Ontology type: schema:ScholarlyArticle Open Access: True
2022-04-26
AUTHORSChinenye Okpara, Chidozie Edokwe, George Ioannidis, Alexandra Papaioannou, Jonathan D. Adachi, Lehana Thabane
ABSTRACTBackgroundMissing data are common in longitudinal studies, and more so, in studies of older adults, who are susceptible to health and functional decline that limit completion of assessments. We assessed the extent, current reporting, and handling of missing data in longitudinal studies of older adults.MethodsMedline and Embase databases were searched from 2015 to 2019 for publications on longitudinal observational studies conducted among persons ≥55 years old. The search was restricted to 10 general geriatric journals published in English. Reporting and handling of missing data were assessed using questions developed from the recommended standards. Data were summarised descriptively as frequencies and proportions.ResultsA total of 165 studies were included in the review from 7032 identified records. In approximately half of the studies 97 (62.5%), there was either no comment on missing data or unclear descriptions. The percentage of missing data varied from 0.1 to 55%, with a 14% average among the studies that reported having missing data. Complete case analysis was the most common method for handling missing data with nearly 75% of the studies (n = 52) excluding individual observations due to missing data, at the initial phase of study inclusion or at the analysis stage. Of the 10 studies where multiple imputation was used, only 1 (10.0%) study followed the guideline for reporting the procedure fully using online supplementary documents.ConclusionThe current reporting and handling of missing data in longitudinal observational studies of older adults are inadequate. Journal endorsement and implementation of guidelines may potentially improve the quality of missing data reporting. Further, authors should be encouraged to use online supplementary files to provide additional details on how missing data were addressed, to allow for more transparency and comprehensive appraisal of studies. More... »
PAGES122
http://scigraph.springernature.com/pub.10.1186/s12874-022-01605-w
DOIhttp://dx.doi.org/10.1186/s12874-022-01605-w
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1147365863
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/35473665
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Public Health and Health Services",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Databases, Factual",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Longitudinal Studies",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Middle Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Periodicals as Topic",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Research Design",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Surveys and Questionnaires",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Department of Health Research Methods, Evidence and Impact, McMaster University, L8S 4L8, Hamilton, ON, Canada",
"id": "http://www.grid.ac/institutes/grid.25073.33",
"name": [
"Department of Health Research Methods, Evidence and Impact, McMaster University, L8S 4L8, Hamilton, ON, Canada"
],
"type": "Organization"
},
"familyName": "Okpara",
"givenName": "Chinenye",
"id": "sg:person.010073545275.00",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010073545275.00"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Roche Products Ltd, Ikeja, Lagos, Nigeria",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Roche Products Ltd, Ikeja, Lagos, Nigeria"
],
"type": "Organization"
},
"familyName": "Edokwe",
"givenName": "Chidozie",
"id": "sg:person.011035241065.10",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011035241065.10"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Medicine, McMaster University, Hamilton, ON, Canada",
"id": "http://www.grid.ac/institutes/grid.25073.33",
"name": [
"Department of Health Research Methods, Evidence and Impact, McMaster University, L8S 4L8, Hamilton, ON, Canada",
"GERAS Centre, Hamilton Health Sciences, Hamilton, ON, Canada",
"Department of Medicine, McMaster University, Hamilton, ON, Canada"
],
"type": "Organization"
},
"familyName": "Ioannidis",
"givenName": "George",
"id": "sg:person.01335723334.91",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01335723334.91"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Medicine, McMaster University, Hamilton, ON, Canada",
"id": "http://www.grid.ac/institutes/grid.25073.33",
"name": [
"Department of Health Research Methods, Evidence and Impact, McMaster University, L8S 4L8, Hamilton, ON, Canada",
"GERAS Centre, Hamilton Health Sciences, Hamilton, ON, Canada",
"Department of Medicine, McMaster University, Hamilton, ON, Canada"
],
"type": "Organization"
},
"familyName": "Papaioannou",
"givenName": "Alexandra",
"id": "sg:person.01150566707.31",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01150566707.31"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Medicine, McMaster University, Hamilton, ON, Canada",
"id": "http://www.grid.ac/institutes/grid.25073.33",
"name": [
"GERAS Centre, Hamilton Health Sciences, Hamilton, ON, Canada",
"Department of Medicine, McMaster University, Hamilton, ON, Canada"
],
"type": "Organization"
},
"familyName": "Adachi",
"givenName": "Jonathan D.",
"id": "sg:person.01153361534.42",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01153361534.42"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa",
"id": "http://www.grid.ac/institutes/grid.412988.e",
"name": [
"Department of Health Research Methods, Evidence and Impact, McMaster University, L8S 4L8, Hamilton, ON, Canada",
"GERAS Centre, Hamilton Health Sciences, Hamilton, ON, Canada",
"Biostatistics Unit, Research Institute of St Joseph\u2019s Healthcare, Hamilton, ON, Canada",
"Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa"
],
"type": "Organization"
},
"familyName": "Thabane",
"givenName": "Lehana",
"id": "sg:person.01016450746.82",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01016450746.82"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1186/s13063-016-1402-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009121643",
"https://doi.org/10.1186/s13063-016-1402-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13063-015-1128-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029455204",
"https://doi.org/10.1186/s13063-015-1128-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1745-6215-15-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015305475",
"https://doi.org/10.1186/1745-6215-15-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2288-14-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014538937",
"https://doi.org/10.1186/1471-2288-14-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1745-6215-15-237",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014742229",
"https://doi.org/10.1186/1745-6215-15-237"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1477-7525-7-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011663978",
"https://doi.org/10.1186/1477-7525-7-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12874-020-01018-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1128014142",
"https://doi.org/10.1186/s12874-020-01018-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-1-4614-4018-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040568584",
"https://doi.org/10.1007/978-1-4614-4018-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2288-12-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029294667",
"https://doi.org/10.1186/1471-2288-12-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12877-018-0908-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1107210473",
"https://doi.org/10.1186/s12877-018-0908-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2288-12-96",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016352567",
"https://doi.org/10.1186/1471-2288-12-96"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12916-019-1443-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1123789526",
"https://doi.org/10.1186/s12916-019-1443-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12916-020-01598-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1128294386",
"https://doi.org/10.1186/s12916-020-01598-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1477-7525-7-57",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047598260",
"https://doi.org/10.1186/1477-7525-7-57"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11749-009-0138-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034747807",
"https://doi.org/10.1007/s11749-009-0138-x"
],
"type": "CreativeWork"
}
],
"datePublished": "2022-04-26",
"datePublishedReg": "2022-04-26",
"description": "BackgroundMissing data are common in longitudinal studies, and more so, in studies of older adults, who are susceptible to health and functional decline that limit completion of assessments. We assessed the extent, current reporting, and handling of missing data in longitudinal studies of older adults.MethodsMedline and Embase databases were searched from 2015 to 2019 for publications on longitudinal observational studies conducted among persons \u226555\u2009years old. The search was restricted to 10 general geriatric journals published in English. Reporting and handling of missing data were assessed using questions developed from the recommended standards. Data were summarised descriptively as frequencies and proportions.ResultsA total of 165 studies were included in the review from 7032 identified records. In approximately half of the studies 97 (62.5%), there was either no comment on missing data or unclear descriptions. The percentage of missing data varied from 0.1 to 55%, with a 14% average among the studies that reported having missing data. Complete case analysis was the most common method for handling missing data with nearly 75% of the studies (n\u2009=\u200952) excluding individual observations due to missing data, at the initial phase of study inclusion or at the analysis stage. Of the 10 studies where multiple imputation was used, only 1 (10.0%) study followed the guideline for reporting the procedure fully using online supplementary documents.ConclusionThe current reporting and handling of missing data in longitudinal observational studies of older adults are inadequate. Journal endorsement and implementation of guidelines may potentially improve the quality of missing data reporting. Further, authors should be encouraged to use online supplementary files to provide additional details on how missing data were addressed, to allow for more transparency and comprehensive appraisal of studies.",
"genre": "article",
"id": "sg:pub.10.1186/s12874-022-01605-w",
"inLanguage": "en",
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1024940",
"issn": [
"1471-2288"
],
"name": "BMC Medical Research Methodology",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "22"
}
],
"keywords": [
"longitudinal observational study",
"older adults",
"geriatric journals",
"observational study",
"longitudinal study",
"implementation of guidelines",
"ResultsA total",
"Embase databases",
"study inclusion",
"functional decline",
"current reporting",
"journal endorsement",
"adults",
"complete case analysis",
"online supplementary file",
"multiple imputation",
"data reporting",
"reporting",
"guidelines",
"unclear description",
"MethodsMEDLINE",
"study",
"comprehensive appraisal",
"initial phase",
"total",
"health",
"data",
"review",
"years",
"proportion",
"persons",
"percentage",
"methodological survey",
"assessment",
"completion",
"half",
"decline",
"records",
"handling",
"database",
"common method",
"procedure",
"survey",
"journals",
"search",
"additional details",
"appraisal",
"case analysis",
"stage",
"frequency",
"extent",
"publications",
"inclusion",
"quality",
"imputation",
"standards",
"endorsement",
"analysis",
"authors",
"files",
"questions",
"observations",
"English",
"method",
"supplementary files",
"phase",
"individual observations",
"implementation",
"detail",
"comments",
"description",
"more transparency",
"analysis stage",
"supplementary documents",
"documents",
"transparency"
],
"name": "The reporting and handling of missing data in longitudinal studies of older adults is suboptimal: a methodological survey of geriatric journals",
"pagination": "122",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1147365863"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s12874-022-01605-w"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"35473665"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s12874-022-01605-w",
"https://app.dimensions.ai/details/publication/pub.1147365863"
],
"sdDataset": "articles",
"sdDatePublished": "2022-06-01T22:25",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_941.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1186/s12874-022-01605-w"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12874-022-01605-w'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12874-022-01605-w'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12874-022-01605-w'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12874-022-01605-w'
This table displays all metadata directly associated to this object as RDF triples.
276 TRIPLES
22 PREDICATES
125 URIs
102 LITERALS
15 BLANK NODES