Category: Knowledge

Sedentary Mood – Study II

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Study Diary "Sedentary Mood-Study"

Sedentary Behavior Study

The following article continues our series on "Sedentary Mood-Studies". Throughout the series we'll take you through a course of sedentary behavior studies, describing the process from planning to results. We'll start with the process of capturing the necessary data to examine the link between sedentary behavior and mood. To do this, we'll detail a particular sedentary behavior study to illustrate the idea.

Part 2: Recording mood and sedentary behavior data

When studying sedentary behavior, it's important to select a time frame that provides enough data to analyse. In this case, the researcher chose a five day period in an ambulatory setting to capture data in everyday life. Over this five day period participants received mood assessments several times per day, and had their activity recorded during waking hours.

To capture the participants mood, it's necessary to use an experience sampling method. For this study, the android based experience sampling app movisensXS displayed the short version of the "Multidimensional Mood Questionnaire (MDMQ)" at random intervals. The MDMQ measures the mood in three dimensions - Valence, Energetic Arousal, and Calmness - and was specifically conceptualized for ambulatory studies (see Wilhelm and Schoebi, 2007, p. 259ff.)

Whilst there's no technical device that captures sedentary behavior (see Kang and Rowe, 2015, p.113), the activity sensor serves as the de facto research instrument of choice. Given the abundance of fitness trackers on the market, it's often tempting to purchase inexpensive devices in order to obtain more data points. However, for research grade data it's important to use research grade devices. Whilst that may mean fewer devices and fewer participants, the quality of the data more than compensates.

The Sedentary Behavior Research Network (SBRN, 2017) defines Sedentary Behavior as: "Sedentary behavior is any waking behavior characterized by an energy expenditure ≤1.5 metabolic equivalents (METs), while in a sitting, reclining or lying posture". So in order to obtain an optimal recording, we need to evaluate both body position and energy expenditure.

In the next part of this series, we'll describe how the guidelines for sedentary behavior were met within this study

“Sedentary Mood Study”

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Study Diary "Sedentary Mood Study"

The following article begins a "Sedentary Behavior Studies" series, in which we'll detail the study process from conception through to results. We'll focus on the link between sedentary behavior and mood. But first, we need to address an important point.

Why research sedentary behavior?

"Whoever sits longer dies younger" and "Sitting is the new smoking". These headlines come from recent behavioral and health related studies. Due to such conclusions sedentary behavior demands the attention of researchers, and the general public looks on with interest. As the understanding of sedentary behavior and it's consequences develops, further research appears illustrating its adverse effects on cardiovascular health, metabolic and muscular parameters, and it's dire risk for overall physical health (Owen et al., 2010, p.3).

Despite these findings, there's little research on the effect of sedentary behavior on psychological health. Preliminary findings indicate a possible connection between the two. As Fuchs et al. suggest (2015. p. 7) "Sitting changes the activity of metabolism and therefore it doesn´t seem absurd, that this can also influence the psychological processes." If the link between sedentary behaviour and adverse psychological health exists, understanding it would prove valuable in the fight against psychosomatic diseases.

"How do we measure sedentary behavior and mood?" ... to be continued in the next articles

Measuring “Sedentary Behavior” – General recommendations and solutions by movisens

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“Sedentary behavior” is defined as sitting or lying with low energy expenditure (SBRN, 2012). In isolation, energy expenditure provides no reliable information about body posture (e.g. sitting vs. standing), an essential component of assessing sedentary behavior (Holtermann, et al., 2017). Conversley, assessing body posture alone cannot provide insights into energy expenditure, e.g. machine sewing while sitting, crane operators, lifting weights in the gym (Holtermann, et al., 2017). To accurately determine sedentary behaviour requires the assessment of both body posture and energy expenditure.

Reliable methods to measure and assess "sedentary behavior"

  • Case 1: Known environment – e.g. no possibility to stand and all low physical activity ≙ sitting. In this case attaching a sensor at the hip (Move 3) provides only a rough estimation of sedentary behavior.
  • Case 2: Differentiating between sitting/lying & standing. By attaching a sensor (Move 3) to the thigh, the different angles of the axis allow differentiation between sitting/lying and standing. But it is not possible to differentiate between sitting and lying (Byrom, Stratton, McCarthy, & Muelhausen, 2016).
  • Case 3: Assessing changes in time distribution of sedentary behavior – requiring the precise distribution of sedentary behavior and physical activity intensity. This case requires the assessment of both body posture and energy expenditure. This is possible by attaching one sensor (Move 3) at the thigh (sitting/lying vs. standing) and one (Move 3) at the upper body/hip (standing/sitting vs. lying). Additionally, the sensor at the upper body/hip provides the data necessary to estimate energy expenditure (Holtermann, et al., 2017)
  • Case 4: Assessing changes in time distribution of sedentary behavior with a static load. In this case the use of an ecg-sensor provides additional data to assess energy expenditure. Initially the ecg-sensor requires calibration to estimate energy expenditure with additional load. Attaching one sensor (Move 3) at the thigh (sitting/lying vs. standing) and one physical activity and ecg-sensor (EcgMove 3) at the upper body (standing/sitting vs. lying) provides acceleration data from two positions, and the additional ecg-signal allows improved energy expenditure estimations during static work, due to the linear relationship between cardiorespiratory stress and energy expenditure (Holtermann, et al., 2017).
  • Case 5: If an intervention is necessary, or if the research requires additional subjective parameters, we offer the possibility to trigger a questionnaire with our experience sampling platform movisensXS via our SensorTrigger. After the application detects 30 minutes (customizable by the researcher) of sedentary behaviour (<1.5MET) from the sensor, the trigger displays a form on a smartphone app prompting the participant to answer a questionnaire. This offers the possibility to obtain detailed feedback and insights into the daily routine of the study participant.