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Journal of Population Sciences

Table 2 Factor loadings of items for attitudes, subjective norms and perceived behavioural control for one-child 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

0.92

  

 Your employment opportunities

− 0.01

0.77

  

 Your financial situation

− 0.16

0.53

  

 What people around you think of you

0.50

− 0.19

  

 Joy and satisfaction you get from life

0.74

− 0.09

  

 The closeness between you and your partner/spouse

0.72

− 0.04

  

 The care and security you may get in old age

0.78

0.11

  

 Certainty in life

0.83

0.02

  

 The closeness between you and your parents

0.73

0.00

  

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

 Your financial situation

  

0.73

 

 Your work

  

0.70

 

 Your housing conditions

  

0.71

 

 Your health

  

0.81

 

 You having a suitable partner

  

0.69

 

 Your partner’s/spouse’s work

  

0.72

 

 Your partner’s/spouse’s health

  

0.81

 

 Availability of childcare

  

0.66

 

“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

   

0.91

 Your parents think that you should have a/another child

   

0.90

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

   

0.99

Cronbach alpha

0.83

0.74

0.87

0.92

KMO

 

0.83

0.86

0,74

RMSR

0.04

 

0.1

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. Source: GGS, Romania, 2005, own computations