Literature DB >> 25586646

Measuring the Preferences of Homeless Women for Cervical Cancer Screening Interventions: Development of a Best-Worst Scaling Survey.

Eve Wittenberg1, Monica Bharel2,3,4, Adrianna Saada5, Emely Santiago2, John F P Bridges6, Linda Weinreb7.   

Abstract

OBJECTIVE: Despite having multiple risk factors, women experiencing homelessness are screened for cervical cancer at a lower rate than women in the general US population. We report on the design of a stated preference study to assess homeless women's preferences for cervical cancer screening interventions, to inform efforts to overcome this disparity.
METHODS: We conducted focus groups with homeless women (n = 8) on cervical cancer screening decisions and analyzed the data using thematic analysis. We applied inclusion criteria to select factors for a stated preference survey: importance to women, relevance to providers, feasibility, and consistency with clinical experience. We conducted pretests (n = 35) to assess survey procedures (functionality, recruitment, administration) and content (understanding, comprehension, wording/language, length).
RESULTS: We chose best-worst scaling (BWS)-also known as object scaling-to identify decision-relevant screening intervention factors. We chose an experimental design with 11 "objects" (i.e., factors relevant to women's screening decision) presented in 11 subsets of five objects each. Of 25 objects initially identified, we selected 11 for the BWS instrument: provider-related factors: attitude, familiarity, and gender; setting-related factors: acceptance and cost; procedure-related factors: explanation during visit and timing/convenience of visit; personal fears and barriers: concerns about hygiene, addiction, and delivery/fear of results; and a general factor of feeling overwhelmed.
CONCLUSION: Good practices for the development of stated preference surveys include considered assessment of the experimental design that is used and the preference factors that are included, and pretesting of the presentation format. We demonstrate the development of a BWS study of homeless women's cervical cancer screening intervention preferences. Subsequent research will identify screening priorities to inform intervention design.

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Year:  2015        PMID: 25586646      PMCID: PMC4501895          DOI: 10.1007/s40271-014-0110-z

Source DB:  PubMed          Journal:  Patient        ISSN: 1178-1653            Impact factor:   3.883


  26 in total

1.  Use of preventive services in a population of very low-income women.

Authors:  Allison L Diamant; Robert H Brook; Arlene Fink; Lillian Gelberg
Journal:  J Health Care Poor Underserved       Date:  2002-05

2.  Pap smear testing among homeless and very low-income housed mothers.

Authors:  Linda Weinreb; Robert Goldberg; Darleen Lessard
Journal:  J Health Care Poor Underserved       Date:  2002-05

3.  Conjoint Analysis Applications in Health - How are Studies being Designed and Reported?: An Update on Current Practice in the Published Literature between 2005 and 2008.

Authors:  Deborah Marshall; John F P Bridges; Brett Hauber; Ruthanne Cameron; Lauren Donnalley; Ken Fyie; F Reed Johnson
Journal:  Patient       Date:  2010-12-01       Impact factor: 3.883

Review 4.  Valuing citizen and patient preferences in health: recent developments in three types of best-worst scaling.

Authors:  Terry N Flynn
Journal:  Expert Rev Pharmacoecon Outcomes Res       Date:  2010-06       Impact factor: 2.217

5.  Cancer screening - United States, 2010.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2012-01-27       Impact factor: 17.586

Review 6.  The disparity of cervical cancer in diverse populations.

Authors:  Levi S Downs; Jennifer S Smith; Isabel Scarinci; Lisa Flowers; Groesbeck Parham
Journal:  Gynecol Oncol       Date:  2008-05       Impact factor: 5.482

7.  Universal health insurance and health care access for homeless persons.

Authors:  Stephen W Hwang; Joanna J M Ueng; Shirley Chiu; Alex Kiss; George Tolomiczenko; Laura Cowan; Wendy Levinson; Donald A Redelmeier
Journal:  Am J Public Health       Date:  2010-06-17       Impact factor: 9.308

8.  What is most important to patients when deciding about colorectal screening?

Authors:  Avlin Imaeda; Danielle Bender; Liana Fraenkel
Journal:  J Gen Intern Med       Date:  2010-03-23       Impact factor: 5.128

9.  Mortality among homeless adults in Boston: shifts in causes of death over a 15-year period.

Authors:  Travis P Baggett; Stephen W Hwang; James J O'Connell; Bianca C Porneala; Erin J Stringfellow; E John Orav; Daniel E Singer; Nancy A Rigotti
Journal:  JAMA Intern Med       Date:  2013-02-11       Impact factor: 21.873

10.  Best--worst scaling: What it can do for health care research and how to do it.

Authors:  Terry N Flynn; Jordan J Louviere; Tim J Peters; Joanna Coast
Journal:  J Health Econ       Date:  2006-05-16       Impact factor: 3.883

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  9 in total

1.  Art and Science of Instrument Development for Stated-Preference Methods.

Authors:  Ellen M Janssen; John F P Bridges
Journal:  Patient       Date:  2017-08       Impact factor: 3.883

2.  The Best of Both Worlds: An Example Mixed Methods Approach to Understand Men's Preferences for the Treatment of Lower Urinary Tract Symptoms.

Authors:  Divine Ikenwilo; Sebastian Heidenreich; Mandy Ryan; Colette Mankowski; Jameel Nazir; Verity Watson
Journal:  Patient       Date:  2018-02       Impact factor: 3.883

3.  Using Best-Worst Scaling to Understand Patient Priorities: A Case Example of Papanicolaou Tests for Homeless Women.

Authors:  Eve Wittenberg; Monica Bharel; John F P Bridges; Zachary Ward; Linda Weinreb
Journal:  Ann Fam Med       Date:  2016-07       Impact factor: 5.166

4.  Instrument Development in Choice Experiments. Commentary on: "Applying a Framework for Instrument Development of a Choice Experiment to Measure Treatment Preferences in Type 2 Diabetes".

Authors:  Eve Wittenberg
Journal:  Patient       Date:  2016-10       Impact factor: 3.883

5.  A Framework for Instrument Development of a Choice Experiment: An Application to Type 2 Diabetes.

Authors:  Ellen M Janssen; Jodi B Segal; John F P Bridges
Journal:  Patient       Date:  2016-10       Impact factor: 3.883

Review 6.  Using Best-Worst Scaling to Investigate Preferences in Health Care.

Authors:  Kei Long Cheung; Ben F M Wijnen; Ilene L Hollin; Ellen M Janssen; John F Bridges; Silvia M A A Evers; Mickael Hiligsmann
Journal:  Pharmacoeconomics       Date:  2016-12       Impact factor: 4.981

7.  It's hard to reach the "hard-to-reach": the challenges of recruiting people who do not access preventative healthcare services into interview studies.

Authors:  Lauren Rockliffe; Amanda J Chorley; Laura A V Marlow; Alice S Forster
Journal:  Int J Qual Stud Health Well-being       Date:  2018-12

8.  Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview.

Authors:  Axel C Mühlbacher; Anika Kaczynski; Peter Zweifel; F Reed Johnson
Journal:  Health Econ Rev       Date:  2016-01-08

9.  Utilising Patient and Public Involvement in Stated Preference Research in Health: Learning from the Existing Literature and a Case Study.

Authors:  Gemma E Shields; Lindsey Brown; Adrian Wells; Lora Capobianco; Caroline Vass
Journal:  Patient       Date:  2021-07       Impact factor: 3.883

  9 in total

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