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Journal of Population Sciences

Table 1 Factor loadings of items for attitudes, subjective norms and perceived behavioural control for childless respondents

From: Childbearing intentions in a low fertility context: the case of Romania

 

Factor 1

Positive attitudes: benefits

Factor 2

Negative attitudes: costs

Factor 3

Perceived behavioural control

Factor 4

Subjective norms

“Suppose you will have a/another child during the next 3 years, would it be worse or better for...?”

 The possibility to do what you want

0.02

0.91

  

 Your employment opportunities

0.01

0.75

  

 Your financial situation

− 0.12

0.63

  

 What people around you think of you

0.61

− 0.13

  

 Joy and satisfaction you get from life

0.78

− 0.09

  

 The closeness between you and your partner/spouse

0.71

− 0.04

  

 The care and security you may get in old age

0.79

0.12

  

 Certainty in life

0.82

0.06

  

 The closeness between you and your parents

0.65

− 0.05

  

“How much would the decision on whether to have a/another child during the next 3 years depend on the following?”

 Your financial situation

  

0.79

 

 Your work

  

0.77

 

 Your housing conditions

  

0.77

 

 Your health

  

0.75

 

 You having a suitable partner

  

0.70

 

 Your partner’s/spouse’s work

  

0.74

 

 Your partner’s/spouse’s health

  

0.80

 

 Availability of childcare

  

0.64

 

“Others might think about you having a/another child during the next 3 years, do you disagree or agree with these statements?”

 Most of your friends think that you should have a/another child

   

0.89

 Your parents think that you should have a/another child

   

0.91

 Most of your relatives think that you should have a/another child

   

0.96

Cronbach alpha

0.84

0.75

0.89

0.94

KMO

 

0.83

0.87

0.76

RMSR

0.05

 

0.08

0

  1. Items with communalities less than 0.4 and with factor loadings over 0.5 were retained in the model; RMSR: the root mean square of the residuals; a value less than 0.08 is generally considered a good fit (Hu and Bentler 1999); KMO: Kaiser-Meyer-Olkin measure of sampling adequacy; values higher than 0.7 are generally considered good, suggesting sample size and data are appropriate for factor analysis
  2. Source: GGS, Romania 2005, own computations