Simple scoring algorithm to identify community-dwelling older adults with limited health literacy: a cross-sectional study in Taiwan

ObjectiveHealth literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make appropriate health decisions. This study aimed to establish a predictive algorithm for identifying community-dwelling older adults with a hi...

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Published inBMJ open Vol. 11; no. 11; p. e045411
Main Authors Hou, Wen-Hsuan, Kuo, Ken N, Chen, Mu-Jean, Chang, Yao-Mao, Tsai, Han-Wei, Chan, Ding-Cheng, Su, Chien-Tien, Han, Der-Sheng, Shen, Hsiu-Nien, Li, Chung-Yi
Format Journal Article
LanguageEnglish
Published London British Medical Journal Publishing Group 25.11.2021
BMJ Publishing Group LTD
BMJ Publishing Group
SeriesOriginal research
Subjects
Algorithms
Consortia
Cross-sectional studies
Datasets
Empowerment
Health behavior
Health education
health informatics
Health literacy
Health services
health services administration & management
Interviews
Older people
Participation
Public Health
Questionnaires
Taiwan
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Abstract ObjectiveHealth literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make appropriate health decisions. This study aimed to establish a predictive algorithm for identifying community-dwelling older adults with a high risk of limited HL.DesignA cross-sectional study.SettingFour communities in northern, central and southern Taiwan.ParticipantsA total of 648 older adults were included. Moreover, 85% of the core data set was used to generate the prediction model for the scoring algorithm, and 15% was used to test the fitness of the model.Primary and secondary outcome measuresPearson’s χ2 test and multiple logistic regression were used to identify the significant factors associated with the HL level. An optimal cut-off point for the scoring algorithm was identified on the basis of the maximum sensitivity and specificity.ResultsA total of 350 (54.6%) patients were classified as having limited HL. We identified 24 variables that could significantly differentiate between sufficient and limited HL. Eight factors that could significantly predict limited HL were identified as follows: a socioenvironmental determinant (ie, dominant spoken dialect), a health service use factor (ie, having family doctors), a health cost factor (ie, self-paid vaccination), a heath behaviour factor (ie, searching online health information), two health outcomes (ie, difficulty in performing activities of daily living and requiring assistance while visiting doctors), a participation factor (ie, attending health classes) and an empowerment factor (ie, self-management during illness). The scoring algorithm yielded an area under the curve of 0.71, and an optimal cut-off value of 5 represented moderate sensitivity (62.0%) and satisfactory specificity (76.2%).ConclusionThis simple scoring algorithm can efficiently and effectively identify community-dwelling older adults with a high risk of limited HL.
AbstractList ObjectiveHealth literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make appropriate health decisions. This study aimed to establish a predictive algorithm for identifying community-dwelling older adults with a high risk of limited HL.DesignA cross-sectional study.SettingFour communities in northern, central and southern Taiwan.ParticipantsA total of 648 older adults were included. Moreover, 85% of the core data set was used to generate the prediction model for the scoring algorithm, and 15% was used to test the fitness of the model.Primary and secondary outcome measuresPearson’s χ2 test and multiple logistic regression were used to identify the significant factors associated with the HL level. An optimal cut-off point for the scoring algorithm was identified on the basis of the maximum sensitivity and specificity.ResultsA total of 350 (54.6%) patients were classified as having limited HL. We identified 24 variables that could significantly differentiate between sufficient and limited HL. Eight factors that could significantly predict limited HL were identified as follows: a socioenvironmental determinant (ie, dominant spoken dialect), a health service use factor (ie, having family doctors), a health cost factor (ie, self-paid vaccination), a heath behaviour factor (ie, searching online health information), two health outcomes (ie, difficulty in performing activities of daily living and requiring assistance while visiting doctors), a participation factor (ie, attending health classes) and an empowerment factor (ie, self-management during illness). The scoring algorithm yielded an area under the curve of 0.71, and an optimal cut-off value of 5 represented moderate sensitivity (62.0%) and satisfactory specificity (76.2%).ConclusionThis simple scoring algorithm can efficiently and effectively identify community-dwelling older adults with a high risk of limited HL.
Objective Health literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make appropriate health decisions. This study aimed to establish a predictive algorithm for identifying community-dwelling older adults with a high risk of limited HL. Design A cross-sectional study. Setting Four communities in northern, central and southern Taiwan. Participants A total of 648 older adults were included. Moreover, 85% of the core data set was used to generate the prediction model for the scoring algorithm, and 15% was used to test the fitness of the model. Primary and secondary outcome measures Pearson’s χ 2 test and multiple logistic regression were used to identify the significant factors associated with the HL level. An optimal cut-off point for the scoring algorithm was identified on the basis of the maximum sensitivity and specificity. Results A total of 350 (54.6%) patients were classified as having limited HL. We identified 24 variables that could significantly differentiate between sufficient and limited HL. Eight factors that could significantly predict limited HL were identified as follows: a socioenvironmental determinant (ie, dominant spoken dialect), a health service use factor (ie, having family doctors), a health cost factor (ie, self-paid vaccination), a heath behaviour factor (ie, searching online health information), two health outcomes (ie, difficulty in performing activities of daily living and requiring assistance while visiting doctors), a participation factor (ie, attending health classes) and an empowerment factor (ie, self-management during illness). The scoring algorithm yielded an area under the curve of 0.71, and an optimal cut-off value of 5 represented moderate sensitivity (62.0%) and satisfactory specificity (76.2%). Conclusion This simple scoring algorithm can efficiently and effectively identify community-dwelling older adults with a high risk of limited HL.
Objective Health literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make appropriate health decisions. This study aimed to establish a predictive algorithm for identifying community-dwelling older adults with a high risk of limited HL.Design A cross-sectional study.Setting Four communities in northern, central and southern Taiwan.Participants A total of 648 older adults were included. Moreover, 85% of the core data set was used to generate the prediction model for the scoring algorithm, and 15% was used to test the fitness of the model.Primary and secondary outcome measures Pearson’s χ2 test and multiple logistic regression were used to identify the significant factors associated with the HL level. An optimal cut-off point for the scoring algorithm was identified on the basis of the maximum sensitivity and specificity.Results A total of 350 (54.6%) patients were classified as having limited HL. We identified 24 variables that could significantly differentiate between sufficient and limited HL. Eight factors that could significantly predict limited HL were identified as follows: a socioenvironmental determinant (ie, dominant spoken dialect), a health service use factor (ie, having family doctors), a health cost factor (ie, self-paid vaccination), a heath behaviour factor (ie, searching online health information), two health outcomes (ie, difficulty in performing activities of daily living and requiring assistance while visiting doctors), a participation factor (ie, attending health classes) and an empowerment factor (ie, self-management during illness). The scoring algorithm yielded an area under the curve of 0.71, and an optimal cut-off value of 5 represented moderate sensitivity (62.0%) and satisfactory specificity (76.2%).Conclusion This simple scoring algorithm can efficiently and effectively identify community-dwelling older adults with a high risk of limited HL.
Author Chen, Mu-Jean
Hou, Wen-Hsuan
Kuo, Ken N
Su, Chien-Tien
Shen, Hsiu-Nien
Chan, Ding-Cheng
Li, Chung-Yi
Han, Der-Sheng
Tsai, Han-Wei
Chang, Yao-Mao
AuthorAffiliation 8 School of Health Care Administration , Taipei Medical University , Taipei , Taiwan
3 Cochrane Taiwan , Taipei Medical University , Taipei , Taiwan
12 School of Public Health, College of Public Health , Taipei Medical University , Taipei , Taiwan
9 Department of Geriatrics and Gerontology , National Taiwan University Hospital , Taipei , Taiwan
11 Department of Family Medicine , Taipei Medical University Hospital , Taipei , Taiwan
10 Superintendent Office , National Taiwan University Hospital Chutung Branch , Hsinchu , Taiwan
14 Department of Physical Medicine and Rehabilitation , National Taiwan University Hospital Beihu Branch , Taipei , Taiwan
18 Faculty of Public Health, Department of Epidemiology , Universitas Airlangga , Surabaya , Indonesia
13 Department of Family Medicine, School of Medicine, College of Medicine , Taipei Medical University , Taipei , Taiwan
15 Health Science and Wellness Center , National Taiwan University , Taipei , Taiwan
2 Department of Geriatric Medicine & Physical M
AuthorAffiliation_xml – name: 19 Department of Public Health, College of Public Health , China Medical University , Taichung , Taiwan
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crossref_primary_10_1016_j_gerinurse_2023_11_016
crossref_primary_10_1136_bmjopen_2023_075693
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2024102804524989000_11.11.e045411.16
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2024102804524989000_11.11.e045411.32
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2024102804524989000_11.11.e045411.30
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2024102804524989000_11.11.e045411.31
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2024102804524989000_11.11.e045411.25
2024102804524989000_11.11.e045411.47
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  publication-title: Arch Gerontol Geriatr
  doi: 10.1016/j.archger.2015.06.015
  contributor:
    fullname: Chung
– volume: 30
  start-page: 197
  year: 2017
  ident: 2024102804524989000_11.11.e045411.14
  article-title: Examining the impacts of health literacy on healthcare costs. An evidence synthesis
  publication-title: Health Serv Manage Res
  doi: 10.1177/0951484817733366
  contributor:
    fullname: Palumbo
– ident: 2024102804524989000_11.11.e045411.24
  doi: 10.1186/1471-2458-13-179
– ident: 2024102804524989000_11.11.e045411.29
  doi: 10.1161/CIRCULATIONAHA.107.697714
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Snippet ObjectiveHealth literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to make...
Objective Health literacy (HL) is the degree of individuals’ capacity to access, understand, appraise and apply health information and services required to...
OBJECTIVEHealth literacy (HL) is the degree of individuals' capacity to access, understand, appraise and apply health information and services required to make...
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SubjectTerms Algorithms
Consortia
Cross-sectional studies
Datasets
Empowerment
Health behavior
Health education
health informatics
Health literacy
Health services
health services administration & management
Interviews
Older people
Participation
Public Health
Questionnaires
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Title Simple scoring algorithm to identify community-dwelling older adults with limited health literacy: a cross-sectional study in Taiwan
URI http://dx.doi.org/10.1136/bmjopen-2020-045411
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https://pubmed.ncbi.nlm.nih.gov/PMC8627398
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Volume 11
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