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The most popular scale used in agricultural extension research for measurement of attitudes, beliefs, emotions, feelings, perceptions and personality
The scale follows following steps
Define Construct
Design scale
Pilot Testing
Item Analysis
Standardization
Yates’ algorithm for 2n factorial experiment - Dr. Manu Melwin Joy - School o...manumelwin
In statistics, a Yates analysis is an approach to analyzing data obtained from a designed experiment, where a factorial design has been used. This algorithm was named after the English statistician Frank Yates and is called Yates' algorithm.
Case-control study is a variety of analytical studies. This is a brief presentation regarding history, design, issues, advantages - disadvantages and examples of Case-control study.
Presentation for Research Methodology
Please download the file and view the presentation.
Notes for each of the slides are present in the notes section
(Images used for representational purposes only)
This presentation gives a brief overview of what a case study is, the different types of case studies, the strengths, and weaknesses this method of investigation. It also includes an example of a case study, and how a it can be used in an investigation.
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#Gamification is the strategy of transforming mundane daily activities into a fun, engaging and a motivating activity.
The process of incorporating gaming constructs such as
rules, actions and challenges create a gamification platform
to transform a mundane task as engaging in Physical Activity for health wellness and fitness goals.
Engaging in a fitness or physical activity is a mundane activity, which can be transformed into a fun activity through Gamification
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How should we measure habit? (And does it matter?)
1. How should we
measure habit?
(And does it matter?)
Benjamin Gardner Sood
Health Behaviour Research Centre, UCL
b.gardnersood@ucl.ac.uk
23rd April 2012
3. Conceptualisations of habit
• “Learned sequences of acts that have become
automatic responses to specific cues”
(Verplanken & Aarts, 1999; also Hull, 1943; James, 1890)
• Learned
– through context-dependent repetition (Lally et al, 2010)
• Cue-dependent
• Automatic 3
4. Habitual versus intentional behaviour
Habitual behaviour Intentional behaviour
Bottom-up Top-down
Directly cued Consciously mediated
Impulsive Deliberative
Does not require intention Requires intention
Effortless initiation Effortful initiation
4
5. Habit-behaviour effects (in associated contexts)
Triandis (1977)
1. Habit strength will be associated with behaviour
frequency
2. Habit strength will moderate the intention-
behaviour relationship:
- where habit is strong, intentions have weakened
impact on behaviour
- where habits and intentions conflict, behaviour more
likely to be habitual than intentional
5
7. Automaticity is the essence of habit
Gardner (in press); Sniehotta & Presseau (2012)
1. Habit strength will be associated with behaviour
frequency
… because stronger cue-response automaticity
is more likely to prompt behaviour
2. Habit strength will moderate the intention-
behaviour relationship
… because habits are more immediately
enacted than are intentions 7
8. How to measure habit?
• Self-reporting habit is problematic
– Different interpretations of word ‘habit’
– Can people reliably reflect on automatic actions? (Eagly
& Chaiken, 1993)
• Past behaviour?
– Correlates with future behaviour
– Often moderates intention-behaviour relation (e.g.
Norman & Conner, 2006)
– Captures only behavioural stability
– And stable determinants of behaviour
8
– These determinants may or may not include habit
9. How to measure habit?
Objective measures?
• Response times
– Faster = more cognitively accessible = habitual
– Cannot distinguish between habit and rapid deliberation
• Implicit associations
– E.g. lexical decision tasks (‘gym’ > ‘running’)
– Word cues (‘gym’) may not capture real-world cues (the
physical gym location)
9
10. How to measure habit?
The Self-Report Habit Index
Verplanken & Orbell (2003)
• 12 items
• Incorporates
– Automaticity
– Behavioural frequency
– Self-identity relevance
10
12. SRHI appears adequate
• Reliable (alpha >.90)
• Single-factor structure
• Convergent validity with existing measures
(Verplanken et al, 2005)
• Moderates intention-behaviour relationship
(e.g. Gardner, de Bruijn & Lally, 2011)
• Assumes people can be aware on reflection that
they were not aware when performing behaviour
(Gardner, Abraham, Lally & de Bruijn, under review)
14. Is identity a necessary component of habit?
“[H]abits are part of how we organize everyday life and
thus might reflect a sense of identity or personal style. We
thus assumed that although this might not hold for all
habits, at least some might be descriptive of a person and
thus express someone’s identity.”
Verplanken & Orbell (2003, p1317; emphasis added)
14
15. Is identity necessary in the SRHI?
Gardner, de Bruijn & Lally (in press)
• SRHI tests are biased against extraction of
identity as separate factor:
– Cronbach’s alpha increases with item quantity
– Factor analysis criterion (eigenvalue > 1) not useful
where one true factor is loaded on by only one item
15
16. Is identity necessary in the SRHI?
Gardner, de Bruijn & Lally (in press)
• What happens when SRHI is augmented with 4
additional self-identity items?
• SRHI: ‘Drinking more than 8 units on one
occasion is something that’s typically “me”’
• Identity: ‘It would be out of character for me not to
drink more than 8 units on one occasion’
Sparks & Shepherd (1992)
16
17. Is identity necessary in the SRHI?
Gardner, de Bruijn & Lally (in press)
• N = 167 UK students
• Prospective design
– Habit, identity, TPB measured at baseline
– Number of binge-drink sessions reported one week later
• Best model in confirmatory factor analysis:
– SRHI (minus ‘typically me’ item) = Factor 1
– Identity (‘typically me’ SRHI item + 4 items) = Factor 2 17
18. Integrating habit and identity into TPB
Gardner, de Bruijn & Lally (in press)
• Identity:
– predicted intention, not behaviour
• Habit:
– predicted behaviour, not intention
– moderated intention-behaviour relationship
(but in ‘wrong’ direction!)
18
19. What does frequency add to the SRHI?
• A crude proxy for context-dependent repetition
• Conceptual error (Gardner, in press)
– Once formed, habits need not be frequently performed
– Habit will be elicited only as frequently as cue is
encountered
• e.g. habits for eating popcorn in cinema are only elicited when
visiting the cinema
19
20. What does frequency add to the SRHI?
• Methodological error
– Frequency is not directly responsible for habit-
behaviour effects (Gardner, in press)
• May capture habit and non-habit influences on
behaviour (Ajzen, 2002)
• Can habit-behaviour effects be captured by
automaticity alone?
20
21. Content validation of SRHI
Gardner, Abraham, Lally & de Bruijn (under review)
Aim: To systematically extract parsimonious subset
of automaticity items
- Discriminant content validity (Pollard & Johnston, 2005)
- 7 participants asked to rate extent to which each
SRHI item met definitions of automaticity, identity
and frequency
- Yes (+1) vs No (-1)
- Confidence (0-10) 21
22.
23. Content validation of SRHI
Gardner, Abraham et al (under review)
• Of 12 items:
– 3 not consensually thought to measure automaticity,
frequency, or identity
• ‘makes me feel weird if I do not do it’
• ‘something that belongs to my (daily, weekly, monthly) routine’
• ‘I have been doing a long time’
– 1 judged to measure frequency (‘I do frequently’)
– 1 judged to measure identity (‘typically “me”’)
– 7 judged to measure automaticity
23
24. Content validation of SRHI
Gardner, Abraham et al (under review)
• All judges 90+% confident that four items
measured automaticity:
– “I do automatically”
– “I do without having to consciously remember”
– “I do without thinking”
– “I start doing before I realise I’m doing it”
= ‘Self-Report Behavioural Automaticity Index’
24
(SRBAI)
25. Criteria for assessing the SRBAI
Gardner, Abraham et al (under review)
• Criteria?
– Reliability (alpha) & convergent validity
– Least worst option is to evaluate against well-developed
theoretical criteria
• Correlation with behaviour
• Moderation of intention-behaviour relationship
• Because of removal of behavioural frequency
items…
– Correlation: SRBAI-behaviour r < SRHI-behaviour r
25
– Moderation: More clearly detected using SRBAI
26. Data sources
Gardner, Abraham et al (under review)
Secondary data
• Systematic database search
• (47) papers citing Verplanken & Orbell (2003)
• Corresponding authors asked to reanalyse using
SRBAI
– Reliability (45 tests)
– Habit-behaviour correlations (28 tests)
– Moderation tests (7 tests)
26
27. Data sources
Gardner, Abraham et al (under review)
Primary data
• Four datasets
– Inactive (car) and active (bicycle) commuting
– Snacking (habit vs intention conflict)
– Alcohol consumption with evening meal (habit incl.
potential context cue)
• Comparison of SRBAI with SRHI and 8-item ‘non-
SRBAI’ scale
27
28. Secondary data analyses
Gardner, Abraham et al (under review)
Reliability:
• 40 tests showed SRBAI alpha >=.80
Meta-analysis of correlations:
• SRHI-SRBAI, r = .92***
• SRBAI-behaviour, r = .42*** Z for
difference =
• SRHI-behaviour, r = .47*** 14.40***
28
29. Secondary data analyses
Gardner, Abraham et al (under review)
Moderation:
• 4 tests: SRBAI and SRHI both found moderation
• 1 test: Neither SRBAI nor SRHI found moderation
• 1 test: SRHI found moderation, SRBAI did not
• 1 test: SRBAI detected tendency (p=.052; in
‘wrong’ direction), SRHI did not 29
30. Primary data analyses
Gardner, Abraham et al (under review)
Reliability:
• SRBAI alpha >.80
Correlations:
• SRHI, SRBAI and non-SRBAI correlated >=.90
• 3 datasets: rSRBAI-bhvr < rSRHI-bhvr
• 1 dataset: rSRBAI-bhvr = rSRHI-bhvr
30
31. Primary data analyses
Gardner, Abraham et al (under review)
Moderation tests:
• Commuting: SRBAI, SRHI and non-SRBAI found
moderation
• Snacking: No habit index found moderation
• Alcohol consumption: SRBAI found moderation,
SRHI and non-SRBAI did not
31
32. Conclusions of SRBAI tests
Gardner, Abraham et al (under review)
• SRBAI more conceptually precise & parsimonious
• As sensitive to hypothesised moderation
• Lower correlation with bhvr, due to removal of
potential noise
• Repetition history items only needed to demarcate
habit from other automatic actions
32
33. Habit measurement matters!
• Measurement precision is crucial
• Developments in habit theory and application
depend on adequate measures of habit
• Inadequate measures may misdirect development
33
34. Towards better habit measurement
Cue-relatedness
• Cues can be incorporated into SRHI/SRBAI
– ‘Drinking alcohol with the evening meal’
• But if ‘wrong’ cue is chosen, habit will not be
detected
vs
• Context-free habit measures
– ‘Drinking alcohol’
• (Probably) captures only reflection on overall
automaticity across contexts 34
35. Towards better habit measurement
Study design
• Group-level data are limited
– Cues and responses are idiosyncratic
– What does moderation of intention-behaviour
relationship at group level mean?
• Individual-level studies needed (e.g. N-of-1)
• Group-level studies should be seen as pilot data
– Effects need to be explored further at individual-level 35
36. Towards better habit measurement
Is self-report adequate?
• Still largely unclear whether people can accurately
reflect on habits
• SRBAI (and SRHI) require validation against
‘objective’ measures
• We should be open to new measures (e.g. in-situ
observations)
36
37. Thank you!
b.gardnersood@ucl.ac.uk
Key references:
Gardner (in press [June 2012]) Habit as automaticity, not frequency. European
Health Psychologist.
Gardner, Abraham, Lally & de Bruijn (under review)
Gardner, de Bruijn & Lally (in press) Habit, identity and repetitive action: A
prospective study of binge-drinking in UK students. Brit J Health Psychol.
Gardner, de Bruijn & Lally (2011) A systematic review and meta-analysis of
applications of the Self-Report Habit Index to nutrition and physical activity
behaviors. Annals of Behav Med, 42, 174-187.
Sniehotta & Presseau (2012) The habitual use of the Self-Report Habit Index.
Annals of Behav Med, 43, 139-140.
37