Model　checking　is　essential　for　making　reliable　statistical　inferences.　For　massive　datasets,　we　develop　a　new　distributed　method　for　testing　parametric　single-index　models　by　integrating　the　divide　and　conquer　strategy　into　the　dimension　reduction　model-adaptive　(DRMA)　test.　A　distributed　method　for　the　determination　of　the　structural　dimension　is　also　proposed.　The　asymptotic　behaviors　of　the　proposed　test　statistic　under　the　null　and　alternative　model　are　derived,　which　shows　that　the　proposed　test　has　the　same　limiting　behavior　of　the　DRMA　test　based　on　the　entire　dataset.　In　addition,　the　proposed　test　achieves　adaptive　rate-optimality　using　the　sample-splitting　strategy　for　selecting　bandwidth.　Our　simulation　results　and　a　data　illustration　demonstrate　that　the　proposed　test　performs　better　than　the　existing　tests　for　massive　datasets,　especially　when　the　dimension　of　covariates　is　large.　©　2023　Elsevier　B.V.