Suicidality and Mood: The Impact of Trends, Seasons, Day of the Week, and Time of Day on Implicit and Explicit Cognitions

Abstract

Decades of research have established seasonality effects on completed and attempted suicides, with an increase in rates during spring and early summer. Using more than six years of data (April 2012 – November 2018), we used new Prophet models to forecast mood and explicit and implicit measures of self-harm among an online community sample residing in the US and UK (N > 7,975). We decomposed the time series into trends across the years, within years (seasons), weekly, and daily seasonal patterns. Across all outcomes, the long-term changes across the years and the seasonal patterns show the strongest variation on explicit and implicit cognitions, followed by the time of day (negative cognitions peaking around 4 am – 5 am), with the day of the week showing the weakest effects. The data show a general increase of negative cognitions across the six years, paralleling trends in suicide rates and depression prevalence in the US and UK. Autoregressive-integrated moving average (ARIMA) models showed seasonality effects for mood and desire to die among US, UK, and Canadian respondents (N > 10,445), particularly in the group of respondents who previously made a suicide attempt. Negative cognitions were generally the lowest in summer (June) and peaked in winter (December). These negative cognitions precede the rise in suicidal behaviors during spring and early summer. We discuss potential reasons for lagged effects of negative cognitions on suicidal behavior and implicit cognitions, which may be crucial for theoretical advancements. Our findings have implications for the clinical risk assessment of patients witha history of suicide attempts and public policies regarding the availability of health services.

How do explicit, implicit, and sociodemographic measures relate to concurrent suicidal ideation? A comparative machine learning approach

“…Decades of research have identified several key risk factors for suicide, including past psychiatric disorders, such as depression (Chesney et al., 2014), past self‐harm behavior, suicide cognitions (Chan et al., 2016), and different sociodemographic factors, such as being middle‐aged (Berkelmans et al., 2021). Research has also identified more distal population‐wide risk factors associated with increased risk for suicidal behavior, including economic turmoil (Turecki & Brent, 2016), and seasonality (Freichel & O’Shea, 2023), with increases in deaths by suicide in spring (Christodoulou et al., 2012). In particular, the field has gained a better understanding of explicit cognitions (e.g., negative affect, Gee et al., 2020) and psychophysiological processes (e.g., sleep, Brüdern et al., 2022) in their prediction of daily self‐harm behavior and suicide cognitions, thanks to the modern‐day abundance of smartphones and the associated popularity of ecological momentary assessment in suicide research (Kleiman et al., 2017).…”

Understanding EMA Data: A Tutorial on Exploring Item Performance in Ecological Momentary Assessment Data

“…display how information about situations can be leveraged for individual prediction of behaviors and experiences and discuss the relevance of situation information for personality research, whileCloos et al (2022) use the sensitivity to emotionally relevant events as a quality criterion for EMA items. Both weekend effects and time-of-day effects have been studied across a range of constructs (see, e.g.,Freichel and O'Shea (2021) for suicide and mood orEgloff et al (1995) for positive affect) Gabriel et al (2019). offer a discussion on time trends and how to model them, whileZhang and Volkow (2023) discuss the role of seasonality and circadian rhythms in psychiatric disorders.…”