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Why self-report variables inter-correlate: the role of Homeostatically Protected Mood (HPMood)
journal contributionposted on 01.12.2018, 00:00 authored by Robert CumminsRobert Cummins, Tanja CapicTanja Capic, Matthew Fuller-TyszkiewiczMatthew Fuller-Tyszkiewicz, Delyse HutchinsonDelyse Hutchinson, Craig OlssonCraig Olsson, Ben Richardson
This manuscript provides systematic insight into the automatic correlations between positively-valenced, self-report variables that are typically used to measure subjective wellbeing. The theoretical basis for this study is the Theory of Subjective Wellbeing Homeostasis. This theory, in turn, rests on: (1) an assumption of genetically-determined set-points for subjective wellbeing and, (2) the existence of a composite affect, called Homeostatically Protected Mood (HPMood), as the phenotypic product of each set-point. HPMood perfuses all self-report variables to an extent predicted by each variable’s relationship to the self on the dimensions of proximal-distal and abstract-specific. Because HPMood is an individual difference, the extent of perfusion shared by any two variables strongly influences the magnitude of their correlation. These assumptions are empirically tested through six hypotheses, using data from two, independent, general population samples of Australian respondents. The results generally support the predictions of homeostasis theory and draw attention to the potential for HPMood to be a biasing – yet theoretically predictable factor in self-report data.