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Aim: To identify key predictors of GP satisfaction and increase insight into the mechanisms behind ethnic health inequities in New Zealand.
Method: Regression analyses were conducted using data from the 2019 New Zealand Attitudes and Values Study (N = 38, 465). 
Results: Initially, Māori and Asian peoples showed lower, and Pacific peoples showed no significant difference in GP satisfaction level relative to New Zealand (NZ) Europeans. However, after accounting for differences in patient-perceived GP cultural respect and GP ethnic similarity, Māori and Pacific peoples showed higher and Asian peoples showed no difference in GP satisfaction level relative to NZ Europeans. These effects continued to hold when adjusting for a range of demographic factors. Subsequent regression analyses were conducted to investigate the impact of GP perceptions, GP satisfaction and demographic factors on healthcare access satisfaction and health status across ethnic groups. For all ethnic groups, GP satisfaction was the strongest predictor of satisfaction with access to healthcare. Higher GP satisfaction was also a significant predictor of higher self-rated health and lower psychological distress.
Conclusion: Lack of GP cultural respect is a key contributor to lower GP satisfaction among ethnic minorities, which can further exacerbate disproportionate health outcomes. GP provision of culturally respectful and safe healthcare may help reduce ethnic health inequities and improve population health.

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Ethnic group differences in patient satisfaction with GP services: Findings from the New Zealand Attitudes and Values Study

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The data described in the paper are part of the New Zealand Attitudes and Values Study (NZAVS). Full copies of the NZAVS data files are held by all members of the NZAVS management team and advisory board. A de-identified dataset containing the variables analysed in this manuscript is available upon request from the corresponding author, or any member of the NZAVS advisory board for the purposes of replication or checking of any published study using NZAVS data. The Mplus syntax used to test all models reported in this manuscript are available on the NZAVS OSF: https://osf.io/75snb/

The NZAVS data are not available publicly. This is because the information and consent form for the NZAVS assured participants that anonymized data from the study would be shared specifically on a case-by-case basis. The exact statement is: ‘Your questionnaire data is therefore anonymised, and Prof. Chris Sibley and other members of the NZAVS research team will have access to an electronic encrypted copy of your anonymous questionnaire data. This anonymous data file may also be shared with other competent professionals on a case-by-case basis for research purposes.’