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Screening and vaccination as determined by the Social Ecological Model and the Theory of Triadic Influence: a systematic review

Identifieur interne : 000497 ( Pmc/Checkpoint ); précédent : 000496; suivant : 000498

Screening and vaccination as determined by the Social Ecological Model and the Theory of Triadic Influence: a systematic review

Auteurs : Anayawa Nyambe [Belgique] ; Guido Van Hal [Belgique] ; Jarl K. Kampen [Pays-Bas, Belgique]

Source :

RBID : PMC:5114823

Abstract

Background

Vaccination and screening are forms of primary and secondary prevention methods. These methods are recommended for controlling the spread of a vast number of diseases and conditions. To determine the most effective preventive methods to be used by a society, multi-level models have shown to be more effective than models that focus solely on individual level characteristics. The Social Ecological Model (SEM) and the Theory of Triadic Influence (TTI) are such models. The purpose of this systematic review was to identify main differences and similarities of SEM and TTI regarding screening and vaccination in order to prepare potentially successful prevention programs for practice.

Methods

A systematic review was conducted. Separate literature searches were performed during January and February 2015 using Medline, Ovid, Proquest, PubMed, University of Antwerp Discovery Service and Web of Science, for articles that apply the SEM and TTI.

A Data Extraction Form with mostly closed-end questions was developed to assist with data extraction. Aggregate descriptive statistics were utilized to summarize the general characteristics of the SEM and TTI as documented in the scientific literature.

Results

A total of 290 potentially relevant articles referencing the SEM were found. As for the TTI, a total of 131 potentially relevant articles were found. After strict evaluation for inclusion and exclusion criteria, 40 SEM studies and 46 TTI studies were included in the systematic review.

Conclusions

The SEM and TTI are theoretical frameworks that share many theoretical concepts and are relevant for several types of health behaviors. However, they differ in the structure of the model, and in how the variables are thought to interact with each other, the TTI being a matrix while the SEM has a ring structure. The main difference consists of the division of the TTI into levels of causation (ultimate, distal and proximal) which are not considered within the levels of the SEM. It was further found that in the articles studied in this systematic review, both models are often considered effective, while the empirical basis of these (and other) conclusions reached by their authors is in many cases unclear or incompletely specified.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3802-6) contains supplementary material, which is available to authorized users.


Url:
DOI: 10.1186/s12889-016-3802-6
PubMed: 27855680
PubMed Central: 5114823


Affiliations:


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PMC:5114823

Le document en format XML

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<p>Vaccination and screening are forms of primary and secondary prevention methods. These methods are recommended for controlling the spread of a vast number of diseases and conditions. To determine the most effective preventive methods to be used by a society, multi-level models have shown to be more effective than models that focus solely on individual level characteristics. The Social Ecological Model (SEM) and the Theory of Triadic Influence (TTI) are such models. The purpose of this systematic review was to identify main differences and similarities of SEM and TTI regarding screening and vaccination in order to prepare potentially successful prevention programs for practice.</p>
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<p>A systematic review was conducted. Separate literature searches were performed during January and February 2015 using Medline, Ovid, Proquest, PubMed, University of Antwerp Discovery Service and Web of Science, for articles that apply the SEM and TTI.</p>
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<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">BMC Public Health</journal-id>
<journal-id journal-id-type="iso-abbrev">BMC Public Health</journal-id>
<journal-title-group>
<journal-title>BMC Public Health</journal-title>
</journal-title-group>
<issn pub-type="epub">1471-2458</issn>
<publisher>
<publisher-name>BioMed Central</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">27855680</article-id>
<article-id pub-id-type="pmc">5114823</article-id>
<article-id pub-id-type="publisher-id">3802</article-id>
<article-id pub-id-type="doi">10.1186/s12889-016-3802-6</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Screening and vaccination as determined by the Social Ecological Model and the Theory of Triadic Influence: a systematic review</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<contrib-id contrib-id-type="orcid">http://orcid.org/0000-0002-8929-8573</contrib-id>
<name>
<surname>Nyambe</surname>
<given-names>Anayawa</given-names>
</name>
<address>
<email>anayawa@gmail.com</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Van Hal</surname>
<given-names>Guido</given-names>
</name>
<address>
<email>guido.vanhal@uantwerpen.be</email>
</address>
<xref ref-type="aff" rid="Aff2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kampen</surname>
<given-names>Jarl K.</given-names>
</name>
<address>
<email>jarl.kampen@uantwerpen.be</email>
</address>
<xref ref-type="aff" rid="Aff3">3</xref>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<aff id="Aff1">
<label>1</label>
Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium</aff>
<aff id="Aff2">
<label>2</label>
Department of Epidemiology and Social Medicine, University of Antwerp, Antwerp, Belgium</aff>
<aff id="Aff3">
<label>3</label>
Biometris, Wageningen University, Wageningen, The Netherlands</aff>
<aff id="Aff4">
<label>4</label>
StatUA (Core Facility for Statistical Analysis), University of Antwerp, Antwerp, Belgium</aff>
</contrib-group>
<pub-date pub-type="epub">
<day>17</day>
<month>11</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>17</day>
<month>11</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection">
<year>2016</year>
</pub-date>
<volume>16</volume>
<elocation-id>1166</elocation-id>
<history>
<date date-type="received">
<day>19</day>
<month>10</month>
<year>2015</year>
</date>
<date date-type="accepted">
<day>1</day>
<month>11</month>
<year>2016</year>
</date>
</history>
<permissions>
<copyright-statement>© The Author(s). 2016</copyright-statement>
<license license-type="OpenAccess">
<license-p>
<bold>Open Access</bold>
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>
) applies to the data made available in this article, unless otherwise stated.</license-p>
</license>
</permissions>
<abstract id="Abs1">
<sec>
<title>Background</title>
<p>Vaccination and screening are forms of primary and secondary prevention methods. These methods are recommended for controlling the spread of a vast number of diseases and conditions. To determine the most effective preventive methods to be used by a society, multi-level models have shown to be more effective than models that focus solely on individual level characteristics. The Social Ecological Model (SEM) and the Theory of Triadic Influence (TTI) are such models. The purpose of this systematic review was to identify main differences and similarities of SEM and TTI regarding screening and vaccination in order to prepare potentially successful prevention programs for practice.</p>
</sec>
<sec>
<title>Methods</title>
<p>A systematic review was conducted. Separate literature searches were performed during January and February 2015 using Medline, Ovid, Proquest, PubMed, University of Antwerp Discovery Service and Web of Science, for articles that apply the SEM and TTI.</p>
<p>A Data Extraction Form with mostly closed-end questions was developed to assist with data extraction. Aggregate descriptive statistics were utilized to summarize the general characteristics of the SEM and TTI as documented in the scientific literature.</p>
</sec>
<sec>
<title>Results</title>
<p>A total of 290 potentially relevant articles referencing the SEM were found. As for the TTI, a total of 131 potentially relevant articles were found. After strict evaluation for inclusion and exclusion criteria, 40 SEM studies and 46 TTI studies were included in the systematic review.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>The SEM and TTI are theoretical frameworks that share many theoretical concepts and are relevant for several types of health behaviors. However, they differ in the structure of the model, and in how the variables are thought to interact with each other, the TTI being a matrix while the SEM has a ring structure. The main difference consists of the division of the TTI into levels of causation (ultimate, distal and proximal) which are not considered within the levels of the SEM. It was further found that in the articles studied in this systematic review, both models are often considered effective, while the empirical basis of these (and other) conclusions reached by their authors is in many cases unclear or incompletely specified.</p>
</sec>
<sec>
<title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/s12889-016-3802-6) contains supplementary material, which is available to authorized users.</p>
</sec>
</abstract>
<kwd-group xml:lang="en">
<title>Keywords</title>
<kwd>Screening</kwd>
<kwd>Vaccination</kwd>
<kwd>Multi-level ecological models</kwd>
<kwd>Social Ecological Model</kwd>
<kwd>Theory of Triadic Influence</kwd>
</kwd-group>
<custom-meta-group>
<custom-meta>
<meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2016</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>Belgique</li>
<li>Pays-Bas</li>
</country>
<region>
<li>Gueldre (province)</li>
<li>Province d'Anvers</li>
<li>Région flamande</li>
</region>
<settlement>
<li>Anvers</li>
<li>Wageningue</li>
</settlement>
<orgName>
<li>Université d'Anvers</li>
<li>Université de Wageningue</li>
</orgName>
</list>
<tree>
<country name="Belgique">
<region name="Région flamande">
<name sortKey="Nyambe, Anayawa" sort="Nyambe, Anayawa" uniqKey="Nyambe A" first="Anayawa" last="Nyambe">Anayawa Nyambe</name>
</region>
<name sortKey="Kampen, Jarl K" sort="Kampen, Jarl K" uniqKey="Kampen J" first="Jarl K." last="Kampen">Jarl K. Kampen</name>
<name sortKey="Van Hal, Guido" sort="Van Hal, Guido" uniqKey="Van Hal G" first="Guido" last="Van Hal">Guido Van Hal</name>
</country>
<country name="Pays-Bas">
<region name="Gueldre (province)">
<name sortKey="Kampen, Jarl K" sort="Kampen, Jarl K" uniqKey="Kampen J" first="Jarl K." last="Kampen">Jarl K. Kampen</name>
</region>
</country>
</tree>
</affiliations>
</record>

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