psychiatric Research Wiley, 2020 31(2022), 2, Seite n/a-n/a (DE-627)379051672 (DE-600)2135760-2 15570657 nnns volume:31 year:2022 number:2 pages:n/a-n/a https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/article/92a6ff28a1474ea1b1cdcbcf8f36c50a kostenfrei https://doi.org/10.1002/mpr.1910 kostenfrei https://doaj.org/toc/1049-8931 Journal toc kostenfrei https://doaj.org/toc/1557-0657 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 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_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_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 31 2022 2 n/a-n/a |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ021274576</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230307044948.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/mpr.1910</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ021274576</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC321-571</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Elsa‐Lynn Nassar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. 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Elsa‐Lynn Nassar |
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Elsa‐Lynn Nassar misc RC321-571 misc bias misc depression misc diagnostic test accuracy misc sample size misc screening misc Neurosciences. Biological psychiatry. Neuropsychiatry Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 |
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RC321-571 Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 bias depression diagnostic test accuracy sample size screening |
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misc RC321-571 misc bias misc depression misc diagnostic test accuracy misc sample size misc screening misc Neurosciences. Biological psychiatry. Neuropsychiatry |
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Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 |
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Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 |
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Elsa‐Lynn Nassar |
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International Journal of Methods in Psychiatric Research |
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10.1002/mpr.1910 |
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sample size and precision of estimates in studies of depression screening tool accuracy: a meta‐research review of studies published in 2018–2021 |
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RC321-571 |
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Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 |
| abstract |
Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. |
| abstractGer |
Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. |
| abstract_unstemmed |
Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. |
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Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ021274576</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230307044948.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/mpr.1910</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ021274576</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ92a6ff28a1474ea1b1cdcbcf8f36c50a</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC321-571</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Elsa‐Lynn Nassar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Sample size and precision of estimates in studies of depression screening tool accuracy: A meta‐research review of studies published in 2018–2021</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Objectives Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods MEDLINE was searched from January 1, 2018, through May 21, 2021. Results Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. 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