- Email: [email protected]
Transferring training to child welfare practice: Individual and collective efforts
Children and Youth Services Review 33 (2011) 149–156
Contents lists available at ScienceDirect
Children and Youth Services Review j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c h i l d yo u t h
Transferring training to child welfare practice: Individual and collective efforts Junqing Liu a,⁎, Brenda D. Smith b a b
School of Social Welfare, University at Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, United States School of Social Work, The University of Alabama, United States
a r t i c l e
i n f o
Article history: Received 21 June 2010 Received in revised form 27 August 2010 Accepted 31 August 2010 Available online 7 September 2010 Keywords: Child welfare Training Training transfer Supervision Organizations
a b s t r a c t The transfer of training to practice constitutes an ongoing challenge in child welfare services. Many efforts to understand and promote training transfer address the concept as an individual-level behavior. This study suggests that training transfer is both an individual and collective process. The study involves a survey at two time points of 214 workers from child welfare agencies who attended a training program. Principle components analysis identified two meaningful sub-components within the concept of the training transfer. Hierarchical linear regression was used to assess the influence of individual-level and contextual factors on both components. Findings suggest that to promote collective training transfer and enhance both individual and group performance, child welfare administrators may need to strengthen supervisory support and to promote positive work climates in which trainees can discuss training concepts and work together to apply them. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Training has been an important means of introducing new knowledge and practice to child welfare workers (Wehrmann, Shin, & Poertner, 2002). Federal, state and localities invest heavily in training child welfare staff (see Antle, Barbee, Sullivan, & Christensen, 2009). There can be considerable gaps, however, between training content delivered and the practices of trainees. Child welfare is not unusual in this respect. Across a range of fields, studies estimate that only 10–15% of the training content is transferred back to the workplace (Kontoghiorghes, 2004). Such conditions highlight the need to examine the training transfer and the contextual factors that may affect the transfer of training to practice. To promote the transfer of training to child welfare practice, this study addresses these questions: (1) Does the commonly used unitary concept of training transfer contain sub-components, such as individual and collective components? (2) If so, are individual and collective training transfer influenced by different contextual factors, such as training motivation, supervisory support, or organizational climate and culture?
2. Background Training transfer is defined as applying knowledge, skills, and attitudes that are learned from training to trainees' everyday practice (Baldwin & Ford, 1988). All fields, in and outside of human services, are challenged to promote the transfer of training to practice. Because ⁎ Corresponding author. Tel.: + 1 518 334 2590. E-mail address: [email protected] (J. Liu). 0190-7409/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.childyouth.2010.08.027
child welfare organizations rely so heavily on ongoing training to promote best practices and to ensure compliance with the new regulations and procedures, we might expect greater attention to training transfer and further progress in efforts to achieve it. Training transfer has commonly been treated as an individuallevel behavior in the cognitive psychology and business literatures (see Kontoghiorghes, 2004). Accordingly, individual trainees' characteristics have been a focus of research on training transfer. Selfefficacy, for example, is commonly used to explain the different training transfer outcomes among individual trainees. The basic argument is that people with higher self-efficacy have stronger confidence in their capabilities and tend to set more challenging goals than to people with lower self-efficacy, they are more likely to transfer training to everyday work (Bandura, 1986). Consistent with this logic, research has found that self-efficacy is positively related to pretraining motivation and, in turn, training motivation is positively associated with training transfer (Chiaburu & Marinova, 2005). Within this line of work, research on child welfare training has identified that an individual's learning readiness is related to transfer of training (Antle, Barbee, & van Zyl, 2008). In contrast to an individual-focused point of view on training transfer, organizational researchers have recently revealed that training transfer in an organization can be a systemic or holistic process rather than, or in addition to, an individual-level process (Kontoghiorghes, 2004). Researchers have found that within an organization, individuals, groups, departments, or even a whole organization can be agents of training transfer (Eraut & Hirsh, 2007). This line of work also suggests that training transfer might not necessarily be a unitary concept, and it might contain different components representing the efforts of various work units.
150
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
In the field of child welfare, it is especially important to investigate training transfer at levels beyond individual trainees. This is because: (1) child welfare training often contains information that is complex, tacit, and hard to articulate, and under such circumstances group discussion can help clarify the information and promote shared understanding of a new practice (Frank, Bagdasaryan, & Furman, 2008; Laughlin & Hollingshead, 1995); (2) very often child welfare professionals expect and prefer training at the group or organization level, especially when training addresses practice standards such as regulatory compliance or evidence-based practices (Luongo, 2007); (3) child welfare workers often work in teams (e.g., case planning teams or treatment teams) which require team members to develop common understandings regarding new practices or regulations in order to effectively achieve common team goals (Ellemers, Gilder, & Haslam, 2004; Lewandowski & GlenMaye, 2002). In the past, when research on training transfer focused on individual trainees, researchers sometimes downplayed or ignored as nuisance the influence of contextual variables. Currently, however, practice context, including organizational factors, are considered an essential aspect of the transfer process. For example, Antle et al. (2008) studied training transfer in child welfare and found that supervisory support was significantly associated with training transfer. Research, mostly on human service training, has recognized the following additional contextual factors as being important to training transfer: organizational continuous learning culture (Kontoghiorghes, 2004), organizational climate (Glisson & Hemmelgarn, 1998) and organizational formalization (Clark, 2002; Glission, 2007). We used research on these factors to inform the development of the conceptual framework of this study.
3. Conceptual model and research hypotheses We conceptualize training transfer as having two components of individual and collective training transfer. Fig. 1 presents the hypothesized relationships between the previously mentioned individual and contextual factors and individual and collective training transfer. These associations are specified in the following research hypotheses.
3.1. Contextual factors and training motivation Supervisor support plays an important role in encouraging workers to attend trainings and embrace training content. Supervisors, for example, can emphasize or explain the importance of training and give workers the time and resources to attend and complete trainings. Studies of child protective services caseworkers (Curry, McCarragher, & Dellmann-Jenkins, 2005) and of state government managers and supervisors (Facteau, Dobbins, Russell, Ladd, & Kudisch, 1995) have
Organizational Climate Perception
Supervisor Support H1
H3a
H4a-b
H5a-b H2
Organizational Formalization Perception
H1: Supervisory support will be positively related to training motivation. In an organization, a continuous learning culture is defined as an environment in which knowledge and skill attainment are considered essential responsibilities of employees and are supported by informal interactions in the workplace and formal-policies and structures (Tracey, Tannenbaum, & Kavanagh, 1995). It is logical to expect that child welfare workers will be more motivated to attend trainings when they perceive that their organizations value and support new knowledge and skill acquisition. Chiaburu and Tekleab (2005) studied employees of a U.S. company and found that organizational continuous learning culture was positively related to training motivation. Thus, we hypothesize: H2: Organizational continuous learning culture (as reflected by coworkers (H2a) and organizational administration (H2b)) will be positively related to training motivation. 3.2. Training motivation and individual and collective training transfer Training motivation is the aspiration to engage in training activities and fully embrace the training experience (Carlson, Bozeman, Kacmar, Wright, & McMahan, 2000). It is logical to expect that individuals with high training motivation are also more likely to utilize training content in their job. Empirical child welfare training studies also support the relationship between training motivation and individual training transfer. Antle et al. (2008) found that learning readiness affected training transfer among public child welfare workers. Learning readiness was indicated by traits similar to training motivation such as self-directness in learning and valuing learning as a life skill (Antle et al., 2008). Curry et al. (2005) studied child protective services caseworkers and found that participants' training motivation was associated with training transfer. Therefore, we hypothesize: H3a: Individual training motivation will be positively related to individual training transfer. Individuals who are strongly motivated to attend training should be more eager to apply training into practice. However, the complex and tacit information learned from child welfare training may require individuals to confer with their co-workers in order to understand and evaluate the effectiveness and feasibility of new practices. In addition, individual child welfare worker's desired-outcomes of new practices may rely on the performance of their co-workers and teams (Ellemers et al., 2004). Therefore, due to the nature of the information conveyed in child welfare training and the connections between individual and group outcomes, individual child welfare workers who are highly motivated to use the training will also commit to collective training transfer. Based on the conceptual argument, we hypothesize: H3b: Training motivation will be positively related to collective training transfer.
Individual Training Transfer
Training Motivation
Organizational Continuous Learning Culture
found that supervisory support was positively related to training motivation. Therefore we hypothesize:
H3b
Collective Training Transfer
Fig. 1. Conceptual model of training transfer and the practice context.
3.3. Formal organizational climates and individual and collective training transfer The basis of organizational climate exists within individuals at a workplace (Joyce & Slocum, 1979). James and James (1989) proposed that employees integrate components of their work environments into a general appraisal or “psychological climate.” Extending these ideas, Glisson and James (2002) proposed that if employees in a work unit share similar perceptions of the environment, such perceptions can be aggregated and conceptualized as the “organizational climate” (Glisson & James, 2002).
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
151
In child welfare, organizational climates tend to be characterized by emotional exhaustion and role complexity (Glisson & Green, 2006; Jayaratne & Chess, 1984). The transfer of training into practice requires trainees to spend time and resources applying new information in practice. If an organizational climate is stressful, then even motivated trainees may lack time, energy or emotional resources to engage in transferring training into practice. Thus we expect that the effect of training motivation on individual and collective training transfer will be modified by the nature of the organizational climate. We expect workers in stressful organizational climates to have difficulty applying training content in practice and workers in supportive or friendly work climates to be more able to apply training content in practice. Indeed, Tracey et al. (1995) studied 505 managers from 52 supermarket stores owned by a single private organization and found that supportive organizational climates were positively associated with post-training behaviors, such as problem solving and communication. Although studies have not specifically addressed the impact of organizational climate on training transfer in child welfare, studies focusing on concepts related to training transfer underscore the importance of organizational climates in child welfare. Organizational climates in child welfare or related children's services settings have been associated with service quality and outcomes (Glisson & Hemmelgarn, 1998), access to services (Glisson & Green, 2006), inter-agency collaboration (Smith & Mogro-Wilson, 2006), and staff retention (Cahalane & Sites, 2007; Shim, 2010). Hence, we hypothesize:
training attendees, 192 (90%) completed a Time 1 pre-training survey. Approximately, five months after the training, survey participants were sent a Time 2 follow-up survey by mail. Of this group, 92 (43%) responded. To assess response bias at Time 2, we compared demographic characteristics of the follow-up survey respondents to the characteristics of non-respondents. For most of the demographic characteristics we examined, there were no differences between respondents and non-respondents. We found, however, that compared to nonrespondents, respondents were more likely to be white, and less likely to be African American or Latino/Hispanic. As shown in Table 1, of all pre-training survey respondents, more than half were white females. The mean age was 35 years old. Twenty six percent of the participants held a master's degree. Fifty five percent of participants had worked in their organizations for more than two years. About 60% of the respondents had an annual salary of less than $35,000.
H4: Organizational climate will moderate the relationships between training motivation and (a) individual training transfer, and (b) collective training transfer. The relationships will be positive in more supportive organizational climates and negative in more stressful organizational climates.
4.2.1. Dependent variable Training transfer was measured with twelve-item scale adapted from items used in previous research (Curry et al., 2005; Facteau et al., 1995). To assess whether training transfer involved more than one dimension, we conducted principle components analysis of the 12 items. Two components were extracted. The seven items loading on the first component addressed perceived individual endeavors to use training content in practice. An example item is “I have been able to transfer the skills learned in training back to my actual job.” Five items loading on a second component reflected perceived collective efforts with colleagues to apply training content in practice. An example item is “In the past four months, I made a plan with a co-worker to apply training content.” We conceptualize the two components as individual and collective training transfer. Individual training transfer refers
Organizational formalization is the extent to which formal organizational rules, regulations, and procedures guide work activities (Glisson & Martin, 1980; Hall, 1963). Training transfer increases when organizations are tolerant and open to experimenting with new practices, and when supervisors give workers autonomy and discretion over practices (Collins-Carmago & Royse, 2010). If organizational cultures of child welfare agencies are formal and rigid, individual child welfare workers and teams may have little discretion in their practice or flexibility in applying new skills into everyday work. Thus, we expect that the effect of child welfare workers' training motivation on individual and collective training transfer will depend on the level of organizational formalization. Based on the conceptual argument, we hypothesize that: H5: Organizational formalization will moderate the relationship between training motivation and (a) individual training transfer, and (b) collective training transfer. The relationships will be negative in highly formal organizations and positive in organizations with less formality. 4. Methodology 4.1. Sample and survey procedure The study involves workers from child welfare agencies in a northeastern state who attended a training program. From February 2007 to August 2008, 214 child welfare workers from both voluntary and public child welfare agencies attended 13 separate training workshops on substance abuse and adolescent services. The training workshops were led by staff from a university-based professional development program. Training staff who received training and certification in human subject protection invited trainees to participate in a voluntary and confidential pre-training survey. Of the 214
4.2. Measures The Time 1 pre-training survey addressed training motivation, and perceptions of supervisor support and organizational conditions. The follow-up survey addressed perceived training transfer as well as perceptions of supervisory support and organizational conditions. We used the pre-training survey scores for the independent variables and follow-up survey scores for the dependent variables in all analysis.
Table 1 Demographic information. Demographic variables
n
Mean /percentage (Sta. deviation)
Age Gender Male Female Have a master degree or not Yes No Race White Africa American Latino /Hispanic Asian Other Agency tenure ≤Two Years NTwo Years Child welfare tenure ≤Two Years NTwo Years Salary ≤35,000 N35,000
192 192
35 (10) 20.6 79.4
192 26.1 73.9 192 67.0 19.2 12.8 2.0 2.0 191 44.8 55.2 175 25.4 74.9 190 58.7 41.3
152
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
to individual trainees' perceived use of knowledge or skills learned from training. We define collective training transfer as the perceived use of knowledge or skills from training as part of a work group, such as team, department, or unit (regardless of whether members attended training together). The Cronbach's alpha is .75 for individual training transfer and .87 for collective training transfer. Individual training transfer focuses on the efforts of individual trainees. In contrast, collective training transfer places a heavier emphasis on interactions among units at work (Argote & Ingram, 2000). In our study, the actions of collective training transfer included, but were not limited to group planning, discussion, and feedback on performance. Collective training transfer is not a simply addition of individual training transfer; rather, it involves interaction among group members and may include the adoption of common goals regarding new practices (Chang & Simpson, 1997). 4.2.2. Independent variables 4.2.2.1. Supervisor support. Supervisor support was measured by a nine-item scale adapted from measures used by Chiaburu and Tekleab (2005), and Facteau et al. (1995). A sample item is “My supervisor is tolerant of changes that I initiate as a result of learning new skills in training.” The Cronbach's alpha for the scale is .93. 4.2.2.2. Organizational continuous learning culture. Organizational continuous learning culture was measured by a thirteen-item scale adapted from Tracey et al. (1995). Two of the 13 items were developed for this study. Principle components analysis identified two components in the scale. Five items loaded on a component reflecting co-worker continuous learning culture; eight items loaded on a component reflecting administrative continuous learning culture. Co-worker's continuous learning culture indicates that co-workers provide new information to each other and encourage each other to use new knowledge and skills to increase job performance. An example item is “Co-workers encourage one another to use new knowledge and skills on the job.” Administrative learning culture indicates that administration matches a worker's professional development need with training, evaluates workers' ability to solve problems with alternative methods, and give credit to those who apply new knowledge to job. An example item is “Job assignments continually require the evaluation of alternative solutions to problems.” The Cronbach's alpha is .67 for co-workers' continuous learning culture and .81 for the administrative continuous learning culture. 4.2.2.3. Training motivation. Training motivation was measured by a five-item scale adapted from a measure previously used by Noe and Schmidt (1986). An example item is “Increasing my skills through training will help me perform my job better.” The Cronbach's alpha for the scale is .76. 4.2.2.4. Organizational climate. Organizational climate was measured with three dimensions (14-items) of a scale used by the University of Tennessee Children's Mental Health Services Research Center (UTCMHSRC) (2000). The measure included organizational climate dimensions of role conflict, emotional exhaustion, and role overload. Alpha reliability tests and principle components analysis suggested that for this study, the three dimensions were not distinct. Hence, the 14 items were used together as a measure of organizational climate. An example item is “Once I start an assignment, I am not given enough time to complete it.” The Cronbach's alpha for the scale is .94. 4.2.2.5. Organizational formalization. Organizational rigidity and formalization were measured with items from the formalization dimension of an organizational culture measure used by the University of Tennessee Children's Mental Health Services Research
Center (UT-CMHSRC) (2000). Only one component was extracted via principle components analysis. An example item is “We are to follow strict operating procedures at all times.” The Cronbach's alpha for the scale is .85. 4.3. Data analysis Hierarchical OLS regression models were used to assess the influence of contextual factors on training motivation (H1, H2a, and H2b) and on individual and collective training transfer (H3a and H3b). OLS regression models with interaction terms were used to assess moderating effects of organizational climate (H4) and organizational formalization (H5). To create the interaction terms, we first mean centered the variables of interests, for example, organizational climate and training motivation, then the product of the two mean terms was used as the interaction term. We used this mean centering method to minimize the problem of multicollinearity between the interaction term and the interacting variables (Chiaburu & Tekleab, 2005). 5. Results Table 2 shows the means, standard deviations, and correlations among the variables. Of the demographic variables, only having a master degree was related to training motivation. Hence, we used only master degree as a control variable in the regression models. The bivariate correlation between supervisory support and administrative continuous learning culture is high (.73). However, subsequent analysis indicated no multicollinarity because the VIF values for the independent variables in all models are all less than four, the accepted standard (Hair, Anderson, Tatham, & Black, 2006). H1 predicted a positive relationship between supervisory support and training motivation. As shown in the second step of the regression in Table 3, supervisory support is positively related to training motivation (β = .10, P b .05). Supervisory support explains an additional three percent of the variance in training motivation. Thus, the results indicate some support for H1. The relationship between supervisory support and training motivation loses significance, however, when the variables for continuous learning culture are added to the model. These findings suggest that supervisory support may be mediated by continuous learning culture in organizations. H2a predicted a positive relationship between co-worker continuous learning culture and training motivation and it is supported. The test of H2a is shown in Table 3, Step 3. After controlling for master degree and supervisory support, the more respondents perceived a co-worker-supported continuous learning culture, the greater their motivation for training (β = .13, p b .05). H2b predicted a positive relationship between administrative continuous learning culture and training motivation. As shown in Table 3, Step 4, administrative continuous learning culture is not related to training motivation. H2b is not supported. H3a and H3b predicted that training motivation will be positively related to individual and collective training transfer. The results of the hypothesis tests are presented in Table 4. After controlling for having a master's degree, supervisory support, co-worker continuous learning culture, and administrative continuous learning culture, training motivation is positively associated with individual training transfer(β = .36, P b .05). It explains an extra 6% of the variance in individual training transfer. Training motivation is not related to collective training transfer, however. Thus, H3a is supported, but not H3b. H4a-b predicated that organizational climate would moderate the relationships between training motivation and individual and collective training transfer. The tests of H4a and H4b are shown in the upper and lower part respectively of Table 4, Step 5. Because the interaction terms are not significant, the results suggest that organizational climate does not moderate the relationship between
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
153
Table 2 Means, standard deviations, and correlations. Item
M
SD
1
2
1.Agency tenure 2.Child welfare tenure 3.Master degree 4.Training motivation 5.Supervisory support 6.Administrative culture 7.Co-worker culture 8.Climate 9.Formalization 10.Time 2 Individual training transfer¹ 11.Time 2 Collective training transfer¹
.55 .75 .45 4.38 3.57 3.28 3.67 2.75 3.08 3.93 2.83
.50 .44 .50 .49 .85 .67 .69 .82 .98 .55 .76
1 .56** −.18 −.05 −.09 −.10 −.04 .06 .10 .04 −.13
3
1 .18 .09 −.09 .05 −.03 .03 −.00 −.07 .04
4
5
6
7
8
9
10
1 −.12 .32** .30** .31**
1 .49** .24** .06
1 .12 −.27**
1
11
1 .33** −.11 .07 .16 .01 −.05 −.06 −.08
1 .16** .11 .20** −.12 .02 .27** .05
1 .73** .32** −.20** −.26** .15 .33**
1 .42** −.39** −.46** .09 .24**
.46**
1
1: sample size is 92, for others sample size is 192. *p b .05; ** p b .01.
training motivation and individual training transfer (β = .11, ns) or the relationship between training motivation and collective training transfer (β = −.02, ns). Thus, neither H4a nor H4b are supported. However, Table 4, step 4 shows that stressful organizational climates have a negative marginal effect on collective training transfer (β = −.24, P b .05), but not on individual training transfer. H5a and H5b predicated that organizational formalization would moderate the relationships between training motivation and individual and collective training transfer. As shown in Table 5, Step 5, organizational formalization does not moderate the relationship between training motivation and individual training transfer (β = .24, ns) or the association between training motivation and collective training transfer (β = −.12, ns). Thus, neither H5a nor H5b are supported. Although we did not hypothesize a direct effect of co-worker learning culture on individual or collective training transfer, the results depicted in Tables 4 and 5 indicate that the stronger respondents perceive their co-workers' support for continuous learning, the greater their perceived training transfer (both individual and collective). In addition, the results indicate a direct positive association between supervisory support and collective training transfer.
6. Conclusions and discussion 6.1. Conclusions A few primary findings emerge from this study (see Fig. 2). First, we found that the concept of training transfer in child welfare settings might be conceptualized as having two dimensions. Individual training transfer reflects the efforts of individual trainees to apply training content on the job; collective training transfer reflects efforts of groups, such as work teams or units, to apply training content. Table 3 Regression results predicting training motivation. Predictors
Step 1(β) Step 2 (β) Step 3 (β) Step 4 (β)
Step 1 Master degree .24** Step 2 Supervisory support Step 3 Co-worker learning culture Step 4 Administrative learning culture R² .05 ΔR² F 9.63** ΔF n = 192, *p b .05; **p b .01.
.25**
.25**
.26**
.10*
.06
.10
.13*
.14**
.07 .03 7.76** 5.67*
.10 .03 7.44** 6.39*
−.08 .11 .01 5.87** 1.12
Second, we found support for hypotheses indicating that training motivation is strengthened by both supervisory support and coworkers who embrace continuous learning. In contrast, training motivation was not strengthened by the perception that one's organizational administration embraces continuous learning culture. Perhaps individuals are more influenced by their co-workers than by the administration when it comes to training motivation. Third, we found, that the greater an individual's motivation for training, the greater his or her individual training transfer; but training motivation did not promote collective training transfer. Instead, we found that
Table 4 Organizational climate and individual and collective training transfer. Predictors
Step 1 (β)
Step 2 (β)
Individual training transfer Step 1 Master degree −.04 −.07 Step 2 Supervisory support .16 Co-worker learning culture .33⁎⁎ Administrative learning −.18 culture Step 3 Training motivation Step 4 Organizational climate Step 5 Training motivation Organizational climate⁎ R² .00 .12 Δr² .12 F .07 2.93⁎ Δf 3.88⁎ Collective training transfer Step 1 Master degree −.17 −.16 Step 2 Supervisory support .36⁎ Co-worker learning culture .40⁎ Administrative learning −.14 culture Step 3 Training motivation Step 4 Organizational climate Step 5 Training motivation Organizational climate⁎ R² .01 .19 Δr² .18 F .54⁎⁎ 4.87⁎⁎ Δf 6.28⁎⁎ n = 92. ⁎⁎ p b .01. ⁎ p b .05.
Step 3 (β)
Step 4 (β)
Step 5 (β)
−.19
−.18
−.18
.12 .32⁎⁎ −.17
.12 .30⁎⁎ −.09
.12 .31⁎⁎ −.10
.36⁎
.34⁎
.03
.08
.18 .06 3.77⁎⁎ 6.40⁎
.20 .01 3.38⁎⁎ 1.34
−.15
−.20
.36⁎ .40⁎⁎ −.14
.37⁎ .47⁎⁎ −.38
−.01
.04 −.24⁎
.19 .00 3.85⁎⁎ .00
.24 .06 4.47⁎⁎ 6.39⁎
−.39 .11 .20 .01 2.99⁎⁎ .70
−.19 .37⁎ .46⁎⁎ −.38
.11 −.14 −.02 .24 .00 3.79⁎⁎ .02
154
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
Table 5 Organizational formalization and individual and collective training transfer. Predictors
Step 1 (β)
Step 2 (β)
Individual training transfer Step 1 Master degree −.04 −.07 Step 2 Supervisory support .16 Co-worker learning Culture .33⁎⁎ Administrative learning culture −.18 Step 3 Training motivation Step 4 Organizational formalization Step 5 Training motivation Organization formalization⁎ R² .00 .12 Δr² .12 F .07 2.93⁎ Δf 3.88⁎⁎ Collective training transfer Step 1 Master degree −.17 −.16 Step 2: Supervisory support .36⁎ Co-worker learning culture .40⁎⁎ Administrative learning −.14 culture Step 3 Training motivation Step 4 Organizational formalization Step 5 Training motivation Organizational formalization⁎ R² .01 .19 Δr² .18 F .54 4.87⁎⁎ Δf 6.28⁎⁎
Step 3 (β)
Step 4 (β)
Step 5 (β)
−.19
−.22
−.22
.12 .32⁎⁎ −.17
.3 .32⁎⁎ −.11
.13 .37⁎⁎ −.12
.36⁎
.40⁎
.86
−.13
.18 .06 3.77⁎⁎ 6.40⁎⁎
.23 .02 4.05⁎⁎ 2.56
.47 −.14 .24 .01 3.58⁎⁎ .79
−.15
−.19
−.18
.36⁎ .40⁎⁎ −.14
.36⁎ .44⁎⁎ −.14
.36⁎ .43⁎⁎ −.15
−.01
−.04
.36
−.01
.54
.19 .00 3.85⁎⁎ .00
.20 .00 3.43⁎⁎ .01
−.12 .20 .00 2.97⁎⁎ .36
n = 92. ⁎⁎ p b .01. ⁎ p b .05.
collective training transfer is more likely to occur when workers positively perceive their co-workers' support for learning and their organizational climate. Fourth, organizational formalization did not moderate the impact of training motivation on individual or collective training transfer. More research is needed of the impact of organizational formalization on training motivation and training transfer. Finally, as with many previous studies, this study's results underscore the importance of supervisory support in child welfare. The results suggest that the more support workers perceive from
Supervisor Support Training Motivation
Co-worker support for learning culture
Individual Training Transfer
Collective Training Transfer Organizational Climate Perception
Fig. 2. Results model of training transfer and the practice context.
supervisors, the more motivated they are to attend training, and the more they feel able to transfer training to the job in collective workgroups and teams. That is, we found that supervisory support relates to individual training transfer through training motivation and to collective training transfer directly. Perhaps supervisory support directly promotes collective training transfer because supportive supervisors create a platform for workers to discuss training content and implement it together. 6.2. Limitations The study findings should be interpreted in the context of its limitations. Although the study had a high response rate at Time 1, when the survey was distributed at training, the follow-up response rate at Time 2 was only 43%. In addition to the usual challenges in finding time to participate, Time 1 participants were often hard to locate even 4–5 months after the training. Some had switched jobs or agencies; others had left child welfare positions all together. The low response rate at Time 2 raises questions about how well the study findings represent the perspectives of all child welfare staff. Another important limitation pertains to the use of only self-report measures of training transfer. With the self-report measures we face the possibility that factors such as participants' levels of confidence, self-efficacy, or desire to appear socially desirable will influence the measure of training transfer. The study is also limited by potential questions about the validity of its brief measures. Due to the considerable time constraints of the participants, study measures primarily involved shortened versions of measures used in previous research. Whereas the full versions of some of these measures have documented assessments of validity, the brief measures adapted for this study do not. 6.3. Discussion Child welfare work is challenging and states and localities invest heavily in training child welfare staff (see Antle et al., 2009). Too often, however, trainers and trainees are disappointed in the extent to which content from training is implemented in practice. The field is increasingly seeking to understand and improve the transfer process. This study makes a small step toward that goal by offering empirical support for the concept of collective training transfer and identifying individual and contextual factors associated with training transfer. The study findings have implications for practice, policy and research in child welfare. Child welfare practitioners and policy makers might consider further the merits of conceptualizing and understanding the mechanisms that enable training to be implemented in practice. Collective training transfer involves discussing with others and evaluating the effectiveness of old and new practices. These practice activities are consistent with Argyris and Schon's (1978) double-loop learning concept. The double-loop learning concept emphasizes the importance of feedback mechanisms and reflection in learning (Argyris & Schon, 1978). In efforts to reinforce and foster training implementation, administrators and supervisors might consider ways to promote reflection, discussion, and group accountability mechanisms. van Zyl, Antle, and Barbee (2010), for example, recently found that face-toface group case consultation after training increased the transfer of assessment and case planning skills into practice. In addition, perhaps child welfare administrators and practitioners should evaluate training transfer and its effects at levels beyond individual trainees. Training outcomes could be assessed for groups, teams, departments, and, possibly, organizations as a whole. Findings on the differential impact of contextual factors on the two types of training transfer can help child welfare administrators to be proactive in promoting organizational environments that can enhance both individual and collective training transfer. To increase individual
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
training transfer, child welfare administrators should motivate individuals by focusing on individual needs and goals that people may value (Ellemers et al., 2004). To promote collective training transfer, which may be related to both individual and group performance, child welfare administrators and practitioners may want to strengthen supervisory support and employ innovate strategies designed to create and maintain positive organizational climates (Chiaburu & Marinova, 2005; Glission, 2007; van Zyl et al., 2010). Cultivating a supportive co-worker continuous learning culture could strengthen both individual and collective training transfer. The study findings are consistent with other research suggesting that both individual and collective training transfer is important to the job performance of both individuals and groups (Chang & Simpson, 1997; van Zyl et al., 2010). Studies have not only found that groups benefit from efficient group members, but individuals also benefit from groups through interpersonal corrections of errors and the exchange of ideas among group members (Azmitia & Montgomery, 1993; Brodbeck & Greitemeyer, 2000). To promote both types of training transfer, child welfare researchers should investigate more of the different dynamics of individual and collective training transfer and the organizational conditions that are critical in promoting individual and collective training transfer. In a study of frontline human services workers, Sandfort (1999) illustrated the importance of collective beliefs and shared knowledge to frontline practice in human service organizations. She illustrated how frontline staff interpret their experiences and develop practice norms via interactions with colleagues. Sandfort's study suggested that interactions among colleagues can lead staff units or teams to resist new practices. The present study suggests that interactions among colleagues might also have potential to reinforce or enhance collective support for new practices. The study findings also suggest that certain organizational contexts might foster interactions among colleagues that promote training transfer and, thereby, the implementation of new practices. Just as previous research has demonstrated the importance of post-training efforts to enforce training content (Antle et al., 2009; van Zyl et al., 2010); this study's findings indicate that post-training workplace interactions, conversations, and team efforts warrant further study as potential influences on training transfer. As pressures increase to implement evidence-based practices, child welfare researchers have made progress in conceptualizing components of organizational contexts and identifying possible influences of organizational environments on child welfare practice and outcomes. The capacity for child welfare trainees to transfer training content to practice surely has implications for the implementation of new and evidence-based practices. Researchers must continue to advance conceptualization and empirical investigation of training transfer and other aspects of efforts to implement new or evidence-based practices in challenging human service settings.
References Antle, B. F., Barbee, A. P., & van Zyl, M. A. (2008). A comprehensive model for child welfare training evaluation. Children and Youth Services Review, 30, 1063−1080. Antle, B. F., Barbee, A. P., Sullivan, D. J., & Christensen, D. N. (2009). The effects of training reinforcement on training transfer in child welfare. Child Welfare, 88(3), 5−26. Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes, 82(1), 150−169. Argyris, C., & Schon, D. (1978). Organisational learning: A theory of action perspective. Reading, Mass: Addison Wesley. Azmitia, M., & Montgomery, R. (1993). Friendship, transactive dialogues, and the development of scientific reasoning. Social Development, 2, 202−221. Baldwin, T. T., & Ford, J. K. (1988). Transfer of training: A review and directions for future research. Personnel Psychology, 41(1), 63−103. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
155
Brodbeck, F., & Greitemeyer, T. (2000). Effects of individual versus mixed individual and group experience in rule induction on group member learning and group performance. Journal of Experimental Social Psychology, 36, 621−648. Cahalane, H., & Sites, E. W. (2007). The climate of child welfare employee retention. Child Welfare, 87(1), 91−114. Carlson, D., Bozeman, D., Kacmar, M., Wright, P., & McMahan, G. (2000). Training motivation in organizations: An analysis of individual-level antecedents. Journal of Managerial Issues, 12, 271−287. Chang, E., & Simpson, D. (1997). The circle of learning: Individual and group processes. Education Policy Analysis Archive, 5(7), 1−21. Chiaburu, D., & Marinova, S. (2005). What predicts skill transfer? Exploratory study of goal orientation, training self-efficacy and organizational supports. International Journal of Training and Development, 9(2), 110−123. Chiaburu, D., & Tekleab, A. (2005). Individual and contextual influences on multiple dimensions of training effectiveness. Journal of European Industrial Training, 29 (8/9), 604−626. Clark, N. (2002). Job/work environment factors influencing training transfer within human service agency: Some indicative support for Baldwin and Ford's transfer climate construct. International Journal of Training and Development, 6(3), 146−162. Collins-Carmago, C., & Royse, D. (2010). A study of the relationships among effective supervision, organizational culture promoting evidence-based practice, and worker self-efficacy in public child welfare. Journal of Public Child Welfare, 4(1), 1−24. Curry, D., McCarragher, T., & Dellmann-Jenkins, M. (2005). Training, transfer, and turnover: Exploring the relationship among transfer of learning factors and staff retention in child welfare. Children and Youth Services Review, 27(8), 931−948. Ellemers, N., Gilder, D., & Haslam, S. (2004). Motivating individuals and groups at work: a social identity perspective on leadership and group performance. Academy of Management Review, 29(3), 459−478. Eraut, Michael, & Hirsh, Wendy (2007). The significance of workplace learning for individuals, groups and organisations.SKOPE Monograph 9. Oxford University Department of Economics URL: http://www.skope.ox.ac.uk/WorkingPapers/ Eraut-Hirshmonograph.pdf Facteau, J. D., Dobbins, G. H., Russell, J. E. A., Ladd, R. T., & Kudisch, J. D. (1995). The influence of general perceptions of the training environment on pretraining motivation and perceived training transfer. Journal of Management, 21(1), 1−25. Frank, Todd, Bagdasaryan, Sofya, & Furman, Walter (2008, Aprill). Transfer of learning (TOL) in child welfare.Research Brief 1 Retrieved June 3, 2010 from, http://iuc.sppsr. ucla.edu/iucmain/PDF_DownLoad/TOL_Brief_GET-CW.pdf Glission, C. (2007). Assessing and changing organizational cultural and climate for effective services. Research on Social Work Practice, 17(6), 736−747. Glisson, C., & Green, P. (2006). The effects of organizational culture and climate on the access to mental health care in child welfare and juvenile justice systems. Mental Health Services Research, 33(4), 443−448. Glisson, C., & Hemmelgarn, A. L. (1998). The effects of organizational climate and interorganizational coordination on the quality and outcomes of children's service systems. Child Abuse & Neglect, 22, 401−421. Glisson, C., & James, L. R. (2002). The cross-level effects of culture and climate in human service teams. Journal of Organizational Behavior, 23(6), 767−794. Glisson, C., & Martin, P. Y. (1980). Productivity and efficiency in human service organizations as related to structure, size, and age. Academy of Management Journal, 23(1), 21−37. Hair, J., Anderson, R., Tatham, R., & Black, W. (2006). Multivariate data analysis. Upper Saddle River: Prentice Hall. Hall, R. H. (1963). The concept of bureaucracy: An empirical assessment. The American Journal of Sociology, 69, 32−40. James, L. A., & James, L. R. (1989). Integrating work environment perceptions: Explorations into the measurement of meaning. The Journal of Applied Psychology, 74(5), 739−751. Jayaratne, S., & Chess, W. A. (1984). Job satisfaction, burnout, and stress: A national study. Child Welfare, 29(5), 448−553. Joyce, W. F., & Slocum, J. W. (1979). Climates in organizations. In S. Kerr (Ed.), Organizational behavior (pp. 317−333). Columbus Ohio: Grid. Kontoghiorghes, C. (2004). Reconceptualizing the learning transfer conceptual framework: Empirical validation of a new systemic model. International Journal of Training and Development, 8(3), 1−25. Laughlin, P. R., & Hollingshead, A. B. (1995). A theory of collective induction. Organizational Behavior and Human Decision Processes, 61, 94−107. Lewandowski, C. A., & GlenMaye, L. F. (2002). Teams in child welfare settings: Interprofessional and collaborative processes. Families in Society, 83(3), 245−256. Luongo, G. (2007). Rethinking child welfare training models to achieve evidence-based practices. Administration in Social Work, 31(2), 87−96. Noe, R., & Schmidt, N. (1986). The influence of trainee attitudes on training effectiveness: Test of a model. Personnel Psychology, 39, 497−523. Sandfort, J. (1999). The structural impediments to human service collaboration: Examining welfare reform at the front lines. The Social Service Review, 73(3), 314−339. Shim, M. (2010). Factors influencing child welfare employee's turnover: Focusing on organizational culture and climate. Children and Youth Services Review, 32, 847−856. Smith, B. D., & Mogro-Wilson, C. (2006). Multi-level influences on the practice of interagency collaboration in child welfare and substance abuse treatment. Children and Youth Services Review, 29(5), 545−556.
156
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
Tracey, J. B., Tannenbaum, S., & Kavanagh, M. (1995). Applying trained skills on the job: The importance of the work environment. The Journal of Applied Psychology, 80(2), 239−252. University of Tennessee Children's Mental Health Services Research Center (UTCMHSRC). (2000). Children's services organizational climate survey and children's services organizational culture survey. Knoxville, TN: author.
van Zyl, M. A., Antle, B. F., & Barbee, A. P. (2010). Organizational change in child welfare agencies. In S. Fogel, & M. Roberts-DeGennero (Eds.), Empirically supported interventions for community and organizational change (pp. 177−199). New York: Lyceum Books. Wehrmann, K., Shin, H., & Poertner, J. (2002). Transfer of training: An evaluation study. Journal of Health & Social Policy, 15(3/4), 23−37.
Contents lists available at ScienceDirect
Children and Youth Services Review j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c h i l d yo u t h
Transferring training to child welfare practice: Individual and collective efforts Junqing Liu a,⁎, Brenda D. Smith b a b
School of Social Welfare, University at Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, United States School of Social Work, The University of Alabama, United States
a r t i c l e
i n f o
Article history: Received 21 June 2010 Received in revised form 27 August 2010 Accepted 31 August 2010 Available online 7 September 2010 Keywords: Child welfare Training Training transfer Supervision Organizations
a b s t r a c t The transfer of training to practice constitutes an ongoing challenge in child welfare services. Many efforts to understand and promote training transfer address the concept as an individual-level behavior. This study suggests that training transfer is both an individual and collective process. The study involves a survey at two time points of 214 workers from child welfare agencies who attended a training program. Principle components analysis identified two meaningful sub-components within the concept of the training transfer. Hierarchical linear regression was used to assess the influence of individual-level and contextual factors on both components. Findings suggest that to promote collective training transfer and enhance both individual and group performance, child welfare administrators may need to strengthen supervisory support and to promote positive work climates in which trainees can discuss training concepts and work together to apply them. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Training has been an important means of introducing new knowledge and practice to child welfare workers (Wehrmann, Shin, & Poertner, 2002). Federal, state and localities invest heavily in training child welfare staff (see Antle, Barbee, Sullivan, & Christensen, 2009). There can be considerable gaps, however, between training content delivered and the practices of trainees. Child welfare is not unusual in this respect. Across a range of fields, studies estimate that only 10–15% of the training content is transferred back to the workplace (Kontoghiorghes, 2004). Such conditions highlight the need to examine the training transfer and the contextual factors that may affect the transfer of training to practice. To promote the transfer of training to child welfare practice, this study addresses these questions: (1) Does the commonly used unitary concept of training transfer contain sub-components, such as individual and collective components? (2) If so, are individual and collective training transfer influenced by different contextual factors, such as training motivation, supervisory support, or organizational climate and culture?
2. Background Training transfer is defined as applying knowledge, skills, and attitudes that are learned from training to trainees' everyday practice (Baldwin & Ford, 1988). All fields, in and outside of human services, are challenged to promote the transfer of training to practice. Because ⁎ Corresponding author. Tel.: + 1 518 334 2590. E-mail address: [email protected] (J. Liu). 0190-7409/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.childyouth.2010.08.027
child welfare organizations rely so heavily on ongoing training to promote best practices and to ensure compliance with the new regulations and procedures, we might expect greater attention to training transfer and further progress in efforts to achieve it. Training transfer has commonly been treated as an individuallevel behavior in the cognitive psychology and business literatures (see Kontoghiorghes, 2004). Accordingly, individual trainees' characteristics have been a focus of research on training transfer. Selfefficacy, for example, is commonly used to explain the different training transfer outcomes among individual trainees. The basic argument is that people with higher self-efficacy have stronger confidence in their capabilities and tend to set more challenging goals than to people with lower self-efficacy, they are more likely to transfer training to everyday work (Bandura, 1986). Consistent with this logic, research has found that self-efficacy is positively related to pretraining motivation and, in turn, training motivation is positively associated with training transfer (Chiaburu & Marinova, 2005). Within this line of work, research on child welfare training has identified that an individual's learning readiness is related to transfer of training (Antle, Barbee, & van Zyl, 2008). In contrast to an individual-focused point of view on training transfer, organizational researchers have recently revealed that training transfer in an organization can be a systemic or holistic process rather than, or in addition to, an individual-level process (Kontoghiorghes, 2004). Researchers have found that within an organization, individuals, groups, departments, or even a whole organization can be agents of training transfer (Eraut & Hirsh, 2007). This line of work also suggests that training transfer might not necessarily be a unitary concept, and it might contain different components representing the efforts of various work units.
150
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
In the field of child welfare, it is especially important to investigate training transfer at levels beyond individual trainees. This is because: (1) child welfare training often contains information that is complex, tacit, and hard to articulate, and under such circumstances group discussion can help clarify the information and promote shared understanding of a new practice (Frank, Bagdasaryan, & Furman, 2008; Laughlin & Hollingshead, 1995); (2) very often child welfare professionals expect and prefer training at the group or organization level, especially when training addresses practice standards such as regulatory compliance or evidence-based practices (Luongo, 2007); (3) child welfare workers often work in teams (e.g., case planning teams or treatment teams) which require team members to develop common understandings regarding new practices or regulations in order to effectively achieve common team goals (Ellemers, Gilder, & Haslam, 2004; Lewandowski & GlenMaye, 2002). In the past, when research on training transfer focused on individual trainees, researchers sometimes downplayed or ignored as nuisance the influence of contextual variables. Currently, however, practice context, including organizational factors, are considered an essential aspect of the transfer process. For example, Antle et al. (2008) studied training transfer in child welfare and found that supervisory support was significantly associated with training transfer. Research, mostly on human service training, has recognized the following additional contextual factors as being important to training transfer: organizational continuous learning culture (Kontoghiorghes, 2004), organizational climate (Glisson & Hemmelgarn, 1998) and organizational formalization (Clark, 2002; Glission, 2007). We used research on these factors to inform the development of the conceptual framework of this study.
3. Conceptual model and research hypotheses We conceptualize training transfer as having two components of individual and collective training transfer. Fig. 1 presents the hypothesized relationships between the previously mentioned individual and contextual factors and individual and collective training transfer. These associations are specified in the following research hypotheses.
3.1. Contextual factors and training motivation Supervisor support plays an important role in encouraging workers to attend trainings and embrace training content. Supervisors, for example, can emphasize or explain the importance of training and give workers the time and resources to attend and complete trainings. Studies of child protective services caseworkers (Curry, McCarragher, & Dellmann-Jenkins, 2005) and of state government managers and supervisors (Facteau, Dobbins, Russell, Ladd, & Kudisch, 1995) have
Organizational Climate Perception
Supervisor Support H1
H3a
H4a-b
H5a-b H2
Organizational Formalization Perception
H1: Supervisory support will be positively related to training motivation. In an organization, a continuous learning culture is defined as an environment in which knowledge and skill attainment are considered essential responsibilities of employees and are supported by informal interactions in the workplace and formal-policies and structures (Tracey, Tannenbaum, & Kavanagh, 1995). It is logical to expect that child welfare workers will be more motivated to attend trainings when they perceive that their organizations value and support new knowledge and skill acquisition. Chiaburu and Tekleab (2005) studied employees of a U.S. company and found that organizational continuous learning culture was positively related to training motivation. Thus, we hypothesize: H2: Organizational continuous learning culture (as reflected by coworkers (H2a) and organizational administration (H2b)) will be positively related to training motivation. 3.2. Training motivation and individual and collective training transfer Training motivation is the aspiration to engage in training activities and fully embrace the training experience (Carlson, Bozeman, Kacmar, Wright, & McMahan, 2000). It is logical to expect that individuals with high training motivation are also more likely to utilize training content in their job. Empirical child welfare training studies also support the relationship between training motivation and individual training transfer. Antle et al. (2008) found that learning readiness affected training transfer among public child welfare workers. Learning readiness was indicated by traits similar to training motivation such as self-directness in learning and valuing learning as a life skill (Antle et al., 2008). Curry et al. (2005) studied child protective services caseworkers and found that participants' training motivation was associated with training transfer. Therefore, we hypothesize: H3a: Individual training motivation will be positively related to individual training transfer. Individuals who are strongly motivated to attend training should be more eager to apply training into practice. However, the complex and tacit information learned from child welfare training may require individuals to confer with their co-workers in order to understand and evaluate the effectiveness and feasibility of new practices. In addition, individual child welfare worker's desired-outcomes of new practices may rely on the performance of their co-workers and teams (Ellemers et al., 2004). Therefore, due to the nature of the information conveyed in child welfare training and the connections between individual and group outcomes, individual child welfare workers who are highly motivated to use the training will also commit to collective training transfer. Based on the conceptual argument, we hypothesize: H3b: Training motivation will be positively related to collective training transfer.
Individual Training Transfer
Training Motivation
Organizational Continuous Learning Culture
found that supervisory support was positively related to training motivation. Therefore we hypothesize:
H3b
Collective Training Transfer
Fig. 1. Conceptual model of training transfer and the practice context.
3.3. Formal organizational climates and individual and collective training transfer The basis of organizational climate exists within individuals at a workplace (Joyce & Slocum, 1979). James and James (1989) proposed that employees integrate components of their work environments into a general appraisal or “psychological climate.” Extending these ideas, Glisson and James (2002) proposed that if employees in a work unit share similar perceptions of the environment, such perceptions can be aggregated and conceptualized as the “organizational climate” (Glisson & James, 2002).
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
151
In child welfare, organizational climates tend to be characterized by emotional exhaustion and role complexity (Glisson & Green, 2006; Jayaratne & Chess, 1984). The transfer of training into practice requires trainees to spend time and resources applying new information in practice. If an organizational climate is stressful, then even motivated trainees may lack time, energy or emotional resources to engage in transferring training into practice. Thus we expect that the effect of training motivation on individual and collective training transfer will be modified by the nature of the organizational climate. We expect workers in stressful organizational climates to have difficulty applying training content in practice and workers in supportive or friendly work climates to be more able to apply training content in practice. Indeed, Tracey et al. (1995) studied 505 managers from 52 supermarket stores owned by a single private organization and found that supportive organizational climates were positively associated with post-training behaviors, such as problem solving and communication. Although studies have not specifically addressed the impact of organizational climate on training transfer in child welfare, studies focusing on concepts related to training transfer underscore the importance of organizational climates in child welfare. Organizational climates in child welfare or related children's services settings have been associated with service quality and outcomes (Glisson & Hemmelgarn, 1998), access to services (Glisson & Green, 2006), inter-agency collaboration (Smith & Mogro-Wilson, 2006), and staff retention (Cahalane & Sites, 2007; Shim, 2010). Hence, we hypothesize:
training attendees, 192 (90%) completed a Time 1 pre-training survey. Approximately, five months after the training, survey participants were sent a Time 2 follow-up survey by mail. Of this group, 92 (43%) responded. To assess response bias at Time 2, we compared demographic characteristics of the follow-up survey respondents to the characteristics of non-respondents. For most of the demographic characteristics we examined, there were no differences between respondents and non-respondents. We found, however, that compared to nonrespondents, respondents were more likely to be white, and less likely to be African American or Latino/Hispanic. As shown in Table 1, of all pre-training survey respondents, more than half were white females. The mean age was 35 years old. Twenty six percent of the participants held a master's degree. Fifty five percent of participants had worked in their organizations for more than two years. About 60% of the respondents had an annual salary of less than $35,000.
H4: Organizational climate will moderate the relationships between training motivation and (a) individual training transfer, and (b) collective training transfer. The relationships will be positive in more supportive organizational climates and negative in more stressful organizational climates.
4.2.1. Dependent variable Training transfer was measured with twelve-item scale adapted from items used in previous research (Curry et al., 2005; Facteau et al., 1995). To assess whether training transfer involved more than one dimension, we conducted principle components analysis of the 12 items. Two components were extracted. The seven items loading on the first component addressed perceived individual endeavors to use training content in practice. An example item is “I have been able to transfer the skills learned in training back to my actual job.” Five items loading on a second component reflected perceived collective efforts with colleagues to apply training content in practice. An example item is “In the past four months, I made a plan with a co-worker to apply training content.” We conceptualize the two components as individual and collective training transfer. Individual training transfer refers
Organizational formalization is the extent to which formal organizational rules, regulations, and procedures guide work activities (Glisson & Martin, 1980; Hall, 1963). Training transfer increases when organizations are tolerant and open to experimenting with new practices, and when supervisors give workers autonomy and discretion over practices (Collins-Carmago & Royse, 2010). If organizational cultures of child welfare agencies are formal and rigid, individual child welfare workers and teams may have little discretion in their practice or flexibility in applying new skills into everyday work. Thus, we expect that the effect of child welfare workers' training motivation on individual and collective training transfer will depend on the level of organizational formalization. Based on the conceptual argument, we hypothesize that: H5: Organizational formalization will moderate the relationship between training motivation and (a) individual training transfer, and (b) collective training transfer. The relationships will be negative in highly formal organizations and positive in organizations with less formality. 4. Methodology 4.1. Sample and survey procedure The study involves workers from child welfare agencies in a northeastern state who attended a training program. From February 2007 to August 2008, 214 child welfare workers from both voluntary and public child welfare agencies attended 13 separate training workshops on substance abuse and adolescent services. The training workshops were led by staff from a university-based professional development program. Training staff who received training and certification in human subject protection invited trainees to participate in a voluntary and confidential pre-training survey. Of the 214
4.2. Measures The Time 1 pre-training survey addressed training motivation, and perceptions of supervisor support and organizational conditions. The follow-up survey addressed perceived training transfer as well as perceptions of supervisory support and organizational conditions. We used the pre-training survey scores for the independent variables and follow-up survey scores for the dependent variables in all analysis.
Table 1 Demographic information. Demographic variables
n
Mean /percentage (Sta. deviation)
Age Gender Male Female Have a master degree or not Yes No Race White Africa American Latino /Hispanic Asian Other Agency tenure ≤Two Years NTwo Years Child welfare tenure ≤Two Years NTwo Years Salary ≤35,000 N35,000
192 192
35 (10) 20.6 79.4
192 26.1 73.9 192 67.0 19.2 12.8 2.0 2.0 191 44.8 55.2 175 25.4 74.9 190 58.7 41.3
152
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
to individual trainees' perceived use of knowledge or skills learned from training. We define collective training transfer as the perceived use of knowledge or skills from training as part of a work group, such as team, department, or unit (regardless of whether members attended training together). The Cronbach's alpha is .75 for individual training transfer and .87 for collective training transfer. Individual training transfer focuses on the efforts of individual trainees. In contrast, collective training transfer places a heavier emphasis on interactions among units at work (Argote & Ingram, 2000). In our study, the actions of collective training transfer included, but were not limited to group planning, discussion, and feedback on performance. Collective training transfer is not a simply addition of individual training transfer; rather, it involves interaction among group members and may include the adoption of common goals regarding new practices (Chang & Simpson, 1997). 4.2.2. Independent variables 4.2.2.1. Supervisor support. Supervisor support was measured by a nine-item scale adapted from measures used by Chiaburu and Tekleab (2005), and Facteau et al. (1995). A sample item is “My supervisor is tolerant of changes that I initiate as a result of learning new skills in training.” The Cronbach's alpha for the scale is .93. 4.2.2.2. Organizational continuous learning culture. Organizational continuous learning culture was measured by a thirteen-item scale adapted from Tracey et al. (1995). Two of the 13 items were developed for this study. Principle components analysis identified two components in the scale. Five items loaded on a component reflecting co-worker continuous learning culture; eight items loaded on a component reflecting administrative continuous learning culture. Co-worker's continuous learning culture indicates that co-workers provide new information to each other and encourage each other to use new knowledge and skills to increase job performance. An example item is “Co-workers encourage one another to use new knowledge and skills on the job.” Administrative learning culture indicates that administration matches a worker's professional development need with training, evaluates workers' ability to solve problems with alternative methods, and give credit to those who apply new knowledge to job. An example item is “Job assignments continually require the evaluation of alternative solutions to problems.” The Cronbach's alpha is .67 for co-workers' continuous learning culture and .81 for the administrative continuous learning culture. 4.2.2.3. Training motivation. Training motivation was measured by a five-item scale adapted from a measure previously used by Noe and Schmidt (1986). An example item is “Increasing my skills through training will help me perform my job better.” The Cronbach's alpha for the scale is .76. 4.2.2.4. Organizational climate. Organizational climate was measured with three dimensions (14-items) of a scale used by the University of Tennessee Children's Mental Health Services Research Center (UTCMHSRC) (2000). The measure included organizational climate dimensions of role conflict, emotional exhaustion, and role overload. Alpha reliability tests and principle components analysis suggested that for this study, the three dimensions were not distinct. Hence, the 14 items were used together as a measure of organizational climate. An example item is “Once I start an assignment, I am not given enough time to complete it.” The Cronbach's alpha for the scale is .94. 4.2.2.5. Organizational formalization. Organizational rigidity and formalization were measured with items from the formalization dimension of an organizational culture measure used by the University of Tennessee Children's Mental Health Services Research
Center (UT-CMHSRC) (2000). Only one component was extracted via principle components analysis. An example item is “We are to follow strict operating procedures at all times.” The Cronbach's alpha for the scale is .85. 4.3. Data analysis Hierarchical OLS regression models were used to assess the influence of contextual factors on training motivation (H1, H2a, and H2b) and on individual and collective training transfer (H3a and H3b). OLS regression models with interaction terms were used to assess moderating effects of organizational climate (H4) and organizational formalization (H5). To create the interaction terms, we first mean centered the variables of interests, for example, organizational climate and training motivation, then the product of the two mean terms was used as the interaction term. We used this mean centering method to minimize the problem of multicollinearity between the interaction term and the interacting variables (Chiaburu & Tekleab, 2005). 5. Results Table 2 shows the means, standard deviations, and correlations among the variables. Of the demographic variables, only having a master degree was related to training motivation. Hence, we used only master degree as a control variable in the regression models. The bivariate correlation between supervisory support and administrative continuous learning culture is high (.73). However, subsequent analysis indicated no multicollinarity because the VIF values for the independent variables in all models are all less than four, the accepted standard (Hair, Anderson, Tatham, & Black, 2006). H1 predicted a positive relationship between supervisory support and training motivation. As shown in the second step of the regression in Table 3, supervisory support is positively related to training motivation (β = .10, P b .05). Supervisory support explains an additional three percent of the variance in training motivation. Thus, the results indicate some support for H1. The relationship between supervisory support and training motivation loses significance, however, when the variables for continuous learning culture are added to the model. These findings suggest that supervisory support may be mediated by continuous learning culture in organizations. H2a predicted a positive relationship between co-worker continuous learning culture and training motivation and it is supported. The test of H2a is shown in Table 3, Step 3. After controlling for master degree and supervisory support, the more respondents perceived a co-worker-supported continuous learning culture, the greater their motivation for training (β = .13, p b .05). H2b predicted a positive relationship between administrative continuous learning culture and training motivation. As shown in Table 3, Step 4, administrative continuous learning culture is not related to training motivation. H2b is not supported. H3a and H3b predicted that training motivation will be positively related to individual and collective training transfer. The results of the hypothesis tests are presented in Table 4. After controlling for having a master's degree, supervisory support, co-worker continuous learning culture, and administrative continuous learning culture, training motivation is positively associated with individual training transfer(β = .36, P b .05). It explains an extra 6% of the variance in individual training transfer. Training motivation is not related to collective training transfer, however. Thus, H3a is supported, but not H3b. H4a-b predicated that organizational climate would moderate the relationships between training motivation and individual and collective training transfer. The tests of H4a and H4b are shown in the upper and lower part respectively of Table 4, Step 5. Because the interaction terms are not significant, the results suggest that organizational climate does not moderate the relationship between
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
153
Table 2 Means, standard deviations, and correlations. Item
M
SD
1
2
1.Agency tenure 2.Child welfare tenure 3.Master degree 4.Training motivation 5.Supervisory support 6.Administrative culture 7.Co-worker culture 8.Climate 9.Formalization 10.Time 2 Individual training transfer¹ 11.Time 2 Collective training transfer¹
.55 .75 .45 4.38 3.57 3.28 3.67 2.75 3.08 3.93 2.83
.50 .44 .50 .49 .85 .67 .69 .82 .98 .55 .76
1 .56** −.18 −.05 −.09 −.10 −.04 .06 .10 .04 −.13
3
1 .18 .09 −.09 .05 −.03 .03 −.00 −.07 .04
4
5
6
7
8
9
10
1 −.12 .32** .30** .31**
1 .49** .24** .06
1 .12 −.27**
1
11
1 .33** −.11 .07 .16 .01 −.05 −.06 −.08
1 .16** .11 .20** −.12 .02 .27** .05
1 .73** .32** −.20** −.26** .15 .33**
1 .42** −.39** −.46** .09 .24**
.46**
1
1: sample size is 92, for others sample size is 192. *p b .05; ** p b .01.
training motivation and individual training transfer (β = .11, ns) or the relationship between training motivation and collective training transfer (β = −.02, ns). Thus, neither H4a nor H4b are supported. However, Table 4, step 4 shows that stressful organizational climates have a negative marginal effect on collective training transfer (β = −.24, P b .05), but not on individual training transfer. H5a and H5b predicated that organizational formalization would moderate the relationships between training motivation and individual and collective training transfer. As shown in Table 5, Step 5, organizational formalization does not moderate the relationship between training motivation and individual training transfer (β = .24, ns) or the association between training motivation and collective training transfer (β = −.12, ns). Thus, neither H5a nor H5b are supported. Although we did not hypothesize a direct effect of co-worker learning culture on individual or collective training transfer, the results depicted in Tables 4 and 5 indicate that the stronger respondents perceive their co-workers' support for continuous learning, the greater their perceived training transfer (both individual and collective). In addition, the results indicate a direct positive association between supervisory support and collective training transfer.
6. Conclusions and discussion 6.1. Conclusions A few primary findings emerge from this study (see Fig. 2). First, we found that the concept of training transfer in child welfare settings might be conceptualized as having two dimensions. Individual training transfer reflects the efforts of individual trainees to apply training content on the job; collective training transfer reflects efforts of groups, such as work teams or units, to apply training content. Table 3 Regression results predicting training motivation. Predictors
Step 1(β) Step 2 (β) Step 3 (β) Step 4 (β)
Step 1 Master degree .24** Step 2 Supervisory support Step 3 Co-worker learning culture Step 4 Administrative learning culture R² .05 ΔR² F 9.63** ΔF n = 192, *p b .05; **p b .01.
.25**
.25**
.26**
.10*
.06
.10
.13*
.14**
.07 .03 7.76** 5.67*
.10 .03 7.44** 6.39*
−.08 .11 .01 5.87** 1.12
Second, we found support for hypotheses indicating that training motivation is strengthened by both supervisory support and coworkers who embrace continuous learning. In contrast, training motivation was not strengthened by the perception that one's organizational administration embraces continuous learning culture. Perhaps individuals are more influenced by their co-workers than by the administration when it comes to training motivation. Third, we found, that the greater an individual's motivation for training, the greater his or her individual training transfer; but training motivation did not promote collective training transfer. Instead, we found that
Table 4 Organizational climate and individual and collective training transfer. Predictors
Step 1 (β)
Step 2 (β)
Individual training transfer Step 1 Master degree −.04 −.07 Step 2 Supervisory support .16 Co-worker learning culture .33⁎⁎ Administrative learning −.18 culture Step 3 Training motivation Step 4 Organizational climate Step 5 Training motivation Organizational climate⁎ R² .00 .12 Δr² .12 F .07 2.93⁎ Δf 3.88⁎ Collective training transfer Step 1 Master degree −.17 −.16 Step 2 Supervisory support .36⁎ Co-worker learning culture .40⁎ Administrative learning −.14 culture Step 3 Training motivation Step 4 Organizational climate Step 5 Training motivation Organizational climate⁎ R² .01 .19 Δr² .18 F .54⁎⁎ 4.87⁎⁎ Δf 6.28⁎⁎ n = 92. ⁎⁎ p b .01. ⁎ p b .05.
Step 3 (β)
Step 4 (β)
Step 5 (β)
−.19
−.18
−.18
.12 .32⁎⁎ −.17
.12 .30⁎⁎ −.09
.12 .31⁎⁎ −.10
.36⁎
.34⁎
.03
.08
.18 .06 3.77⁎⁎ 6.40⁎
.20 .01 3.38⁎⁎ 1.34
−.15
−.20
.36⁎ .40⁎⁎ −.14
.37⁎ .47⁎⁎ −.38
−.01
.04 −.24⁎
.19 .00 3.85⁎⁎ .00
.24 .06 4.47⁎⁎ 6.39⁎
−.39 .11 .20 .01 2.99⁎⁎ .70
−.19 .37⁎ .46⁎⁎ −.38
.11 −.14 −.02 .24 .00 3.79⁎⁎ .02
154
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
Table 5 Organizational formalization and individual and collective training transfer. Predictors
Step 1 (β)
Step 2 (β)
Individual training transfer Step 1 Master degree −.04 −.07 Step 2 Supervisory support .16 Co-worker learning Culture .33⁎⁎ Administrative learning culture −.18 Step 3 Training motivation Step 4 Organizational formalization Step 5 Training motivation Organization formalization⁎ R² .00 .12 Δr² .12 F .07 2.93⁎ Δf 3.88⁎⁎ Collective training transfer Step 1 Master degree −.17 −.16 Step 2: Supervisory support .36⁎ Co-worker learning culture .40⁎⁎ Administrative learning −.14 culture Step 3 Training motivation Step 4 Organizational formalization Step 5 Training motivation Organizational formalization⁎ R² .01 .19 Δr² .18 F .54 4.87⁎⁎ Δf 6.28⁎⁎
Step 3 (β)
Step 4 (β)
Step 5 (β)
−.19
−.22
−.22
.12 .32⁎⁎ −.17
.3 .32⁎⁎ −.11
.13 .37⁎⁎ −.12
.36⁎
.40⁎
.86
−.13
.18 .06 3.77⁎⁎ 6.40⁎⁎
.23 .02 4.05⁎⁎ 2.56
.47 −.14 .24 .01 3.58⁎⁎ .79
−.15
−.19
−.18
.36⁎ .40⁎⁎ −.14
.36⁎ .44⁎⁎ −.14
.36⁎ .43⁎⁎ −.15
−.01
−.04
.36
−.01
.54
.19 .00 3.85⁎⁎ .00
.20 .00 3.43⁎⁎ .01
−.12 .20 .00 2.97⁎⁎ .36
n = 92. ⁎⁎ p b .01. ⁎ p b .05.
collective training transfer is more likely to occur when workers positively perceive their co-workers' support for learning and their organizational climate. Fourth, organizational formalization did not moderate the impact of training motivation on individual or collective training transfer. More research is needed of the impact of organizational formalization on training motivation and training transfer. Finally, as with many previous studies, this study's results underscore the importance of supervisory support in child welfare. The results suggest that the more support workers perceive from
Supervisor Support Training Motivation
Co-worker support for learning culture
Individual Training Transfer
Collective Training Transfer Organizational Climate Perception
Fig. 2. Results model of training transfer and the practice context.
supervisors, the more motivated they are to attend training, and the more they feel able to transfer training to the job in collective workgroups and teams. That is, we found that supervisory support relates to individual training transfer through training motivation and to collective training transfer directly. Perhaps supervisory support directly promotes collective training transfer because supportive supervisors create a platform for workers to discuss training content and implement it together. 6.2. Limitations The study findings should be interpreted in the context of its limitations. Although the study had a high response rate at Time 1, when the survey was distributed at training, the follow-up response rate at Time 2 was only 43%. In addition to the usual challenges in finding time to participate, Time 1 participants were often hard to locate even 4–5 months after the training. Some had switched jobs or agencies; others had left child welfare positions all together. The low response rate at Time 2 raises questions about how well the study findings represent the perspectives of all child welfare staff. Another important limitation pertains to the use of only self-report measures of training transfer. With the self-report measures we face the possibility that factors such as participants' levels of confidence, self-efficacy, or desire to appear socially desirable will influence the measure of training transfer. The study is also limited by potential questions about the validity of its brief measures. Due to the considerable time constraints of the participants, study measures primarily involved shortened versions of measures used in previous research. Whereas the full versions of some of these measures have documented assessments of validity, the brief measures adapted for this study do not. 6.3. Discussion Child welfare work is challenging and states and localities invest heavily in training child welfare staff (see Antle et al., 2009). Too often, however, trainers and trainees are disappointed in the extent to which content from training is implemented in practice. The field is increasingly seeking to understand and improve the transfer process. This study makes a small step toward that goal by offering empirical support for the concept of collective training transfer and identifying individual and contextual factors associated with training transfer. The study findings have implications for practice, policy and research in child welfare. Child welfare practitioners and policy makers might consider further the merits of conceptualizing and understanding the mechanisms that enable training to be implemented in practice. Collective training transfer involves discussing with others and evaluating the effectiveness of old and new practices. These practice activities are consistent with Argyris and Schon's (1978) double-loop learning concept. The double-loop learning concept emphasizes the importance of feedback mechanisms and reflection in learning (Argyris & Schon, 1978). In efforts to reinforce and foster training implementation, administrators and supervisors might consider ways to promote reflection, discussion, and group accountability mechanisms. van Zyl, Antle, and Barbee (2010), for example, recently found that face-toface group case consultation after training increased the transfer of assessment and case planning skills into practice. In addition, perhaps child welfare administrators and practitioners should evaluate training transfer and its effects at levels beyond individual trainees. Training outcomes could be assessed for groups, teams, departments, and, possibly, organizations as a whole. Findings on the differential impact of contextual factors on the two types of training transfer can help child welfare administrators to be proactive in promoting organizational environments that can enhance both individual and collective training transfer. To increase individual
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
training transfer, child welfare administrators should motivate individuals by focusing on individual needs and goals that people may value (Ellemers et al., 2004). To promote collective training transfer, which may be related to both individual and group performance, child welfare administrators and practitioners may want to strengthen supervisory support and employ innovate strategies designed to create and maintain positive organizational climates (Chiaburu & Marinova, 2005; Glission, 2007; van Zyl et al., 2010). Cultivating a supportive co-worker continuous learning culture could strengthen both individual and collective training transfer. The study findings are consistent with other research suggesting that both individual and collective training transfer is important to the job performance of both individuals and groups (Chang & Simpson, 1997; van Zyl et al., 2010). Studies have not only found that groups benefit from efficient group members, but individuals also benefit from groups through interpersonal corrections of errors and the exchange of ideas among group members (Azmitia & Montgomery, 1993; Brodbeck & Greitemeyer, 2000). To promote both types of training transfer, child welfare researchers should investigate more of the different dynamics of individual and collective training transfer and the organizational conditions that are critical in promoting individual and collective training transfer. In a study of frontline human services workers, Sandfort (1999) illustrated the importance of collective beliefs and shared knowledge to frontline practice in human service organizations. She illustrated how frontline staff interpret their experiences and develop practice norms via interactions with colleagues. Sandfort's study suggested that interactions among colleagues can lead staff units or teams to resist new practices. The present study suggests that interactions among colleagues might also have potential to reinforce or enhance collective support for new practices. The study findings also suggest that certain organizational contexts might foster interactions among colleagues that promote training transfer and, thereby, the implementation of new practices. Just as previous research has demonstrated the importance of post-training efforts to enforce training content (Antle et al., 2009; van Zyl et al., 2010); this study's findings indicate that post-training workplace interactions, conversations, and team efforts warrant further study as potential influences on training transfer. As pressures increase to implement evidence-based practices, child welfare researchers have made progress in conceptualizing components of organizational contexts and identifying possible influences of organizational environments on child welfare practice and outcomes. The capacity for child welfare trainees to transfer training content to practice surely has implications for the implementation of new and evidence-based practices. Researchers must continue to advance conceptualization and empirical investigation of training transfer and other aspects of efforts to implement new or evidence-based practices in challenging human service settings.
References Antle, B. F., Barbee, A. P., & van Zyl, M. A. (2008). A comprehensive model for child welfare training evaluation. Children and Youth Services Review, 30, 1063−1080. Antle, B. F., Barbee, A. P., Sullivan, D. J., & Christensen, D. N. (2009). The effects of training reinforcement on training transfer in child welfare. Child Welfare, 88(3), 5−26. Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes, 82(1), 150−169. Argyris, C., & Schon, D. (1978). Organisational learning: A theory of action perspective. Reading, Mass: Addison Wesley. Azmitia, M., & Montgomery, R. (1993). Friendship, transactive dialogues, and the development of scientific reasoning. Social Development, 2, 202−221. Baldwin, T. T., & Ford, J. K. (1988). Transfer of training: A review and directions for future research. Personnel Psychology, 41(1), 63−103. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
155
Brodbeck, F., & Greitemeyer, T. (2000). Effects of individual versus mixed individual and group experience in rule induction on group member learning and group performance. Journal of Experimental Social Psychology, 36, 621−648. Cahalane, H., & Sites, E. W. (2007). The climate of child welfare employee retention. Child Welfare, 87(1), 91−114. Carlson, D., Bozeman, D., Kacmar, M., Wright, P., & McMahan, G. (2000). Training motivation in organizations: An analysis of individual-level antecedents. Journal of Managerial Issues, 12, 271−287. Chang, E., & Simpson, D. (1997). The circle of learning: Individual and group processes. Education Policy Analysis Archive, 5(7), 1−21. Chiaburu, D., & Marinova, S. (2005). What predicts skill transfer? Exploratory study of goal orientation, training self-efficacy and organizational supports. International Journal of Training and Development, 9(2), 110−123. Chiaburu, D., & Tekleab, A. (2005). Individual and contextual influences on multiple dimensions of training effectiveness. Journal of European Industrial Training, 29 (8/9), 604−626. Clark, N. (2002). Job/work environment factors influencing training transfer within human service agency: Some indicative support for Baldwin and Ford's transfer climate construct. International Journal of Training and Development, 6(3), 146−162. Collins-Carmago, C., & Royse, D. (2010). A study of the relationships among effective supervision, organizational culture promoting evidence-based practice, and worker self-efficacy in public child welfare. Journal of Public Child Welfare, 4(1), 1−24. Curry, D., McCarragher, T., & Dellmann-Jenkins, M. (2005). Training, transfer, and turnover: Exploring the relationship among transfer of learning factors and staff retention in child welfare. Children and Youth Services Review, 27(8), 931−948. Ellemers, N., Gilder, D., & Haslam, S. (2004). Motivating individuals and groups at work: a social identity perspective on leadership and group performance. Academy of Management Review, 29(3), 459−478. Eraut, Michael, & Hirsh, Wendy (2007). The significance of workplace learning for individuals, groups and organisations.SKOPE Monograph 9. Oxford University Department of Economics URL: http://www.skope.ox.ac.uk/WorkingPapers/ Eraut-Hirshmonograph.pdf Facteau, J. D., Dobbins, G. H., Russell, J. E. A., Ladd, R. T., & Kudisch, J. D. (1995). The influence of general perceptions of the training environment on pretraining motivation and perceived training transfer. Journal of Management, 21(1), 1−25. Frank, Todd, Bagdasaryan, Sofya, & Furman, Walter (2008, Aprill). Transfer of learning (TOL) in child welfare.Research Brief 1 Retrieved June 3, 2010 from, http://iuc.sppsr. ucla.edu/iucmain/PDF_DownLoad/TOL_Brief_GET-CW.pdf Glission, C. (2007). Assessing and changing organizational cultural and climate for effective services. Research on Social Work Practice, 17(6), 736−747. Glisson, C., & Green, P. (2006). The effects of organizational culture and climate on the access to mental health care in child welfare and juvenile justice systems. Mental Health Services Research, 33(4), 443−448. Glisson, C., & Hemmelgarn, A. L. (1998). The effects of organizational climate and interorganizational coordination on the quality and outcomes of children's service systems. Child Abuse & Neglect, 22, 401−421. Glisson, C., & James, L. R. (2002). The cross-level effects of culture and climate in human service teams. Journal of Organizational Behavior, 23(6), 767−794. Glisson, C., & Martin, P. Y. (1980). Productivity and efficiency in human service organizations as related to structure, size, and age. Academy of Management Journal, 23(1), 21−37. Hair, J., Anderson, R., Tatham, R., & Black, W. (2006). Multivariate data analysis. Upper Saddle River: Prentice Hall. Hall, R. H. (1963). The concept of bureaucracy: An empirical assessment. The American Journal of Sociology, 69, 32−40. James, L. A., & James, L. R. (1989). Integrating work environment perceptions: Explorations into the measurement of meaning. The Journal of Applied Psychology, 74(5), 739−751. Jayaratne, S., & Chess, W. A. (1984). Job satisfaction, burnout, and stress: A national study. Child Welfare, 29(5), 448−553. Joyce, W. F., & Slocum, J. W. (1979). Climates in organizations. In S. Kerr (Ed.), Organizational behavior (pp. 317−333). Columbus Ohio: Grid. Kontoghiorghes, C. (2004). Reconceptualizing the learning transfer conceptual framework: Empirical validation of a new systemic model. International Journal of Training and Development, 8(3), 1−25. Laughlin, P. R., & Hollingshead, A. B. (1995). A theory of collective induction. Organizational Behavior and Human Decision Processes, 61, 94−107. Lewandowski, C. A., & GlenMaye, L. F. (2002). Teams in child welfare settings: Interprofessional and collaborative processes. Families in Society, 83(3), 245−256. Luongo, G. (2007). Rethinking child welfare training models to achieve evidence-based practices. Administration in Social Work, 31(2), 87−96. Noe, R., & Schmidt, N. (1986). The influence of trainee attitudes on training effectiveness: Test of a model. Personnel Psychology, 39, 497−523. Sandfort, J. (1999). The structural impediments to human service collaboration: Examining welfare reform at the front lines. The Social Service Review, 73(3), 314−339. Shim, M. (2010). Factors influencing child welfare employee's turnover: Focusing on organizational culture and climate. Children and Youth Services Review, 32, 847−856. Smith, B. D., & Mogro-Wilson, C. (2006). Multi-level influences on the practice of interagency collaboration in child welfare and substance abuse treatment. Children and Youth Services Review, 29(5), 545−556.
156
J. Liu, B.D. Smith / Children and Youth Services Review 33 (2011) 149–156
Tracey, J. B., Tannenbaum, S., & Kavanagh, M. (1995). Applying trained skills on the job: The importance of the work environment. The Journal of Applied Psychology, 80(2), 239−252. University of Tennessee Children's Mental Health Services Research Center (UTCMHSRC). (2000). Children's services organizational climate survey and children's services organizational culture survey. Knoxville, TN: author.
van Zyl, M. A., Antle, B. F., & Barbee, A. P. (2010). Organizational change in child welfare agencies. In S. Fogel, & M. Roberts-DeGennero (Eds.), Empirically supported interventions for community and organizational change (pp. 177−199). New York: Lyceum Books. Wehrmann, K., Shin, H., & Poertner, J. (2002). Transfer of training: An evaluation study. Journal of Health & Social Policy, 15(3/4), 23−37.