Literature DB >> 17126947

Population impact--definition, calculation and its use in prevention science in the example of tobacco smoking reduction.

Jochen René Thyrian1, Ulrich John.   

Abstract

INTRODUCTION: Population Impact is a criterion that can enhance prevention practices and provide a solid foundation for integrating policies and programs for prevention. However, to quantify the population impact of programs a statistical measure is needed. The objective of this article is to (a) deduct a formula to quantify population impact (PI), (b) define the formula for population impact of smoking prevention measures and (c) apply this formula on smoking prevention programs.
METHODS: Decision analytical approach.
RESULTS: The measurement of PI is defined with four parameters: recruitment, retention, efficacy and prevalence. A formula is mathematically deducted and the PI for different smoking prevention programs is calculated. DISCUSSION: The formula supports decision makers in deciding what prevention measure shows a higher impact on the population, gives hints where to improve the measure to increase the impact, whether recruitment, retention or efficacy needs to be improved and makes it easy to do analyses of costs on the population level.
CONCLUSIONS: To enhance prevention practice prevention measures need to provide all parameters to calculate the PI, research needs to focus on all parameters influencing the PI and costs of prevention measures need to be provided.

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Year:  2006        PMID: 17126947     DOI: 10.1016/j.healthpol.2006.10.001

Source DB:  PubMed          Journal:  Health Policy        ISSN: 0168-8510            Impact factor:   2.980


  3 in total

1.  Severity of unhealthy alcohol consumption in medical inpatients and the general population: is the general hospital a suitable place for brief interventions?

Authors:  Gallus Bischof; Susa Reinhardt; Jennis Freyer-Adam; Beate Coder; Janina M Grothues; Christian Meyer; Ulrich John; Hans-Jürgen Rumpf
Journal:  Int J Public Health       Date:  2010-02-09       Impact factor: 3.380

2.  Assessment of the Efficacy of a Mobile Phone-Delivered Just-in-Time Planning Intervention to Reduce Alcohol Use in Adolescents: Randomized Controlled Crossover Trial.

Authors:  Severin Haug; Raquel Paz Castro; Urte Scholz; Tobias Kowatsch; Michael Patrick Schaub; Theda Radtke
Journal:  JMIR Mhealth Uhealth       Date:  2020-05-26       Impact factor: 4.773

3.  Life- and person-centred help in Mecklenburg-Western Pomerania, Germany (DelpHi): study protocol for a randomised controlled trial.

Authors:  Jochen René Thyrian; Thomas Fiß; Adina Dreier; Georgia Böwing; Aniela Angelow; Sven Lueke; Stefan Teipel; Steffen Fleßa; Hans Jörgen Grabe; Harald Jürgen Freyberger; Wolfgang Hoffmann
Journal:  Trials       Date:  2012-05-10       Impact factor: 2.279

  3 in total

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