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these techniques. As mentioned earlier, the expectations, interests, perspectives, and prejudices of the interviewer and observer may uniquely influence each assessment. To avoid these disadvantages, many psychologists utilize checklists and inventories to assess behavior. These are brief pencil-andpaper questionnaires that assess one or more traits or problem areas. They can be administered to a large number of people at one time, are inexpensive, and can be quickly scored and analysized. Clinical information obtained from checklists and inventories tends to be more reliable and valid than information collected through most interview and observational methods. This is because extensive research is conducted on most of these measures before they become available for purchase and use. Numerous checklists and inventories have been developed to assess and diagnose a wide variety of problems such as anxiety, depression, eating disorders, and attention deficit disorders. These instruments generally are very brief, easy to complete, and need little instruction or supervision from a professional. They may focus on feelings, thoughts, and/or behavior and are typically either hand or computer scored. While seemingly straightforward, checklists and inventories also need to be sensitively interpreted in the context of other measures as well as biological, psychological, and social factors. This section highlights three of the most commonly used instruments in clinical psychology: the Beck Inventories, the Child Behavior Checklist, and the Symptom Checklist 90-Revised.

mediator of increased physical activity in other groups (ie, young adolescent girls; Dishman et al, 2004) Studies reporting relationships between intentions and physical activity share the same limitations found in the studies of physical activity and self-efficacy, namely, a reliance on correlational rather than experimental designs and the use of unvalidated self-report measures of physical activity Hence, it is difficult to determine how much of the association between intentions and actual exercise behavior was an artifact of using self-report to estimate both the presumed determinant and the behavior This concern is highlighted by the observation that in five studies that assessed both past physical activity (ie, habit) and intentions for future physical activity, the correlation with current physical activity was higher for habit (mean 43) than for intention (mean 38) (Dishman, 1994a) Because habit and intention were also related in these studies (r 50 to .

Figure 9-3

A great number of business operations prepare their payroll and maintain employee records and information using a computerized payroll program within their system For locations where food and beverages are recorded, two types of systems are available electronic cash register (ECR) and a point-of-sale (POS) system Basically, the ECR is a stand-alone electronic register, whereas a POS system may link several ECRs to a separate remote host computer, the sales register is primarily a keyboard rather than a separate machine Customer service terminals respond to creation of customer checks by issuing instructions to the food preparation area for menu items, and print out the customer s bill (customer check) Unfortunately, the acronyms ECR and POS are often used interchangeably.

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65), a substantial portion of the relationship between intention and exercise adherence observed in cross-sectional studies is reflecting past exercise habits and cannot be viewed as causing contemporary exercise Recent evidence from a prospective cohort study supports a predictive relationship between intention and physical activity in adolescents (Godin, Anderson, Lambert, & Desharnais, 2005), but other evidence suggests that this relationship declines across time (Chatzisarantis, Hagger, Biddle, & Smith, 2005) and might be explainable by self-efficacy (Hagger, Chatzisarantis, & Biddle, 2002a; Motl et al, 2002) The mean correlation (weighted for sample size) between self-reports of physical activity and intentions reported in 15 studies before 1994 was 50 (Dishman, 1994a).

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Expressed as a binomial effect size, this correlation suggests that an intervention that results in high intentions to be active will lead to a 75% rate of exercise adherence, compared with a 25% rate of adherence under control conditions of low intention The few controlled clinical experiments to increase intentions to exercise, however, have not led to persisting effects Also, mediated interventions in communities or population-based designs to increase intentions for other behavior changes clearly show that a much smaller increase in physical activity can be expected than the large increase implied by correlations between intentions and physical activity obtained in descriptive studies Intrinsic Factors Factors such as self-schemata and enjoyment are potentially important influences on physical activity but have been understudied The core traits of an individual s identity.