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The majority of resilience interventions focus on the individual. Workplace resilience is a growing field of research. Given the ever-increasing interconnectedness in businesses, teamwork is a guarantee. There is also growing recognition that resilience functions at the team level.
The objective of our work was to address three shortcomings in the study of workplace resilience interventions: lack of interventions focusing on group-level or team resilience, the need for brief interventions, and the need for more theoretical precision in intervention studies.
The authors took an established evidence-based program (Team Resilience) and modified it based on these needs. A working model for brief intervention evaluation distinguishes outcomes that are proximal (perceptions that the program improved resilience) and distal (dispositional resilience). A total of 7 hypotheses tested the model and program efficacy.
Two samples (n=118 and n=181) of engineering firms received the Web-based training and provided immediate reactions in a posttest-only design. The second sample also included a control condition (n=201). The findings support the model and program efficacy. For example, workplace resilience was greater in the intervention group than in the control group. Other findings suggest social dissemination effects, equal outcomes for employees at different stress levels, and greater benefit for females.
This preliminary research provides evidence for the capabilities of e-learning modules to effectively promote workplace resilience and a working model of team resilience.
Recent national studies indicate increases in worker stress [
This individual-level focus ignores research showing psychosocial factors impact stress and health [
The study of WR interventions may be advanced in several ways. First, interventions could more fully address resilience at the group or team level. Indeed, recent studies support resilience as a team phenomenon [
To address these needs, we selected Team Resilience (TR), cited previously and also independently recognized as evidence-based by the national government [
TR promotes social dissemination, or peer-to-peer sharing, of resilience. Employees assessed at follow-up who were not exposed to the original training or employed at the time of the intervention had reduced stress and exposure to counterproductive work behaviors (CWBs) [
Several factors suggest that TR is promising for e-learning: a detailed and modular training manual; evidence for effectiveness; potential for social dissemination; advances in our understanding of team or social resilience; and a strong theoretical basis. A core feature of TR was the inclusion of participant exercises on 5 resilience competencies [
Centering (positive coping skills)
Confidence (self-efficacy and positive thinking)
Commitment (mental toughness, perseverance, and value-based behavior)
Community (social support, connectedness, and unit cohesion)
Compassion (empathy, perspective taking, and nurturing).
In their meta-analysis, Leppin et al [
To modify the previous classroom training for e-learning delivery, we reviewed original TR training manuals and studies on effective e-learning features. Such features include customization to the user or workplace, interactive elements, regular quizzing, personalized feedback, multimodule information, and psychoeducational resources [
As noted, progress in the study of resilience has been limited because of lack of conceptual clarity. Recently, the use of “wise interventions” [
Working model for brief intervention evaluation.
These perceived changes should correlate with proximal outcomes, yet ultimately affect distal outcomes also targeted by the intervention. We propose a “situational-to-dispositional” ordering of outcomes, from
First, as a result of the training, participants should perceive that their workplace—including their coworkers—provides them with resources for resilience (ie, WR). For example, TR makes multiple references to their Employee Assistance Program (EAP) and other workplace health resources. Although newcomer employees learn about these resources during orientation, they may be overwhelmed with information. Reminders (in the context of resilience) are designed to heighten awareness of their workplace as a resource.
Second, the adapted TR guides users to focus on
Furthermore, resilience may best be measured in the context of adversity (eg,
The primary goals of this pilot project were to assess (1) the feasibility of condensing a classroom training into e-learning and (2) employees’ reactions to the program using the working model described previously (see
A total of 7 hypotheses were derived from these goals:
As a study of self-reported resilience, we explore a new measure to distinguish ratings of WR, IR, and DR. H3 and H4 reflect these distinct outcomes:
To support construct validity, we examined other distinctions between workplace and DR. Accordingly, variables should relate to those variables one would expect them to relate to (ie, convergent validity) and not relate to those expected to be different (ie, discriminant validity). For convergent validity, measures of resilience would be expected to show an inverse relationship with recent stress. For example, employees who have either DR or WR might be less inclined to experience recent stress; therefore, we examined how both of these correlate with stress:
This study purposely assessed only short-term reactions to training. As noted previously, research suggests resilience training may be more effective in a high-stress sample [
One aspect of the original TR is its potential for social dissemination [
This paper also explores other factors related to the sample. First, we examine whether the training is more effective for women. A recent meta-analysis suggested that women may benefit more from increases in resilience [
Participants were recruited in 2015 and 2017 from firms within a national engineering association. Most firms were using a wellness benefit through the association for between 1 and 4 years. All 2015 participants were recruited to receive the program. In 2017, participants were also recruited to receive the program; a month later, only those who had not previously participated were then eligible to participate in a control sample.
A total of 217 participants from 40 firms began the survey; 174 ultimately completed it. Firm size ranged from 6 to 142 participants. The average number of participants from each firm was 4.28 (SD 3.91). The sample was 56.9% (99/174) female, and the modal (40%) age group was 26 to 40 years. Most participants had at least a Bachelor’s degree (78.7%; 117/174).
A total of 121 experimental participants began the survey, and 118 ultimately completed it. The control group consisted of 186 individuals. More men (64.5%; 120/186) than women (35.5%; 66/186) participated in the control group (χ22=19.0,
Program participants were recruited by an email sent from the local “Wellness Champion” within their firm. A “Wellness Champion” is an employee within the business that takes it upon themselves, whether formally or informally, to help coworkers take advantage of the company’s wellness resources. These champions also encourage participation in wellness programs, not unlike the one described in this paper. The association’s wellness director first sent an email template to each champion, who then distributed the email to employees. The email invited confidential participation in a Web-based, e-learning resilience module and a postsurvey questionnaire.
On receipt of the invitation email, participants clicked a URL link and entered their name and email address (used only for tracking and incentive purposes) to begin the training program. Participants had access to the modules at all times, via desktop, mobile, or tablet. More details about the program are discussed below.
Demographic breakdown of participants in all samples.
Demographics | Sample 1 (2015; n=174) | Sample 2 (2017; n=304) | ||
Program only | Program (n=118) | Control (n=186) | ||
Male | 75 (43.1) | 54 (45.8) | 120 (64.5) | |
18-25 | 18 (10.3) | 13 (11.0) | 29 (15.6) | |
26-40 | 70 (40.2) | 58 (49.2) | 75 (40.3) | |
41-50 | 35 (20.1) | 22 (18.6) | 38 (20.4) | |
≥51 | 51 (29.3) | 25 (21.2) | 44 (23.7) | |
Less than high school | 1 (0.6) | 7 (5.9) | 3 (1.6) | |
High school | 4 (2.3) | 4 (3.4) | 10 (5.4) | |
Some college | 32 (18.4) | 17 (14.4) | 38 (20.4) | |
Completed college | 98 (56.3) | 56 (47.5) | 93 (50.0) | |
Advanced degree | 19 (22.4) | 34 (28.8) | 42 (22.5) |
The same program was administered in 2015 and 2017. However, the 2 samples received different program completion incentives. Sample 1 received both individual- and firm-level incentives. Participants were informed at the beginning of the survey that they would be entered into a raffle to win a fitness armband. Sample 1 firms with the highest proportion of participants earned a US $200 award to use their wellness program. Sample 2 participants received US $5 for completing the program and an additional US $5 for completing the survey. Sample 2 control group participants received a US $5 Amazon.com gift card for filling out the survey after reading a short article on resilience tips.
For purposes of estimating social dissemination, we assessed how many 2017 participants came from 2015 firms. Of the 118 employees participating in the 2017 program, 36 participants came from 16 firms with no prior participation, 10 from 5 firms with one prior participant, and 54 from 11 firms with 2 or more participants. Of 201 employees participating in the 2017 control condition, corresponding numbers were 95 participants from 17 firms with no prior participation, 28 from 4 firms with one prior participant, and 56 from 10 firms with 2 or more participants. In 2017, 20 firms participated in the program condition, 19 firms participated in the control condition, and 12 firms participated in both conditions.
The e-learning module sought to increase participants’ ability to be resilient in the workplace, their knowledge of resiliency, their awareness of resources, and their willingness to access those resources when necessary. The program consisted of tips and strategies around building “5 Cs of Resilience” (ie, Centering, Commitment, Community, Compassion, and Confidence).
We followed 6 design goals for developing the electronic module: (1)
The module was created using Articulate Storyline (Articulate, New York, NY) and included video, audio, interactive exercises, and quizzes in 4 sections: (1)
Participants in both samples were given 4 to 6 weeks to complete the program and accessibility from any computer or mobile device. The program contained 55 slides; the minimum number of slides to be viewed to receive credit for the program was 38, but most participants viewed at least 45 slides. Immediately after program completion, participants were automatically provided the survey link.
Core sequence of each Five C component and final profile.
On completion of the 2017 program condition, wellness champions sent an email to employees asking for input from those who had never completed any wellness program. Participants filled out a survey after reading a one-page article featuring 8 tips on how to “build resilience” (eg, sleep, relaxation, ask for help). Participants were given 1 week to complete the survey. Any individual who had previously participated was removed from data analyses.
A survey assessed participants in 4 areas: (1) demographic information; (2) PI or impact of the resilience module (eg, “My willingness to: be more resilient at work, use resilience resources, has…”); (3) measures in 3 areas of resilience: WR, IR, and DR; and (4) one satisfaction item (“Overall, how satisfied were you with the online module?”). Response options were on 5-point Likert scales for PI (1—“Stayed the same” to 5—“Improved greatly”) and for resilience (1—“Not true about me” to 5—“Very true about me”). WR was evaluated using 3 items derived from a review of recent writings on the topic [
Reliabilities, assessed by combining data across all samples, were PI: alpha=.92; WR: alpha=.68; IR: alpha=.59; and DR: alpha=.86. The 2017 survey included an item asking about stress: “How much has stress hurt your ability to stay healthy and productive in the past month?” Response options ranged from “not at all” (1) to a “great amount” (5). This survey was given to participants on completion of the training program.
We compared responses for all items for samples 1 and 2 and found no significant differences (all
H1 proposes the idea that the mean PI score would be greater than chance. A mean rating of 2.5 was used as a conservative baseline, as it represented the mid-point between improving “slightly” and “some.” For the program group, ratings on all 4 items reflected significant improvements (ability—
H3 predicted that, across all 4 measures, resilience would be greater for program versus control participants. As expected, the strongest effect was for WR; program (mean 3.85; SD 0.68) versus control (mean 3.11; SD 0.75),
H4 proposes that WR would correlate most strongly with PI. Again, training objectives sought to improve both TR
H5 predicted that DR would have the strongest relationship with stress (measured in sample 2).
There was no difference in stress levels between program (mean 2.58; SD 0.96) and control (mean 2.60; SD 1.04) participants. Because the brief resilience program focused on helping employees with stress, we explored whether those across 3 levels of stress (low, medium, and high) benefitted from the program (
Relationship of resilience measures to perceived improvement and stress.
Outcome | Perceived improvement | Stressa | ||||||
Program | Control | Program | Control | |||||
Partial |
Partial |
Partial |
Partial |
|||||
Workplace resilience | .24b | .24b | .47b | .44b | −.36b | −.13 | −.08 | −.05 |
Inner resources | .09 | −.02 | .27b | .18c | −.28b | −.02 | −.05 | .01 |
Dispositional resilience | .06 | −.06 | .14 | −.19b | −.56b | −.46b | −.07 | −.04 |
aOnly measured in sample 2.
b
c
Comparing program and control outcomes at different stress levels (sample 2). Adjusted means are shown, controlling for gender, age, and education.
Analysis | Stress levela | Analysis of variance | ||||||||
Program (n=118) | Control (n=186) | Main Effect | Interact | |||||||
Low | Med | High | Low | Med | High | Stress | Program | |||
Subsample, n | 54 | 48 | 16 | 90 | 62 | 34 | – | – | – | |
Perceived improvement | 2.99 | 3.16 | 3.08 | 2.39 | 2.83 | 2.35 | NSb | 15.66c | NS | |
Workplace resilience | 3.91 | 3.76 | 3.35 | 3.19 | 3.08 | 2.98 | 5.17c | 42.37d | NS | |
Inner resources | 4.09 | 3.89 | 3.59 | 3.83 | 3.73 | 3.62 | 5.49c | NS | NS | |
Dispositional resilience | 4.31 | 4.20 | 3.31 | 4.08 | 3.97 | 3.88 | 18.33c | NS | 10.94c | |
Satisfaction | 3.41 | 3.60 | 3.44 | 3.12 | 3.19 | 3.00 | NS | 6.27d | NS |
aLow: not at all or a little; med: some; high: much or great amount.
bNS: nonsignificant.
c
d
Gender differences in outcomes.
Item | Program, mean (SD) | Control, mean (SD) | ||||
Female (n=149) | Male (n=126) | Female (n=66) | Male (n=120) | |||
Perceived improvement | 3.10 (0.90) | 3.08 (0.82) | 0.19 (273) | 2.66 (1.08) | 2.46 (1) | 0.63 (184) |
Workplace resilience | 3.96 (0.59) | 3.81 (0.64) | 2.02a (273) | 3.11 (0.72) | 3.12 (0.66) | 0.10 (184) |
Inner resources | 4.07 (0.60) | 4.08 (0.58) | 0.14 (273) | 3.79 (0.61) | 3.74 (0.70) | 0.49 (184) |
Dispositional resilience | 4.19 (0.60) | 4.27 (0.53) | 1.16 (273) | 3.88 (0.57) | 4.07 (0.55) | 2.23a (184) |
Satisfaction | 3.67 (0.87) | 3.44 (0.88) | 2.17a (273) | 3.30 (1.04) | 3.02 (0.97) | 1.84 (184) |
a
A two (condition) by three (stress level) analysis of variance (ANOVA) was conducted while controlling for demographics (gender, age, and education). There was a main program effect for PI, WR, and program satisfaction. Consistent with correlations in
Employees in the 2017 sample worked in firms that had different amounts of previous exposure to the resilience training. Both the 2015 and 2017 datasets allowed comparison of employees from “nonexposed” firms to those firms where employees may have learned something from previous participants. H7 posited that PI and WR would be strongest among employees from firms with two or more previous participants versus only one or no previous participants.
No differences in PI or WR were found across these 3 levels of previous exposure for either the program or control groups. However, stress was lowest among program participants coming from firms where two or more employees had previously had the training: none (mean 2.78; SD 0.96), one (mean 2.7; SD 1.06), or more than one (mean 2.39; SD 0.86),
Additional tests, shown in
A total of 7 hypotheses were tested through an exploratory pilot study. Results generally support the conclusion that a brief Web-based resilience program can lead to proximal improvements in resilience as a social resource within work settings. This finding is supported by tests of H1, H2, and H3; the latter hypothesis included a control group comparison. Experimental versus control study comparisons showed positive outcomes for PI, WR, and satisfaction.
Stress has an impact on employee health and performance, and employees have a need for effective programs to address stress. Ideally, employers who purchase or promote such programs should know that their investments are wise ones, based on evidence [
We add this to list the need for programs that enhance social well-being and educate workers about the impact of their own health on coworkers. This social focus can enhance potential dissemination or ripple effects [
In support of H4, PI (ratings of how much the training improved resilience at work) showed a correlation with WR. Several factors could account for these results. In particular, TR was designed to be distributed to employees
In support of construct validity, only DR was significantly and inversely correlated with recent stress, after controlling for the other resilience measures (
Overall, findings also support a newly proposed working model for brief intervention evaluation that distinguishes proximal outcomes from longer-term dispositional resilience. Given the lack of clarity in previous resilience intervention studies, we hope that the findings from this study lead future researchers to clearly distinguish WR from dispositional measures.
Of special interest was a test of dissemination effects. We compared sample 2 (2017) employees from firms with no previous (2015) exposure to the resilience training with employees from firms that had previous exposure. H7 claimed that the previously exposed group would show more positive outcomes. Results did not show any differences among the variables in the working model for brief intervention evaluation (eg, PI, WR). However, those in the program group who came from firms with previous exposure reported less recent stress and lesser program satisfaction. It is difficult to say whether these employees benefited from their previous coworker’s experience or whether those who were less stressed also self-selected into the program. However, the same finding was not apparent in the control sample, suggesting that TR may have made previous coworker’s exposure more salient to current and new participants.
This study contained several important limitations. First, we used a nonrandomized quasi-experimental design, with a self-selected, convenience sample. Differences found between conditions may be due to preexisting characteristics in these groups or some other sampling artifact. This includes types of incentives used (between experimental and control groups), varying study time frames, and a sole focus on engineering firms. Although the findings of intervention-control comparisons are strengthened by the fact that there were 2 samples in the intervention condition, the control group was highly selected. Employees were recruited who specifically had not participated in any previous wellness program and who were asked to participate partly to share why they had not previously engaged in previous programs.
Other limitations may be considered in light of the pilot nature of the study. The measures that were used were themselves piloted, without full-scale development and factor analyses. Although the DR measure was adapted from Connor and Davidson [
Another limitation of this study was its focus on only immediate or proximal reactions. A more useful test would assess longer-term outcomes, especially taking ongoing stress into consideration. However, the workplace training literature suggests that utility types of reactions—as used here with PI—may correlate with more distal outcomes (eg, program satisfaction) [
Finally, the organizations sampled in this study varied in size, and none of them employed a substantial amount of people, compared with large organizations (ie, 500+ employees). It could be safely assumed that there is a positive linear relationship between the number of employees and the number of teams that are within the organization, which could result in stronger findings (eg, more dissemination throughout employees). This would be an interesting avenue to explore in further research, especially as research on small business wellness is limited [
Overall, this study is best viewed as an exploratory pilot. However, it makes several contributions. First this work also included both a new theoretical model and an e-learning extension or adaptation of an established classroom training. Furthermore, besides adapting the classroom training into an e-learning training, this work also tested the intervention on a different occupational sample (engineers) than the original study (restaurant workers). Findings suggest further and more rigorous tests of the model may be promising for the science of Web-based workplace TR training.
analysis of variance
counterproductive work behavior
dispositional resilience
Employee Assistance Program
inner resources
perceived improvement
team resilience
workplace resilience
The authors would like to thank the American Council of Engineering Companies Life/Health Trust and Yukon Learning for their support and collaboration.
The Team Resilience program is owned by Organizational Wellness & Learning Systems in which one of the authors (JBB) has a financial interest.