Example of Prevention Science format
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Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format
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Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format Example of Prevention Science format
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This content is only for preview purposes. The original open access content can be found here.
open access Open Access

Prevention Science — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Public Health, Environmental and Occupational Health #62 of 526 down down by 9 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 410 Published Papers | 2357 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 18/07/2020
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Related Journals

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SJR: 0.575
SNIP: 1.117
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SJR: 0.666
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open access Open Access

SAGE

Quality:  
High
CiteRatio: 4.6
SJR: 1.649
SNIP: 2.198

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

3.103

9% from 2018

Impact factor for Prevention Science from 2016 - 2019
Year Value
2019 3.103
2018 2.851
2017 2.594
2016 2.57
graph view Graph view
table view Table view

5.7

14% from 2019

CiteRatio for Prevention Science from 2016 - 2020
Year Value
2020 5.7
2019 5.0
2018 4.8
2017 4.9
2016 5.1
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 9% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 14% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.785

27% from 2019

SJR for Prevention Science from 2016 - 2020
Year Value
2020 1.785
2019 1.407
2018 1.461
2017 1.223
2016 1.752
graph view Graph view
table view Table view

1.811

12% from 2019

SNIP for Prevention Science from 2016 - 2020
Year Value
2020 1.811
2019 1.616
2018 1.426
2017 1.271
2016 1.644
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 27% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 12% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Prevention Science

Guideline source: View

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Springer

Prevention Science

Prevention Science serves as an interdisciplinary forum designed to disseminate new developments in the theory, research and practice of prevention. Prevention sciences encompassing etiology, epidemiology and intervention are represented through peer-reviewed original research...... Read More

Public Health, Environmental and Occupational Health

Medicine

i
Last updated on
18 Jul 2020
i
ISSN
1389-4986
i
Impact Factor
High - 1.476
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
SPBASIC
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Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1023/A:1026595011371
Equivalence of the Mediation, Confounding and Suppression Effect
David P. MacKinnon1, Jennifer L. Krull1, Chondra M. Lockwood1
01 Dec 2000 - Prevention Science

Abstract:

This paper describes the statistical similarities among mediation, confounding, and suppression. Each is quantified by measuring the change in the relationship between an independent and a dependent variable after adding a third variable to the analysis. Mediation and confounding are identical statistically and can be disting... This paper describes the statistical similarities among mediation, confounding, and suppression. Each is quantified by measuring the change in the relationship between an independent and a dependent variable after adding a third variable to the analysis. Mediation and confounding are identical statistically and can be distinguished only on conceptual grounds. Methods to determine the confidence intervals for confounding and suppression effects are proposed based on methods developed for mediated effects. Although the statistical estimation of effects and standard errors is the same, there are important conceptual differences among the three types of effects. read more read less

Topics:

Confounding (61%)61% related to the paper, Controlling for a variable (55%)55% related to the paper, Variables (54%)54% related to the paper
View PDF
3,285 Citations
open accessOpen access Journal Article DOI: 10.1007/S11121-007-0070-9
How Many Imputations are Really Needed? Some Practical Clarifications of Multiple Imputation Theory
John W. Graham1, Allison E. Olchowski1, Tamika D. Gilreath1
05 Jun 2007 - Prevention Science

Abstract:

Multiple imputation (MI) and full information maximum likelihood (FIML) are the two most common approaches to missing data analysis. In theory, MI and FIML are equivalent when identical models are tested using the same variables, and when m, the number of imputations performed with MI, approaches infinity. However, it is impo... Multiple imputation (MI) and full information maximum likelihood (FIML) are the two most common approaches to missing data analysis. In theory, MI and FIML are equivalent when identical models are tested using the same variables, and when m, the number of imputations performed with MI, approaches infinity. However, it is important to know how many imputations are necessary before MI and FIML are sufficiently equivalent in ways that are important to prevention scientists. MI theory suggests that small values of m, even on the order of three to five imputations, yield excellent results. Previous guidelines for sufficient m are based on relative efficiency, which involves the fraction of missing information (γ) for the parameter being estimated, and m. In the present study, we used a Monte Carlo simulation to test MI models across several scenarios in which γ and m were varied. Standard errors and p-values for the regression coefficient of interest varied as a function of m, but not at the same rate as relative efficiency. Most importantly, statistical power for small effect sizes diminished as m became smaller, and the rate of this power falloff was much greater than predicted by changes in relative efficiency. Based our findings, we recommend that researchers using MI should perform many more imputations than previously considered sufficient. These recommendations are based on γ, and take into consideration one’s tolerance for a preventable power falloff (compared to FIML) due to using too few imputations. read more read less

Topics:

Missing data (50%)50% related to the paper
View PDF
2,253 Citations
Journal Article DOI: 10.1007/S11121-005-5553-Y
Standards of Evidence: Criteria for Efficacy, Effectiveness and Dissemination
16 May 2005 - Prevention Science

Abstract:

Ever increasing demands for accountability, together with the proliferation of lists of evidence-based prevention programs and policies, led the Society for Prevention Research to charge a committee with establishing standards for identifying effective prevention programs and policies. Recognizing that interventions that are ... Ever increasing demands for accountability, together with the proliferation of lists of evidence-based prevention programs and policies, led the Society for Prevention Research to charge a committee with establishing standards for identifying effective prevention programs and policies. Recognizing that interventions that are effective and ready for dissemination are a subset of effective programs and policies, and that effective programs and policies are a subset of efficacious interventions, SPR’s Standards Committee developed overlapping sets of standards. We designed these Standards to assist practitioners, policy makers, and administrators to determine which interventions are efficacious, which are effective, and which are ready for dissemination. Under these Standards, an efficacious intervention will have been tested in at least two rigorous trials that (1) involved defined samples from defined populations, (2) used psychometrically sound measures and data collection procedures; (3) analyzed their data with rigorous statistical approaches; (4) showed consistent positive effects (without serious iatrogenic effects); and (5) reported at least one significant long-term follow-up. An effective intervention under these Standards will not only meet all standards for efficacious interventions, but also will have (1) manuals, appropriate training, and technical support available to allow third parties to adopt and implement the intervention; (2) been evaluated under real-world conditions in studies that included sound measurement of the level of implementation and engagement of the target audience (in both the intervention and control conditions); (3) indicated the practical importance of intervention outcome effects; and (4) clearly demonstrated to whom intervention findings can be generalized. An intervention recognized as ready for broad dissemination under these Standards will not only meet all standards for efficacious and effective interventions, but will also provide (1) evidence of the ability to “go to scale”; (2) clear cost information; and (3) monitoring and evaluation tools so that adopting agencies can monitor or evaluate how well the intervention works in their settings. Finally, the Standards Committee identified possible standards desirable for current and future areas of prevention science as the field develops. If successful, these Standards will inform efforts in the field to find prevention programs and policies that are of proven efficacy, effectiveness, or readiness for adoption and will guide prevention scientists as they seek to discover, research, and bring to the field new prevention programs and policies. read more read less

Topics:

Poison control (57%)57% related to the paper, Prevention science (53%)53% related to the paper, Information Dissemination (51%)51% related to the paper, Psychological intervention (51%)51% related to the paper
View PDF
1,264 Citations
Journal Article DOI: 10.1023/B:PREV.0000013980.12412.CD
The cultural adaptation of prevention interventions: resolving tensions between fidelity and fit.
Felipe González Castro1, Manuel Barrera1, Charles R. Martinez
01 Mar 2004 - Prevention Science

Abstract:

A dynamic tension has developed in prevention science regarding two imperatives: (a) fidelity of implementation—the delivery of a manualized prevention intervention program as prescribed by the program developer, and (b) program adaptation—the modification of program content to accommodate the needs of a specific consumer gro... A dynamic tension has developed in prevention science regarding two imperatives: (a) fidelity of implementation—the delivery of a manualized prevention intervention program as prescribed by the program developer, and (b) program adaptation—the modification of program content to accommodate the needs of a specific consumer group. This paper examines this complex programmatic issue from a community-based participatory research approach for program adaptation that emphasizes motivating community participation to enhance program outcomes. Several issues, key concepts, and implementation strategies are presented under a strategic approach to address issues of fidelity and adaptation. Despite the noted tension between fidelity and adaptation, both are essential elements of prevention intervention program design and they are best addressed by a planned, organized, and systematic approach. Towards this aim, an innovative program design strategy is to develop hybrid prevention programs that “build in” adaptation to enhance program fit while also maximizing fidelity of implementation and program effectiveness. read more read less

Topics:

Fidelity (56%)56% related to the paper, Program Design Language (53%)53% related to the paper, Prevention science (53%)53% related to the paper
1,067 Citations
open accessOpen access Journal Article DOI: 10.1007/S11121-011-0201-1
Latent Class Analysis: An Alternative Perspective on Subgroup Analysis in Prevention and Treatment
Stephanie T. Lanza1, Brittany L. Rhoades1
01 Apr 2013 - Prevention Science

Abstract:

The overall goal of this study is to introduce latent class analysis (LCA) as an alternative approach to latent subgroup analysis. Traditionally, subgroup analysis aims to determine whether individuals respond differently to a treatment based on one or more measured characteristics. LCA provides a way to identify a small set ... The overall goal of this study is to introduce latent class analysis (LCA) as an alternative approach to latent subgroup analysis. Traditionally, subgroup analysis aims to determine whether individuals respond differently to a treatment based on one or more measured characteristics. LCA provides a way to identify a small set of underlying subgroups characterized by multiple dimensions which could, in turn, be used to examine differential treatment effects. This approach can help to address methodological challenges that arise in subgroup analysis, including a high Type I error rate, low statistical power, and limitations in examining higher-order interactions. An empirical example draws on N = 1,900 adolescents from the National Longitudinal Survey of Adolescent Health. Six characteristics (household poverty, single-parent status, peer cigarette use, peer alcohol use, neighborhood unemployment, and neighborhood poverty) are used to identify five latent subgroups: Low Risk, Peer Risk, Economic Risk, Household & Peer Risk, and Multi-Contextual Risk. Two approaches for examining differential treatment effects are demonstrated using a simulated outcome: 1) a classify-analyze approach and, 2) a model-based approach based on a reparameterization of the LCA with covariates model. Such approaches can facilitate targeting future intervention resources to subgroups that promise to show the maximum treatment response. read more read less

Topics:

Latent class model (62%)62% related to the paper, Subgroup analysis (59%)59% related to the paper
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801 Citations
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With SciSpace, you do not need a word template for Prevention Science.

It automatically formats your research paper to Springer formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Prevention Science format uses SPBASIC citation style.

Automatically format and order your citations and bibliography in a click.

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Frequently asked questions

1. Can I write Prevention Science in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Prevention Science guidelines and auto format it.

2. Do you follow the Prevention Science guidelines?

Yes, the template is compliant with the Prevention Science guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Prevention Science?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Prevention Science citation style.

4. Can I use the Prevention Science templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Prevention Science.

5. Can I use a manuscript in Prevention Science that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Prevention Science that you can download at the end.

6. How long does it usually take you to format my papers in Prevention Science?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Prevention Science.

7. Where can I find the template for the Prevention Science?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Prevention Science's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Prevention Science's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Prevention Science an online tool or is there a desktop version?

SciSpace's Prevention Science is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Prevention Science?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Prevention Science?”

11. What is the output that I would get after using Prevention Science?

After writing your paper autoformatting in Prevention Science, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Prevention Science's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Prevention Science?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Prevention Science. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Prevention Science?

The 5 most common citation types in order of usage for Prevention Science are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Prevention Science?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Prevention Science's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Prevention Science in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Prevention Science Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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