Cargando…

Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa

BACKGROUND: Integration of depression treatment into primary care could improve patient outcomes in low-resource settings. Losses along the depression care cascade limit integrated service effectiveness. This study identified patient-level factors that predicted detection of depressive symptoms by n...

Descripción completa

Detalles Bibliográficos
Autores principales: Kemp, Christopher G., Mntambo, Ntokozo, Bachmann, Max, Bhana, Arvin, Rao, Deepa, Grant, Merridy, Hughes, James P., Simoni, Jane M., Weiner, Bryan J., Gigaba, Sithabisile Gugulethu, Luvuno, Zamasomi Prudence Busisiwe, Petersen, Inge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443607/
https://www.ncbi.nlm.nih.gov/pubmed/32913657
http://dx.doi.org/10.1017/gmh.2020.11
_version_ 1783573658214596608
author Kemp, Christopher G.
Mntambo, Ntokozo
Bachmann, Max
Bhana, Arvin
Rao, Deepa
Grant, Merridy
Hughes, James P.
Simoni, Jane M.
Weiner, Bryan J.
Gigaba, Sithabisile Gugulethu
Luvuno, Zamasomi Prudence Busisiwe
Petersen, Inge
author_facet Kemp, Christopher G.
Mntambo, Ntokozo
Bachmann, Max
Bhana, Arvin
Rao, Deepa
Grant, Merridy
Hughes, James P.
Simoni, Jane M.
Weiner, Bryan J.
Gigaba, Sithabisile Gugulethu
Luvuno, Zamasomi Prudence Busisiwe
Petersen, Inge
author_sort Kemp, Christopher G.
collection PubMed
description BACKGROUND: Integration of depression treatment into primary care could improve patient outcomes in low-resource settings. Losses along the depression care cascade limit integrated service effectiveness. This study identified patient-level factors that predicted detection of depressive symptoms by nurses, referral for depression treatment, and uptake of counseling, as part of integrated care in KwaZulu-Natal, South Africa. METHODS: This was an analysis of baseline data from a prospective cohort. Participants were adult patients with at least moderate depressive symptoms at primary care facilities in Amajuba, KwaZulu-Natal, South Africa. Participants were screened for depressive symptoms prior to routine assessment by a nurse. Generalized linear mixed-effects models were used to estimate associations between patient characteristics and service delivery outcomes. RESULTS: Data from 412 participants were analyzed. Nurses successfully detected depressive symptoms in 208 [50.5%, 95% confidence interval (CI) 38.9–62.0] participants; of these, they referred 76 (36.5%, 95% CI 20.3–56.5) for depression treatment; of these, 18 (23.7%, 95% CI 10.7–44.6) attended at least one session of depression counseling. Depressive symptom severity, alcohol use severity, and perceived stress were associated with detection. Similar factors did not drive referral or counseling uptake. CONCLUSIONS: Nurses detected patients with depressive symptoms at rates comparable to primary care providers in high-resource settings, though gaps in referral and uptake persist. Nurses were more likely to detect symptoms among patients in more severe mental distress. Implementation strategies for integrated mental health care in low-resource settings should target improved rates of detection, referral, and uptake.
format Online
Article
Text
id pubmed-7443607
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Cambridge University Press
record_format MEDLINE/PubMed
spelling pubmed-74436072020-09-09 Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa Kemp, Christopher G. Mntambo, Ntokozo Bachmann, Max Bhana, Arvin Rao, Deepa Grant, Merridy Hughes, James P. Simoni, Jane M. Weiner, Bryan J. Gigaba, Sithabisile Gugulethu Luvuno, Zamasomi Prudence Busisiwe Petersen, Inge Glob Ment Health (Camb) Original Research Paper BACKGROUND: Integration of depression treatment into primary care could improve patient outcomes in low-resource settings. Losses along the depression care cascade limit integrated service effectiveness. This study identified patient-level factors that predicted detection of depressive symptoms by nurses, referral for depression treatment, and uptake of counseling, as part of integrated care in KwaZulu-Natal, South Africa. METHODS: This was an analysis of baseline data from a prospective cohort. Participants were adult patients with at least moderate depressive symptoms at primary care facilities in Amajuba, KwaZulu-Natal, South Africa. Participants were screened for depressive symptoms prior to routine assessment by a nurse. Generalized linear mixed-effects models were used to estimate associations between patient characteristics and service delivery outcomes. RESULTS: Data from 412 participants were analyzed. Nurses successfully detected depressive symptoms in 208 [50.5%, 95% confidence interval (CI) 38.9–62.0] participants; of these, they referred 76 (36.5%, 95% CI 20.3–56.5) for depression treatment; of these, 18 (23.7%, 95% CI 10.7–44.6) attended at least one session of depression counseling. Depressive symptom severity, alcohol use severity, and perceived stress were associated with detection. Similar factors did not drive referral or counseling uptake. CONCLUSIONS: Nurses detected patients with depressive symptoms at rates comparable to primary care providers in high-resource settings, though gaps in referral and uptake persist. Nurses were more likely to detect symptoms among patients in more severe mental distress. Implementation strategies for integrated mental health care in low-resource settings should target improved rates of detection, referral, and uptake. Cambridge University Press 2020-07-21 /pmc/articles/PMC7443607/ /pubmed/32913657 http://dx.doi.org/10.1017/gmh.2020.11 Text en © The Author(s) 2020 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Paper
Kemp, Christopher G.
Mntambo, Ntokozo
Bachmann, Max
Bhana, Arvin
Rao, Deepa
Grant, Merridy
Hughes, James P.
Simoni, Jane M.
Weiner, Bryan J.
Gigaba, Sithabisile Gugulethu
Luvuno, Zamasomi Prudence Busisiwe
Petersen, Inge
Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa
title Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa
title_full Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa
title_fullStr Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa
title_full_unstemmed Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa
title_short Patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in KwaZulu-Natal, South Africa
title_sort patient-level predictors of detection of depressive symptoms, referral, and uptake of depression counseling among chronic care patients in kwazulu-natal, south africa
topic Original Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443607/
https://www.ncbi.nlm.nih.gov/pubmed/32913657
http://dx.doi.org/10.1017/gmh.2020.11
work_keys_str_mv AT kempchristopherg patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT mntambontokozo patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT bachmannmax patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT bhanaarvin patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT raodeepa patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT grantmerridy patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT hughesjamesp patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT simonijanem patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT weinerbryanj patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT gigabasithabisilegugulethu patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT luvunozamasomiprudencebusisiwe patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica
AT peterseninge patientlevelpredictorsofdetectionofdepressivesymptomsreferralanduptakeofdepressioncounselingamongchroniccarepatientsinkwazulunatalsouthafrica