The role of secondary traumatic stress breakthrough champions in reducing worker trauma and improving organizational health using a configurational analysis approach

Abstract

Background

Emerging research has demonstrated that organizational efforts at becoming secondary traumatic stress (STS)-informed can improve the overall well-being of the workforce, especially when implementation activity by a champion team is high. Questions remain, however, regarding the mechanisms that enable these improvements.

Method

This study uses configurational analysis to determine necessary and sufficient conditions to produce reductions in STS symptoms in workers as well as organizational improvements toward being more STS-informed in a cohort survey of 6,033 professionals working with individuals exposed to trauma representing 52 organizations. The Secondary Traumatic Stress Informed Organizational Assessment (STSI-OA) was used to measure professional's perceptions of how well the unit addressed secondary trauma in the workplace, and the Secondary Traumatic Stress Scale (STSS) assessed traumatic stress symptoms in respondents. Champions' activity was scored using the categories suggested by Shea.

Results

For the STSS outcome, either a STSI-OA positive increase of 10 or more points or high levels of champion problem-solving were independently sufficient for an improvement in the outcome. The STSI-OA model had two pathways: high levels of peer engagement via the scaling up of innovations using PDSAs or the combination of facilitation of peer knowledge and skills together with working in a child welfare organization. Either pathway was sufficient by itself to yield the STSI-OA outcome.

Conclusions

Identifying and cultivating the champions' use of problem-solving and peer engagement strategies can transform the threat posed by indirect trauma exposure into an opportunity for shared experience and healing.

Plain Language Summary

Organizational champions are individuals or teams that strive to promote change within their workplace. These champions are integral to spreading innovative ideas and strategies and creating organization-wide changes ( Powell et al., 2015). However, little is known about the processes or specific strategies that make champions successful. One area in which champions are needed is in improving organizations' response to and understanding of secondary traumatic stress (STS), among those in helping professions that are indirectly exposed to trauma through the traumatic stories of those they work with. In fact, research has shown that organizational efforts to address STS improve the well-being of individual professionals within that organization ( Sprang et al., 2021). The present study sought to better understand what champion-related processes or conditions led to organizational change in addressing the effects of indirect exposure and improving symptoms related to STS. Results showed that organizational change in addressing STS and champions' problem-solving strategies resulted in reductions in individual professionals' STS symptoms. Furthermore, champions' use of peer engagement or sharing of knowledge among peers in child welfare settings led to improvements at an organizational level. These results show that organization-level change can have a direct impact on individual well-being and there are specific champion activities that can promote this change. Specifically, results demonstrate a need to identify and support champions' use of problem-solving and peer engagement strategies to turn the individual and organizational threat posed by indirect trauma into an opportunity for shared healing.

Keywords

secondary traumatic stress champions STSI-OA worker trauma configurational analysis organizational change

Introduction

Trauma is a pervasive public health issue that drives survivors toward interactions with service systems (e.g., child welfare, justice, behavioral health, and healthcare) with high needs and at above-average utilization rates (Briggs et al., 2012; Huang et al., 2014). Professionals working in these systems can experience a myriad of reactions to these demands due to high caseloads, indirect trauma exposure, and inadequate resources (Brady, 2017; Shoji et al., 2015). In a parallel and cascading process, organizations are impacted by the nature of this trauma work, which if unaddressed can create toxic, and ineffective service delivery systems characterized by high absenteeism, presenteeism, attrition, and an unsupportive culture (Ratrout & Hamdan-Mansour, 2020). To address the dual harms (individual and organizational) created by the intensity and onus of trauma work, efforts have focused on creating trauma-informed or secondary trauma-informed cultures that promote physical and psychological safety and resist retraumatization (Jankowski et al., 2019; Lang et al., 2016). Successful implementation of a trauma-informed approach to service delivery is often facilitated by a group of champions, who lead these efforts (Jankowski et al., 2019; Loomis et al., 2019). This article examines the role that champions play in addressing the impact of trauma on the workforce and the organizations that deliver services to those affected by trauma.

Those within the workforce that envision, produce, and promote change have been deemed the dreamers and seers of organizational possibility (Wolverton, 1998). Powell et al., (2015) define these champions as those “who dedicate themselves to supporting, marketing, and driving through an implementation, overcoming indifference or resistance that the intervention may provoke in an organization” (p. 9). The role of champion has been operationalized as an internal employee, with intrinsic commitment, who through diligent effort demonstrates their enthusiasm, persistence, and energy toward change with conviction (Miech et al., 2018). These individuals may be emergent, responding to an identified need they feel compelled to address (Howell & Higgins, 1990), or appointed by a senior leader or colleague based on perceived interest and expertise (Wood et al., 2020). These champions may work in teams representing single units (Papadakis et al., 2014) or act as boundary spanners across different organizational domains (Ash et al., 2003; Clack et al., 2018). Recently the literature has documented the importance of champions in creating systems and organizations that are trauma-informed, and able to address the deleterious impact of trauma on client and patient populations, and those who serve them (Dichter et al., 2018; Koury & Green, 2017; Sprang et al., 2021).

Most of the research on champions is descriptive and documents that these individuals and teams outperform control conditions in producing change, though there is some equivocality in results (Shea & Belden, 2015). In 2015, the identification and preparation of champions were included in the taxonomy of implementation strategies derived from the Expert Recommendations for Implementing Change Project (Powell et al., 2015). This inclusion, based on input from implementation scientists and practitioners, reflects and supports widespread research that documents the importance of champion efforts at successful change (Bonawitz et al., 2020; Shaw et al., 2012; Shea & Belden, 2015; Slaunwhite et al., 2009), with only a few studies showing no impact (Hendy & Barlow, 2012; Verhoeven et al., 2009). Despite widespread recognition that change or innovations champions are integral to the process of implementation (Powell et al., 2015), an integrative review of 199 articles on the state of the literature on champions in healthcare revealed that over 90% of the studies focused on determining the presence or absence of champions, with only a few providing estimates of degree of leadership, advocacy effectiveness, and the relative strength and direction of their influence on implementation (Miech et al., 2018). The limited number of investigations that explore the nuances of the champion role, which contributes to innovation, limits our understanding of the various ways that these actors may affect change (Shea, 2021). Accordingly, the use of champions in implementation efforts is lacking guidance regarding the necessary preparation, protocols, and methods to measure champion-specific factors that positively impact outcomes.

Recently, there have been efforts to examine the role of champions in addressing the issue of secondary traumatic stress (STS) in the workplace, and efforts toward creating secondary trauma-informed organizations (Levin et al., 2021; Sprang et al., 2021). STS is a trauma condition that arises in professional staff due to indirect trauma exposure to client or patient trauma narratives (via psychotherapy), hearing trauma details (during law enforcement or child welfare investigations), seeing the aftermath of trauma and violence in healthcare settings, and through court testimony (May & Wisco, 2016; Hensel et al., 2015). In 2017, researchers operationalized the characteristics of a secondary traumatic stress-informed organization via an organizational assessment measure (the Secondary Traumatic Stress-Informed Organizational Assessment, or STSI-OA). This prompted several investigations into how change toward reducing secondary trauma at the individual and agency level occurs (Rowland, 2021; Sprang et al., 2021; Wilson, 2020). While it is recognized that organizational efforts toward becoming secondary trauma-informed are driven by teams of committed and/or concerned employees, the types of activities these champions engage in to produce change are largely unknown (Koury & Green, 2017; Sprang et al., 2021).

The current library of studies on champions in implementation research has used a wide array of quantitative and qualitative methodologies including case and cross-case analysis and comparisons, surveys, interviews, quality improvement and evaluation methods, pre- and post-repeated design, and secondary data analysis (Miech et al., 2018). However, this is one of few, if not the only study, that uses configurational analysis to examine how specific combinations of champion-related conditions and practice-level characteristics uniquely distinguish individuals that experienced substantial change in their STSI-OA and Secondary Traumatic Stress Scale (STSS) scores from those who did not. Configurational analysis is a systematic, cross-case approach that draws on set theory, formal logic, and Boolean algebra to identify a “minimal theory” for an outcome of interest (Baumgartner & Falk, 2019; Rich et al., 2020). Specifically, configurational analysis identifies necessary and sufficient conditions for an outcome of interest; particular combinations of conditions that jointly yield an outcome of interest; and multiple solution pathways that lead to the same outcome. To this end, the analytic objective of this study was to identify necessary and sufficient conditions to produce reductions in STS symptoms in cohorts of workers, as well as organizational improvements toward being STS-informed.

Method

Procedure

This observational cohort study includes data from 52 organizations that were involved in a change initiative aimed at creating STS-informed organizations representing schools (20.7%), community mental health centers (25.9%), child welfare agencies (46.6%), social services (5.1%), and public health (1.7%) during a 4-year time period. Organizations applied to be part of this process and were selected based on the type of organization (so that similar systems could be clustered into groups) and expressed commitment to the process. The final sample included 100% of those invited to participate. Each organization created a team of self-reported champions to lead the organization's efforts that were selected based on four eligibility criteria: (1) their desire to be an early adopter and champion of the initiative, (2) self-reported concern about the impact of indirect exposure to trauma on the organization, (3) evidence of senior leader support, and (4) expressed commitment to participate in the full process. Across all Secondary Traumatic Stress Breakthrough Series Collaboratives (STS-BSCs), the champions team represented all aspects of the organization including front-line workers (e.g., clinicians, child welfare investigators, case managers, healthcare providers in public health settings, school mental health professionals, teachers, etc.; 72.1%), supervisors and senior leaders in these organizations (23.8%), and administrative services (4.1%; e.g., schedulers, intake coordinators, etc.). This pattern of representation was similar across all teams. The data used in this study represent the aggregate organizational data from all employees (N = 6,033) within these 52 organizations who responded to baseline and end-of-initiative (9 months later) surveys. Surveys were completed anonymously in Survey Monkey to control for social desirability bias. All responses were reported in aggregate only. Response rates across organizations were high, ranging from 78% to 99% at baseline, and 67% to 94.4% at post due in part to high staff turnover in many of the organizations (not the champions team where turnover was <4%). All study protocols received approval from the university's Institutional Review Board and participants provided informed consent before completing study measures. We used the STROBE cohort checklist when writing our report (Von Elm et al., 2007).

Change Process (Intervention)

Each champion's team consisted of 5–10 employees representing diverse aspects of the organization. These champions received coaching and consultation, from STS and organizational change experts, which was driven by the unit's survey results to develop specific goals toward being STS-informed based on their data dashboards.

The process toward organizational change was structured by a learning system called a Breakthrough Series Collaborative that brings teams from across multiple organizations together with the common purpose of quality improvement in a focused topic area (Bate et al., 2001). The STS-BSC faculty provided technical assistance and teaching via coaching, and consultation on microstrategies that could be used to help each team's identified goals, as well as implementation approaches to improve the successful planting and sustainability of the teams. The STS-BSC consisted of three learning sessions, affinity groups, senior leader calls, all-team learning calls, individual consultation calls, as well as champions meetings with their own staff and leaders. The Basecamp project management platform was used to share content, engage cross-team communication and fertilization, and track team progress. Innovations and barriers to goal attainment were addressed by using the Plan, Do, Study, Act (PDSA) problem-solving process to test possible interventions to address STS or enhance resiliency, and to guide the scale-up of successful activities (Taylor et al., 2014).

Measurement

The STSI-OA (Sprang et al., 2017) was used to categorize and drive organizational efforts toward being STS-informed. Psychometric analysis of the 40-item measure has revealed a five-factor structure that includes domains of activity related to organizational promotion of resilience-building activities (seven items); the degree to which an organization promotes physical and psychological safety (seven items); the degree to which the organization has STS relevant policies (six items); how STS-informed respondents rate leadership practices (nine items) and routine organizational practices (11 items). Each item is scored on a six-item Likert scale where response categories include 0 (not applicable), 1 (not at all), 2 (rarely), 3 (somewhat), 4 (mostly), and 5 (completely). Total scores range from 0 to 200, with higher scores indicating the organization is more STS-informed. With these data, internal consistency for the overall STSI-OA is excellent (.977) with domain αs established as .888 (safety), .940 (resilience building), .922 (organizational policy), .941 (leader practices), and .955 for organizational practices.

The STSS for Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM–5; B. Bride, personal communication, October 5, 2013) was used to assess the professionals' self-reported symptoms of STS related to intrusion, avoidance, alterations in mood and cognition, and alterations in arousal and reactivity. These domains map onto the DSM-5 (American Psychiatric Association, 2013) depiction of symptoms of posttraumatic stress disorder (PTSD) with the exception of the item “I felt discouraged about the future,” which is no longer included in the DSM-5 item domain so was not included in the scoring of the STSS. Responses were solicited using a 5-point Likert scale to determine the presence and frequency of symptoms with 1 representing never and 5 signifying very often. Possible scores range from 21 to 105, with higher scores indicating higher levels of STS. The STSS demonstrated good internal consistency in this study (α = .961), with subscale αs ranging from .759 (avoidance) to .895 (alterations in cognitions and mood).

Champion Factors were identified using the conceptual framework proposed by Shea (2021). In this study, organizational and champion acts toward becoming STS-informed were organized into the domains of Performance (Organization provides time and resources to champions; Organization delegates authority; Organization rewards champions; Champions allocate time to role; Champions problem solve), Peer engagement (Champions use peer data to drive activities, Champions effectively communicate with colleagues, Champions facilitate peer knowledge and skills, Champions use PDSA to scale up innovations) and Impact (penetration, impact of initiatives on policy and protocols, and securing additional funding). Prior to final data collection and blind to posttest results, the faculty rated the champion team on the degree to which the specified factor was achieved by reviewing all documents and applying a rating score based on the level of activity relative to each item. The following scale was used to rate the organization on each individual indicator: 0 = not at all (no evidence of activity related to the item); 1 = somewhat (level of activity low, sporadic, infrequent, and/or incomplete); 2 = mostly (activity was moderate with some minor issues with consistency or completion); 3 = completely (level of activity was uniformly high and/or complete. These scores were determined using a review of Basecamp postings (activity logs that chronicled the use of tools, workgroup minutes, and application of learning in team meetings), STS-BSC attendance and participation, review of PDSA cycles and outcomes including evidence of scale-up and spread, and goal content, refinement, and attainment. Cronbach's αs for the champions factors subscale were very good ranging from .913 (Impact), .965 (Peer Engagement), and .968 (Performance). The type of organization (school, community mental health, child welfare, and social services) was also considered in the analysis.

Analysis

The particular configurational approach used in this study was coincidence analysis (CNA; Ambuhl et al., 2021; Whitaker et al., 2020), a relatively new configurational method within the larger family of configurational comparative methods (CCMs) with a rapidly growing literature that numbers over 55 peer-reviewed publications.

Configurational analysis in general was selected for this study for three main reasons. First, configurational analysis explicitly embraces complexity and controls for bias, with its capacity to assess how the interplay of specific conditions can lead to an outcome of interest. Second, configurational analysis can identify equifinality, when more than one pathway leads to the same outcome. Third, configurational analysis is versatile in that it can be applied to datasets large or small, including small-n studies (Whitaker et al., 2020).

Within the larger family of CCMs, there two most prominent approaches are qualitative comparative analysis (QCA) and CNA (Swiatczak, 2022). Both methods draw upon Boolean algebra and set theory and both search for necessary and sufficient conditions. A fundamental difference between the two methods, though, is their central algorithm. QCA applies the top-down Quine-McCluskey algorithm from electrical engineering (Thiem, 2022), whereas CNA uses a bottom-up algorithm custom-designed for application in social sciences research (Swiatczak, 2022). CNA was selected for this study because of the advantages conferred by this bottom-up approach: CNA produces a single-solution type, instead of the three different solution types generated by QCA (Thiem, 2022); unlike QCA, CNA does not require the use of counterfactuals (Thiem, 2022); and CNA is the only configurational approach with a systematic routine to assist in factor selection (Yakovchenko et al., 2020).

Specific software used to support this analysis included the R package “cna” for Coincidence Analysis, RStudio, R, and Microsoft Excel (Ambuhl et al., 2021). As this CNA analysis required outcomes to be expressed as categorical values, the STSS outcome was dichotomized and coded as “1” if improvement in STSS scores were ≥1 and “0” if <1. The STSI-OA outcome was coded as “1” if improvement in STSI-OA was ≥10 and “0” if <10. The next step was to develop an analytic dataset for use in model-building with CNA, as the 15 potential explanatory factors in the original dataset were too many to include in a single model. There were no compelling a priori theoretical reasons to select certain factors over others for inclusion in model development: each factor had a plausible connection to the outcome and hence was included in the original dataset. There were no missing data. To achieve data reduction, we used a configurational approach using the “minimally sufficient conditions” (i.e., “msc”) function that has been described in detail elsewhere (Yakovchenko et al., 2020) but summarized here. In brief, we applied the “minimally sufficient conditions” (i.e., “msc”) function within the R package “cna” to look across all 52 cases and all 15 factors at once to identify specific combinations of conditions with especially strong connections to the outcome of interest. This exhaustive process considers every combination of values instantiated in the original dataset and identifies all one-, two-, and three-condition configurations that meet the specified consistency threshold. During this exploratory data analysis, the msc function was run at five different consistency levels: 100%, 95%, 90%, 85%, and 80% (Rich et al., 2022; Yakovchenko et al., 2020). As the primary focus of the analysis was on champion-related conditions, when reviewing this mathematical output we considered only those configurations that met all of the following criteria: “best of class” coverage scores (i.e., top coverage score among configurations with the same number of conditions); coverage scores >15%; ≥1 champion-related condition; and consistent with logic, theory, and prior knowledge. We then used that condition-level information to guide selection of a smaller subset of factors to include in model iteration.

During model development, the goal was to develop an overall model with ≥ 80% scores for both consistency and coverage, and with no model ambiguity: our model needed to explain at least 80% of the cases with the outcome (coverage), yield the outcome at least 80% of the time the solution appeared anywhere in the dataset (consistency), and be the only solution (Baumgartner & Ambuhl, 2020). Data reduction and subsequent model development were conducted separately for the STSS and STSI-OA outcomes.

Results

The sample consisted of champion teams from child welfare organizations (46.6%), community mental health agencies (25.9%), schools (20.7%), and social service agencies (6.8%). Mean STSS scores were 41.5 at baseline and 36.7 at the end of initiative, representing a statistically significant improvement in individual levels of STS from pre to post-STS-BSC (t = 4.571, p = .001). Similarly, organizational scores on the STSI-OA improved in a significant manner from pre (71.76) to post (85.08) (t = −7.705, p = .001). Champion performance was variable across teams (see Table 1).

Table 1

Descriptives for Champion Factors (N = 52)

Factor	Not at all(0)	Somewhat (1)	Mostly(2)	Completely(3)
Performance—Organization Provides Time and Resources	4 (7.7%)	19 (36.5%)	14 (26.9%)	15 (28.8%)
Performance—Organization Delegates Authority	7 (13.5%)	18 (34.6%)	13 (25%)	14 (26.9%)
Performance—Organization Recognizes and Rewards Champion	7 (13.5%)	17 (32.7%)	14 (26.9%)	14 (26.9%)
Performance—Champions Allocate Time to Role	9 (17.3%)	15 (28.8%)	13 (25%)	15 (28.8%)
Performance—Champions Problem-Solve	1 (1.9%)	14 (26.9%)	22 (42.3%)	15 (28.8%)
Peer Engagement—Uses Data to Drive Engagement	10 (19.2%)	9 (17.3%)	14 (26.9%)	19 (36.5%)
Peer Engagement—Communication	4 (7.7%)	16 (30.8%)	13 (25%)	19 (36.5%)
Peer Engagement—Facilitate Knowledge and Skills	7 (13.5%)	7 (13.5%)	20 (38.5%)	18 (34.6%)
Peer Engagement—PDSA Scale-up of Innovations	12 (23.1%)	11 (21.2%)	15 (28.8%)	14 (26.9%)
Impact—Penetration	10 (19.2%)	14 (26.9%)	15 (28.8%)	13 (25%)
Impact—Policy and Protocol Development	11 (21.2%)	14 (26.9%)	14 (26.9%)	13 (25%)
Impact—Secured additional funding	21 (40.4%)	17 (32.7%)	12 (23.1%)	2 (3.8%)

STSS Positive Model

For the STSS outcome, a model with only two factors explained a STSS improvement of ≥1 point: a STSI-OA positive increase of 10 or more points or a “Champions Problem Solving” value of 2 or 3, corresponding to (respectively) “To a great extent” or “Completely.” Either one of these two conditions was sufficient on its own for the outcome. A solution visualization for this model is found in Table 2. For the STSS outcome (column A), negative values indicate improvement (i.e., fewer self-reported symptoms of STS).

Table 2

STSS Positive Model: STSIO_CHANGE_10PLUS = 1 + PerformProbSolve2or3 = 1 ↔ STSS_CHANGE_1Plus = 1

STSSCHANGE	STSS_CHANGE_ 1Plus	STSIO_CHANGE_ 10PLUS	PerformProbSolve_ 2OR3	STSIO_ CHANGE	Perform Probsolve
−9.75	1	1	1	61.57	3
−14.4	1	1	1	37.33	3
−4.83	1	1	1	33.33	3
−14.06	1	1	1	32.32	3
−5.92	1	1	1	29.74	3
−3.02	1	1	1	29.65	3
−10.38	1	1	1	25.24	3
−14.24	1	1	1	18.77	3
−3.08	1	1	1	17.01	3
−1.26	1	1	1	15.02	3
−1.47	1	0	1	8.36	3
−1.26	1	0	1	6.09	3
−1.55	1	0	1	5.61	3
−9.52	1	0	1	3.09	3
−4.1	1	1	1	38.72	2
−9.59	1	1	1	27.84	2
−1.91	1	1	1	18.62	2
−3.51	1	1	1	18.43	2
−5.7	1	1	1	17.56	2
−2.58	1	1	1	17.5	2
−12.8	1	1	1	16.22	2
−9.53	1	1	1	14.88	2
−1.2	1	1	1	14.63	2
−2.58	1	1	1	13.82	2
−10.7	1	1	1	11.03	2
−4.33	1	1	1	10.67	2
−4.27	1	1	1	10.03	2
−1.39	1	1	1	10.02	2
−1.09	1	0	1	7.49	2
−2.83	1	0	1	4.03	2
−1.63	1	0	1	3.71	2
−2.63	1	0	1	2.18	2
−1.24	1	1	0	15.5	1
−2.23	1	0	0	5.88	1
−2.65	1	0	0	3.36	1
−1.19	1	0	0	1	1
−0.24	0	0	0	1.1	1
9.2	0	0	1	4.28	3
−0.59	0	1	1	15.5	2
−0.47	0	0	1	6.85	2
−0.26	0	0	1	2.64	2
−0.38	0	0	1	0.22	2
−0.37	0	1	0	20.33	1
−0.58	0	1	0	16.33	1
−0.74	0	0	0	8.53	1
−0.4	0	0	0	4.55	1
1.69	0	0	0	1.64	1
0.08	0	0	0	1.01	1
−0.67	0	0	0	0.24	1
8.83	0	0	0	0.21	1
5.37	0	0	0	−1.29	1
−0.86	0	0	0	4.11	0

This model accounted for nearly every case with STSS change of ≥1 point and had an excellent coverage score of 92% (33/36); this model also reliably yielded the outcome, with a consistency score of 83% (33/40).

STSI-OA Positive Model

In the model for the STSI-OA outcome, only three factors accounted for a STSI-OA improvement of ≥10 points. This model had two pathways: (Pathway 1) a “Champions use PDSA to scale up innovations” score of either 2 or 3 or (Pathway 2) a “Champions facilitate peer knowledge and skills” score of either 2 or 3 and a system value of 3 (indicating the champion worked in a child welfare organization). Either pathway was sufficient by itself to yield the STSI-OA outcome. As before, a 2 or 3 value for the champion-related factors corresponded to “To a great extent” (value =2) or “Completely” (value =3). A solution visualization for this model is found in Table 3. This model accounted for every case with STSI-OA change of ≥10 points but one with a near-perfect coverage score of 97% (27/28). It also reliably yielded the outcome, with an overall consistency score of 82% (27/33).

Table 3

STSI-OA Positive Model: PDSAscaleup_2or3 = 1 + (FacilitateKS2or3 = 1 × SYSTEM = 3) ↔ STSIOA_10PLUS = 1

STSIOA CHANGE	STSIOCHANGE_10PLUS	PDSAscaleup_2OR3	FaciliateKS_2OR3	system	PDSAscaleup	FacilitateKS
15.5	1	0	0	3	0	1
20.33	1	0	1	3	1	2
15.5	1	0	1	3	1	2
10.02	1	0	1	3	1	2
16.33	1	1	1	1	3	3
27.84	1	1	1	1	2	2
18.62	1	1	1	3	2	2
18.43	1	1	1	2	2	2
17.56	1	1	1	2	2	2
17.5	1	1	1	2	2	2
16.22	1	1	1	1	2	2
14.63	1	1	1	2	2	2
13.82	1	1	1	3	2	2
11.03	1	1	1	1	2	3
10.67	1	1	1	3	2	2
17.01	1	1	1	2	3	3
10.03	1	1	1	3	2	2
14.88	1	1	1	3	3	2
29.74	1	1	1	3	2	3
61.57	1	1	1	1	2	3
33.33	1	1	1	2	2	3
38.72	1	1	1	3	3	3
37.33	1	1	1	1	3	3
32.32	1	1	1	2	3	3
29.65	1	1	1	3	3	3
25.24	1	1	1	3	3	3
18.77	1	1	1	1	3	3
15.02	1	1	1	2	3	3
3.36	0	0	0	1	0	0
1.1	0	0	0	1	0	0
0.24	0	0	0	3	0	0
8.53	0	0	0	1	0	0
4.11	0	0	0	2	0	0
1.64	0	0	0	3	0	0
1.01	0	0	0	2	0	1
0.21	0	0	0	3	0	1
4.55	0	0	0	5	0	0
1	0	0	0	2	0	1
7.49	0	0	1	1	1	2
6.85	0	0	1	3	1	2
5.88	0	0	0	3	1	1
4.03	0	0	1	2	1	2
2.64	0	0	1	1	1	2
2.18	0	0	1	2	1	2
0.22	0	0	1	2	1	2
6.09	0	1	1	2	3	3
3.71	0	0	0	2	1	1
−1.29	0	0	0	3	0	1
8.36	0	1	1	2	2	3
5.61	0	1	1	3	3	3
4.28	0	1	1	3	3	3
3.09	0	1	1	7	3	3

Discussion

Prior research has suggested that organizational efforts at becoming more STS-informed can reduce the aggregate levels of STS in the workforce, especially when implementation activity by the champion team is high (Sprang et al., 2021). Questions remain, however, regarding the mechanisms that enable these improvements. In this study, a champion's performance and peer engagement strategies in certain settings were found to be key pathways linking organizational efforts to the reduction of traumatic stress symptoms at the individual level. Clearly delineating how organizations can contribute to the overall emotional well-being of their employees opens up new opportunities for bifocal responses to indirect trauma exposure, and mezzo-level adjunctive supplements to individual interventions to address traumatic stress symptoms in professionals.

At the individual level, there were two conditions that were sufficient on their own to reduce individual-level distress by at least 1 point (see Sprang et al., 2021 for the significance of this reduction), a STSI-OA increase of at least 10 points, and high rates of problem-solving by the STS champion. To date, the majority of the literature on champions documents that these change agents can be helpful in producing organizational improvements specific to enhanced client care. For example, Wood et al., (2020) noted in their systematic review that champions were effectual in solving systems-level issues that hampered evidence-based practice implementation. Similarly, Bonawitz et al., (2020) noted the ability of the champion to navigate and overcome implementation barriers to quality health care innovations. However, there is scarce evidence on the champion's role in producing organizational change to address a professional's vicarious trauma. Nielsen et al., (2010) propose that the relationship between individual and organizational outcomes is reciprocal and transactional, so that in application to this context, positive, incremental changes at the organizational level might ignite individual perceptions of safety and healthy coping in the workplace. These subjective experiences of organizational support and action are key to employee well-being and engagement (Rasool et al., 2021), as DeJoy and Wilson (2003) report the “perceived qualities of the organization are at least as important as the objective or actual qualities” (p. 338). The relationship between STSI-OA (organizational) improvements and STS (individual) symptom declines over time suggests that the STS-BSC process may be improving professional well-being by altering the way in which work is perceived and experienced, as well as the level of control associated with decision-making (Nielsen et al., 2010; Bond & Bunce, 2001). In this case, participative problem-solving, noted in the healthcare literature as effective in reducing the psychosocial demands of work may be highly applicable and exportable to the trauma field, as it may be the conduit by which workers become their own healers, co-creating workplace environments that address the realities of the work (Bourbonnais et al., 2006). Important next steps would be to further examine barriers identified by champions as impeding the work of creating STS-informed organizations, so that future interventions could be tailored to address these challenges. It is noteworthy that problem-solving was the only performance-related champion indicator (as described by Shea, 2021) that produced change in individual levels of STS besides significant organizational transformation. In fact, in this study, the champion's performance indicators may be further understood by how they engaged their peers.

High levels of peer engagement in the form of involving colleagues in the scaling up of innovations using PDSA cycles, across all types of organizations, and facilitating increased knowledge of and skills related to addressing STS, in child welfare organizations, produced an increase of STSI-OA (organizational) scores by at least 10 points. This finding is consistent with Shea's (2021) contention that workplace peers look to champions to see how to follow through, and engage with change initiatives, suggesting that the activities of champions involve multiple peer engagement tasks, beyond just personal problem-solving. A primary goal of PDSAs is to implement and test small changes quickly, scale up changes that are showing positive benefits, and improve those that are not (Crowl et al., 2015). Within the first step, “plan,” ways to implement small change and measure the impact of any transformation are established, including answering questions such as who will implement the change, how and when will the modifications be implemented, what is the primary goal of the process, and how and when will progress toward the STS goals be measured. In the second step, “do,” the small-scale change begins to be implemented and the champion includes an expanding list of actors (others concerned about STS in the workplace) in the plan. Then in the “study” step, evidence related to the impact of the change on limiting exposure, enhancing self-regulation, or improving resilience is assessed. Lastly, in the “act” step, actions are decided based on the results of the assessment (e.g., is the small-scale change ready to be scaled up or does the implementation need modification?) (Crowl et al., 2015; Deming, 1986). To complete the tasks of PDSA scale-up and spreading knowledge about STS, these team members act as transformational leaders who function in three key ways. First, as gatekeepers who acquire, translate and transmit innovations in how to prevent and address STS to their colleagues, then as technical innovators who are refining the STS-related microstrategies for goodness of fit within their environments. Finally, these champions act as user leads who train and provide technical assistance on how to engage with the organization to reduce exposure and manage emerging trauma symptoms in real-time (Howell & Higgins, 1990; Sim et al., 2007). While PDSA cycles have been frequently applied within healthcare settings (Nicolay et al., 2012), present results demonstrate the use of these small tests of change to help a broad range of organizations (e.g., healthcare, schools, and child welfare) begin implementing and scaling up STS innovations.

It has been said that the simplicity of the PDSA process “belies its sophistication” (Reed & Card, 2016, p. 148), and indeed the process of using this iterative method of solving complex problems requires reflective and data-informed practice. In this study, these STS champions seem to have mastered these skills, as they model for others how to manage and reduce their trauma exposure and distress in an environment where they may be experiencing the same phenomenon. Future research that investigates the potential protective benefits of being a champion is warranted, as functioning in this capacity may provide increased self-efficacy in addressing the agents' own STS responses. Although the field of improvement science is well established, how PDSAs are implemented and who is leading the effort has been determined to be an understudied phenomenon (Taylor et al., 2014; Walley & Gowland, 2004). It appears these champions are extending and spreading the efforts of the STS-BSC faculty by integrating the work of the change initiative into the practice culture of the organization.

It is important to note that the second pathway toward being STS-informed was context-dependent. Champions' facilitation of knowledge and skills was relevant for child welfare organizations, but not for other organizations such as community mental health, public health, social services, or schools. This result suggests that child welfare organizations specifically benefit from having organizational champions facilitate knowledge and skills related to STS. Addressing secondary trauma within the child welfare context has been identified as especially challenging due to high case complexity, involuntary, court-involved service provision, and high turnover, which yields less experienced workers on the front-line, dealing with high-intensity cases (Aarons & Palinkas, 2007; Sprang et al., 2011). In many systems, supervisors are the conduit for on-the-job learning. However, in child welfare these encounters may be more administrative and crisis management focused (e.g., Collins-Camargo & Millar, 2010; Munson, 2012), with little time for knowledge and skill building around managing indirect exposure and STS. Skill building through collaborative learning and champion-guided modeling and application may be filling this gap in child welfare settings and has been reported as a salient factor promoting successful implementation in other studies (Akin, 2016).

This study was novel in that it used configurational analysis to examine the interplay of individual and organizational efforts to address STS. This is a fundamentally different approach than that of correlation-based methods. Because it employs Boolean rather than linear algebra, an often-cited strength of configurational analysis is its versatility with small-n studies. In this case, the analysis allowed for rigorous examination of champion-level data in ways not allowed by traditional multivariate analysis. As such, configurational analysis provided a systematic, mathematical approach to account for both complexity and context in the relationship between organizational efforts and individual-level outcomes. The results from this study illustrate how CNA can be particularly well suited for addressing the nuances of setting and interaction in implementation research in that one of the two pathways for the STSI-OA outcome was context-dependent, and in that both models identified two separate ways to achieve the same outcome.

Limitations

This study used response scaling to improve on nominal dichotomous categorizations used in other studies to capture champion efforts. This allowed for more nuanced assessments of champions' behavior, and incorporated multiple data sources such as direct observation, activity logs, and administrative documentation (Bunger et al., 2017). However, single-item assessments of champion behavior were aggregated and reported on the team versus champion behavior at the individual level, which could have diluted the effects of single-member contributions. Similarly, this study uses individual and organizational data that are aggregated for comparisons over time. This method provided anonymity at the individual and departmental levels but may have obscured within-group differences that might have provided additional useful information about structural variations influencing champion behavior. Furthermore, champion activities were measured over a 9-month period, which could have limited the assessment of performance, peer engagement, and impact achievements that were not yet realized. Although the organizational and champion activities identified by Shea (2021) were combined into an overall performance category, the analysis was at the item level, allowing the distinctions between the two to emerge. The nature of the study did not allow for randomization of organizations into the study, limiting generalizability, but delineating factors for further exploration in future studies.

Conclusion

Regardless of the organizational setting, the importance of individuals within an organization taking on a champion role should not be minimized, as results show the strong impact these agents can have on their organizations' implementation of STS-informed policies and practices. Therefore, to help facilitate STS-informed improvements, organizations should support individuals' interest and motivation in becoming champions, through means such as dedicated time for related activities and training, encouraging employees' initiative and leadership (e.g., allowing them to present STS information at staff meetings), and/or support or reward for increased work demands of leading innovations. Identifying and cultivating the champions' use of problem-solving and peer engagement strategies can help organizations transform the threat posed by indirect trauma exposure into an opportunity for shared experience and healing.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded in part by a grant from the Substance Abuse and Mental Health Administrations (5H79SM082826, Sprang PI).

ORCID iD

Ginny Sprang

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