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Table 3 Primary datasets: Habit indices as correlates of behaviour and moderators of intention-behaviour relationship in four primary datasets

From: Towards parsimony in habit measurement: Testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index

Source N† Behaviour Habit Intention Habit index (α) Correlations†† Moderation of intention-behaviour relationship
SRHI-SRBAI Habit-RFM Habit-behaviour Model R 2††† Significance of moderation effect†††† (p) Intention-behaviour β
Weak or no habit Moderate habit Strong habit
Dataset 1: ( [16], Study 1) 105 Inactive (car) commuting “Using a car to commute to campus” “To use a car to commute to campus on most days” SRHI (.95) .94 .52 .82a .75 .001 .54*** .27* .01
SRBAI (.92) .52 .76b .75 <.001 .69*** .41*** .12
Non-SRBAI (.91) .49 .81a .73 .01 .57*** .37** .16
Dataset 2: ( [16], Study 2) 102 Active (bicycle) commuting “Using a bicycle to commute to campus” “To use a bicycle to commute to campus on most days” SRHI (.95) .97 .67 .86 a .77 .04 .16 .02 -.12
SRBAI (.93) .65 .86 a .77 .04 .21* .08 -.05
Non-SRBAI (.91) .67 .84 a .74 .04 .26** .12 -.02
Dataset 3: New dataset 188 Unhealthy snacking “Eating high-calorie snacks” “To avoid high-calorie snacks” SRHI (.89) .90 - .50a .26 .89    
SRBAI (.84) - .42b .19 .35    
Non-SRBAI (.81) - .50a .27 .95    
Dataset 4: New dataset 204 Alcohol consumption with the evening meal “Drinking an alcoholic drink with my evening meal” “To drink an alcoholic drink with my evening meal” SRHI (.89) .95 - .80 a .68 .14    
SRBAI (.84) - .75 b .64 .02 .56*** .46*** .35***
Non-SRBAI (.81) - .80 a .68 .18    
  1. *p < .05, ** p < .01, *** p < .001. Further details and analyses of all datasets are available on request from the first author.
  2. Ns are reduced for correlations with RFM in Datasets 1 (N = 102) and 2 (N = 99) due to missing RFM data.
  3. †† Differing superscript letters in ‘habit-behaviour’ column indicate differences in the magnitude of habit-behaviour correlations at p < .05 (see [37]). Correlations with the transport-specific RFM were only available in Datasets 1 and 2. All correlations significant at p < .01.
  4. ††† All regression models were significant at p < .001.
  5. †††† ‘Moderation effect’ refers to the predictive impact of a means-centred habit x intention interaction term on behaviour, controlling for habit and intention as independent predictors. Simple slope coefficients are provided for significant moderation effects only (p < .05).