PMID- 31452524
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221007
IS  - 1929-0748 (Print)
IS  - 1929-0748 (Electronic)
IS  - 1929-0748 (Linking)
VI  - 8
IP  - 8
DP  - 2019 Aug 26
TI  - A Systematic Framework for Analyzing Patient-Generated Narrative Data: Protocol 
      for a Content Analysis.
PG  - 13914
LID - 10.2196/13914 [doi]
LID - e13914
AB  - BACKGROUND: Patient narrative data in online health care forums (communities) are 
      receiving increasing attention from the scientific community for implementing 
      patient-centered care. Natural language processing (NLP) methods are gaining more 
      and more attention because of the enormous data volume. However, state-of-the-art 
      NLP still cannot meet the need of high-resolution analysis of patients' 
      narratives. Manual qualitative analysis still plays a pivotal role in answering 
      complicated research questions from analyzing patient narratives. OBJECTIVE: This 
      study aimed to develop a systematic framework for qualitative analysis of 
      patient-generated narratives in online health care forums. METHODS: Our 
      systematic framework consists of 4 phases: (1) data collection, (2) data 
      preparation, (3) content analysis, and (4) interpretation of the results. Data 
      collection and data preparation phases are constructed based on text mining 
      methods for identifying appropriate online health forums for data collection, 
      differentiating posts of patients from other stakeholders, protecting patients' 
      privacy, sampling, and choosing the unit of analysis. Content analysis phase is 
      built on the framework method, which facilitates and accelerates the 
      identification of patterns and themes by an interdisciplinary research team. In 
      the end, the focus of interpretation of the results phase is to measure the data 
      quality and interpret the findings regarding the dimensions and aspects of 
      patients' experiences and concerns in their original contexts. RESULTS: We 
      demonstrated the usability of the proposed systematic framework using 2 case 
      studies: one on determining factors affecting patients' attitudes toward 
      antidepressants and another on identifying the disease management strategies in 
      patient with diabetes facing financial difficulties. The framework provides a 
      clear step-by-step process for systematic content analysis of patient narratives 
      and produces high-quality structured results that can be used for describing 
      patterns or regularities in patients' experiences, generating and testing 
      hypotheses, and identifying areas of improvement in the health care systems. 
      CONCLUSIONS: The systematic framework is a rigorous and standardized method for 
      qualitative analysis of patient narratives. Findings obtained through such a 
      process indicate authentic dimensions and aspects of patient experiences and shed 
      light on patients' concerns, needs, preferences, and values, which are the core 
      of patient-centered care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): 
      RR1-10.2196/13914.
CI  - (c)Maryam Zolnoori, Joyce E Balls-Berry, Tabetha A Brockman, Christi A Patten, Ming 
      Huang, Lixia Yao. Originally published in JMIR Research Protocols 
      (http://www.researchprotocols.org), 26.08.2019.
FAU - Zolnoori, Maryam
AU  - Zolnoori M
AUID- ORCID: 0000-0003-4484-2990
AD  - Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United 
      States.
FAU - Balls-Berry, Joyce E
AU  - Balls-Berry JE
AUID- ORCID: 0000-0003-3497-1115
AD  - Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United 
      States.
AD  - College of Medicine and Science, Mayo Clinic, Rochester, MN, United States.
FAU - Brockman, Tabetha A
AU  - Brockman TA
AUID- ORCID: 0000-0003-4008-4395
AD  - Community Engagement Program, Center for Clinical and Translational Science, Mayo 
      Clinic, Rochester, MN, United States.
AD  - Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United 
      States.
FAU - Patten, Christi A
AU  - Patten CA
AUID- ORCID: 0000-0002-7194-8160
AD  - Community Engagement Program, Center for Clinical and Translational Science, Mayo 
      Clinic, Rochester, MN, United States.
AD  - Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United 
      States.
FAU - Huang, Ming
AU  - Huang M
AUID- ORCID: 0000-0001-7367-3626
AD  - Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United 
      States.
FAU - Yao, Lixia
AU  - Yao L
AUID- ORCID: 0000-0002-5187-6120
AD  - Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United 
      States.
LA  - eng
GR  - TL1 TR002380/TR/NCATS NIH HHS/United States
PT  - Journal Article
DEP - 20190826
PL  - Canada
TA  - JMIR Res Protoc
JT  - JMIR research protocols
JID - 101599504
PMC - PMC6786846
OTO - NOTNLM
OT  - deductive approach
OT  - framework method
OT  - inductive approach
OT  - online social networking
OT  - patient-centered care
OT  - qualitative research
OT  - social media
OT  - text mining
COIS- Conflicts of Interest: None declared.
EDAT- 2019/08/28 06:00
MHDA- 2019/08/28 06:01
PMCR- 2019/08/26
CRDT- 2019/08/28 06:00
PHST- 2019/03/04 00:00 [received]
PHST- 2019/07/22 00:00 [accepted]
PHST- 2019/06/21 00:00 [revised]
PHST- 2019/08/28 06:00 [entrez]
PHST- 2019/08/28 06:00 [pubmed]
PHST- 2019/08/28 06:01 [medline]
PHST- 2019/08/26 00:00 [pmc-release]
AID - v8i8e13914 [pii]
AID - 10.2196/13914 [doi]
PST - epublish
SO  - JMIR Res Protoc. 2019 Aug 26;8(8):13914. doi: 10.2196/13914.