Cargando…

Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

BACKGROUND: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD...

Descripción completa

Detalles Bibliográficos
Autores principales: Campbell, Cynthia I, Chen, Ching-Hua, Adams, Sara R, Asyyed, Asma, Athale, Ninad R, Does, Monique B, Hassanpour, Saeed, Hichborn, Emily, Jackson-Morris, Melanie, Jacobson, Nicholas C, Jones, Heather K, Kotz, David, Lambert-Harris, Chantal A, Li, Zhiguo, McLeman, Bethany, Mishra, Varun, Stanger, Catherine, Subramaniam, Geetha, Wu, Weiyi, Zegers, Christopher, Marsch, Lisa A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337375/
https://www.ncbi.nlm.nih.gov/pubmed/37310787
http://dx.doi.org/10.2196/45556
_version_ 1785071409558454272
author Campbell, Cynthia I
Chen, Ching-Hua
Adams, Sara R
Asyyed, Asma
Athale, Ninad R
Does, Monique B
Hassanpour, Saeed
Hichborn, Emily
Jackson-Morris, Melanie
Jacobson, Nicholas C
Jones, Heather K
Kotz, David
Lambert-Harris, Chantal A
Li, Zhiguo
McLeman, Bethany
Mishra, Varun
Stanger, Catherine
Subramaniam, Geetha
Wu, Weiyi
Zegers, Christopher
Marsch, Lisa A
author_facet Campbell, Cynthia I
Chen, Ching-Hua
Adams, Sara R
Asyyed, Asma
Athale, Ninad R
Does, Monique B
Hassanpour, Saeed
Hichborn, Emily
Jackson-Morris, Melanie
Jacobson, Nicholas C
Jones, Heather K
Kotz, David
Lambert-Harris, Chantal A
Li, Zhiguo
McLeman, Bethany
Mishra, Varun
Stanger, Catherine
Subramaniam, Geetha
Wu, Weiyi
Zegers, Christopher
Marsch, Lisa A
author_sort Campbell, Cynthia I
collection PubMed
description BACKGROUND: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. OBJECTIVE: The aim is to examine patient engagement with multiple digital phenotyping methods among patients receiving buprenorphine medication for OUD. METHODS: The study enrolled 65 patients receiving buprenorphine for OUD between June 2020 and January 2021 from 4 addiction medicine programs in an integrated health care delivery system in Northern California. Ecological momentary assessment (EMA), sensor data, and social media data were collected by smartphone, smartwatch, and social media platforms over a 12-week period. Primary engagement outcomes were meeting measures of minimum phone carry (≥8 hours per day) and watch wear (≥18 hours per day) criteria, EMA response rates, social media consent rate, and data sparsity. Descriptive analyses, bivariate, and trend tests were performed. RESULTS: The participants’ average age was 37 years, 47% of them were female, and 71% of them were White. On average, participants met phone carrying criteria on 94% of study days, met watch wearing criteria on 74% of days, and wore the watch to sleep on 77% of days. The mean EMA response rate was 70%, declining from 83% to 56% from week 1 to week 12. Among participants with social media accounts, 88% of them consented to providing data; of them, 55% of Facebook, 54% of Instagram, and 57% of Twitter participants provided data. The amount of social media data available varied widely across participants. No differences by age, sex, race, or ethnicity were observed for any outcomes. CONCLUSIONS: To our knowledge, this is the first study to capture these 3 digital data sources in this clinical population. Our findings demonstrate that patients receiving buprenorphine treatment for OUD had generally high engagement with multiple digital phenotyping data sources, but this was more limited for the social media data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fpsyt.2022.871916
format Online
Article
Text
id pubmed-10337375
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-103373752023-07-13 Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder Campbell, Cynthia I Chen, Ching-Hua Adams, Sara R Asyyed, Asma Athale, Ninad R Does, Monique B Hassanpour, Saeed Hichborn, Emily Jackson-Morris, Melanie Jacobson, Nicholas C Jones, Heather K Kotz, David Lambert-Harris, Chantal A Li, Zhiguo McLeman, Bethany Mishra, Varun Stanger, Catherine Subramaniam, Geetha Wu, Weiyi Zegers, Christopher Marsch, Lisa A J Med Internet Res Original Paper BACKGROUND: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. OBJECTIVE: The aim is to examine patient engagement with multiple digital phenotyping methods among patients receiving buprenorphine medication for OUD. METHODS: The study enrolled 65 patients receiving buprenorphine for OUD between June 2020 and January 2021 from 4 addiction medicine programs in an integrated health care delivery system in Northern California. Ecological momentary assessment (EMA), sensor data, and social media data were collected by smartphone, smartwatch, and social media platforms over a 12-week period. Primary engagement outcomes were meeting measures of minimum phone carry (≥8 hours per day) and watch wear (≥18 hours per day) criteria, EMA response rates, social media consent rate, and data sparsity. Descriptive analyses, bivariate, and trend tests were performed. RESULTS: The participants’ average age was 37 years, 47% of them were female, and 71% of them were White. On average, participants met phone carrying criteria on 94% of study days, met watch wearing criteria on 74% of days, and wore the watch to sleep on 77% of days. The mean EMA response rate was 70%, declining from 83% to 56% from week 1 to week 12. Among participants with social media accounts, 88% of them consented to providing data; of them, 55% of Facebook, 54% of Instagram, and 57% of Twitter participants provided data. The amount of social media data available varied widely across participants. No differences by age, sex, race, or ethnicity were observed for any outcomes. CONCLUSIONS: To our knowledge, this is the first study to capture these 3 digital data sources in this clinical population. Our findings demonstrate that patients receiving buprenorphine treatment for OUD had generally high engagement with multiple digital phenotyping data sources, but this was more limited for the social media data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fpsyt.2022.871916 JMIR Publications 2023-06-13 /pmc/articles/PMC10337375/ /pubmed/37310787 http://dx.doi.org/10.2196/45556 Text en ©Cynthia I Campbell, Ching-Hua Chen, Sara R Adams, Asma Asyyed, Ninad R Athale, Monique B Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C Jacobson, Heather K Jones, David Kotz, Chantal A Lambert-Harris, Zhiguo Li, Bethany McLeman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Christopher Zegers, Lisa A Marsch. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.06.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Campbell, Cynthia I
Chen, Ching-Hua
Adams, Sara R
Asyyed, Asma
Athale, Ninad R
Does, Monique B
Hassanpour, Saeed
Hichborn, Emily
Jackson-Morris, Melanie
Jacobson, Nicholas C
Jones, Heather K
Kotz, David
Lambert-Harris, Chantal A
Li, Zhiguo
McLeman, Bethany
Mishra, Varun
Stanger, Catherine
Subramaniam, Geetha
Wu, Weiyi
Zegers, Christopher
Marsch, Lisa A
Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder
title Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder
title_full Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder
title_fullStr Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder
title_full_unstemmed Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder
title_short Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder
title_sort patient engagement in a multimodal digital phenotyping study of opioid use disorder
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337375/
https://www.ncbi.nlm.nih.gov/pubmed/37310787
http://dx.doi.org/10.2196/45556
work_keys_str_mv AT campbellcynthiai patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT chenchinghua patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT adamssarar patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT asyyedasma patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT athaleninadr patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT doesmoniqueb patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT hassanpoursaeed patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT hichbornemily patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT jacksonmorrismelanie patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT jacobsonnicholasc patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT jonesheatherk patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT kotzdavid patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT lambertharrischantala patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT lizhiguo patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT mclemanbethany patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT mishravarun patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT stangercatherine patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT subramaniamgeetha patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT wuweiyi patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT zegerschristopher patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder
AT marschlisaa patientengagementinamultimodaldigitalphenotypingstudyofopioidusedisorder