The Relationship Between Self-Efficacy and Help Evasion

Abstract

Objective. To examine the relationship between self-efficacy and not wanting help to change health behaviors. Method. All employees in the Danish police department were invited to respond to an electronic questionnaire. All respondents expressing a desire to change health behaviors in relation to smoking (n = 845), alcohol (n = 684), eating (n = 4431), and physical activity (n = 5179) and who subsequently responded to questions on self-efficacy were included. Results. Both the bivariate and multiple regression analyses showed that all four specific self-efficacy scores were positively related to reporting that one did not want help. Conclusion. A high belief in one’s own ability to change lifestyle behaviors in relation to smoking, alcohol, eating, and physical activity may lead to avoidance of help offers in a workplace setting.

Keywords

barriers health promotion motivation police self-efficacy work

The interest in workplace health promotion activities targeting physical activity and nutrition is high and is motivated by public health and productivity concerns (Black, 2008; Pencak, 1991; Wolfe, Ulrich, & Parker, 1987). However, many health promotion initiatives struggle with low participation and have problems achieving optimal effect. Low participation may be because of a multitude of factors related to individual, institutional, community, and governmental actions or policies (Linnan, Sorensen, Colditz, Klar, & Emmons, 2001). Yet, since many worksite health promotion programs are, for ethical reasons, made voluntary, participation is, in the end, contingent on the individual employee’s motivation and willingness to participate in a given program.

Human behavior can be described as a compromise between processes residing within the person and external and situational circumstances (Bandura, 1978; Blumberg & Pringle, 1982; Buss, 1991). Accordingly, decisions to change health behaviors may be viewed as the result of an interaction between behavioral, cognitive, and environmental influences (Bandura, 1978). Notwithstanding the plentiful range of external incentives that may motivate individuals into action (Cialdini, 2001), a person’s self-efficacy (i.e., the perceived belief about his or her ability to achieve a specific behavior in a particular situation) is often considered important for understanding changes in health behaviors (Bandura, 2004). Indeed, in social cognitive theory, self-efficacy is viewed as a core psychological belief that affects basic processes of change, whether this is concerns, contemplations, mobilization of efforts, or dealing with relapses (Bandura, 2004).

In a recent review, it was concluded that self-efficacy was important for adherence to physical activity and exercise therapy (Rhodes & Fiala, 2009). Although it makes sense that a certain amount of self-efficacy is needed to engage, or to change behavior, it also seems reasonable to assume that exaggerated belief in one’s own efficacy could lead to the rejection or evasion of offers of help or assistance. This aspect of self-efficacy seems, however, to have been poorly elucidated in research.

For this reason, as part of a process evaluation of a multipurpose in-house health promotion service in the Danish police (Persson et al., 2013), we decided to address this issue in relation to the use of an in-house wellness service. The wellness service consisted of six full-time consultants (five women) who served all employees in the Danish National Police and the 12 police districts. Hence, the consultants travelled a lot with the goal to visit the main stations in the various districts at least once every 4 to 6 weeks. The work of the wellness service focused on improving physical well-being related to the four major lifestyle factors (i.e., exercise, eating, drinking, and smoking) and was available, free of charge, to all employees. The service could be used during working hours so long as the appointments did not conflict with daily work tasks. At times the consultation served to increase the employee’s awareness; on other occasions the consultation served to support more radical lifestyle changes. Furthermore, the counseling contained elements of primary, secondary, and tertiary prevention. Although most activities were directed toward individual employees, other activities, such as group activities, health campaigns, and education, were also occasionally endorsed. In view of the wellness service’s main focus, we decided to explore how well, statistically speaking, self-efficacy could predict the preference for not receiving help, among participants who had acknowledged that they wanted to change health behaviors in relation to smoking, alcohol, eating, and physical activity.

Materials and Method

Participants

The research was conducted in accordance with Danish law and institutional guidelines on ethics in research. All potential users of the wellness service, that is, all administrative workers (e.g., lawyers, clerks, and mechanics) and police officers, were invited to respond to an electronic questionnaire (n = 15,284). To guarantee anonymity and alleviate possible concerns about the access that employers would have to the results, participants were required to log on to an external server in order to complete the questionnaire. There were in total 6,373 respondents (41.8%). Only those employed in the Danish National Police and in the 12 police districts and had responded to at least two third of the items in the questionnaire were included (N = 6,062; mean age = 44 years, SD = 11 years). In the present study, we focus on participants who had responded that they perceived a need for lifestyle changes in relation to the four major life style factors. Thus, of the 6,062 eligible participants, 845 wished to cut down or quit smoking (14 %), 684 wished to reduce their alcohol consumption (11 %), 4,431 wished to adopt healthier eating habits (73 %), and 5,179 wanted to be more physically active (85%). Demographic characteristics and lifestyle factors for each of the subgroupings are presented in Table 1.

Table 1.

Demographic and Lifestyle Characteristics for Each of the Four Subgroupings.

Smokers
Age in years, mean (SD)	45 (11)
Gender, % women	33
Proportion wanting to change behavior, % of the study sample	14
Number of cigarettes/day, median (25th-75th percentile)	12 (7-35)
Number of cigars/day, median (25th-75th percentile)	0 (0-0)
Number of pipe chambers/day, median (25th-75th percentile)	1 (0-4)
Alcohol consumers
Age in years, mean (SD)	47 (10)
Gender, % women	20
Proportion wanting to change behavior, % of the study sample	11
Number of consumed units/week, median (25th-75th percentile)	5 (3-7)
Proportion consuming alcohol up to 3-4 times/week, %	76
Proportion consuming alcohol up to 5-7 times/week, %	24
Healthier diet
Age in years, mean (SD)	43 (11)
Gender, % women	29
Proportion wanting to change behavior, % of the study sample	73
Proportion consuming at least 1 serving of fruit/day, %	43
Proportion consuming at least 1 serving of vegetables/day, %	34
Proportion consuming fast food at least 1 time/week, %	16
Physical activity^a
Age in years, mean (SD)	44 (11)
Gender, % women	29
Proportion wanting to change behavior, % of the study sample	85
Proportion physically active at least 30 minutes 7 days/week, %	7
Proportion physically active at least 30 minutes 0-3 day/week, %	57

Defined as any activity that increases the respiration rate (e.g., heavy garden work, walking at a fast pace, competitive sports, etc.), at least 30 minutes per day (%).

Measures

Predictor variables

General self-efficacy was assessed with three items that read, “I am confident that I can deal efficiently with unexpected events,” “I can solve most problems if I invest the necessary effort,” and “I can usually handle whatever comes my way.” All items had five response categories: always, often, sometimes, seldom, and never/hardly ever. The mean score (range 1-5) was used as a continuous predictor. Higher scores indicated greater self-efficacy. Cronbach’s alpha varied between .71 and .72 when calculated in each of the four study samples.

Specific self-efficacy was assessed with one item for each lifestyle factor: “If you decide to (smoke less/consume less alcohol/eat healthier/be more physically active), do you believe, that you can do it?” All specific self-efficacy items were responded to on a scale from 1 to 10, where the respondents were asked to evaluate how easy it would be: 1 = do not believe it is possible at all and 10 = it should be very easy to do that.

Outcome

All four outcome variables were binary, and reflected whether the participants had marked “I do not want help” on a list that provided several options for help in relation to smoking, alcohol consumption, eating, and physical activity.

Statistical Analyses

The statistical computations were made with IBM SPSS Version 20 for Windows. P values less than .05 were considered statistically significant. Binary logistic regression analyses were used to explore bivariate relationships. Multiple binary logistic regression analyses were used to estimate age-adjusted (continuous) and gender-adjusted (categorical) relationships.

Results

The mean specific self-efficacy scores were as follows: for smoking 5.9 (SD = 2.4; range = 0-10), alcohol 7.6 (SD = 2.0; range = 1-10), eating 6.9 (SD = 1.8; range = 1-10), and physical activity 7.0 (SD = 1.8; range 0-10). The mean general self-efficacy scores in the four subsamples were as follows: smoking 4.2 (SD = 0.5; range = 1.3-5.0), alcohol 4.1 (SD = 0.5; range = 1.7-5.0), eating 4.1 (SD = 0.5; range = 1.3-5.0), and physical activity 4.1 (SD = 0.5; range = 1.3-5.0).

Bivariate Logistic Regression Analyses

The results for the unadjusted bivariate analyses are presented in Table 2. All four specific self-efficacy scores were positively related to reporting that one did not want help. The general self-efficacy score was related, with statistical significance, to not wanting help in relation to changing physical activity patterns. Increasing age was positively related to not wanting help as regards changing eating and physical activity. Women were less likely to report that they did not want help in relation to eating and physical activity.

Table 2.

Results From Bivariate Unadjusted Logistic Regression Analyses.

	N	%	Gender, OR [95% CI]	Age, OR [95% CI]	General Self-Efficacy, OR [95% CI]	Specific Self-Efficacy, OR [95% CI]
Smoking
I do not want help	243	29	0.96 [0.70, 1.32]	1.00 [0.98, 1.01]	1.05 [0.78, 1.40]	1.40 [1.30, 1.52]
Alcohol
I do not want help	520	76	0.98 [0.63, 1.52]	1.01 [0.99, 1.02]	1.14 [0.80, 1.62]	1.12 [1.03, 1.22]
Eating
I do not want help	483	11	0.64 [0.51, 0.80]	1.05 [1.04, 1.06]	1.19 [0.98, 1.44]	1.18 [1.12, 1.25]
Physical activity
I do not want help	893	17	0.77 [0.64, 0.89]	1.04 [1.03, 1.05]	1.33 [1.15, 1.54]	1.14 [1.09, 1.19]

Note. OR = odds ratio; CI = confidence interval. Gender: 0 = male, 1 = female; age (range = 18-65 years; effect per year increase); general self-efficacy was measured as a mean of three items (1-5; effect per unit increase in mean score). Specific self-efficacy was measured with one item (1-10; effect per unit increase).

Multiple Logistic Regression Analyses

The results from the age- and gender-adjusted multiple logistic regression analyses are presented in Table 3. The four specific self-efficacy scores were positively related to reporting that one did not want help with changing health habits. The general self-efficacy score was positively related to reporting that one did not want help with changing health habits in relation to physical activity.

Table 3.

Multiple Logistic Regression Analyses: Age- and Gender-Adjusted Analyses for Specific Self-Efficacy and General Self-Efficacy.

Variable	OR	95% CI	p
Smoking
Specific self-efficacy	1.41	[1.30, 1.52]	<.001
Age	1.01	[0.99, 1.02]	.538
Gender	0.92	[0.66, 1.30]	.645
Alcohol
Specific self-efficacy	1.12	[1.03, 1.22]	.008
Age	1.01	[0.99, 1.02]	.988
Gender	1.03	[0.66, 1.60]	.973
Eating
Specific self-efficacy	1.15	[1.08, 1.21]	<.001
Age	1.04	[1.03, 1.05]	<.001
Gender	1.31	[1.04, 1.66]	.022
Physical activity
Specific self-efficacy	1.14	[1.09, 1.19]	<.001
Age	1.04	[1.03, 1.05]	<.001
Gender	1.05	[0.88, 1.25]	.594
Smoking
General self-efficacy	1.04	[0.77, 1.40]	<.790
Age	1.00	[0.98, 1.01]	.542
Gender	1.05	[0.76, 1.45]	.195
Alcohol
General self-efficacy	1.15	[0.80, 1.64]	.440
Age	1.01	[0.99, 1.02]	.958
Gender	0.99	[0.63, 1.54]	.706
Eating
General self-efficacy	1.18	[0.98, 1.43]	<.087
Age	1.04	[1.03, 1.05]	<.001
Gender	1.31	[1.04, 1.66]	.022
Physical activity
General self-efficacy	1.36	[1.17, 1.57]	<.001
Age	1.04	[1.03, 1.05]	<.001
Gender	1.10	[0.93, 1.31]	.256

Note. OR = odds ratio; CI = confidence interval. Gender: 0 = male, 1 = female; specific self-efficacy was measured with one item (1-10; effect per unit increase); general self-efficacy was measured as a mean of three items (1-5; effect per unit increase in mean score). Variables in italics are outcome variables and those in regular font are independent variables.

Discussion

This study explored how well self-efficacy could statistically predict the preference of not receiving any help among of participants who had acknowledged that they wanted to change health behaviors in relation to smoking, alcohol, eating, and physical activity.

The results from both the bivariate and multiple regression analyses showed that all four specific self-efficacy scores were positively related to reporting that one did not want help. The general self-efficacy score was less clearly associated with the reports of not wanting help. General self-efficacy was only statistically predictive for reporting that one did not need help in relation to physical activity. Irrespective of statistical significance, the results suggest that higher self-efficacy seems to foster feelings of self-reliance. Whether self-reliance in the present context represents a wise and accurate decision or a potentially detrimental one is another question, which can not be reliably answered with the present data. Yet the results show that specific self-efficacy seems to be related to a self-reliant attitude that may affect attitudes toward help initiatives. Hence, our observations underscore the possibility that high self-efficacy might, in certain situations, act as an individual barrier and hindrance to receiving help.

At first glance, our observations seem to contradict both empirical evidence (Andersen, 2011; Rhodes & Fiala, 2009) and social cognitive theory, where self-efficacy is viewed as a core psychological belief that affects basic processes of change, whether this concerns contemplation to change, mobilization of efforts, or dealing with relapses (Bandura, 2004). It is, however, important to state that our observations do not necessarily refute previous empirical findings and that they are quite compatible with theories of social cognition. Given that every person may, in theory, be ranged somewhere on the self-efficacy continuum, an individual’s degree of self-efficacy will always be of relevance when attempting to understand or describe human behavior. As such, the results serve as a reminder that the impact of self-efficacy is the outcome of an interaction with environmental influences (Bandura, 1978). In addition, our observations also suggest that self-efficacy may affect help-seeking behavior and, by extension, that people with high self-efficacy may prefer not to be helped. Hence, it appears important to distinguish between what type of behavior self-efficacy facilitates and in which situations.

Methodological Considerations

The external validity of our findings is strengthened by the fact that the electronic survey was sent to all occupational positions and groups in the Danish police and had a nationwide reach. Obviously, the overall response rate of 41 % is a weakness. The response rate inevitably raises questions about how well the participants represent all employees. Even so, an analysis of e-mails from participants who actively declined to participate in our survey indicated that the reasons for not partaking were multifold, including both positive and negative attribution of causes. Since all information was derived from self-reports, a number of potential sources of common method bias also need to be considered (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). The most critical source seems to be that all scores have been delivered by the same person (i.e., common rater effects). Alternatively, the trustworthiness of the results is increased by the fact that the participants had to actively select the no-help option among the extensive list of alternatives provided for each lifestyle factor. Another issue that warrants attention is that the participants reported a generally high degree of self-efficacy. The general self-efficacy score was, in particular, skewed to the right, almost to the point where there was a risk of a ceiling effect. One potential explanation for this high degree of self-efficacy could relate to the fact that a large proportion of our participants were police officers that conceived themselves as fairly resourceful persons. However, since similarly high levels of self-efficacy have been found in the Danish Work Environment Cohort Study (Det Nationale Forskningscenter for Arbejdsmiljø, 2005), one cannot exclude the possibility that questionnaire respondents are, in general, more prone to possess higher self-efficacy than nonrespondents. In any event, it is plausible that the fairly compressed general self-efficacy scores make it more difficult to find effects. Finally, it may be noted that most smokers wanting to quit indicated that they needed support to do so, whereas they selected the no-help option most frequently in relation to alcohol.

Conclusion

A high belief in one’s own ability to change lifestyle behaviors in relation to smoking, alcohol, eating, and physical activity may lead to a decision to avoid help offers. Although the results presented here cannot be used to provide a reliable answer with regard to whether such a decision is detrimental or beneficial for the health of an individual, the results suggest that a high self-efficacy may, in certain situations, lead to decisions that affect help-seeking behavior in a workplace setting.

Footnotes

Acknowledgements

We are grateful for the cooperation of participants, the wellness service, the employer representatives from the Danish National Police and the Danish police, and the representatives from The Police Union and “HK-politiet” who partook and contributed to the project in various ways.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:

The study received financial support from the Danish National Police.

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