Background
Participation in an assessment may change the behavior that is aimed to be investigated [
1,
2]. In health behavior research, such effects have been called “mere-measurement effect”, “assessment reactivity”, or “question-behavior effect” [
3,
4]. A meta-analysis found small but significant effect sizes for measurement of physical activity (PA) [
4]. Altering PA can occur as a result of wearing a device [
5,
6] or filling out a questionnaire on past behavior or on cognitions related to PA [
7,
8]. Several mechanisms underlying the mere-measurement effect have been discussed. Participants may change their behavior, for example, as a result of reflecting on their attitudes or on discrepancies between beliefs and actual behavior [
9].
It has been suggested that the mere-measurement effect could be used as a simple and cost-effective intervention to improve health behavior across a wide range of people [
8,
10‐
12]. Thus, it needs to be verified that the potential benefit of the effect is not systematically attenuated among groups of individuals according to sociodemographic and health related characteristics. However, there is a lack of evidence about sex, age, and socioeconomic status as moderators of the mere-measurement effect. A recent study on several health behaviors could not conclusively demonstrate a difference in the effect across socioeconomic groups which would potentially lead to increased health inequalities [
13].
Associations between regular PA and cardiovascular health are well established [
14‐
16]. Evidence for increased health risks of prolonged sedentary time (ST) is accumulating [
17,
18]. Thus, it seems of particular interest whether the mere-measurement effect on PA and ST differentially affects individuals with various cardiometabolic risk factors. If improvements of PA and ST result from an increased awareness of discrepancies between desired and actual behavior, individuals with a less favorable cardiometabolic risk profile may be more likely to respond to the mere-measurement effect than individuals with a more favorable risk profile. In contrast, if general benefits from the effect are less pronounced among those with a less favorable cardiometabolic risk profile, health promotion using mere measurement may fail to reach those with the higher need.
In a previous study, it was found that participants of a cardiovascular examination program subsequently increased PA for transport and tended to decrease ST without any formal treatment, referral, or intervention [
19]. As little research has been conducted on individual characteristics of the participants, the objective of the present study was to explore whether the mere-measurement effect on leisure-time PA (PA
leisure), transport-related PA (PA
transport), and ST after attending a cardiovascular examination is moderated by sociodemographic variables (sex, age, and employment) and cardiometabolic risk factors (systolic blood pressure [SBP], waist circumference, glycated hemoglobin [HbA1c], total cholesterol, high-density lipoprotein [HDL], and triglycerides).
Discussion
This study aimed to explore moderators of the mere-measurement effect in adults as indicated by associations between sociodemographic variables and cardiometabolic risk factors and changes in PA and ST after attending a cardiovascular examination program. First, men increased PAtransport more than women. Age tended to be positively associated with PAtransport improvements. Second, among men, results revealed U-shaped associations both between SBP and HbA1c and the reduction of ST. And, men with higher triglycerides increased PAtransport less than men with lower triglycerides.
Responding to an assessment on PA or ST may trigger new thinking about the behavior. Within focus group discussions, some participants of this study reported that after completing the questionnaire they were negatively surprised by the amount of time they spent sedentarily. This may explain the relatively high proportions of participants who have changed their behavior in a positive way. Improvements between baseline and follow-up in PAleisure, PAtransport, and ST were reported by 48, 56, and 52% of the participants, respectively.
There was an increase in PA
transport of 9.3 MET-hours per week in men as compared to women. To put this value into perspective, the IPAQ assigns 3.3 METs to walking and 6.0 METs to cycling [
22]. This means that men spent, for example, an additional 3 h walking or 1.5 h cycling per week compared to women. This difference may result from a worse health condition among men as indicated by less favorable values of SBP, HDL, and triglycerides. In line with suggested mechanisms underlying the mere-measurement effect [
3,
9], men might have altered their behavior as their awareness of the relationship between behavior and health increased in response to reflecting on activity levels when completing a detailed 27-item-questionnaire combined with the assessment of cardiometabolic risk factors. Further, evidence suggests that the built environment is an important factor associated with active transport [
25,
26]. Changing PA
transport may not be achievable to any individual due to long distances between home and work or other daily responsibilities that require transportation using motor vehicles.
Despite the fact that the present sample was restricted to 40- to 65-year olds, it was found that older participants tended to increase PA
transport more than younger participants. This may be contrary to expectations as prior meta-analyses comparing student samples with non-student samples including older adults hint at a larger measurement effect among young adults compared to older adults [
9,
27]. However, compared to younger participants, older participants in this sample had higher levels of HbA1c, total cholesterol, and triglycerides (data not shown). Thus, older participants had a worse health condition and, therefore, may have been more motivated to increase PA.
Associations between SBP as well as HbA1c and ST in men indicate that those with less favorable risk factors improve more than those with more favorable risk factors. In contrast, results on PA point to the opposite direction. Associations between triglycerides and PAtransport in men and between HDL and PAtransport in women revealed that those with more favorable values improved their behavior more than those with less favorable values. Thinking about weekly ST independent of PA levels might have motivated men with a less favorable risk profile to alter inactivity on a lower threshold, in contrast to men in good health, who altered PA rather than ST. Nevertheless, the U-shaped associations indicate that men with blood pressure levels beyond 150 mmHg and men with HbA1c values on the threshold to diabetes seem to refrain from ST reductions possibly due to their worse physical condition. Compared to men, women in this sample had more favorable cardiometabolic risk factors which may explain why these factors did not moderate changes of PA and ST in women.
The present study was conducted to shed some light on a topic that is still a niche area in clinical research. However, there are four limitations to consider. First, a selection of highly motivated individuals is likely. The proportion of individuals who declined participation was high (53%) and non-participation was associated with smoking, lower education, and female sex. Thus, the findings may not be generalizable to the general population. Second, systematic changes in PA and ST observed in this non-controlled study do not necessarily imply mere-measurement effects. To reduce potential confounding, adjustments were made for variables related to individuals’ characteristics and data collection. Future research on transport-related PA should take additional context variables into account, e.g., the distance between home and work. Third, PA and ST were assessed using self-report measures. Due to social desirability bias [
28,
29], an over-reporting of PA or an under-reporting of ST might have occurred in this study. Recent research revealed higher odds of having metabolic syndrome for men who did not meet PA guidelines according to accelerometry data than for men who met the guidelines [
30]. However, this relationship disappeared when PA was measured via self-report, which seems to hint at an over-reporting of PA by men with metabolic syndrome. Similarly, in this sample, men with less favorable risk factors might have under-reported ST. Future studies could assess behavior change via direct measures, e.g. accelerometry, using wearing periods of at least 2 weeks since prior research suggested the presence of reactivity bias during the first week of measurement [
5,
6]. Finally, the findings may suffer from a lack of power to detect differences between subgroups, as this study was not particularly designed to investigate moderators of the mere-measurement effect.
Conclusion
The findings of this study suggest that beneficial alterations of PA and ST after a cardiovascular examination program may be moderated by sex, age, and cardiometabolic risk factors. Researchers and practitioners using the mere-measurement effect to promote behavior change should consider these individual characteristics. For example, completing a questionnaire on PA or ST while waiting in a physician’s practice may trigger new thinking about a behavior in a patient. If cardiometabolic risk factors are assessed, a deeper awareness of the relationship between inactivity and health risks may be raised. In the course of this, men with a less favorable risk profile, for example, may be more responsive to answering a questionnaire on ST instead of PA. Future research using larger sample sizes is needed to verify the moderators found in this exploratory study and to investigate long-term effects on behavior and health.
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