1 / 16

Investigating the prevalence and distribution of views across the UK population

Extending life for people with a terminal illness: a moral right or an expensive death? Empirical and Methodological issues. Investigating the prevalence and distribution of views across the UK population. Helen Mason ECHE Dublin 14 th July 2014. Objectives.

keefe-huber
Download Presentation

Investigating the prevalence and distribution of views across the UK population

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Extending life for people with a terminal illness: a moral right or an expensive death? Empirical and Methodological issues Investigating the prevalence and distribution of views across the UK population Helen Mason ECHE Dublin 14th July 2014

  2. Objectives To identify and describe societal perspectives on the (relative) value of end of life technologies by eliciting the views of both members of the public and experts in relevant fields; To develop methods to investigate the distribution of those views, including their association with other characteristics, in a nationally representative sample of the UK general public.

  3. From ‘describing’ to ‘measuring’ using Q techniques What is the purpose of Q survey methods To understand how many people within a larger population hold these views, to what extent, and do they relate to any other characteristics Could not (would not) complete Q sorting with a larger number of people From Q methodology to Q survey “Q2S”

  4. What are Q survey methods? Derived from the factor solution of an existing Q study Number of potential survey approaches e.g. small number of carefully selected statements short descriptions of factors Respondents indicate strength of agreement using ranking or Likert scale methods Connecting Q factors and surveys

  5. Survey Design “Approach 1 – Individual Item Likert Scale” • Original Q study = 49 statements, 3 factors • How can we best represent our 3 factors from a smaller number of statements • Selection of Statements which are distinguishing and salient for each factor • 18 statements selected from the original 49 – 6 per factor • Rating each statement between 1 (completely disagree) and 7(completely agree)on a Likert Scale

  6. Survey Design – Statements • Factor 1

  7. Survey Design – Statements • Factor 2 “20. We all have the right to life” • Factor 3 “41. I wouldn’t want my life to be extended just for the sake of it - just keeping breathing is not life”

  8. Survey Administration • Online survey conducted in the UK (May 2014) • 3 versions • Introductory Video (all) • (Up to) 3 Q survey approaches • Policy Choice and Social Value Orientation questions (2 versions) • Demographic questions (all)

  9. Sample • Quota sampled to be nationally representative of the UK population based on: • Age • Gender • Socioeconomic status • Ethnicity • N = 4412 (all 3 versions)

  10. Analysis • Reliability analysis of 6 statements representing each factor • Remove 1 statement representing F3 from further analysis • Sum Likert scores for each block of statements • Rescale scores on 0-10 scale (intensity score) to account for different possible max and min score on each Factor

  11. Summary Data

  12. Assigning Factor Membership • Each respondent will be associated with each factor to some extent (will score something between 0-10 on each factor) • In the first instance we set up rules to assign people to the factors • ‘Generous’ rule – assignment to factor if respondents intensity score for an individual factor is greater than the median intensity score for that factor

  13. Assigning Factor Membership • First stage • F1 – intensity score > 6.39 • F2 - intensity score > 6.67 • F3 - intensity score > 5.00 • Not mutually exclusive categories – can have a score higher than on the median on each factor • Can we tease out where people are “pure” factor members?

  14. Assigning Factor Membership Mixed factors – intensity score is higher than the median on more than one factor

  15. Discussion of factor membership • High number of respondents mixed Factor 1/Factor 3 • Not unexpected given correlations between F1 and F3 in original Q sort • More than one viewpoint exists with the UK population • More than just a ‘patient viewpoint’ • Utilitarian view is a common view (approx 45% if including F1, F3, F1/3)

  16. Next steps • Other ‘rules’ to assign respondents to factors • How to make best use of the intensity scores • Examining the data from the other 4 approaches (ranking/rating/choice tasks) • Assessing the Feasibility, Reliability and Validity of each of the 5 approaches • Association with demographics, attitudinal questions and Policy Choice questions

More Related