Journal
JAMA Network Open
Publication Date
8-1-2022
Volume
5
Issue
8
First Page
e2229091
Document Type
Open Access Publication
DOI
10.1001/jamanetworkopen.2022.29091
Rights and Permissions
Kerkhoff AD, Chilukutu L, Nyangu S, Kagujje M, Mateyo K, Sanjase N, Eshun-Wilson I, Geng EH, Havlir DV, Muyoyeta M. Patient Preferences for Strategies to Improve Tuberculosis Diagnostic Services in Zambia. JAMA Netw Open. 2022 Aug 1;5(8):e2229091. doi: 10.1001/jamanetworkopen.2022.29091. This is an open access article distributed under the terms of the CC-BY License.
Recommended Citation
Kerkhoff, Andrew D; Chilukutu, Lophina; Nyangu, Sarah; Kagujje, Mary; Mateyo, Kondwelani; Sanjase, Nsala; Eshun-Wilson, Ingrid; Geng, Elvin H; Havlir, Diane V; and Muyoyeta, Monde, "Patient preferences for strategies to improve tuberculosis diagnostic services in Zambia." JAMA Network Open. 5, 8. e2229091 (2022).
https://digitalcommons.wustl.edu/oa_4/536
eMethods 1. Description of Data Cleaning Procedures Undertaken to Improve the Quality of Individual-Level Respondent Data eMethods 2. Description of Latent Class Analysis Procedures for Identifying Distinct Preference Groups eMethods 3. Description of Hierarchical Bayes Analysis Procedures for Estimating Preference Weights eMethods 4. Description of Simulation Procedures for Estimating Shares of Preference eTable 1. Indices of Statistical Fit for Latent Class Solutions (2 to 5) for Identifying Groups of Tuberculosis Patients With Distinct Preferences Based on Discrete Choice Experiment Results eTable 2. Evaluation of Sociodemographic Characteristics and Health-Seeking Behaviors According to Whether the Participants Were Included in the Final Data Analysis (N=401) eTable 3. Health Influences According to Latent Class Preference Group (N=326) eTable 4. Simulated Shares of Preference (%) for a Health Facility Offering at Least One Enhanced Service Feature Under Three Different Implementation Scenarios According to Latent Class Preference Group* eTable 5. Simulated Shares of Preference Using Two Different Models for a Health Facility Offering at Least One Enhanced Service Feature Using Two Different Estimation Methods According to Latent Class Preference Group eReference
