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Table 3 Standardized item-to-factor correlations for structural model 1: children’s self-efficacy model (N = 857)

From: Children’s active commuting to school: an interplay of self-efficacy, social economic disadvantage, and environmental characteristics

Description

Latent factor/Observed variables

Factor loading

P-value

Types of children’s self-efficacy

Scheduling Self-efficacy (3 items)

  

I’m sure that I can walk to and from school:

  

At least once every week

.78 (.02)

.000

At least 2–4 days of the week

.87 (.02)

.000

Every day of the week

.91 (.02)

.000

Barrier Self-efficacy (6 items)

  

Even if I live far from school

.69 (.03)

.000

Even if there is a lot of traffic

.70 (.03)

.000

Even if it is hot outside

.83 (.02)

.000

Even if it is cold outside

.80 (.02)

.000

Even if it is raining outside

.77 (.03)

.000

Even if my friends or classmates do not walk to school

.87 (.02)

.000

Support-seeking Self-efficacy (4 items)

  

With my parents

.40 (.05)

.000

With my friends or classmates

.80 (.02)

.000

By myself

.91 (.01)

.000

Without my parents

.91 (.01)

.000

Sources of children’s self-efficacy

Emotional States (2 items)

  

Do you feel safe walking in your neighborhood during the day?

.83 (.05)

.000

Do you feel safe riding a bike in your neighborhood during the day?

.64 (.05)

.000

Social Persuasion (2 items)

  

Have your teachers or other school staff encouraged you to walk or ride to or from school?

.78 (.26)

.002

Does your school have a Walking School Bus or a similar program?

.38 (.12)

.003

Social Modeling (2 items)

  

Do many people walk or ride bikes in your neighborhood?

.44 (.06)

.000

How many of your friends usually walk or ride a bike to school?

.46 (.07)

.000

Social economic disadvantage

Number of assistance that a child’s family received

.47 (.09)

.000

Ethnicity (White or non-white)

.61 (.12)

.000

Environmental constraints

Percentage of highway (binary)

.64 (.09)

.000

Auto-related land use (binary)

.73 (.08)

.000

Construction and manufacturing land use (binary)

.46 (.07)

.000

General commercial land use (binary)

.68 (.07)

.000

Presence of crashes per acre (binary)

.31 (.08)

.001

Network distance

.87 (.07)

.000