Interactive effects of work psychosocial factors on participation in workplace wellness programs

Figures & data

Figure 1. The conceptual model of work system components and the previously identified impacts on participation in worksite wellness programs (WWPs).

Table 1. Breakdown of demographics with regard to worksite wellness programs participation among the sample as well as the university workforce.

Category	Nonparticipants (n = 194)	Participants (n = 95)	Engaged participants (n = 54)	Overall university
Age
≤30	10.3%	17.9%	13%	6.4%
30 – 40	24.7%	34.8%	27.8%	20%
41 – 50	25.8%	22.1%	18.5%	24.4%
>50	39.2%	25.3%	40.7%	49.2%
Average (SD)	46.1 (12.5)	44.7 (12.9)	44.2 (11.1)	49.3 (12.3)
Gender
Male	32.5%	20%	24.1%	49.5%
Female	67.5%	80%	75.9%	50.5%
Ethnicity
Other	0.5%	0%	0%	12.2%
White	91.2%	85.2%	91.7%	71.8%
African American	1.5%	1.1%	0%	5.2%
Hispanic	1.5%	1.1%	0%	1.3%
Asian	5.2%	12.6%	7.4%	6.3%
Education level
High school diploma	14.4%	10.5%	1.9%	18.3%
Associate’s degree	9.8%	5.3%	11.1%	5.3%
Bachelor’s degree	21.1%	21.1%	22.2%	17.6%
Master’s degree	27.8%	44.2%	38.9%	17.9%
Doctorate	26.8%	18.9%	25.9%	28.4%
Body Mass Index (kg/m^2)
≤25	51.5%	49.5%	57.4%	—
25.1 – 30	24.2%	29.5%	25.9%	—
30.1 – 35	11.9%	12.6%	11.1%	—
35.1 – 40	7.2%	4.2%	1.9%	—
>40	6.7%	4.2%	3.7%	—
Average (SD)	26.8 (7.3)	26.6 (6.7)	25.6 (6.1)

Note. Due to use of the listserv distribution (convenience sampling), the final sample was not representative of the university population.

Table 2. Descriptive statistics of the six psychosocial measures included in the analysis. Values can range from 1 (low) to 5 (high).

Psychosocial measure	Mean (SD)
Job demand	3.13 (0.58)
Work control	3.23 (0.78)
Social interactions	3.75 (0.81)
Leadership	3.44 (1.06)
Role expectations	3.96 (0.84)
Predictability at work	3.54 (0.80)

Figure 2. The classification tree with the psychosocial variables and covariates as input and predicted participation status as output. Among the six resultant profiles, three were associated with nonparticipation, two with participation, and one with engaged participation.

Table 3. Six profiles emerged from the classification and regression tree analysis with regard to current participation status.

Node no.	Control at work	Superior support	Total job demand	Predicted participation status
1	Low	—	—	Nonparticipant (46.2%)
2	High	High	—	Engaged participant (5.8%)
3	High	Low	Very high	Participant (14%)
4	High	Low	High	Nonparticipant (16.3%)
5	High	Low	Very low	Nonparticipant (4.9%)
6	High	Low	Low	Participant (12.8%)

Figure 3. The classification tree with the psychosocial variables and covariates as input and predicted likelihood of future participation as output. Response from one respondent was excluded from this analysis due to missing data.

Table 4. Six profiles emerged from the classification and regression tree analysis with regard to likelihood of future participation.

Node No.	Age	Predictability (next month)	Control at work	Superior support	Predicted likelihood of future participation
1	>50 years	Low	—	—	1 (not likely at all, 11%)
2	>50 years	High	Low	—	1 (not likely at all, 3%)
3	>50 years	High	High	—	5 (highly probable, 22%)
4	<50 years	—	—	Low	2 (24%)
5	<50 years	—	Low	High	3 (26%)
6	<50 years	—	High	High	5 (highly probable, 14%)

Table 5. Focus group and interview narratives, summarized into three main categories.

	Favorable condition	Quotes	Unfavorable condition	Quotes
Content (n = 31)	^+Flexible working hours (n = 4)^a	“I set my own schedule every day.”	^↔General job stress (n = 7)^a	“Some days I am so anxious about all the things that could go wrong.”
	Skill discretion (n = 4)	“I get to use my skills in a way that is interesting and challenging.”	^−High time pressure (n = 6)^a	“It’s sometimes really critical that you solve [clients’] problems ASAP, I just feel the pressure of it so much.”
	High learning opportunities (n = 3)	“[My job] really fosters a lot of learning.”	^−Inflexible working hours (n = 3)^a	“My boss made it very difficult to access that flex time I was promised.”
	Physically active work (n = 2)	“I can put in 6,000 steps a day on my Fitbit when I have a day out [of the office].”	Resource limitation (n = 2)	“Because of lack of funding, we need to go out there and do what we do to fulfill our mission.”
Social (n = 17)	^+Positive peer relation (n = 6)^a	“It’s a very collaborative office, both inside and outside [the work].”	^−Unsupportive supervisor (n = 5)^a	“[We] get no support from our supervisor, it’s like we are chained to a desk.”
	^+Supportive supervisor (n = 3)^a	“I have the support of my boss to do [my job], she is very encouraging.”	^−Favoritism perception (n = 3)^a	“I feel uncomfortable when I have to do things under the table because of my boss’s hypocrisy.”
Environment (n = 4)	—	—	Excessive sitting (n = 2)	“I don’t like that I do sit a lot.”
	—	—	Outdated technology (n = 1)	“Our computers are so slow.”
	—	—	Limited natural light (n = 1)	“There is no natural light in my office.”

Note. ^aThe subcategories that respondents identified as significant motivator/barrier to participation.

⁺and ⁻ = subcategories with positive and negative associations with worksite wellness programs (WWPs) participation respectively.

^↔ = a bi-directional association between the subcategory and WWP participation status.