Shining the light on abortion: Drivers of online abortion searches across the United States in 2018.
CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associ...
Ausführliche Beschreibung
Autor*in: |
Sylvia Guendelman [verfasserIn] Elena Yon [verfasserIn] Elizabeth Pleasants [verfasserIn] Alan Hubbard [verfasserIn] Ndola Prata [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2020 |
---|
Übergeordnetes Werk: |
In: PLoS ONE - Public Library of Science (PLoS), 2007, 15(2020), 5, p e0231672 |
---|---|
Übergeordnetes Werk: |
volume:15 ; year:2020 ; number:5, p e0231672 |
Links: |
---|
DOI / URN: |
10.1371/journal.pone.0231672 |
---|
Katalog-ID: |
DOAJ075034530 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ075034530 | ||
003 | DE-627 | ||
005 | 20230309131751.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230228s2020 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1371/journal.pone.0231672 |2 doi | |
035 | |a (DE-627)DOAJ075034530 | ||
035 | |a (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 0 | |a Sylvia Guendelman |e verfasserin |4 aut | |
245 | 1 | 0 | |a Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. |
264 | 1 | |c 2020 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. | ||
653 | 0 | |a Medicine | |
653 | 0 | |a R | |
653 | 0 | |a Science | |
653 | 0 | |a Q | |
700 | 0 | |a Elena Yon |e verfasserin |4 aut | |
700 | 0 | |a Elizabeth Pleasants |e verfasserin |4 aut | |
700 | 0 | |a Alan Hubbard |e verfasserin |4 aut | |
700 | 0 | |a Ndola Prata |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t PLoS ONE |d Public Library of Science (PLoS), 2007 |g 15(2020), 5, p e0231672 |w (DE-627)523574592 |w (DE-600)2267670-3 |x 19326203 |7 nnns |
773 | 1 | 8 | |g volume:15 |g year:2020 |g number:5, p e0231672 |
856 | 4 | 0 | |u https://doi.org/10.1371/journal.pone.0231672 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe |z kostenfrei |
856 | 4 | 0 | |u https://doi.org/10.1371/journal.pone.0231672 |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/1932-6203 |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_31 | ||
912 | |a GBV_ILN_34 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_171 | ||
912 | |a GBV_ILN_206 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_224 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_235 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_702 | ||
912 | |a GBV_ILN_2001 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2005 | ||
912 | |a GBV_ILN_2006 | ||
912 | |a GBV_ILN_2008 | ||
912 | |a GBV_ILN_2009 | ||
912 | |a GBV_ILN_2010 | ||
912 | |a GBV_ILN_2011 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_2015 | ||
912 | |a GBV_ILN_2020 | ||
912 | |a GBV_ILN_2021 | ||
912 | |a GBV_ILN_2025 | ||
912 | |a GBV_ILN_2031 | ||
912 | |a GBV_ILN_2038 | ||
912 | |a GBV_ILN_2044 | ||
912 | |a GBV_ILN_2048 | ||
912 | |a GBV_ILN_2050 | ||
912 | |a GBV_ILN_2055 | ||
912 | |a GBV_ILN_2056 | ||
912 | |a GBV_ILN_2057 | ||
912 | |a GBV_ILN_2061 | ||
912 | |a GBV_ILN_2111 | ||
912 | |a GBV_ILN_2113 | ||
912 | |a GBV_ILN_2190 | ||
912 | |a GBV_ILN_2522 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4335 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 15 |j 2020 |e 5, p e0231672 |
author_variant |
s g sg e y ey e p ep a h ah n p np |
---|---|
matchkey_str |
article:19326203:2020----::hnnteihoaotodiesfniebrinerhsco |
hierarchy_sort_str |
2020 |
publishDate |
2020 |
allfields |
10.1371/journal.pone.0231672 doi (DE-627)DOAJ075034530 (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe DE-627 ger DE-627 rakwb eng Sylvia Guendelman verfasserin aut Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. Medicine R Science Q Elena Yon verfasserin aut Elizabeth Pleasants verfasserin aut Alan Hubbard verfasserin aut Ndola Prata verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 15(2020), 5, p e0231672 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:15 year:2020 number:5, p e0231672 https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe kostenfrei https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_95 GBV_ILN_105 GBV_ILN_110 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_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2020 5, p e0231672 |
spelling |
10.1371/journal.pone.0231672 doi (DE-627)DOAJ075034530 (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe DE-627 ger DE-627 rakwb eng Sylvia Guendelman verfasserin aut Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. Medicine R Science Q Elena Yon verfasserin aut Elizabeth Pleasants verfasserin aut Alan Hubbard verfasserin aut Ndola Prata verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 15(2020), 5, p e0231672 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:15 year:2020 number:5, p e0231672 https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe kostenfrei https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_95 GBV_ILN_105 GBV_ILN_110 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_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2020 5, p e0231672 |
allfields_unstemmed |
10.1371/journal.pone.0231672 doi (DE-627)DOAJ075034530 (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe DE-627 ger DE-627 rakwb eng Sylvia Guendelman verfasserin aut Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. Medicine R Science Q Elena Yon verfasserin aut Elizabeth Pleasants verfasserin aut Alan Hubbard verfasserin aut Ndola Prata verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 15(2020), 5, p e0231672 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:15 year:2020 number:5, p e0231672 https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe kostenfrei https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_95 GBV_ILN_105 GBV_ILN_110 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_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2020 5, p e0231672 |
allfieldsGer |
10.1371/journal.pone.0231672 doi (DE-627)DOAJ075034530 (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe DE-627 ger DE-627 rakwb eng Sylvia Guendelman verfasserin aut Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. Medicine R Science Q Elena Yon verfasserin aut Elizabeth Pleasants verfasserin aut Alan Hubbard verfasserin aut Ndola Prata verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 15(2020), 5, p e0231672 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:15 year:2020 number:5, p e0231672 https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe kostenfrei https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_95 GBV_ILN_105 GBV_ILN_110 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_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2020 5, p e0231672 |
allfieldsSound |
10.1371/journal.pone.0231672 doi (DE-627)DOAJ075034530 (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe DE-627 ger DE-627 rakwb eng Sylvia Guendelman verfasserin aut Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. Medicine R Science Q Elena Yon verfasserin aut Elizabeth Pleasants verfasserin aut Alan Hubbard verfasserin aut Ndola Prata verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 15(2020), 5, p e0231672 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:15 year:2020 number:5, p e0231672 https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe kostenfrei https://doi.org/10.1371/journal.pone.0231672 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_95 GBV_ILN_105 GBV_ILN_110 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_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2020 5, p e0231672 |
language |
English |
source |
In PLoS ONE 15(2020), 5, p e0231672 volume:15 year:2020 number:5, p e0231672 |
sourceStr |
In PLoS ONE 15(2020), 5, p e0231672 volume:15 year:2020 number:5, p e0231672 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Medicine R Science Q |
isfreeaccess_bool |
true |
container_title |
PLoS ONE |
authorswithroles_txt_mv |
Sylvia Guendelman @@aut@@ Elena Yon @@aut@@ Elizabeth Pleasants @@aut@@ Alan Hubbard @@aut@@ Ndola Prata @@aut@@ |
publishDateDaySort_date |
2020-01-01T00:00:00Z |
hierarchy_top_id |
523574592 |
id |
DOAJ075034530 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ075034530</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309131751.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1371/journal.pone.0231672</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ075034530</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe</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="100" ind1="0" ind2=" "><subfield code="a">Sylvia Guendelman</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Shining the light on abortion: Drivers of online abortion searches across the United States in 2018.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</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">CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches.</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Q</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elena Yon</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elizabeth Pleasants</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alan Hubbard</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ndola Prata</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">PLoS ONE</subfield><subfield code="d">Public Library of Science (PLoS), 2007</subfield><subfield code="g">15(2020), 5, p e0231672</subfield><subfield code="w">(DE-627)523574592</subfield><subfield code="w">(DE-600)2267670-3</subfield><subfield code="x">19326203</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:15</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:5, p e0231672</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1371/journal.pone.0231672</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1371/journal.pone.0231672</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1932-6203</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_34</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_235</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">15</subfield><subfield code="j">2020</subfield><subfield code="e">5, p e0231672</subfield></datafield></record></collection>
|
author |
Sylvia Guendelman |
spellingShingle |
Sylvia Guendelman misc Medicine misc R misc Science misc Q Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. |
authorStr |
Sylvia Guendelman |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)523574592 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
19326203 |
topic_title |
Shining the light on abortion: Drivers of online abortion searches across the United States in 2018 |
topic |
misc Medicine misc R misc Science misc Q |
topic_unstemmed |
misc Medicine misc R misc Science misc Q |
topic_browse |
misc Medicine misc R misc Science misc Q |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
PLoS ONE |
hierarchy_parent_id |
523574592 |
hierarchy_top_title |
PLoS ONE |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)523574592 (DE-600)2267670-3 |
title |
Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. |
ctrlnum |
(DE-627)DOAJ075034530 (DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe |
title_full |
Shining the light on abortion: Drivers of online abortion searches across the United States in 2018 |
author_sort |
Sylvia Guendelman |
journal |
PLoS ONE |
journalStr |
PLoS ONE |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2020 |
contenttype_str_mv |
txt |
author_browse |
Sylvia Guendelman Elena Yon Elizabeth Pleasants Alan Hubbard Ndola Prata |
container_volume |
15 |
format_se |
Elektronische Aufsätze |
author-letter |
Sylvia Guendelman |
doi_str_mv |
10.1371/journal.pone.0231672 |
author2-role |
verfasserin |
title_sort |
shining the light on abortion: drivers of online abortion searches across the united states in 2018 |
title_auth |
Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. |
abstract |
CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. |
abstractGer |
CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. |
abstract_unstemmed |
CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_95 GBV_ILN_105 GBV_ILN_110 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_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
container_issue |
5, p e0231672 |
title_short |
Shining the light on abortion: Drivers of online abortion searches across the United States in 2018. |
url |
https://doi.org/10.1371/journal.pone.0231672 https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe https://doaj.org/toc/1932-6203 |
remote_bool |
true |
author2 |
Elena Yon Elizabeth Pleasants Alan Hubbard Ndola Prata |
author2Str |
Elena Yon Elizabeth Pleasants Alan Hubbard Ndola Prata |
ppnlink |
523574592 |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.1371/journal.pone.0231672 |
up_date |
2024-07-04T01:35:33.892Z |
_version_ |
1803610419535806464 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ075034530</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309131751.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1371/journal.pone.0231672</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ075034530</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJfad7b50a1efb45d2a9fb12ada4322cfe</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="100" ind1="0" ind2=" "><subfield code="a">Sylvia Guendelman</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Shining the light on abortion: Drivers of online abortion searches across the United States in 2018.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</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">CONTEXT:Legal abortion restrictions, stigma and fear can inhibit people's voices in clinical and social settings posing barriers to decision-making and abortion care. The internet allows individuals to make informed decisions privately. We explored what state-level policy dimensions were associated with volume of Google searches on abortion and on the abortion pill in 2018. METHODS:We used Google Trends to quantify the relative search volume (RSV) for "abortion" and "abortion pill" (or "abortion pills" hereafter referred to as "abortion pill") as a proportion of total search volume for all queries in each US state. We also identified the top search queries most related to "abortion" and "abortion pill" and considered these as indicators of population concern. Key exposures were healthcare cost, access and health outcomes, and number of legal restrictions and protections at the state level. In descriptive analyses, we first grouped the states into tertiles according to their RSV on "abortion" and "abortion pill". To examine the association between each exposure (and other covariates) with the two outcomes, we used unadjusted and adjusted linear regression. RESULTS:The average RSV for "abortion" in the low, moderate and high tertile groups was 48 (SD = 3.25), 55.5 (SD = 2.11) and 64 (SD = 4.72) (p-value <0.01) respectively; for "abortion pill" the average RSVs were 39.6 (SD = 16.68), 61.9 (SD = 5.82) and 81.7 (SD = 6.67) (p-value < 0.01) respectively. Concerns about contraceptive availability and access, and unplanned pregnancies independently predicted the relative search volumes for abortion and abortion pill. According to our baseline models, states with low contraceptive access had far higher abortion searches. Volume of abortion pill searches was additionally positively associated with poor health outcomes, poor access to abortion facilities and non-rurality. CONCLUSION:Search traffic analysis can help discern abortion-policy influences on population concerns and require close monitoring. State-policies can predict search volume for abortion and abortion pill. In 2018, concerns about contraceptives and unplanned pregnancies, predicted abortion searches. Current decreases in public contraceptive funding and the Title X Gag rule designed to block millions of people from getting care at Planned Parenthood, the largest provider of birth control and abortion care, may increase concerns about unintended pregnancies that can lead to increases in online relative volume of abortion searches.</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Q</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elena Yon</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elizabeth Pleasants</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Alan Hubbard</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ndola Prata</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">PLoS ONE</subfield><subfield code="d">Public Library of Science (PLoS), 2007</subfield><subfield code="g">15(2020), 5, p e0231672</subfield><subfield code="w">(DE-627)523574592</subfield><subfield code="w">(DE-600)2267670-3</subfield><subfield code="x">19326203</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:15</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:5, p e0231672</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1371/journal.pone.0231672</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/fad7b50a1efb45d2a9fb12ada4322cfe</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1371/journal.pone.0231672</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1932-6203</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_34</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_235</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">15</subfield><subfield code="j">2020</subfield><subfield code="e">5, p e0231672</subfield></datafield></record></collection>
|
score |
7.401638 |