Levine et al. Study summary

Question 1

Procedure

Answer 1

• three sets of data was collected in each city using 3 different measures of helping behaviour
• the helping behaviour for each measure was given a Z-score of helpfulness, then averaged out for the helpfulness of the city overall
• The Z-score / stand score is a statics that tells us where a score lies in relation to the population mean
  negative = below the mean
  positive = above

Question 2

Aim

Answer 2

1. To investigate cultural differences in helping behaviour
2. To explore the influence of socioeconomic factors
3. To analyse the impact of situational variables

Question 3

Methodology

Answer 3

• Quasi experiment and Field experiment
  Independent variable: country / city
  Control variables: population size, economic prosperity, cultural values, “Pace of life”
  Dependent variable: The frequency of help across 3 measures

Question 4

Sample

Answer 4

1. 23 counties that were spread across the continents
2. they chose the largest city or another major city in each country chosen
3. each city has been treated as a single subject

Question 5

Materials

Answer 5

1. Props for scenario: pen, magazine, white cane
2. recording equipment
3. trained local assistants
4. demographic data collection tools

Question 6

Results

Answer 6

OVERALL
City rankings - big differences in terms of helping. from 93% in Brazil to 40% in Malaysia
Consistency across helping measures - 2/3 measures of helping had a big correlation
Gender differences - there were no big differences found to be recorded

Question 7

Conclusion

Answer 7

• You are more likely to receive help in a non-emergency situation in a country with a weaker economy
• You are more likely to receive help in a non-emergency situation in a Simpatia country