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Things I’ve Tried to Measure Remo Ostini Healthy Communities Research Centre University of Queensland Australia.

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Presentation on theme: "Things I’ve Tried to Measure Remo Ostini Healthy Communities Research Centre University of Queensland Australia."— Presentation transcript:

1 Things I’ve Tried to Measure Remo Ostini Healthy Communities Research Centre University of Queensland Australia

2 Overview Community Based Health Organisation Activities Moral concepts Using Polytomous Item Response Theory models MEASURED PROGRESS – Jan. 2009: 2 of 18

3 Community Based Health Organisations “Self-help” organisations for people with chronic illnesses – Diabetes Australia – Arthritis Queensland Prospective survey, two time periods, 4 months apart PS1 N=323; PS2 N=306 respondents surveyed again MEASURED PROGRESS – Jan. 2009: 3 of 18

4 Asked nine questions at both surveys: Member of CBO? Estimate times phoned CBO Estimate times read newsletter or printed info Estimate times in seminar, workshop, info session Estimate times talked with other CBO members Estimate times attend CBO support group or social outing Estimate times volunteer with CBO Estimate times counselling, exercise, discount products Estimate times used CBO info raise others' awareness CBO Activities MEASURED PROGRESS – Jan. 2009: 4 of 18 Dimensionality?

5 CBO Activities Factor analysis suggested 1 or two factors Theory supported 2-factor structure Factor I: High intensity activities Factor II: Low intensity activities Qualitatively different, stage-like relationship MEASURED PROGRESS – Jan. 2009: 5 of 18

6 Rotated Factor Matrix Factor 12 Times attended a support group or social outing (T1) -Ordered.888 Times attended a support group or social outing (T2) -Ordered.786 Times helped as a CBO volunteer (T2) -Ordered.726 Times talked to another CBO member (T2) -Ordered.707 Times helped as a CBO volunteer (T1) -Ordered.694 Times talked to another CBO member (T1) -Ordered.668 Times attended a CBO seminar (T2) -Ordered.461 Ordered membership (T1) response variable.716 Ordered membership (T2) response variable.690 Times read a CBO newsletter (T1) -Ordered.551 Times used CBO counselling, products or other service (T1) -Ordered.519 Times used CBO counselling, products or other service (T2) -Ordered.477 Times used CBO info to raise others' awareness (T1) -Ordered.401 Times read a CBO newsletter (T2) -Ordered.383 Times phoned a CBO (T2) -Ordered.331 Times attended a CBO seminar (T1) -Ordered.313 Times phoned a CBO (T1) -Ordered.302 Times used CBO info to raise others' awareness (T2) -Ordered.294 Factor 1: High Intensity Activities; Factor 2: Low Intensity Activities MEASURED PROGRESS – Jan. 2009: 6 of 18

7 Model  Partial Credit model Results – All items together (assume one dimension); both time periods ( items) -- 5 items with poor fit (< 0.001) IRT Results – Scaled together MEASURED PROGRESS – Jan. 2009: 7 of 18

8 Results – Low Intensity Activity items both time periods - 2 items with poor fit – Low Intensity Activity items PS1 - 2 items with poor fit – No High Intensity Activity items with poor fit (at both times or PS1) Really just want  for further analyses IRT Results – Scaled separately MEASURED PROGRESS – Jan. 2009: 8 of 18

9 Comparing Organisations Recruiting Organisation Low Intensity Activities PS1 & PS2 Low Intensity Activities PS1 High Intensity Activities PS1 & PS2 High Intensity Activities PS1 Diabetes Australia Arthritis Queensland Ankylosing Spondylitis Group of Queensland Heart Support Australia Hepatitis Council of Queensland Arthritis Friendship Group Queensland Renal Association Total Diabetes Aus and Arthritis QLD significantly different on low intensity activities MEASURED PROGRESS – Jan. 2009: 9 of 18 Mean  across activities and time periods

10 Predicting PAM Independent variables95% CI B Lower bound Upper bound P-value Age Gender Highest educational qualification Type of illness Low intensity activities High intensity activities SF12 Physical component <0.001 SF12 Mental component PAM = Patient Activation Measure; a self-report measure of patient confidence in managing their own health MEASURED PROGRESS – Jan. 2009: 10 of 18

11 Moral Conceptualization Initial question: What is morality? Lots of answers. Who knows? Everyone! So ask them… MEASURED PROGRESS – Jan. 2009: 11 of 18

12 Moral Conceptualization - Background 20 Interviews – talkative people 1269 statements – some (~ half) redundant 4 × 150 item questionnaires - MCS  5-point Likert scale (1 – Nothing like what you think; 5 – Exactly what you think) MEASURED PROGRESS – Jan. 2009: 12 of 18

13 Moral Conceptualization - Background Example statements: – Caring about others is the dominant feature of a good person – Everyone is born good – Evil does exist and people can do it – The boundaries between right and wrong are defined by social custom What aspects of morality does the questionnaires cover? MEASURED PROGRESS – Jan. 2009: 13 of 18

14 Moral Conceptualization Structural Analysis Data Screening – bound to be noise Four linear analyses: – Principal Components Analysis – Factor Analysis – Multidimensional Scaling – Cluster Analysis One non-linear analysis Mokken scaling analysis – nonparametric IRT with h test for dimensionality assessment factors MEASURED PROGRESS – Jan. 2009: 14 of 18

15 Moral Conceptualization Structural Analysis Types of Factors – Life definition – Relativism – Responsibility – Socially defined morality – Conscience – Tolerance MEASURED PROGRESS – Jan. 2009: 15 of 18

16 Moral Conceptualization Item Analysis Item-total correlations < 0.20 Serious skew (some items still useful?) IRT for Item analysis Partial Credit Model Reversed boundaries  Evidence of a problem? Item model fit  p <0.001 Too soon for information? MEASURED PROGRESS – Jan. 2009: 16 of 18

17 Moral Conceptualization Construct Validity Concurrent validity – Personality (Agreeableness & Conscientiousness related to Relativism) – Internal State Awareness – multiple MCS – Liberalism & Conservatism – some MCS – Multiple Social Values – multiple MCS – Not Emotional Intelligence; Empathy; Guilt; Religion Predictive validity – Predicting moral judgements? MEASURED PROGRESS – Jan. 2009: 17 of 18

18 Moral Conceptualization Construct Validity Next? – Reduced number of questionnaires with best items from first four – More sophisticated test development, scoring and validation… MEASURED PROGRESS – Jan. 2009: 18 of 18


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