Prospective Study of Functional Status in Veterans at Risk for Unexplained Illnesses View Homepage


Ontology type: schema:MedicalStudy     


Clinical Trial Info

YEARS

2005-2011

ABSTRACT

Background: Previous deployments like that to the Persian Gulf in 1991 produced veterans with post-deployment symptom-based health problems with no medical explanation. This was termed Gulf War illness or medically unexplained illness (MUI). If previous wars are any indication, some soldiers currently deployed to hostile areas also will return home with unexplained symptom-based illnesses. However, when this study began there was virtually no pre-war, prospective data on risk and resilience factors associated with MUI. This study is attempting to fill that gap. Objectives: Our goals are to: (a) determine pre- and immediate post-deployment factors predicting later MUI and poor functional status, (b) improve previous methodological problems (e.g., selection bias, recall bias and lack of baseline controls) in studies of MUI, and (c) relate pre-deployment risk factors (e.g., personality, stressor reactivity) and resilience factors (e.g., coping style, social support) to post-deployment functional status. Detailed Description Background: Previous deployments like that to the Persian Gulf in 1991 produced veterans with post-deployment symptom-based health problems with no medical explanation. This was termed Gulf War illness or medically unexplained illness (MUI). If previous wars are any indication, some soldiers currently deployed to hostile areas also will return home with unexplained symptom-based illnesses. However, was virtually no pre-war, prospective data on risk and resilience factors associated with MUI before 2001. This study will attempt to fill that gap. Objectives: Our goals are to: (a) determine pre- and immediate post-deployment factors predicting later MUI and poor functional status, (b) improve previous methodological problems (e.g., selection bias, recall bias and lack of baseline controls) in studies of MUI, and (c) relate pre-deployment risk factors (e.g., personality, stressor reactivity) and resilience factors (e.g., coping style, social support) to post-deployment functional status. Methods: This study uses a prospective, longitudinal observational design to assess risk and resilience factors for post-war MUI in Reserve and National Guard enlisted personnel. A stratified random sample of more than 700 subjects will be drawn from those undergoing pre- and post-mobilization readiness processing at Fort Dix, NJ and Camp Shelby, MS. Personnel will be tested pre-mobilization (Phase 1), immediately after mobilization (Phase 2) and at 3 months and 1 year post-deployment (Phases 3 & 4). Predictor variables include personality, social support, coping style, non-specific symptoms, sympathetic cardiac stress reactivity, and cortisol stress reactivity. Control variables include prior traumatic events, current distress, PTSD symptoms, socially desirable responding, body mass index, deployment experiences, environmental exposures and demographics (e.g., age, gender). Outcome variables include functional status, healthcare utilization, and MUI status (using CDC criteria for chronic multisymptom illness developed after the first Gulf War). Status: Publications and presentations are being prepared. Impact: The larger, prospective study with soldiers will help us to identify pre- and early post-deployment risk and resilience factors important in MUI, functional status, and healthcare utilization. There is an urgent need for both pre- and post-deployment predictors of later MUI uncontaminated by recall bias, and the selection bias of studying only treatment-seekers. If we are to understand how to best treat veterans presenting with unexplained symptoms, then we need to know which pre-war factors are most useful in predicting who is most likely to be resilient and who is most likely to be at risk for later unexplained illness. More... »

URL

https://clinicaltrials.gov/show/NCT00285246

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/2008/3177", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/3053", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "description": "Background: Previous deployments like that to the Persian Gulf in 1991 produced veterans with post-deployment symptom-based health problems with no medical explanation. This was termed Gulf War illness or medically unexplained illness (MUI). If previous wars are any indication, some soldiers currently deployed to hostile areas also will return home with unexplained symptom-based illnesses. However, when this study began there was virtually no pre-war, prospective data on risk and resilience factors associated with MUI. This study is attempting to fill that gap. Objectives: Our goals are to: (a) determine pre- and immediate post-deployment factors predicting later MUI and poor functional status, (b) improve previous methodological problems (e.g., selection bias, recall bias and lack of baseline controls) in studies of MUI, and (c) relate pre-deployment risk factors (e.g., personality, stressor reactivity) and resilience factors (e.g., coping style, social support) to post-deployment functional status.\n\nDetailed Description\nBackground: Previous deployments like that to the Persian Gulf in 1991 produced veterans with post-deployment symptom-based health problems with no medical explanation. This was termed Gulf War illness or medically unexplained illness (MUI). If previous wars are any indication, some soldiers currently deployed to hostile areas also will return home with unexplained symptom-based illnesses. However, was virtually no pre-war, prospective data on risk and resilience factors associated with MUI before 2001. This study will attempt to fill that gap. Objectives: Our goals are to: (a) determine pre- and immediate post-deployment factors predicting later MUI and poor functional status, (b) improve previous methodological problems (e.g., selection bias, recall bias and lack of baseline controls) in studies of MUI, and (c) relate pre-deployment risk factors (e.g., personality, stressor reactivity) and resilience factors (e.g., coping style, social support) to post-deployment functional status. Methods: This study uses a prospective, longitudinal observational design to assess risk and resilience factors for post-war MUI in Reserve and National Guard enlisted personnel. A stratified random sample of more than 700 subjects will be drawn from those undergoing pre- and post-mobilization readiness processing at Fort Dix, NJ and Camp Shelby, MS. Personnel will be tested pre-mobilization (Phase 1), immediately after mobilization (Phase 2) and at 3 months and 1 year post-deployment (Phases 3 & 4). Predictor variables include personality, social support, coping style, non-specific symptoms, sympathetic cardiac stress reactivity, and cortisol stress reactivity. Control variables include prior traumatic events, current distress, PTSD symptoms, socially desirable responding, body mass index, deployment experiences, environmental exposures and demographics (e.g., age, gender). Outcome variables include functional status, healthcare utilization, and MUI status (using CDC criteria for chronic multisymptom illness developed after the first Gulf War). Status: Publications and presentations are being prepared. Impact: The larger, prospective study with soldiers will help us to identify pre- and early post-deployment risk and resilience factors important in MUI, functional status, and healthcare utilization. There is an urgent need for both pre- and post-deployment predictors of later MUI uncontaminated by recall bias, and the selection bias of studying only treatment-seekers. If we are to understand how to best treat veterans presenting with unexplained symptoms, then we need to know which pre-war factors are most useful in predicting who is most likely to be resilient and who is most likely to be at risk for later unexplained illness.", 
    "endDate": "2011-02-01T00:00:00Z", 
    "id": "sg:clinicaltrial.NCT00285246", 
    "keywords": [
      "prospective study", 
      "functional status", 
      "veteran", 
      "risk", 
      "illness", 
      "deployment", 
      "Indian Ocean", 
      "post-deployment", 
      "explanation", 
      "Gulf War", 
      "war", 
      "indication", 
      "Military Personnel", 
      "home", 
      "symptom", 
      "prospective data", 
      "resilience factor", 
      "gap", 
      "methodological problem", 
      "selection bias", 
      "recall bias", 
      "baseline", 
      "risk factor", 
      "personality", 
      "reactivity", 
      "coping style", 
      "attempt", 
      "method", 
      "post-war", 
      "reserve", 
      "National Guard", 
      "personnel", 
      "stratified random sample", 
      "mobilization", 
      "fort", 
      "cAMP", 
      "multiple sclerosis", 
      "Phase 1", 
      "Phase 2", 
      "phase 3", 
      "predictor variable", 
      "non-specific symptom", 
      "stress reactivity", 
      "control variable", 
      "traumatic event", 
      "current", 
      "PTSD symptom", 
      "body mass index", 
      "environmental exposure", 
      "demographic", 
      "age", 
      "Gender Identity", 
      "outcome variable", 
      "healthcare utilization", 
      "criterion", 
      "chronic multisymptom illness", 
      "status", 
      "publication", 
      "presentation", 
      "urgent need", 
      "resilient"
    ], 
    "name": "Prospective Study of Functional Status in Veterans at Risk for Unexplained Illnesses", 
    "sameAs": [
      "https://app.dimensions.ai/details/clinical_trial/NCT00285246"
    ], 
    "sdDataset": "clinical_trials", 
    "sdDatePublished": "2019-03-07T15:22", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "file:///pack/app/us_ct_data_00002.json", 
    "sponsor": [
      {
        "id": "https://www.grid.ac/institutes/grid.422069.b", 
        "type": "Organization"
      }, 
      {
        "id": "https://www.grid.ac/institutes/grid.418356.d", 
        "type": "Organization"
      }, 
      {
        "id": "https://www.grid.ac/institutes/grid.484325.c", 
        "type": "Organization"
      }, 
      {
        "id": "https://www.grid.ac/institutes/grid.413879.0", 
        "type": "Organization"
      }
    ], 
    "startDate": "2005-12-01T00:00:00Z", 
    "subjectOf": [
      {
        "id": "sg:pub.10.1186/1477-7525-11-73", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004032156", 
          "https://doi.org/10.1186/1477-7525-11-73"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2458-12-1124", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016320320", 
          "https://doi.org/10.1186/1471-2458-12-1124"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/jom.0b013e3182570506", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046035155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11606-012-2247-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052673181", 
          "https://doi.org/10.1007/s11606-012-2247-6"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "type": "MedicalStudy", 
    "url": "https://clinicaltrials.gov/show/NCT00285246"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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/clinicaltrial.NCT00285246'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/clinicaltrial.NCT00285246'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/clinicaltrial.NCT00285246'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/clinicaltrial.NCT00285246'


 

This table displays all metadata directly associated to this object as RDF triples.

104 TRIPLES      16 PREDICATES      84 URIs      70 LITERALS      1 BLANK NODES

Subject Predicate Object
1 sg:clinicaltrial.NCT00285246 schema:about anzsrc-for:3053
2 anzsrc-for:3177
3 schema:description Background: Previous deployments like that to the Persian Gulf in 1991 produced veterans with post-deployment symptom-based health problems with no medical explanation. This was termed Gulf War illness or medically unexplained illness (MUI). If previous wars are any indication, some soldiers currently deployed to hostile areas also will return home with unexplained symptom-based illnesses. However, when this study began there was virtually no pre-war, prospective data on risk and resilience factors associated with MUI. This study is attempting to fill that gap. Objectives: Our goals are to: (a) determine pre- and immediate post-deployment factors predicting later MUI and poor functional status, (b) improve previous methodological problems (e.g., selection bias, recall bias and lack of baseline controls) in studies of MUI, and (c) relate pre-deployment risk factors (e.g., personality, stressor reactivity) and resilience factors (e.g., coping style, social support) to post-deployment functional status. Detailed Description Background: Previous deployments like that to the Persian Gulf in 1991 produced veterans with post-deployment symptom-based health problems with no medical explanation. This was termed Gulf War illness or medically unexplained illness (MUI). If previous wars are any indication, some soldiers currently deployed to hostile areas also will return home with unexplained symptom-based illnesses. However, was virtually no pre-war, prospective data on risk and resilience factors associated with MUI before 2001. This study will attempt to fill that gap. Objectives: Our goals are to: (a) determine pre- and immediate post-deployment factors predicting later MUI and poor functional status, (b) improve previous methodological problems (e.g., selection bias, recall bias and lack of baseline controls) in studies of MUI, and (c) relate pre-deployment risk factors (e.g., personality, stressor reactivity) and resilience factors (e.g., coping style, social support) to post-deployment functional status. Methods: This study uses a prospective, longitudinal observational design to assess risk and resilience factors for post-war MUI in Reserve and National Guard enlisted personnel. A stratified random sample of more than 700 subjects will be drawn from those undergoing pre- and post-mobilization readiness processing at Fort Dix, NJ and Camp Shelby, MS. Personnel will be tested pre-mobilization (Phase 1), immediately after mobilization (Phase 2) and at 3 months and 1 year post-deployment (Phases 3 & 4). Predictor variables include personality, social support, coping style, non-specific symptoms, sympathetic cardiac stress reactivity, and cortisol stress reactivity. Control variables include prior traumatic events, current distress, PTSD symptoms, socially desirable responding, body mass index, deployment experiences, environmental exposures and demographics (e.g., age, gender). Outcome variables include functional status, healthcare utilization, and MUI status (using CDC criteria for chronic multisymptom illness developed after the first Gulf War). Status: Publications and presentations are being prepared. Impact: The larger, prospective study with soldiers will help us to identify pre- and early post-deployment risk and resilience factors important in MUI, functional status, and healthcare utilization. There is an urgent need for both pre- and post-deployment predictors of later MUI uncontaminated by recall bias, and the selection bias of studying only treatment-seekers. If we are to understand how to best treat veterans presenting with unexplained symptoms, then we need to know which pre-war factors are most useful in predicting who is most likely to be resilient and who is most likely to be at risk for later unexplained illness.
4 schema:endDate 2011-02-01T00:00:00Z
5 schema:keywords Gender Identity
6 Gulf War
7 Indian Ocean
8 Military Personnel
9 National Guard
10 PTSD symptom
11 Phase 1
12 Phase 2
13 age
14 attempt
15 baseline
16 body mass index
17 cAMP
18 chronic multisymptom illness
19 control variable
20 coping style
21 criterion
22 current
23 demographic
24 deployment
25 environmental exposure
26 explanation
27 fort
28 functional status
29 gap
30 healthcare utilization
31 home
32 illness
33 indication
34 method
35 methodological problem
36 mobilization
37 multiple sclerosis
38 non-specific symptom
39 outcome variable
40 personality
41 personnel
42 phase 3
43 post-deployment
44 post-war
45 predictor variable
46 presentation
47 prospective data
48 prospective study
49 publication
50 reactivity
51 recall bias
52 reserve
53 resilience factor
54 resilient
55 risk
56 risk factor
57 selection bias
58 status
59 stratified random sample
60 stress reactivity
61 symptom
62 traumatic event
63 urgent need
64 veteran
65 war
66 schema:name Prospective Study of Functional Status in Veterans at Risk for Unexplained Illnesses
67 schema:sameAs https://app.dimensions.ai/details/clinical_trial/NCT00285246
68 schema:sdDatePublished 2019-03-07T15:22
69 schema:sdLicense https://scigraph.springernature.com/explorer/license/
70 schema:sdPublisher Nb9b1a76ea5ab432c854f8f60912988fa
71 schema:sponsor https://www.grid.ac/institutes/grid.413879.0
72 https://www.grid.ac/institutes/grid.418356.d
73 https://www.grid.ac/institutes/grid.422069.b
74 https://www.grid.ac/institutes/grid.484325.c
75 schema:startDate 2005-12-01T00:00:00Z
76 schema:subjectOf sg:pub.10.1007/s11606-012-2247-6
77 sg:pub.10.1186/1471-2458-12-1124
78 sg:pub.10.1186/1477-7525-11-73
79 https://doi.org/10.1097/jom.0b013e3182570506
80 schema:url https://clinicaltrials.gov/show/NCT00285246
81 sgo:license sg:explorer/license/
82 sgo:sdDataset clinical_trials
83 rdf:type schema:MedicalStudy
84 Nb9b1a76ea5ab432c854f8f60912988fa schema:name Springer Nature - SN SciGraph project
85 rdf:type schema:Organization
86 anzsrc-for:3053 schema:inDefinedTermSet anzsrc-for:
87 rdf:type schema:DefinedTerm
88 anzsrc-for:3177 schema:inDefinedTermSet anzsrc-for:
89 rdf:type schema:DefinedTerm
90 sg:pub.10.1007/s11606-012-2247-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052673181
91 https://doi.org/10.1007/s11606-012-2247-6
92 rdf:type schema:CreativeWork
93 sg:pub.10.1186/1471-2458-12-1124 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016320320
94 https://doi.org/10.1186/1471-2458-12-1124
95 rdf:type schema:CreativeWork
96 sg:pub.10.1186/1477-7525-11-73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004032156
97 https://doi.org/10.1186/1477-7525-11-73
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1097/jom.0b013e3182570506 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046035155
100 rdf:type schema:CreativeWork
101 https://www.grid.ac/institutes/grid.413879.0 schema:Organization
102 https://www.grid.ac/institutes/grid.418356.d schema:Organization
103 https://www.grid.ac/institutes/grid.422069.b schema:Organization
104 https://www.grid.ac/institutes/grid.484325.c schema:Organization
 




Preview window. Press ESC to close (or click here)


...