Measuring Flow Experiences in Daily Life: An Examination of the Items Used to Measure Challenge and Skill

When reporting on flow or optimal experiences individuals identify a number of dimensions, including a merging of action and awareness, clear goals and feedback, focused attention, loss of self-consciousness, altered sense of time, a sense of control, and perceived match between challenges and skills (Csikszentmihalyi, 1975, 1988, 1990, 1993; Jackson, 1992; Jackson & Marsh, 1996). Emerging from the flow experiences containing these dimensions are high levels of enjoyment and a nurturing of one's self identify (Csikszentmihalyi, 1975, 1988, 1990, 1993). For the past two decades researchers have strived to understand how the flow model fits the day to day experiences of people. The experience sampling method (ESM), which involves participants carrying a pager or beeper watch and responding to items on a self-report form when "beeped" (e.g., what they are doing, level of challenge, level of skill, affect), has provided a method for gathering extensive data on daily experiences. Previous studies have focused on how the dimension of the challenge-skill relationship predicts levels of enjoyment and various dimensions of the flow experience, such as attention, control, loss of self-consciousness and an awareness of time (e.g., LeFevre, 1988; Massimini & Carli, 1988; Massimini, Csikszentmihalyi, & Carli, 1987; Moneta & Csikszentmihalyi, 1996). In a recent critique on the use of ESM data to examine flow experiences in daily life, Ellis, Voelkl, and Morris (1994) identified several issues including problems with the measurement of challenge and skill and loss of information on individual differences when scores are standardized. Ellis, Voelkl, and Morris (1994) and Moneta and Csikszentmihalyi (1996) have proposed statistical analyses that allow ESM data to be analyzed based on the original flow model without losing information on individual differences. Questions remain, however, as to the valid measurement of challenge and skill (Ellis, Voelkl, & Morris, 1994). Participants are typically asked to record perceived challenge and skill in relation to the "activity" they were involved in just prior to being beeped. However, Csikszentmihalyi (1975) has indicated the complexity of challenge and skill: "at any given moment, people are aware of a finite number of opportunities which challenge them to act" (p. 50). The very "finite number" of challenges may create difficulty for a participant who is responding to one item measuring challenge and one item measuring skill. For example, a social scientist participating in an ESM study who is paged while walking to work and contemplating a difficult methodological issue, may report low level challenge and skill in relation to the activity of walking rather than the high level challenge and skill that is experienced while contemplating a methodological problem. Further evidence of the complexity of measuring challenge and skill was found in 500 ESM selfreports on which respondents indicated 49% of the experiences captured them doing something different than what they were thinking about (Voelkl & Ellis, 1998). Given the complexities inherent in measuring challenge and skill, as well as Csikszentmihalyi's indication that an individual's focus of attention is critically important in the experience of flow (Csikszentmihalyi, 1988; 1990), Ellis, Voelkl, and Morris suggested that researchers consider rewording challenge and skill items to target perceived challenge and skill in relation to the participant's attention or concentration. Therefore, the purpose of the present study was to compare variance explained across two conditions: (1) traditional measurement in which the activity serves as the context for measuring challenge and skill and (2) a reformulated condition in which the focus of attention serves as the context for measuring challenge and skill. Model Conceptualization Previous ESM studies examining flow experiences in daily life have varied in terms of the conceptualization of flow via the challenge-skill relationship and the dependent variables selected. …