Use of Discontinuous Methods of Data Collection in Behavioral Intervention: Guidelines for Practitioners View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-12

AUTHORS

Kate Fiske, Lara Delmolino

ABSTRACT

Over the past three decades, researchers have examined the sensitivity and accuracy of discontinuous data-collection methods. Momentary-time sampling (MTS) and partial-interval recording (PIR) have received particular attention in regards to their ability to estimate the occurrence of behavior and their sensitivity to behavior change compared to continuous data collection. In this article, we summarize these findings and provide recommendations for designing a discontinuous measurement system with consideration of the dimensions of behavior to be measured and the expected direction of behavior change. More... »

PAGES

77-81

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf03391826

DOI

http://dx.doi.org/10.1007/bf03391826

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1078738398

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23730469


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Douglass Developmental Disabilities Center and Rutgers, The State University of New Jersey, New Jersey, USA", 
          "id": "http://www.grid.ac/institutes/grid.430387.b", 
          "name": [
            "Douglass Developmental Disabilities Center and Rutgers, The State University of New Jersey, New Jersey, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fiske", 
        "givenName": "Kate", 
        "id": "sg:person.01074763572.91", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074763572.91"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Douglass Developmental Disabilities Center and Rutgers, The State University of New Jersey, New Jersey, USA", 
          "id": "http://www.grid.ac/institutes/grid.430387.b", 
          "name": [
            "Douglass Developmental Disabilities Center and Rutgers, The State University of New Jersey, New Jersey, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Delmolino", 
        "givenName": "Lara", 
        "id": "sg:person.01143076772.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143076772.48"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2012-12", 
    "datePublishedReg": "2012-12-01", 
    "description": "Over the past three decades, researchers have examined the sensitivity and accuracy of discontinuous data-collection methods. Momentary-time sampling (MTS) and partial-interval recording (PIR) have received particular attention in regards to their ability to estimate the occurrence of behavior and their sensitivity to behavior change compared to continuous data collection. In this article, we summarize these findings and provide recommendations for designing a discontinuous measurement system with consideration of the dimensions of behavior to be measured and the expected direction of behavior change.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/bf03391826", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1042164", 
        "issn": [
          "1998-1929", 
          "2196-8934"
        ], 
        "name": "Behavior Analysis in Practice", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "5"
      }
    ], 
    "keywords": [
      "sampling", 
      "changes", 
      "data collection", 
      "occurrence of behaviors", 
      "collection", 
      "decades", 
      "data collection methods", 
      "occurrence", 
      "particular attention", 
      "continuous data collection", 
      "use", 
      "sensitivity", 
      "attention", 
      "regard", 
      "ability", 
      "recommendations", 
      "consideration", 
      "guidelines", 
      "researchers", 
      "method", 
      "behavior", 
      "behavior change", 
      "system", 
      "accuracy", 
      "findings", 
      "dimensions", 
      "direction", 
      "practitioners", 
      "article", 
      "dimensions of behavior", 
      "intervention", 
      "recordings", 
      "measurement system", 
      "behavioral interventions", 
      "discontinuous method", 
      "momentary time sampling", 
      "partial interval recording", 
      "discontinuous data-collection methods", 
      "discontinuous measurement system"
    ], 
    "name": "Use of Discontinuous Methods of Data Collection in Behavioral Intervention: Guidelines for Practitioners", 
    "pagination": "77-81", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1078738398"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf03391826"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "23730469"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf03391826", 
      "https://app.dimensions.ai/details/publication/pub.1078738398"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:27", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_569.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/bf03391826"
  }
]
 

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/pub.10.1007/bf03391826'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/bf03391826'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf03391826'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf03391826'


 

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

108 TRIPLES      21 PREDICATES      65 URIs      57 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf03391826 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author N8d823827b9aa4d3e839e8faa23e3d423
4 schema:datePublished 2012-12
5 schema:datePublishedReg 2012-12-01
6 schema:description Over the past three decades, researchers have examined the sensitivity and accuracy of discontinuous data-collection methods. Momentary-time sampling (MTS) and partial-interval recording (PIR) have received particular attention in regards to their ability to estimate the occurrence of behavior and their sensitivity to behavior change compared to continuous data collection. In this article, we summarize these findings and provide recommendations for designing a discontinuous measurement system with consideration of the dimensions of behavior to be measured and the expected direction of behavior change.
7 schema:genre article
8 schema:inLanguage en
9 schema:isAccessibleForFree true
10 schema:isPartOf N0e111e17ce8845e28ac5aea48a60fff3
11 N33fab44823c4473aa3d20db7af4c8277
12 sg:journal.1042164
13 schema:keywords ability
14 accuracy
15 article
16 attention
17 behavior
18 behavior change
19 behavioral interventions
20 changes
21 collection
22 consideration
23 continuous data collection
24 data collection
25 data collection methods
26 decades
27 dimensions
28 dimensions of behavior
29 direction
30 discontinuous data-collection methods
31 discontinuous measurement system
32 discontinuous method
33 findings
34 guidelines
35 intervention
36 measurement system
37 method
38 momentary time sampling
39 occurrence
40 occurrence of behaviors
41 partial interval recording
42 particular attention
43 practitioners
44 recommendations
45 recordings
46 regard
47 researchers
48 sampling
49 sensitivity
50 system
51 use
52 schema:name Use of Discontinuous Methods of Data Collection in Behavioral Intervention: Guidelines for Practitioners
53 schema:pagination 77-81
54 schema:productId N3712665e3e8e424dba9b76c58df71226
55 N39a65bd5e4d94391b72cc567e7f98ba5
56 N739642149c9b487ba2b3f9c8f9f7e792
57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078738398
58 https://doi.org/10.1007/bf03391826
59 schema:sdDatePublished 2022-01-01T18:27
60 schema:sdLicense https://scigraph.springernature.com/explorer/license/
61 schema:sdPublisher N3a07e489eaa24453b8608023cf9d850e
62 schema:url https://doi.org/10.1007/bf03391826
63 sgo:license sg:explorer/license/
64 sgo:sdDataset articles
65 rdf:type schema:ScholarlyArticle
66 N0e111e17ce8845e28ac5aea48a60fff3 schema:volumeNumber 5
67 rdf:type schema:PublicationVolume
68 N33fab44823c4473aa3d20db7af4c8277 schema:issueNumber 2
69 rdf:type schema:PublicationIssue
70 N3712665e3e8e424dba9b76c58df71226 schema:name dimensions_id
71 schema:value pub.1078738398
72 rdf:type schema:PropertyValue
73 N39a65bd5e4d94391b72cc567e7f98ba5 schema:name doi
74 schema:value 10.1007/bf03391826
75 rdf:type schema:PropertyValue
76 N3a07e489eaa24453b8608023cf9d850e schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 N739642149c9b487ba2b3f9c8f9f7e792 schema:name pubmed_id
79 schema:value 23730469
80 rdf:type schema:PropertyValue
81 N7916c74e1bf54c2eae930da3c57b9344 rdf:first sg:person.01143076772.48
82 rdf:rest rdf:nil
83 N8d823827b9aa4d3e839e8faa23e3d423 rdf:first sg:person.01074763572.91
84 rdf:rest N7916c74e1bf54c2eae930da3c57b9344
85 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
86 schema:name Mathematical Sciences
87 rdf:type schema:DefinedTerm
88 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
89 schema:name Statistics
90 rdf:type schema:DefinedTerm
91 sg:journal.1042164 schema:issn 1998-1929
92 2196-8934
93 schema:name Behavior Analysis in Practice
94 schema:publisher Springer Nature
95 rdf:type schema:Periodical
96 sg:person.01074763572.91 schema:affiliation grid-institutes:grid.430387.b
97 schema:familyName Fiske
98 schema:givenName Kate
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074763572.91
100 rdf:type schema:Person
101 sg:person.01143076772.48 schema:affiliation grid-institutes:grid.430387.b
102 schema:familyName Delmolino
103 schema:givenName Lara
104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143076772.48
105 rdf:type schema:Person
106 grid-institutes:grid.430387.b schema:alternateName Douglass Developmental Disabilities Center and Rutgers, The State University of New Jersey, New Jersey, USA
107 schema:name Douglass Developmental Disabilities Center and Rutgers, The State University of New Jersey, New Jersey, USA
108 rdf:type schema:Organization
 




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


...