Assessing Usual Seasonal Depression Symptoms: The Seasonality Assessment Form

Michael A. Young*, Paul Hutman, Justin L. Enggasser, Ybe Meesters

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    10 Citations (Scopus)


    This paper presents findings on the psychometric properties of a new measure of the usual severity of winter symptomatology commonly found in Seasonal Affective Disorder (SAD), the Seasonality Assessment Form (SAF). Many existing SAD-related measures focus on diagnostic screening, include a limited range of symptoms or are revisions of standard self-report depression measures that have not undergone psychometric evaluation. The SAF was developed to address these limitations, in particular to include the full range of cognitive, affective, and vegetative symptoms that are in DSM criteria for a depressive episode. Data came from a diverse sample of 741 students, community members recruited for having winter vegetative changes, and diagnosed SAD patients. The SAF total score, as well as vegetative and cognitive/affective subscales, exhibited good internal consistency and convergent and construct validity. The SAF demonstrated a bifactor structure, suggesting a large global severity factor and additional subfactors related to appetite/weight and negative thought content. Symptomatic participants reported relatively high levels of impairment in daily activities, in particular avoiding or delaying doing daily tasks. In sum, the SAF appears to be a concise, comprehensive, reliable, and valid measure of SAD symptom severity. In addition, its instructions can be revised easily to provide parallel forms for assessing the current episode or recent weeks.

    Original languageEnglish
    Pages (from-to)112-121
    Number of pages10
    JournalJournal of Psychopathology and Behavioral Assessment
    Issue number1
    Publication statusPublished - Mar-2015


    • Seasonal affective disorder
    • Seasonality
    • Depression
    • Symptom assessment
    • Factor analysis
    • Impairment
    • MOOD
    • MODELS
    • ONSET

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