Dynamical Modeling of the Relations Between Leisure Activities and Health Indicators

In an extension of maladaptive behavior determinism (MBD) theory, which states that ordered behavior patterns above time are suggestive of disease states, we examined the relation between leisure activity and health behavior above time. MBD is derived from complexity or chaos theory. It was hypothesized that, above time, increased activity levels would be related to more randomly occurring health behaviors. For 68 participants, daily self-monitoring of leisure activities and four health indicators (healthy eating, feeling hassled, positive frame of mind and drinking alcohol) were assessed for five weeks and designed using multiple time series modes Results showed some support for the hypothesis, particularly with revere to the health indicator feeling hassled. The findings reach forth support for MBD, and also insinuate that physically very active leisure time might have health benefits that are dynamical and not necessarily immediately apparent.

KEYWORDS: Leisure activity, health indicator, dynamical modeling, chaos, complexity.

Introduction

The increased appreciation of the benefits of leisure activity and active living (Di Bona, 2000) are well known and throw backed in an increase in exercise participation and a positive reply to public health promotion efforts (Prankish, Milligan, & Reid, 1998) The benefits of leisure activity include alleviation of anxiety (Kaufmann, 1988) increased well-being (Coleman & Iso-Ahola, 1993) identity exhibition (Kleiber & Rickards, 1985), improved physical and mental health (Calclwell, Smith, & Weissinger, 1992; Winefield, Tiggemann, & Winefield, 1992) and stress-coping benefits (Shaw, Caldwell, & Kleiber, 1996) Prior research many times does not distinguish type of leisure activity. However, physically active leisure activities (versus sedentary ones) have been shown to be preventive factors for cardiovascular and other major diseases (Folsom et al., 1997; Mensink, Deketh MuI, Schuit, & Hofmeister, 1996; Schlicht, 2002; Wenger, 1996) Therefore, inspection of the event of different types of leisure activities on health appears to be warranted.

In addition to exploring the event of type of leisure activity, an issue that has nevertheless to be addressed is the dynamical relation between leisure activity and health. (Prankish et al., 1998; Kleiber, Hutchinson, & Williams, 2002; Mahoney & Stattin, 2000; Mota & Esculas, 2002; Zeijl, te Poel du Pois-Reymond, Ravesloot, & Meulman, 2000) Dynamical modeling shows how a system changes or "behaves" as time passes and requires repeated measures of variables, of that kind as by daily self-monitoring. This is in contrast to static modeling, which solitary examines variables at a single point in time. Prior research has relied almost exclusively upon static modeling using retrospective self-reports of leisure activity. Given that a certain number of health indicators are unstable, similar as mood (Hill & Hill, 1991; Thayer, 1996) it is important to inspect their relation to leisure activities above time.

For purposes of this investigation we define health in the broadest faculty of perception to include not only absence of disease, on the other hand also overall well-being (e.g., happiness and quality of life). We define health indicators to include not sole physical behaviors related to (or indicators of) health, on the contrary mood states as well. Our primary objective was to examine the dynamical influences (i.e., above time) of physical leisure activity upon health indicators. This was possible through incorporating daily self-monitoring in a prospective manner for the assessment of all variables (leisure activity and health indicators). Additionally, an open-end format was incorporated for assessing stamps of leisure activity, avoiding the question of pre-determined (and possibly insufficient) categories.

This approach allowed for the testing of an important health theory that has been emerging in new years: maladaptive behavior determinism (MBD) which is based upon complexity or chaos theory. This theory originated from one side studies of behavior involving laboratory-based biological and psychophysiological assessment above time, such as electrocardiograms (Goldberger & West, 1987) Evidence has adviseed that adaptive conditions exhibit a high step of randomness, whereas maladaptive conditions exhibit more deterministic, and possibly chaotic, characteristics (Babloyantz & Destexhe, 1986; Ehler Havstad, Garfinkel, & Kupfer 1991; Goldberger et al., 1987) However, in studies of behavior requiring self-report outside of the laboratory, comparable evidence has been developing sole very gradually (Barton, 1994; Melancon, Joanette, & Belair, 2000)

Nevertheless, the above-cited findings provide support for MBD which states that adaptive behavior is characterized by the agency of a dominant random component because it adjusts to exogenous factors in the environment that be found independently of time (Skarda & Freeman, 1987) Maladaptive behavior is characterized by means of greater determinism because it answers relatively more to endogenous factors, which do present itself as a function of time and perseverate plane in the presence of environmental change. in like manner according to MBD, when an individual is healthy, measures of behavior (indicators) are characterized by means of unstructured (i.e., random) fluctuations above time. When the individual is unhealthy, these same measures exhibit structur (i.e., cyclic or periodic) patterns above time (Goldberger et al, 1987; Heiby, Pagano, Blaine, Nelson & Heath, 2003; Skarda et al., 1987) A revolution of time is simply a pattern of change that repeats itself above time. For example, the rise and fall of the tides tread on the heels ofs a cyclic pattern.