Abstract
BackgroundAfter conducting necessary condition analysis (NCA), researchers have concluded that a certain, not too low, level of well-being is necessary but not sufficient for a high level of resilience. However, as acknowledged by the developers of the test, NCA only evaluates if the association between two variables is characterized by some unspecified type of non-randomness and not conditions of necessity.MethodEarlier reported data on the association between well-being and resilience among Filipino adults (N = 533) in COVID-19 quarantine were re-analyzed with an extended version of NCA.ResultsAnalyses indicated a significant necessity effect of resilience on overall well-being, which is not logically compatible with well-being being necessary but not sufficient for resilience. Analyses with an extended version of NCA suggested that the association between overall well-being and resilience was characterized by equal degrees of necessity and sufficiency.ConclusionsThe original version of NCA is only capable of evaluating if the association between two variables is characterized by some unspecified type of non-randomness. The extended version of NCA allows researchers to draw more specific conclusions.
Highlights
According to rules of logic, if a condition X is necessary but not sufficient for another condition Y, there are no instances where X is absent and Y is present, but there are instances where X is present and Y is absent
We did not include measures of negative emotions, physical health, and loneliness used by Camitan and Bajin in the present study, as these had no significant necessity effect on resilience
The present findings suggested that the conclusion by Camitan and Bajin [16], that well-being is necessary but not sufficient for resilience, may be unwarranted
Summary
According to rules of logic, if a condition X is necessary but not sufficient for another condition Y, there are no instances where X is absent and Y is present, but there are instances where X is present and Y is absent. As there are instances where X is present and Y is absent, if X is necessary but not sufficient for Y, Y cannot, at the same time, be necessary for X. Necessary condition analysis (NCA) is a method that was originally developed to help researchers identify conditions that are necessary but not sufficient for some outcome of interest [1]. According to the logic of the test, the size of the empty space in the upper-left corner when plotting two variables, X and Y, against each other indicates to what degree a low value on X precludes a high value on Y, i.e. to what degree X is necessary for Y [1]. After conducting necessary condition analysis (NCA), researchers have concluded that a certain, not too low, level of well-being is necessary but not sufficient for a high level of resilience. As acknowledged by the developers of the test, NCA only evaluates if the association between two variables is characterized by some unspecified type of non-randomness and not conditions of necessity
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