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Updated: Mar 21, 2026

A New Method for Inducing a Depression-Like Behavior in Rats
Published on: February 22, 2018
Factors contributing to depressive mood states in everyday life: A systematic review
Rachel Pemberton1, Matthew D Fuller Tyszkiewicz1
1School of Psychology, Deakin University, Australia.
Background:
Although accumulated evidence suggests that fluctuations in depressed mood are common among individuals with depression, and may be associated with onset, duration, and severity of illness, a systematic appraisal of putative predictors of depressed mood is lacking.
Methods:
A systematic search for relevant studies in the literature was conducted using PsycInfo and PubMed databases via EbscoHost in February 2016. The search was limited to articles using the experience sampling method, an approach suitable for capturing in situ fluctuations in mood states.
Results:
Forty-two studies met inclusion criteria for the review, from which three key risk factors (poor sleep, stress, and significant life events) and two protective factors (physical activity and quality of social interactions) were identified. The majority of papers supported concurrent and lagged associations between these putative protective/risk factors and depressed mood.
Limitations:
Despite support for each of the proposed protective/risk factors, few studies evaluated multiple factors in the same study. Moreover, the time course for the effects of these predictors on depressed mood remains largely unknown.
Conclusions:
The present review identified several putative risk and protective factors for depressed mood. A review of the literature suggests that poor sleep, negative social interactions, and stressful negative events may temporally precede spikes in depressed mood. In contrast, exercise and positive social interactions have been shown to predict subsequent declines in depressed mood. However, the lack of multivariate models in which the unique contributions of various predictors could be evaluated means that the current state of knowledge prevents firm conclusions about which factors are most predictive of depressed mood. More complex modeling of these effects is necessary in order to provide insights useful for clinical treatment in daily life of the depressed mood component of depressive disorders.
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