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This study presents a meta‐analysis synthesizing the existing research on the effectiveness of workplace coaching. We exclusively explore workplace coaching provided by internal or external coaches and therefore exclude cases of manager–subordinate and peer coaching. We propose a framework of potential outcomes from coaching in organizations, which we examine meta‐analytically ( k = 17). Our analyses indicated that coaching had positive effects on organizational outcomes overall (δ = 0.36), and on specific forms of outcome criteria (skill‐based δ = 0.28; affective δ = 0.51; individual‐level results δ = 1.24). We also examined moderation by a number of coaching practice factors (use of multisource feedback; type of coach; coaching format; longevity of coaching). Our analyses of practice moderators indicated a significant moderation of effect size for type of coach (with effects being stronger for internal coaches compared to external coaches) and use of multisource feedback (with the use of multisource feedback resulting in smaller positive effects). We found no moderation of effect size by coaching format (comparing face‐to‐face, with blended face‐to‐face and e‐coaching) or duration of coaching (number of sessions or longevity of intervention). The effect sizes give support to the potential utility of coaching in organizations. Implications for coaching research and practice are discussed. Practitioner points Our meta‐analysis supports the positive effects of workplace coaching as an approach to employee learning and development in organizations, with a variety of criteria. Our findings indicate that coaching was more effective when conducted by internal coaches and when multisource feedback was excluded. Workplace coaching was effective whether conducted face‐to‐face or using blended techniques (i.e., blending face‐to‐face with e‐coaching).
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Journal of Occupational and Organizational Psychology (2015)
©2015 The British Psychological Society
www.wileyonlinelibrary.com
The effectiveness of workplace coaching:
A meta-analysis of learning and performance
outcomes from coaching
Rebecca J. Jones
1
*, Stephen A. Woods
2
and Yves R. F. Guillaume
3
1
University of Worcester, UK
2
University of Surrey, UK
3
Aston University, Birmingham, UK
This study presents a meta-analysis synthesizing the existing research on the effectiveness
of workplace coaching. We exclusively explore workplace coaching provided by internal
or external coaches and therefore exclude cases of managersubordinate and peer
coaching. We propose a framework of potential outcomes from coaching in organiza-
tions, which we examine meta-analytically (k=17). Our analyses indicated that coaching
had positive effects on organizational outcomes overall (d=0.36), and on specific forms
of outcome criteria (skill-based d=0.28; affective d=0.51; individual-level results
d=1.24). We also examined moderation by a number of coaching practice factors (use of
multisource feedback; type of coach; coaching format; longevity of coaching). Our
analyses of practice moderators indicated a significant moderation of effect size for type of
coach (with effects being stronger for internal coaches compared to external coaches)
and use of multisource feedback (with the use of multisource feedback resulting in smaller
positive effects). We found no moderation of effect size by coaching format (comparing
face-to-face, with blended face-to-face and e-coaching) or duration of coaching (number
of sessions or longevity of intervention). The effect sizes give support to the potential
utility of coaching in organizations. Implications for coaching research and practice are
discussed.
Practitioner points
Our meta-analysis supports the positive effects of workplace coaching as an approach to employee
learning and development in organizations, with a variety of criteria.
Our findings indicate that coaching was more effective when conducted by internal coaches and when
multisource feedback was excluded.
Workplace coaching was effective whether conducted face-to-face or using blended techniques (i.e.,
blending face-to-face with e-coaching).
Is workplace coaching effective in terms of delivering individual learning and develop-
ment, and improvements in performance and results for organizations? Despite the huge
growth in the use of coaching as a strategy for employee learning and development (ICF,
2012), there remains a paucity of scientific evidence examining its benefits for
organizations, coupled with a generally poor specification of the types of outcomes that
*Correspondence should be addressed to Rebecca J. Jones, University of Worcester, Castle Street, Worcester WR1 3AS, UK
(email: rebecca.jones@worc.ac.uk).
DOI:10.1111/joop.12119
1
can be expected from coaching. In this study, we report a meta-analysis of the effects of
coaching on performance, and other learning and development outcome criteria. We also
examine moderators of these effects, focusing on the techniques and features of specific
coaching interventions. Our systematic review of studies evaluating the benefits of
coaching in organizations advances the literature in three main ways. First, we address
problems of criterion specification in the coaching literature by proposing and examining
a framework of coaching outcomes aligned to the learning, training, and development
literature. Second, unlike previous studies (e.g., Theeboom, Beersma, & van Vianen,
2014), we clarify the effectiveness of workplace coaching specifically by focusing our
analyses exclusively on organizational (and not general or educational) samples, and on
coaching provided by practitioner coaches (and not managers or peers), closing an
important empirical gap in the field. Finally, we examine a number of practice moderators
of the effectiveness of coaching, analyses of which have important implications for
practitioner coaches concerning the effectiveness of specific coaching tools and
techniques.
Workplace coaching
Workplace or executive coaching (hereafter referred to as ‘coaching’) is a one-to-one
learning and development intervention that uses a collaborative, reflective, goal-focused
relationship to achieve professional outcomes that are valued by the coachee (Smither,
2011). Coaching has typically been perceived as an ‘executive’ development activity, but
it need not necessarily be limited to managers and executives in organizations. Although
the term coaching may be used to refer to a variety of one-to-one development activities,
there is some emerging consensus about what constitute the core features or elements of
coaching (e.g., see Bono, Purvanova, Towler, & Peterson, 2009; Smither, 2011). These are
(1) formation and maintenance of a helping relationship between the coach and coachee;
(2) a formally defined coaching agreement or contract, setting personal development
objectives; (3) the fulfilment of this agreement (i.e., achievement of the objectives)
through a development process focusing on interpersonal and intrapersonal issues; (4)
striving for growth of the coachee by providing the tools, skills, and opportunities they
need to develop themselves and become more effective (Bono et al., 2009; Kilburg, 1996;
McCauley & Hezlett, 2002; Peterson & Hicks, 1996; Smither, 2011; Witherspoon & White,
1996).
The coaching relationship is one that the coachee enters into for the specific purpose
of fulfilling development objectives. It is important to differentiate coaching from other
forms of developmental relationships in the workplace. Conceptually, it may first be
distinguished from mentoring relationships (see Brockbank & McGill, 2012 for a review).
A mentoring relationship is conventionally long term between a highly experienced
mentor and an inexperienced mentee. The mentor is assumed to be highly experienced in
the discipline or field in which the mentee is working, and in the workplace, the mentor
typically provides guidance on career development and networking (Eby et al., 2013). In
a coaching relationship, there is no such expectation that the coach has expertise or
experience of the coachee’s area of work, and the term of the relationship is rather guided
by specific objectives.
Similarly, there are relative status prerequisites in ‘peer coaching’ (Parker, Hall, &
Kram, 2008; Parker, Kram, & Hall, 2013), in which development is a two-way reciprocal
process between people of equal status in an organization. Peer coaching aims to provide
mutually supportive personal and professional development of both people in the
2Rebecca J. Jones et al.
peer-coaching dyad. The developmental focus in coaching, by contrast, is solely the
coachee, and the relationship is free from the influence or boundaries of organizational
status structures.
The coaching relationship is also typically considered to be distinct from
formalized organizational performance management relationships (e.g., supervisor
subordinate; Feldman & Lankau, 2005). For example, there exists a power relationship
between line managers and their subordinates, which is absent in the helping
relationship a coachee would have with an independent coach. Managers and
supervisors might propose coaching as a developmental intervention for their staff
(and in this sense, coaching might be considered a part of performance management
processes), but to fit with the relational definition of coaching, the developmental
relationship that facilitates learning and development would be with a coach, rather
than the manager or supervisor.
In this study, we conceptualize coaching as distinct from these other forms of
developmental relationship. Correspondingly, in our analyses, we specifically focus on
studies of coaching and exclude studies of other relationships (e.g., mentoring, supervisor
coaching, and peer coaching).
In terms of practical utility, keeping coaching distinct from other organizational
performance management and development relationships offers potential advantages.
Sherman and Freas (2004) report that the relational nature of coaching provides an
individual, customized feel to coaching, with coaches providing candour, and honest
feedback to the coachee in relation to their performance and behaviour. This is frequently
supplemented with feedback from the coachee’s organization (e.g., through multisource
feedback). However, the privacy, non-judgmental perspective, and confidentiality of the
coaching session provide a safe environment for the coachee to reflect on that feedback
and work on improving areas of weakness. The coach may discuss suggested tools and
techniques to help the coachee develop and improve, the content of which is dependent
on the background and approach of the coach. However, coaches generally avoid
providing instructional or prescriptive solutions to coachees, because as highlighted
above, they are often not technical experts in the coachee’s occupational area of specialty
(McAdam, 2005).
In the context of human resource management (HRM), coaching represents an
approach to employee learning, training, and development, and although there
remains lack of consensus about the core processes of coaching as a development
intervention (a point that we return to later), coaching sessions are frequently
characterized either directly or indirectly with a number of performance-promoting
features.
First, coaches apply goal-setting: Well established as a technique of performance
improvement (e.g., Locke & Latham, 1990, 2002; Morisano, Hirsh, Peterson, Pihl, & Shore,
2010; Wegge, Bipp, & Kleinbeck, 2007). Second, goals generally feature activities
undertaken whilst at work, promoting experiential forms of practice and learning (e.g.,
Kolb, 1984). Related to this and thirdly, by enc ouraging learning through practice at work,
coaching rather directly promotes translation of learning to work performance behaviour,
addressing the issue of transfer, often cited as a barrier to performance benefits of training
(e.g., Baldwin & Ford, 1988). In this respect, the personalized nature of coaching may
provide a high-fidelity form of workplace learning (Kozlowski & DeShon, 2004; van der
Locht, van Dam, & Chiaburu, 2013).
Effectiveness of workplace coaching 3
Coaching effectiveness
In the literature to date, the case has been building, based primarily on anecdotal evidence
and uncontrolled studies, that coaching is effective at improving work-based outcomes
including goal accomplishment (Fischer & Beimers, 2009), professional growth (McGuf-
fin & Obonyo, 2010), improved professional relationships (Kom barakaran, Yang, Baker, &
Fernandes, 2008), greater managerial flexibility (Jones, Rafferty, & Griffin, 2006),
increased productivity (Olivero, Bane, & Kopelman, 1997), and improved resilience and
workplace well-being (Grant, Curtayne, & Burton, 2009). Coaching is also aligned with
recent emergent interest in active rather than passive learning, by which employees take
responsibility for shaping their own learning processes (Bell & Kozlowski, 2008).
Coaching is led by the coachee, giving them control over their learning and development,
and the increasing popularity of coaching in organizations may therefore reflect a more
general trend away from ‘one size fits all’ approaches to training (Salas & Kozlowski,
2010).
Despite the apparent potential advantages of coaching, research has not kept pace
with its growth in practice, and the lack of conclusive evidence regarding the
effectiveness of coaching is one of the most frequently cited problems in the field (Grant,
Passmore, Cavanagh, & Parker, 2010). Shortcomings in the research evidence base for
coaching include problems of empirical research design and criterion measurement in
evaluation studies (Grant, Passmore, et al., 2010).
Recognizing the need for systematic evidence in this field, Theeboom et al. (2014)
reported a meta-analysis of the effects of coaching on several outcome criteria. Using
Hedges’ g, which corrects for potential bias due to overestimate of population effect size
when small samples are included in the analysis (Hedges, 1981), they reported positive
overall effects of coaching with aggregated outcomes (g=0.66), and with specific kinds
of criteria: Performance and skills (g=0.60); well-being (g=0.46); coping (g=0.43);
work attitudes (g=0.54); and goal-directed self-regulation (g=0.74). Positive effects
were moderated by research design (within-subjects research design studies g=1.15,
compared to mixed design studies g=0.39). Moderator testing also showed no
moderation by number of coaching sessions leading Theeboom et al. (2014) to conclude
that the number of coaching sessions is not related to the effectiveness of the intervention.
Whilst the meta-analysis of Theeboom et al. (2014) represents an important advance
in the evidence base for coaching generally, the implications for coaching in organizations
specifically are less clear. This is because in their analyses, Theeboom et al. (2014)
compute effect sizes which are derived from studies of coaching in a variety of contexts.
For example, results from studies of workplace coaching are combined with results from
studies of coaching conducted for different purposes (e.g., of the 18 studies included in
the analyses, six report the results of general life coaching, and one reports results of
health coaching). Moreover, Theeboom et al. (2014) mix studies using organizational
samples with studies based on educational and general non-organizational samples (e.g.,
seven of the 18 primary studies included were conducted in non-organizational samples
such as student or general population convenience samples). As a consequence, the
implications of the meta-analysis for organizations applying coaching as part of HRM, for
performance improvement at work, are confounded and therefore inconclusive.
The problem of applying the findings of Theeboom et al. (2014) to the literature on
learning, training, and development in organizations is further compounded by issues of
criterion specification. Although five categories of criteria were analysed (performance/
skills; well-being; coping; work attitudes; goal-directed self-regulation), they appear to
have been defined bottom-up (i.e., based on those criteria measured in the included
4Rebecca J. Jones et al.
studies) instead of top-down (i.e., by applying systematic criterion framework to classify
outcomes). Uncertainty about the specific nature of the work outcomes from coaching
that might be expected (e.g., Bennett, 2006; Brotman, Liberi, & Wasylyshyn, 1998;
Lowman, 2005) therefore remains unaddressed in the literature.
To address these limitations, in our study, we seek to more clearly integrate the
literature on coaching with wider literature on employee learning, training, and
development at work. We therefore focus exclusively on studies using organizational
samples that examine work-relevant outcomes (i.e., excluding variables such as general
life satisfaction). This approach is consistent with recent calls in the organizational
behaviour literature to consider more carefully the context and setting of research studies
(Brutus, Gill, & Duniewicz, 2010; Stone-Romero, 2008). Moreover, we propose and
examine a criterion framework of coaching outcomes at work, derived from existing
criterion models in the learning, training, and development literature. This provides a
more robust classification of criterion effects and enables our findings to be better
integrated with evidence from industrial, work and organizational psychology, and HRM
research on training effectiveness. Finally, addressing the need for research on the
features and techniques of coaching that make it more or less effective (Grant, Passmore,
et al., 2010; Swart & Harcup, 2013), and adding to the practical utility of our study for
coaching practice at work, we also test several coaching practice moderators that may
influence the effectiveness of coaching.
Outcome criteria of coaching and their measurement
There is little consensus in the literature regarding the most appropriate outcome criteria
for evaluating coaching (Grant, Passmore, et al., 2010; MacKie, 2007; Smither, 2011). To
advance in this respect, it is possible to draw on established criterion models from the
literatures on learning, training, and development to propose a criterion framework for
evaluating coaching.
The ultimate aim of learning, training, and development is to maximize the
effectiveness of an organization’s human capital (Ford, Kraiger, & Merritt, 2010) by
improving performance at the individual level, on the assumption that this will
subsequently result in organizational-level improvements (Swart & Harcup, 2013).
Learning, training, and development interventions are therefore positioned as a central
function of HRM, integrated with performance management processes more widely (e.g.,
Murphy & DeNisi, 2008). Coaching is compatible with this conceptualization because the
aim of coaching is to aid the achievement of individual goals for improvement, in order to
positively contribute to organizational-level goals and objectives. Given this compatibility,
outcome criteria for training effectiveness may represent a sensible foundation for
modelling the potential outcomes of coaching.
In the training literature, Kirkpatrick (1967) model of evaluation criteria proposes that
the evaluation of training should be performed at four levels: Reactions, learning,
behaviour, and results. Kirkpatrick’s model is widely applied in research and practice
(e.g., Alliger, Tannenbaum, Bennett, Traver, & Shotland, 1997; Arthur, Bennett, Edens, &
Bell, 2003; Powell & Yalcin, 2010; Tharenou, Saks, & Moore, 2007) and represents a
logical organization and progression of outcomes from basic individual reactions to
training through to training transfer and organizational results. Kraiger, Ford, and Salas
(1993) argued that when evaluating training, it was necessary to examine learning-based
outcomes in a more sophisticated way, rather than combining learning and transfer
outcomes as in the Kirkpatrick levels. Kraiger et al. (1993) proposed a model of three
Effectiveness of workplace coaching 5
classes of learning outcomes that occur following training: Cognitive; skill-based, and
affective outcomes. This three-component model of learning outcomes has been applied
in numerous studies (e.g., Kalinoski et al., 2013; Mesmer-Magus & Viswesvaran, 2010;
Taylor, Russ-Eft, & Chan, 2005).
Based on these existing criterion frameworks, we propose that the outcomes of
coaching be modelled in the following ways. With respect to the Kraiger et al. (1993)
three-component classification, we propose that the potential outcomes of coaching
are similarly separated into cognitive, skill-based, and affective outcome criteria.
Examples of cognitive outcomes from coaching include new declarative and
procedural knowledge which could be acquired by self-directed learning and
problem-solving (guided by goal-setting). The work-based application of improvement
and development activity that is encouraged in coaching is likely to promote skill
acquisition and enhancement, effectively resulting in skill-based outcomes. In addition,
many of the intended benefits of coaching represent affective outcomes, such as the
development of self-efficacy and confidence, reduction of stress, and increased
satisfaction and motivation.
We also note the aims of coaching to contribute to achievement of organizational-
level goals and objectives (e.g., Sonnentag & Frese, 2002). By aligning individual goal-
setting to these organizational-level goals and objectives, coaching may impact
performance, making it sensible to include some measure of results, as per
Kirkpatrick’s model (Kirkpatrick, 1996). Results might be measured in terms of
impact on individual-, team-, and organizational-level performance. Our proposed set of
evaluation criteria for coaching is summarized in Table 1. Drawing on Kraiger et al.
(1993) and Kirkpatrick (1996), we also specify acceptable measurement methodology
for assessing these outcome criteria, which were applied in our coding of studies for
the meta-analysis.
Given its role as a learning and development intervention, we expected coaching to
influence all of our proposed evaluation criteria. However, in our meta-analysis, we were
only able to test effects of coaching on affective, skill-based, and individual-level results
outcomes. We return to this point in our discussion of findings.
H1: Coaching will demonstrate positive effects for affective, skill-based, and
individual-level results outcome criteria.
Table 1. Summary of proposed coaching evaluation criteria
Outcome criteria Description Measurement methodology
Affective outcomes Attitudes and motivational outcomes
(e.g., self-efficacy, well-being, satisfaction)
Self-report questionnaires
Cognitive outcomes Declarative knowledge; procedural
knowledge; cognitive strategies
(e.g., problem-solving)
Recognition and recall tests
Skill-based outcomes Compilation and automaticity of new skills
(e.g., leadership skills, technical skills,
competencies)
Behavioural observation in
the workplace (e.g.,
multisource feedback
questionnaire)
Results Individual, team, and organizational
performance
Financial results, objective
or goal achievement,
and productivity
6Rebecca J. Jones et al.
Research design
Alongside the nature of coaching outcome criteria, a further methodological
consideration for studies examining the effects of coaching is the research design
employed to measure those criteria. Within-subjects research design has frequently
been utilized by other researchers in the field of training evaluation (e.g., Dierdorff,
Surface, & Brown, 2010; Franke & Felfe, 2012; Patrick, Smy, Tombs, & Shelton, 2012).
Effect sizes in within-subjects designs represent the differences between measure-
ments of criteria taken before and after the coaching has taken place (with varying
duration of time between measurements depending on the number and schedule of
coaching sessions). An alternative design is the between-subjects design (e.g., Ayres &
Malouff, 2007; Holladay & Qui~
nones, 2003; Neal et al., 2006; Orvis, Fisher, &
Wasserman, 2009). In these studies, effect sizes represent the differences between
control and experimental (i.e., coaching) groups measured after the coaching has
taken place.
In our meta-analysis, we adopt a position that these two methodologies (within-
subjects and between-subjects) both represent acceptable and robust designs for studies
of coaching outcomes. We therefore only include studies that adopt one or other of these
designs in our meta-analysis. For analytic completeness, we compare the effect size of
coaching in studies that adopt each methodology. Theeboom et al. (2014) found stronger
effects for within-subjects designs compared to between-subjects designs and speculated
that this may be due to the increased level of control over potential bias and confounds in
between-subjects designs, reducing the magnitude of effects compared with within-
subjects designs. For example, inclusion of control groups allows for control of the natural
maturation of participants over time and selection effects in sampling. Following this
reasoning, we hypothesize:
H2: Coaching will demonstrate stronger positive effects on overall outcomes in
studies using within-subjects research designs compared to between-subjects
designs.
Practice moderators of coaching effectiveness
In addition to the meta-analyses of the effectiveness of coaching in relation to specific
criteria, we further extend the scope of our study by examining potential practice
moderators of coaching effectiveness. There are a variety of possible tools and
techniques that specific coaches may use, which might be considered method factors
in the practice and implementation of coaching. As with studies of training
interventions (e.g., Bell & Kozlowski, 2010), it is reasonable to assume that these
method factors in coaching have some impact on its effectiveness. Such factors
therefore represent moderators of the benefits of coaching on the outcome criteria
we have identified. In our meta-analysis, we were able to test how four coaching
method factors (use of multisource feedback; coaching delivery format; internal vs.
external coach; longevity of coaching) moderate the benefits of coaching. We
selected these moderators based on their coverage in the practical literature on
coaching and because our literature search yielded studies that permitted their
analyses. However, we do acknowledge that these are not the only potential practice
moderators in the practice of coaching, a point that we develop further in our
discussion of findings.
Effectiveness of workplace coaching 7
Multisource feedback
Coaching is frequently accompanied by multisource feedback in the research literature.
Coaching is often used to facilitate the interpretation of multisource feedback (Luthans &
Peterson, 2003; Smither, London, Flautt, Vargas, & Kucine, 2003), and in some studies
(including some in our meta-analysis), changes in multisource evaluations over time serve
as an outcome measure for coaching (Kochanowski, Seifert, & Yukl, 2010). Previous
research has shown that multisource feedback can be an effective method of improving
work performance in its own right (Kluger & DeNisi, 1996; Smither, London, & Reilly,
2005). The utility of multisource feedback may also be considered in relation to evidence
that feedback more generally has performance benefits. For example, performance
feedback has been shown to influence goal regulation. Ilies and Judge (2005) and Johnson
(2013) found that both evaluative and objective feedback had significantly positive
impacts on task performance. Seifert, Yukl, and McDonald (2003) found that feedback had
a positive impact on outcomes when given in conjunction with a facilitator during a
workshop rather than as written feedback alone.
Given that the purpose of coaching is to facilitate self-insight and reflection, it seems
logical that combining coaching with multisource feedback is likely to lead to a greater
impact on outcomes than coaching alone. Moreover, the discursive exploration that
comes from coaching is likely to represent a more effective presentation of the
multisource feedback than simple written results, further enhancing the benefits to the
coaching intervention. We hypothesize that:
H3: Coaching utilizing multisource feedback as part of the coaching process (rather
than solely as an outcome measure) will demonstrate a larger effect size than
coaching without multisource feedback.
Format of coaching
Coaching is most commonly conducted face-to-face; however, the use of alternative
formats such as videophone, telephone, and internet coaching is also prevalent
(collectively referred to as e-coaching; the use of technology to conduct coaching).
Research in the field of health psychology has found that telephone discussion is an
effective way of delivering coaching for lifestyle change in older men (Aoun, Osseiran-
Moisson, Shahid, Howat, & O’Connor, 2011) and for reducing people’s health risks (Terry,
Seaverson, Staufacker, & Gingerich, 2010). However, a study by Yan, Wilber, and
Simmons (2011) found that when compared to telephone-delivered health coaching, face-
to-face coaching was more effective at improving exercise performance in high-risk older
adults.
A study by Wentz, Nyden, and Krevers (2012) demonstrated that internet-based
coaching led to improvements in self-efficacy and subjective quality of life in a sample of
young people with autism spectrum disorder and/or attention-deficit/hyperactivity
disorder. Also focusing on the use of internet-mediated development, research has
demonstrated the utility of e-mentoring for a variety of outcomes (Ensher, Heun, &
Blanchard, 2003; Ensher & Murphy, 2007). For example, in a student sample, de Janasz
and Godshalk (2013) found that e-mentoring was positively related to a variety of learning
outcomes and Kyrgidou and Petridou (2013) found that e-mentoring of a sample of
women entrepreneurs had a positive impact on mentees’ knowledge, skills, and attitudes.
Although these findings taken together suggest the developmental support can be
effective when provided in a variety of formats, there are no studies that directly compare
8Rebecca J. Jones et al.
delivery formats for workplace coaching. Indeed, studies often combine approaches such
as telephone and face-to-face, such that the format of the coaching may be considered
mixed method or ‘blended’ format (e.g., Bozer & Sarros, 2012). We have earlier
emphasized the dependence of coaching on the formation of a helping relationship,
which must be established without a priori foundations (i.e., there is no existing
relationship or power or status dynamic on which to build). We therefore propose that the
relational nature of coaching is likely to be more effectively fostered in a face-to-face
personal environment than in e-coaching formats. Studies in our meta-analyses enabled us
to compare face-to-face with blended formats (which all comprised a mixture of face-to-
face and telephone coaching). We therefore hypothesize:
H4: Face-to-face coaching will demonstrate a larger effect size than blended (i.e.,
blending face-to-face with telephone coaching).
Type of coach
Coaches may either be external or internal to the coachee’s employing organization.
Internal coaches are different from managers and supervisors (who may also give
performance feedback and suggest ways to improve as part of performance management)
because they do not have supervisory responsibilities for the coachee. External coaches
are often engaged as consultants to the organization to work with specific employees.
Whilst again there are no published organizational studies of this method factor, a study by
Sue-Chan and Latham (2004) in an educational context found that students receiving
coaching from an external coach achieved significantly higher course grades than
students who had been coached by a peer. Students also rated the external coaches as
more credible than the peer coaches.
In the context of work, Higgins and Kram (2001) propose that the changing nature of
careers is an underlying reason why individuals are likely to need to seek developmental
support from outside the organization. As careers become more protean, acquisition of
skills and perspectives from outside the employing organization becomes more critical.
This is underscored by Arthur, Khapova, and Wilderom (2005) who identify the
importance of extra-organizational support (through coaching or mentoring) in career
success from the boundaryless career perspective. External coaches have the advantage in
this respect of offering the coachee support that is not restricted to the boundaries of the
employing organization.
A counterview from the mentoring literature rather supports the superiority of internal
mentors. Haggard, Dougherty, Turban, and Wilbanks (2011) suggest that mentors
working externally to the mentees organization cannot provide the full range of career
assistance functions that an internal mentor could. In particular, the external mentor is
unlikely to be able to provide sponsorship, protection or challenging assignments for their
mentees. This observation was supported by Murrell, Blake-Beard, Porter, and Perkins-
Williamson (2008) who suggest that despite the benefits of external mentors, an internal
mentor provides a number of functions such as opportunities for exposure, visibility to
key management and coaching around political landmines in a way that an external
mentor could not. However, it is questionable whether these benefits necessarily transfer
to coaching. Unlike mentoring, coaching does not rely on the organizational and career
experience and expertise of the coach with respect to the work of the coachee, and so
effective achievement of development objectives is not necessarily predicated on
Effectiveness of workplace coaching 9
knowledge of the internal workings of the organization. The advantages of working with
an external coach may therefore outweigh the benefits afforded by an internal coach.
We propose that compared to those working with internal coaches, coachees who
receive coaching from an external coach may feel more confident in the wider credibility
and perspective of the coach, and also that the coaching is more likely to be confidential.
Releasing development from the boundaries and constraints of organizational politics and
barriers may also be beneficial in working through development objectives. In
combination, these factors are likely to have a positive impact on the outcomes of the
coaching. We hypothesize that:
H5: Coaching provided by an external coach will demonstrate greater effect sizes
than coaching provided by an internal coach.
Coaching schedule
Research examining the effects of the number of coaching sessions or the overall
longevity of coaching interventions is limited. This is despite calls to address these
questions (e.g., Smither, 2011). Theeboom et al. (2014) tested for the moderation of the
number of coaching sessions in their meta-analysis on coaching and found that a greater
number of coaching sessions did not significantly impact on outcomes. Theeboom et al.
propose that this counterintuitive effect may be due to individuals with less serious or less
complex issues needing fewer coaching sessions and experiencing more positive effects
of coaching than individuals with more serious or complex issues. These findings are
consistent with the mentoring literature. Ensher, Thomas, and Murphy (2001) found that
the longevity of the mentoring relationship had a small but significant association with
social support, but found no relationships with vocational support, role-modelling
support, reciprocity (i.e., level of give and take between mentor and mentee), satisfaction
with mentor, job satisfaction, and perceived career success. A possible explanation for
this is that the mentor themselves (i.e., their success and expertise) is more important than
the longevity of the relationship (Tonidandel, Avery, & Phillips, 2007).
Notably, the above studies tested only for linear effect of coaching schedule variation
(number of sessions and longevity of the relationship). This would prevent detection of
nonlinear relationships, which may occur if, for example, the impact of number of
sessions or longevity plateaus after a certain point. The weight of the research evidence
suggests on balance that coaching schedule does not have an impact on coaching
outcomes, but nevertheless we tested for moderation (including for curvilinear effects) in
our analyses. Given that we did not expect to observe effects, we did not set a hypothesis
regarding these moderation analyses.
Method
Literature search
A range of search strategies were utilized to identify relevant published and unpublished
studies (including doctoral dissertations). Firstly, various electronic databases were
searched including ProQuest, EBSCO, Emerald Full Text, JSTOR Business, SAGE Journals
Online, ScienceDirect, SwetsWise, Taylor and Francis, Wiley Online Library, and Oxford
Journals. The following search terms were used: (coaching) and (effectiveness or
outcome or impact or influence or evaluation). In addition to this database search,
10 Rebecca J. Jones et al.
frequent contributors to coaching research literature were contacted directly by e-mail to
ensure that any unpublished data or work in progress were included in the meta-analysis.
Finally, a manual review of the reference lists of all of the articles identified in the database
search and also the reference list of all relevant reviews was completed. This initial search
identified a total of 54 studies.
Criteria for inclusion
To be included in the meta-analysis, studies had to meet six criteria. First, the study had to
examine workplace coaching effectiveness (i.e., studies in which coaching was provided
with the objective of generating affective, cognitive, skill-based or results outcomes at
work). Studies were included if they adequately described coaching activity (i.e., one-to-
one development intervention based on a coachcoachee relationship) in a work context,
and evaluated that activity in terms of its effectiveness. Studies that measured the impact of
coaching on non-work outcomes (such as exercise or healthy eating) were excluded, as
were studies where coaching was provided by a line manager. Secondly, we included only
studies that evaluated coaching using the within- and between-subjects designs we
reviewed earlier. Thirdly, studies had to have been conducted within an organizational
setting, to ensure all participants were employed working adults. Fourthly, studies needed
to report sample sizes. Fifthly, a dstatistic or other statistic (e.g., means and standard
deviations) that could be converted into a dstatistic must have been reported between
coaching and the outcome variable. Finally, the dependent variable or coaching outcome
had to be measured at the individual level of analysis.
Data set
Of the 54 studies identified in the literature search, 17 met our inclusion criteria
(n=2,267 individuals). The average sample size of these studies was 133 with a range
from 14 to 1,361. Seven studies were conducted in the United States; two in the United
Kingdom; three in Australia; two in Norway; one in Egypt; one in Israel; and one in
Denmark. The studies were conducted in different organization types and industries
including service, manufacturing, construction, and public/government sectors. Occu-
pations of participants were varied; however, the majority held senior management
(k=5, n=1,527) or management roles (k=5, n=326). Other occupations were
nurses (k=1, n=120), high school principals (k=1, n=8), teachers (k=1, n=44),
construction foremen (k=1, n=51), and various occupations within single studies
(k=2, n=69). The earliest study was reported in 1997, and the other studies were
reported after 2003 (2003 =two studies; 2005 =two studies; 2006 =one study;
2007 =one study; 2009 =three studies; 2010 =four studies; 2011 =one study and
2012 =one studies). All studies included in the meta-analysis are summarized in Table 2
and listed in the references marked with asterisks (*).
Description of variables
All useable studies were coded on a number of specific variables including source of study,
sample size, year of publication, occupation of coachee, and organizational context. In
addition, we developed a coding scheme to code for the moderators highlighted in our
hypotheses. Firstly, research design was coded for (i.e., between-subjects design, 14
studies; within-subjects design, three studies). In between-subjects studies, outcome data
Effectiveness of workplace coaching 11
Table 2. Summary of coaching effectiveness studies included in the meta-analysis
Authors Sample Country
Organizational
context
Occupation of
participants
Outcomes
measured Research design
Coaching
technique
Longevity of
intervention
(weeks)
a
Duration of
sessions (min)
Number of
sessions
b
Multisource
feedback
Format of
coaching
Type of
coach
Bozer and
Sarros (2012)
96 Israel Various Management Affective
Skill-based
Between-subjects Cognitive-
behavioural
15.2 30120 68 Not
specified
Face-to-face,
telephone
and e-mail
External
Bright and
Crockett (2012)
115 United States Various Various Affective Between-subjects Not specified 4 30 1 No Telephone External
Cerni et al. (2010) 14 United States Education Principals Skill-based Between-Subjects Epstein’s
constructive
thinking
programme
(1998)
10 60 10 No Face-to-face External
Evers et al. (2006) 60 United States Government
Agency
Management Affective Between-subjects GROW model
(Whitmore,
1992)
17.3 Not specified Not specified No Not specified External
Finn (2007) 17 Australia Not specified Senior
management
Affective
Skill-based
Between-subjects Not specified 12 60 6 Yes Face-to-face
and telephone
External
Grant et al. (2009) 41 Australia Health Executives and
senior
managers
Affective
Results
Between-subjects Cognitive-
behavioural
solution
focussed
(Grant, 2003)
GROW model
(Whitmore,
1992)
10 Not specified 4 Yes Face-to-face
and telephone
External
Grant, Green,
et al. (2010)
44 Australia Education Teachers Affective
Skill-based
Results
Between-subjects Cognitive-
behavioural
solution
focussed
(Grant, 2003)
GROW model
(Whitmore,
1992)
20 Not specified 10 Yes Face-to-face External
Gyllensten and
Palmer (2005)
31 United
Kingdom
Finance Not specified Affective Between-subjects Not specified 34.7 Not specified Not specified No Face-to-face Internal
Kines et al. (2010) 51 Denmark Construction Construction
foremen
Skill-based Between-subjects Not specified 42 Not specified 8 No Face-to-face External
Kochanowski
et al. (2010)
30 United States Retail Store managers Skill-based Between-subjects Not specified 6 3060 6 Yes Face-to-face
and telephone
External
20 United States Manufacturing Various Within-subjects Notspecified 13 Not specified 1 Yes Face-to-face External
Continued
12 Rebecca J. Jones et al.
Table 2. (Continued)
Authors Sample Country
Organizational
context
Occupation of
participants
Outcomes
measured Research design
Coaching
technique
Longevity of
intervention
(weeks)
a
Duration of
sessions (min)
Number of
sessions
b
Multisource
feedback
Format of
coaching
Type of
coach
Luthans and
Peterson (2003)
Affective
Skill-based
Moen and
Allgood (2009)
127 Norway Not specified Executives and
managers
Affective Between-subjects Not specified 52 Not specified Not specified No Not specified Not
specified
Moen and
Skaalvik (2009)
19 Norway Not specified CEOs Affective Between-subjects Not specified 13 6090 7 No Face-to-face
and telephone
External
Olivero et al. (1997) 31 United States Health Management Results Within-subjects Notspecified 8.7 60 8 No Face-to-face Internal
Smither et al. (2003) 1,361 United States No specified Senior managers Skill-based Between-subjects Not specified Not specified Not specified 23 Yes Face-to-face External
Taie (2011) 120 Egypt Health Nurses Skill-based Between-subjects Not specified Not specified Not specified Not specified No Face-to-face Internal
Toegel and
Nicholson (2005)
89 United
Kingdom
Finance Senior managers Skill-based Within-subjects Notspecified 39 90 2 Yes Face-to-face
and telephone
External
Note.
a
Where the longevity was specified in months, we converted to weeks based on an assumption of average 4.33 weeks per month. For our analyses, if a range of longevity was reported, we coded as the mid-point of the range.
b
Where a range of number of sessions was reported (e.g., 68), we coded the data as the mid-point of the range (e.g., 7).
Effectiveness of workplace coaching 13
were collected for all participants at time 1. The coaching group then received the
coaching intervention, whilst the control group received no coaching. Outcome data
were then collected for all participants at time 2. Between-subjects studies compared the
change in outcomes from time 1 to time 2 for both groups (e.g., Evers, Brouwers, & Tomic,
2006; Kochanowski et al., 2010; Taie, 2011). In within-subjects studies, all participants
received coaching and outcomes were recorded before and after the coaching. Within-
subjects studies examined the change in outcomes from time 1 to time 2 (e.g., Luthans &
Peterson, 2003; Olivero et al., 1997; Toegel & Nicholson, 2005).
We also coded for classification of outcome in accordance with the model outlined
earlier, and summarized in Table 1: Outcome measures were classified as affective (e.g.,
job satisfaction; Luthans & Peterson, 2003) (10 studies), skill-based (e.g., competency
skills; Taie, 2011) (10 studies), or results (e.g., productivity; Olivero et al., 1997) (three
studies). All three studies within the results category measured individual-level rather than
team-level or organizational-level results. Note that some studies utilized multiple
outcome measures falling within different outcome categories. Further, we coded for
whether coaching was accompanied by multisource feedback. Studies were classified as
either utilizing multisource feedback as part of the coaching process (e.g., Smither et al.,
2003) or coaching where multisource feedback was not used (e.g., Bright & Crockett,
2012). Studies that utilized multisource feedback solely as an outcome measure and not
part of the coaching process were included in the latter category as the details of the
multisource feedback were not disclosed to the coachee (e.g., Cerni, Curtis, & Colmar,
2010). We coded the coach as either external to the organization (e.g., a consultant as a
coach; Grant, Green, & Rynsaardt, 2010) or internal to the organization (e.g., Gyllensten &
Palmer, 2005). In the instances where an internal coach was used, the coach did not have
line management responsibility for the coachee. Our coding for coaching format classified
coaching as either face-to-face (e.g., Kines et al., 2010) coaching or ‘blended coaching
format. Blended coaching format was the category created for any format not solely face-
to-face. Studies were grouped in this way due to the small number of studies present that
used a format other than traditional face-to-face. Five studies utilized a combination of
telephone with face-to-face coaching (Finn, 2007; Grant et al., 2009; Kochanowski et al.,
2010; Moen & Skaalvik, 2009; Toegel & Nicholson, 2005), and one study used a
combination of telephone, face-to-face, and email coaching (Bozer & Sarros, 2012).
Finally, we coded for the number of coaching sessions (mean =5.56; median =6.00;
SD =3.18; range =9) and the longevity, in weeks, of the coaching intervention
(mean =18.80; median =12.00; SD =13.85; range =44). We also coded for the
duration of each coaching session; however, we did not explore this variable as Table 2
shows the duration of coaching sessions was relatively invariant.
Coding accuracy and inter-rater agreement
All studies were coded independently by two coders. The first was the first author, and the
second, a doctoral student with experience of meta-analytic techniques (who was briefed
on the coding procedure, and provided with the coding scheme and instructions). No
discrepancies between coders were encountered.
Meta-analytic procedure
The meta-analysis relied on the widely used Hunter and Schmidt (1990, 2004) approach: A
random effects model that accounts for sampling bias and measurement error. We
14 Rebecca J. Jones et al.
calculated sample-weighted effect sizes and corrected for reliability of dependent
variables. Given that we were interested in the treatment effects of coaching, we
converted all effect sizes obtained from the primary studies to r, conducted a meta-analysis
on r, and then converted the final results to d(Hunter & Schmidt, 2004). Missing artefact
values (i.e., reliability of dependent variables) were estimated by inserting mean
values across the studies where information was not given or could not be obtained
from the authors after contacting them, as recommended by Hunter and Schmidt (2004).
Objective performance data were not corrected for unreliability because it has been
frequently argued that measures based on objective performance data are unbiased
(Riketta, 2005), and also as no procedure is currently available to correct for unreliability
of such measures.
Additionally, we report the 90% confidence intervals (90% CI) of the sample-weighted
effect size d, and the 80% credibility intervals (80% CV) of the corrected population d
statistic d. Confidence intervals estimate variability in the sample-weighted effect size that
is due to sampling error, whereas credibility intervals estimate variability in the individual
correlations across studies that are due to the moderator variables (Whitener, 1990). If the
90% confidence interval of the sample-weighted effect size does not include zero, we can
be 95% confident that the sample-weighted effect size is different from zero. Confidence
intervals can also be used to test whether two estimates differ from each other; two
estimates are considered different when their confidence intervals are non-overlapping.
If the 80% credibility interval of the corrected population effect size is large and
includes zero, it indicates that there is considerable variation across studies and
moderators are likely operating. To further corroborate that moderators are present, we
assessed whether sampling error and error of measurement accounted for more than 75%
of the variance between studies in the primary estimates (Hunter & Schmidt, 1990). To do
this, we report the percentage of variance accounted for in the corrected population
effect size by sampling and measurement error (% VE). Moderators are assumed to be
operating when sampling and measurement error account for <75% of the variance. The
majority of the moderators in our study are categorical moderators (only the number of
coaching sessions and longevity of the intervention were continuous moderators). The
categorical moderators were computed using Hunter and Schmidt (1990, 2004) subgroup
analyses techniques by conducting separate meta-analyses at each of the specified
moderator level. To examine whether there is significant difference between the mean
corrected effect sizes of sublevels of the hypothesized moderator variable, we compared
their confidence intervals as discussed above. To test the continuous moderators, we
conducted weighted least squares (WLS) regression as suggested by Steel and Kammeyer-
Mueller (2002). Unlike subgroup analysis of moderators as suggested by Hunter and
Schmidt (2004), this approach avoids artificial categorization of continuous moderator
variables. For the WLS regression, we have regressed the uncorrected correlations of
overall coaching effectiveness in SPSS on each moderator variable using the inverse square
root of the sampling error for each correlation as the weighting factor (as specified by Steel
& Kammeyer-Mueller, 2002) to see whether the moderator explained variance in the
uncorrected correlations of overall coaching effectiveness.
Results
Table 2 presents an overview of the coaching effectiveness studies included in our
analysis. We report our results in two sections. Firstly, we report overall coaching
Effectiveness of workplace coaching 15
effectiveness and with respect to different outcome criteria. This is followed by
exploration of the impact of moderator variables.
1
Criterion effects of coaching
Coaching had a positive effect on all outcomes (supporting hypothesis 1). As can be seen
in Table 3, none of the 90% CI included zero and coaching had a positive effect on overall
outcomes (d=0.36, 90% CI [0.16, 0.50]).
We distinguished between affective, skill-based, and individual-level results outcomes
in our analyses. Table 3 suggests that coaching had positive effects on affective outcomes
(d=0.51, 90% CI [0.17, 0.78]), skill-based outcomes (d=0.28, 90% CI [0.07, 0.44]), and
individual-level results outcomes (d=1.24, 90% CI [0.88, 1.47]). The non-overlapping
confidence intervals of these three outcomes suggest that coaching has a stronger effect
on individual-level results outcomes than on affective and skill-based outcomes. There are
no differences with regard to affective and skill-based outcomes.
The low amount of variance accounted for by artefacts, and the large credibility
intervals around the effects of coaching on overall outcomes (17.68%, 80% CV [0.16,
0.97]) suggest that moderating variables are operating.
Moderators of coaching effectiveness
Research design
Most of the studies within our sample were between-subjects design (k=14, n=2,109).
A small group of studies used a within-subjects design (k=3, n=158). Coaching had a
positive effect on outcomes for both types of research design. Table 3 suggests that
coaching had a greater effect on outcomes for within-subjects (d=0.57) compared to
between-subjects design (d=0.35). However, the 90% CI were overlapping ([0.43, 0.62];
[0.12, 0.51]), which suggests that the two effects are not different; therefore, research
design does not appear to moderate the effects of coaching on outcomes (therefore,
hypothesis 2 was not supported).
Multisource feedback
We examined the effects of whether the coaching included multisource feedback as part
of the coaching process. Table 3 suggests that coaching had a positive effect on outcomes
for both groups; however, this effect was greater on outcomes when coaching was
provided without multisource feedback (d=0.88 vs. d=0.21). The non-overlapping
confidence intervals suggest that coaching has a stronger effect when it is provided
without multisource feedback ([0.40, 1.29]; [0.12, 0.26]); therefore, hypothesis 3 was not
supported.
1
An anonymous reviewer of an earlier draft of our paper rightly noted that one study (Smither et al., 2003) had a markedly high
sample size compared to others in our meta-analysis. Based on the idea that there is a trade-off between weighting individual
effect sizes by their sample size and individual effect sizes obtained from very large samples overly influencing the weighted
average effect size, it has been suggested to limit the Nof any primary study to 500, and to substitute any sample size with a value
larger than that with 500 (Riketta, 2005). When we applied this modification, the effect sizes for the analyses that included the
Smither et al. study increased slightly. However, we observed no other changes, and our conclusions regarding our hypotheses
were unaffected. Parsimoniously, we therefore report the meta-analytic results with the original sample size for the Smither et al.
study.
16 Rebecca J. Jones et al.
Table 3. Meta-analytic results
Variable kn d
90% CI
dSD
d
% Var. acc. for
80% CV
Lower Upper Lower Upper
Overall effectiveness 17 2,267 0.33 0.16 0.50 0.36 0.42 17.68 0.16 0.97
Affective outcomes 10 592 0.46 0.17 0.78 0.51 0.55 22.84 0.15 1.39
Skill-based outcomes 10 1,784 0.26 0.07 0.44 0.28 0.35 19.02 0.16 0.76
Individual-level results outcomes 3 116 1.15 0.88 1.47 1.24 0.00 100.00 1.25 1.25
Research design
Overall outcomes between-subjects 14 2,109 0.31 0.12 0.51 0.35 0.44 14.88 0.20 0.99
Overall outcomes within-subjects 3 158 0.53 0.43 0.62 0.57 0.00 100.00 0.56 0.56
Multisource feedback (MSF)
Overall outcomes MSF not used 9 569 0.80 0.40 1.29 0.88 0.82 12.53 0.00 2.73
Overall outcomes MSF used 7 1,620 0.19 0.12 0.26 0.21 0.00 100.00 0.20 0.20
Format of coaching
Overall outcomes face-to-face coaching 8 1,691 0.27 0.06 0.48 0.29 0.36 15.49 0.16 0.80
Overall outcomes blended coaching 6 274 0.25 0.09 0.43 0.28 0.00 100.00 0.24 0.24
Type of coach
Overall outcomes external coach 13 1,958 0.18 0.11 0.26 0.20 0.00 100.00 0.20 0.20
Overall outcomes internal coach 3 182 1.27 0.65 2.36 1.40 0.89 14.23 0.54 3.81
Note.k=number of studies; n=number of respondents; d=sample-weighted mean effect size; 90% CI =90% confidence interval of the d;d=corrected
population dstatistic; SD
d
=standard deviation of the corrected population dstatistic; % var. acc. for =percentage of variance attributed to sampling error and
artefact corrections; 80% CV =80% credibility interval of the d.
Effectiveness of workplace coaching 17
Format of coaching
We compared the effects of coaching provided in the face-to-face format with blended
formats. Table 3 shows that both effect sizes were positive and neither coaching format
demonstrated stronger criterion effects; the two effects on outcomes are similar and their
90% CI are overlapping (d=0.29, [0.06, 0.48] vs. d=0.28 [0.09, 0.43]; therefore,
hypothesis 4 was not supported).
Type of coach
We examined effects for coaches that were employed internally by the organization, and
compared with effects for external consultant coaches. Table 3 shows that the effects of
coaching on outcomes were weaker when the coach is external to the organization
(d=0.20 vs. d=1.40) and that the 90% CI were non-overlapping ([0.11, 0.26]; [0.65,
2.36]). This suggests that contrary to our prediction, the effects of coaching on outcomes
were weaker for external coaches in comparison with internal coaches (therefore,
hypothesis 5 was not supported).
Coaching schedule
We tested whether the longevity in weeks of the coaching intervention and number of
coaching sessions moderated overall coaching effectiveness. As longevity of the
coaching intervention and number of coaching sessions might have a decreasingly
positive effect on coaching effectiveness, we tested for both linear and curvilinear
effects. To test for linear effects, we entered the moderator variable as predictor
variable, and to test for curvilinear effects, we entered the moderator variable and the
squared term of the moderator variable as predictor variables. None of the effects
were significant (linear effect of longevity in weeks of the coaching intervention:
B=.01, SE =0.00, ns, R
2
=.14; curvilinear effect of longevity in weeks of the
coaching intervention: B=.00, SE =0.00, ns, R
2
=.18; linear effect of number of
coaching sessions: B=.01, SE =0.02, ns, R
2
=.01; curvilinear effect of number of
coaching sessions: B=.01, SE =0.01, ns, R
2
=.07). Therefore, neither longevity in
weeks of the coaching intervention nor number of coaching sessions moderated
overall coaching effectiveness.
Discussion
In the present study, we reported results of a meta-analysis to synthesize the existing
research on coaching effectiveness at work in order to understand the impact that
coaching has on a variety of workplace outcomes. We examined outcome criteria
classified on a framework modelled on the learning, training, and development
literature and tested whether particular techniques or tools of coaching moderated its
effectiveness. Our analyses demonstrated that for all outcomes, coaching had a
positive impact. Effect sizes nevertheless varied for different types of outcome
criteria, and based on some specific applied method features of coaching.
Collectively, our findings have important implications for research and practice of
coaching.
18 Rebecca J. Jones et al.
Criterion effects of coaching
To align our analyses with literatures on training and development, and HRM, we
proposed a criterion framework for the outcomes of coaching. We hypothesized that
coaching would have an overall positive impact on all outcome criteria, specifically in our
meta-analyses for affective, skill-based, and individual-level results outcomes. We found
that in the combined analyses of all 17 studies, coaching demonstrated a positive impact
on outcome criteria (d=0.36). Within this finding, there was variation for different types
of outcome criteria ranging from 0.28 to 1.24. These effect sizes appear to be comparable
to those obtained for other types of organizational interventions. For example, in their
meta-analysis of the training effectiveness literature, Arthur et al. (2003) obtained effect
sizes ranging from 0.60 to 0.63, whereas Powell and Yalcin (2010) found a smaller effect
size of 0.24 for managerial training interventions. Looking at wider interventions, findings
from Arthur et al. (2005), Smither et al.’s (2005) meta-analysis of multisource feedback
on performance reported much smaller effect sizes ranging from 0.05 to 0.15. Therefore,
compared to the impact of a popular intervention such as multisource feedback, coaching
appears to have larger and more consistent positive effects on outcome criteria.
Interestingly, the largest effect size in our study (1.24) was observed for individual-
level results outcomes, a key organizational focus representing translation of learning
through to performance benefits. Evidence that coaching has a significantly positive
impact on individual-level results in particular indicates that businesses can expect
positive performance and impact improvements from investment in coaching. By
contrast, Powell and Yalcin (2010) reported the smallest effects for results criteria in their
meta-analysis of managerial training interventions explai ning their findings with reference
to potential issues in training transfer, leading to a smaller impact of training on results
outcomes. We earlier described how coaching encourages development activities that are
personalized to individual need, and carried out in day-to-day work. These may therefore
serve to promote development that is directly relevant to the workplace, and is therefore
more straightforward for the coachee to implement in their performance behaviour.
These processes may promote transfer of learning to work activity resulting in improved
performance results, a proposition that appears to be supported in our findings,
representing a potential advantage of coaching over other forms of training.
We did not find moderation of the criterion effects of coaching by research design,
contrary to our hypothesis 2, and the results of Theeboom et al. (2014). Although the
effect size for within-subjects designs was higher than for between-subjects designs, the
difference was non-significant. We must conclude therefore that whilst there is some
evidence that research design may influence criterion effect sizes in studies of coaching,
the specific nature or importance of those effects remains to be confirmed.
Practice moderators of coaching criterion effects
Coaches often employ different practice factors in the form of techniques or tools into
their coaching approaches, and we tested the moderating effects of some of these in our
analyses. Firstly, our analyses revealed that when controlling for moderation effects of
these practice factors, the positive effects of coaching were maintained. Moreover, we did
not find significant moderation by the use of face-to-face compared to blended coaching.
This finding, although contrary to our original prediction, is consistent with findings from
the field of e-mentoring (de Janasz & Godshalk, 2013; Kyrgidou and Petridou (2013) who
demonstrated that e-mentoring has a positive impact on academic and workplace
outcomes. This finding has positive implications for the practice of coaching. One of the
Effectiveness of workplace coaching 19
main advantages of providing coaching in alternative formats such as telephone or e-mail
is the efficiencies in terms of cost and time commitment. Our finding that both face-to-face
and blended coaching were effective provides some justification for applying blended
formats in order to extend its accessibility to a wider audience. Notwithstanding this
point, our data do not permit us to draw conclusions about the effectiveness of e-coaching
(i.e., the use of technology such as internet or telephone to conduct coaching) alone. Only
one study used solely e-coaching (in which coaching was conducted exclusively by
telephone), so we were unable to compute a meta-analytic effect. Future research on the
effectiveness of e-coaching is therefore clearly warranted.
Our analysis showed that there was no significant moderation of outcomes by the
number of coaching sessions or the longevity of the coaching intervention, consistent
with the previous findings of Theeboom et al. (2014). Our tests for curvilinear effects also
indicated that there is not a plateauing of the impact of coaching (by which additional
sessions or weeks of intervention would make an impact up until a certain point, after
which more coaching would cease to result in imp roved impact). Taken together, our data
indicate that even short-term coaching has a beneficial impact. These findings once again
have positive implications for the practice of coaching as they suggest that shorter and
potentially more cost effective coaching interventions are likely to be effective. However,
like previous studies (e.g., Theeboom et al., 2014), we caution that fut ure research should
qualify this finding by factoring in the severity of the presenting employee development
issues at the outset of coaching. Some employee development issues may require a greater
number of sessions, and a longer term coaching intervention than others. Data analysed in
this study did not permit this possibility to be tested.
Two significant moderator variables were identified in our meta-analyses: Use of
multisource feedback, and type of coach. In both cases, the results ran counter to our
hypotheses.
We hypothesized that coaching combined with multisource feedback would have a
greater effect on outcomes. However, our findings showed that coaching without
multisource feedback actually had a significantly stronger positive impact on outcomes.
This finding may possibly be explained by previous research findings on the impact of
feedback (including multisource feedback) on performance. For example, in their meta-
analysis of the effects of performance feedback, Kluger and DeNisi (1996) reported that
whilst on average feedback interventions resulted in higher performance, over a third of
the studies included in their analyses actually reported that feedback resulted in lower
performance. They concluded that their findings were meaningful, and could not be
explained by sampling error, feedback sign or existing theory, but speculated that
attentional processes may help to explain the negative impact of feedback on
performance. In the context of coaching, feedback (especially negative feedback)
received by the coachee in the coaching session may divert attention so that the coachee
becomes pre-occupied with the content of the feedback. This could leave insufficient
attentional resources to engage in the subsequent coaching process, limiting the positive
benefits of the session. An additional factor may be the content of the multisource
feedback. Such instruments are often focused on leadership behaviour, which may be
rather distal from the development objectives of the coachee. Collectively, these
potentially negative mechanisms associated with feedback and its content, may explain
why in our meta-analyses, we observed weaker performance benefits when multisource
feedback was combined with coaching.
We also hypothesized that external coaches would have a greater impact on outcomes
as they would provide an external perspective, unrestricted by the constraints of the
20 Rebecca J. Jones et al.
employing organization, and more consistent with contemporary boundaryless models of
work and careers. This was not confirmed in our findings, which rather showed that
although coaching by both internal and external coaches was beneficial for learning and
performance, the effects of coaching by internal coaches had a stronger effect compared
to external coaches. This is an interesting finding given the growing scale of the coaching
industry, which is strongly based around a model of contracted external (e.g., consulting)
coaches. Some potential explanations as to why internal coaches appear to be more
effective than external coaches are provided by Strumpf (2002), who questions the
assumption that bringing in an external coach is necessarily the best option for
organizations. Strumpf suggests that the choice to use either an internal or external coach
is dependent on a number of factors. These factors include a cultural bias and readiness, as
some organizations prefer to use ‘homegrown’ solutions versus those generated by
external consultants and a strong, strategically placed head of human resources who may
provide an excellent role model for internal coaches and consequently increase the
credibility of an internal coach. A further potential explanation is that internal coaches
inevitably have a better understanding of the organization’s culture and climate and may
therefore be better placed to enable the coachee to be more productive in their specific
workplace (i.e., by setting goals in such a way that organization-specific barriers or
facilitators to their achievement are realistically discussed, addressed and incorporated
into development). Our earlier arguments that an internal perspective would be less
critical for coaching as compared to mentoring, for example, are not borne out in the data
we analysed. Our interpretations here should be viewed appropriately cautiously given
the relatively low number of studies using internal coaches.
Implications for research and future directions
Our study represents an important advance in the evidence base for the effectiveness of
coaching in organizations. To consider the implications of our findings for future research,
we highlight three themes emerging from our analyses: (1) criterion effects measured in
primary research on coaching; (2) practice methodology in studies of coaching; (3)
theoretical explication of the processes of coaching.
Considering first the criterion effects of coaching, we propose that our framework of
criterion effects could be used by researchers to organize more clearly the criteria that are
measured in coaching evaluating studies. We presented some methods of measurement
for each of the criteria we include in our framework, which could guide researchers in
choosing measurement methods. Our framework also highlighted gaps in the literature
for certain kinds of outcome criteria. Specifically, none of our included studies examined
cognitive, or team or organizational-level results outcome criteria, areas where further
studies are clearly warranted. Moreover, future research might examine how the relative
impact of coaching on different kinds of criteria, and compare this with other forms of
learning and development intervention (e.g., training).
Second, we acknowledged earlier that our selection of practice moderators was
somewhat governed by those factors that were described and operationalized in the
studies we examined. This observation speaks to a broader limitation of many studies of
coaching effectiveness, namely a lack of detail in the descriptions of coaching
interventions employed. Failing to completely describe coaching techniques and
approaches employed in empirical studies prevents later classification in meta-analyses
such as ours. We therefore encourage greater thoroughness on the part of researchers in
this area to specify precisely the nature and format of coaching employed in empirical
Effectiveness of workplace coaching 21
studies. Such specification should include description of who provided coaching, to
whom, in what format, for how long, over how many individual sessions, using which
coaching approaches or models, and including which (if any) tools or techniques.
Greater level of detail in the specification of coaching undertaken in empirical
studies is also essential for the development of theory and understanding of the
processes of coaching. Like Theeboom et al. (2014), and echoing similar observations
for all training and development intervention literatures (Ford et al., 2010), we strongly
feel that there is a need for the development of theory concerning why, how and in
what ways coaching leads to the positive effects we reported in this study. We earlier
argued that potential processes that are common features of coaching are goal-setting
(Locke & Latham, 2002), encouragement of experiential learning (Kolb, 1984), and
setting of development activities that are completed in day-to-day work activity.
Coaching may therefore be considered to be a high-fidelity form of training and
development intervention (e.g., Baldwin & Ford, 1988). However, it remains impossible
to test these or other processes in meta-analyses because individual studies do not
consistently describe, for example, if objectives or goals were set, what kind of
development or learning activities were recommended, or how they were formulated.
There are of course methodological challenges to adequately describing multiple
sessions with multiple clients, but failure to address these will continue to hold back
development of the coaching literature.
With regard to future research directions, the implications of these observations are
twofold. First, there is a need for experimental studies that manipulate the features of
coaching to examine directly the impact of particular coaching processes. Theoretical and
conceptual development should clearly accompany or precede such research. Second, all
empirical studies of coaching should adequately describe in detail any particular general
processes that applied to the coaching sessions under study.
Applied implications for organizations and coaches
Our study has a number of implications for practitioners and coaches in organizations.
Firstly, our meta-analysis demonstrated that coaching had a positive effect on all outcome
criteria we examined, providing an evidence base from which practitioners can draw
confidence.
Second, our proposed framework of outcome criteria from coaching provides
researchers and organizations with a method of categorizing the types of outcomes that
can be expected from coaching. These can be applied in evaluation studies by
practitioners, or by organizations to examine the impact of coaching.
Finally, our findings are informative for decisions about using particular tools and
coaching techniques. Although our results show that overall, coaching appears to be
effective irrespective of the format of the coaching and the longevity of the coaching
intervention (including number of sessions), practitioners and organizations should
consider carefully the use of multisource feedback, and the engagement of external
coaches, both of which resulted in smaller positive effects of coaching. If multisource
feedback is used, practitioners should review and apply evidence in the literature about
the determinants of effective use of feedback. When engaging external coaches,
organizations could ensure that a thorough familiarization process is undertaken to enable
coaches to have a full and complete understanding of the organizational context of
employee learning and performance.
22 Rebecca J. Jones et al.
Limitations and strengths
There are a number of limitations of our study. First, with respect to the coding of data, due
to incomplete reporting of sample characteristics and coaching variables, a number of the
coded variables had to be listed as either unspecified or, in the case of reliability data,
estimated. Although estimation from means is consistent with recommendations for
replacing other forms of missing data (e.g., Hunter & Schmidt, 1990), such replacements
are less satisfactory than reported data. In some cases, lack of reporting in research articles
meant that we did not have enough studies in each group to fully analyse moderators. In
addition, as we comment on earlier, incomplete reporting meant that the moderators we
were able to explore were limited to those included in the primary studies.
Second, due to the relatively nascent nature of coaching research, our meta-analysis
included a relatively small number of studies. Whilst the number of studies included in our
analyses is similar to some other meta-analyses in work and organizational psychology
(e.g., Riketta, 2008), some caution is warranted in interpreting and generalizing from our
results, which invite replication as the number of research studies in this area grows.
Alongside these limitations, our study has a number of significant strengths. Ours is the
first systematic examination of the effectiveness of coaching to exclusively focus on
coaching in organizations, marking an important advance in the literature on coaching at
work. The positive findings prompt future development of the coaching literature, and
coaching practices. Moreover, we align our analyses of coaching outcomes with existing
taxonomies of outcomes from learning, training, and development, making our findings
easy to view alongside these literatures. Our examination of moderators is particularly
informative for practising coaches to understand the impact of particular tools and
techniques of coaching, enabling them to make informed choices about their work.
Conclusion and final comments
At the outset of this study, we asked whether workplace coaching was effective in terms of
delivering individual learning and development, and improvements in performance and
results for organizations. Our meta-analysis has made significant steps in addressing the
lack of systematic scientific evidence about the benefits of coaching for organizations. Our
findings suggest that the answer to our question is yes, and our analyses indicated that
coaching resulted in a number of key positive effects for learning and performance
outcomes in the studies we examined. Our study gives support to the further
development of coaching research and practice, providing evidence of the potential
utility of coaching at work.
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Effectiveness of workplace coaching 29
... Other research has shown that workplace-related online coaching to improve mental health can also be successful (25)(26)(27) and increase productivity (25). A meta-analysis of Jones, Woods, & Guillaume (28) found no significant differences in organizational outcomes (cognitive, skill-based and affective outcome criteria) between online and face-to-face coaching in the workplace. In contrast, to our knowledge, no research exists so far that directly compared online and face-to-face coaching aiming to improve employees' mental health in a single study. ...
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Introduction: Online formats provide promising and low-threshold options for mental health coaching. However, research on online mental health interventions compared to traditional face-to-face interventions remains scarce. In the present study, the established prevention tool “Teacher Groupcoaching Program” (TGP) was applied in both the original face-to-face setting as well as online. TGP focuses on promoting mental health in teachers by strengthening relational skills using the Balint group technique. This technique roots back to a psychoanalytic approach to explore the emotional aspects of (stress inducing) professional relationships. The current study aimed at comparing the satisfaction with and effectiveness of TGP between both settings. Method: The sample consisted of 104 teachers who voluntarily chose between face-to-face (n = 51) and online (n = 53) setting. In a pre-posttest design, participants completed questionnaires before and after the intervention. Additionally participant’s satisfaction with the program was assessed during and after TGP. Results: Intervention effects did not differ significantly in terms of mental health, general life satisfaction and emotional distancing between TGP online and faceto- face. In line with previous research, there was a pre-posttest improvement for mental distress and the ability to distance oneself for both groups, which did not differ significantly between face-to-face and online setting. Satisfaction with the program was rated high in both settings, suggesting similar acceptance. Discussion: Although, the absence of an effect is not the evidence of equality of the groups, the present study highlights the potential of online admissions of mental health interventions as possible alternatives and additions to traditional face-to-face programs, especially when in-person meetings are not feasible. Specifically, it shows evidence that the Balint group technique can also be applied successfully by trained experts in the online setting.
... Unlike conventional self-awareness methods that may focus primarily on introspective exercises, the 'Decontaminated Self-Awareness' approach actively addresses and minimizes the influence of external biases and social conditioning, promoting a more authentic and individualized form of self-reflection. This approach aligns with recent studies that call for more personalized and context-sensitive coaching interventions (Jones et al., 2016), bridging the gap between theoretical frameworks and practical application. ...
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Background: Self-awareness is a critical component of personal development, influencing emotional regulation, decision-making, interpersonal relationships, and overall well-being. Traditional self-awareness practices often overlook the impact of external biases and social conditioning on an individual's authentic self-perception. The 'Decontaminated Self-Awareness' approach emerges as a novel methodology aimed at eliminating these external influences to facilitate a purer form of self-understanding. Objective: This study investigates the effectiveness of guided self-awareness coaching using the 'Decontaminated Self-Awareness' approach in enhancing individuals' well-being across professional, social, and personal domains. It also examines whether guided coaching yields greater benefits than self-directed learning and explores the universality of the approach across different demographic groups. Methods: A total of 400 participants were assigned to either a 300-person experimental group receiving guided self-awareness coaching or a 100-person control group engaging in self-directed self-awareness exploration. The experiment spanned seven weeks and included a pre-and post-intervention assessments focused on areas of emotional regulation, decision-making clarity, interpersonal relationships, and goal alignment. In addition to quantitative data, qualitative data were collected through participant testimonials and observations. Statistical analyses were conducted using paired samples t-tests and descriptive statistics to evaluate the hypotheses. Results: The experimental group demonstrated high improvements (≥20% increase in scores) across all measured domains, significantly outperforming the control group, which showed only slight improvements (1-9% increase). Participants attributed their personal growth to the 3 self-awareness coaching session. The session used the novel 'Decontaminated Self-Awareness' approach, which focuses on eliminating external biases and uncovering the participants' authentic selves. The results highlight the effectiveness of such an approach. No significant differences were found across age or demographic groups, indicating the approach's universal applicability. Conclusion: Guided self-awareness coaching using the 'Decontaminated Self-Awareness' methodology significantly enhances individuals' well-being in emotional, cognitive, and social domains. The approach proves more effective than self-directed methods and is universally beneficial across diverse populations. These findings suggest that integrating guided self-awareness coaching into personal development programs can facilitate personal growth and offer a valuable tool for individuals seeking meaningful personal transformation.
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Doctoral degree programs in Counselor Education and Supervision are intended to prepare graduates to be leaders and advocates in the profession. As such, Leadership and Advocacy is designated as one of the five core areas outlining the roles and responsibilities of being a counselor educator. Understanding the CACREP leadership standards and how this may intersect with your developing leadership framework is important as a counselor educator in training, and as a new CES professional who may one day become an administrator. This chapter focuses on understanding leadership from a liberation paradigm, learning the CACREP leadership standards, wellness and self-care for leaders, and leader development models.
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Objectives: Cognitive behavioural techniques have been the mainstay of psychological treatment for many psychologists in clinical practice. However, there is little known in relation to the efficacy of cognitive behavioural techniques for performance enhancement within a non-clinical setting, such as those found in organisational environments. The present study examined the effects of a cognitive behavioural based executive coaching intervention for a finance sales executive. Design: A within subject, ABAB single case design was utilised in this study. Methods: The participant was a 30-year-old Australian male, employed as a full-time finance sales executive. Each phase of the single case design had a duration of three weeks. Follow-up measures were taken at six months (week 36) and at 18 months (week 88) after the conclusion of the intervention. Results: It was shown that a cognitive behavioural executive coaching programme enhanced a 30-year-old Australian male finance executive’s sales performance, core self-evaluation, and global self-ratings of performance following his participation in an executive coaching intervention. Conclusions: The present study suggests that executive coaches should consider incorporating cognitive behavioural techniques into their coaching programmes. Further research into executive coaching models, approaches and outcomes, is needed, particularly by academics within the field of organisational psychology.
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Objectives The coaching relationship has been described as the catalyst for change. This study explores the coaching relationship by comparing the working alliance and the ‘real relationship’ – the undistorted and authentic experience of the other – in participants in skills coaching and transformational coaching. Design A 2 (coaching condition) x 2 (time) factorial design was used. Method Staff from community psychiatric recovery services were trained in a new service delivery approach (Collaborative Recovery Model), followed by coaching from internal coaches once per month to enhance implementation of the training. All trained staff were invited to participate in the research. Forty coachees met the requirements for inclusion in the study (>=3 coaching sessions in six months). Coaches completed a coaching alliance measure after each session. Coachees completed measures of working alliance and real relationship after six months of coaching. Results Analyses indicated that the coaching relationship is stronger after receiving transformational coaching, from both coachees’ and coaches’ perspectives. Relationships developed over time in transformational coaching, but not with skills coaching. Conclusions The results provide preliminary evidence that transformational coaching encourages the development of stronger coaching relationships. Future research should examine the effect of coaching approach on the outcomes of coaching.
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Objectives: Findings from a study exploring the links between leadership development coaching and performance are reported in this paper. Design: The study adopted a mixed-method approach. The participants were drawn from an opportunity sample of 36 senior managers who took part in a leadership development programme in a metropolitan borough council. Surveys were used to assess the impact of coaching on performance before, during and after several one-to-one coaching sessions. Semi-structured interviews were also undertaken with 10 coachees at the end of the coaching. Methods: Surveys assessed individual and organisational benefits of coaching, including interpersonal relationship and task accomplishment skills. Semi-structured interviews focused on the impact of coaching on individual and organisational performance, together with its impact on the organisational client base: the public. Results: There was a difference in leadership skills in the pre- and post-survey results. Both the quantitative and qualitative results indicate improved individual and organisational performance. The qualitative data also illustrate a positive impact on the organisational client base: the public. Conclusions: Coaching impacts positively on individual and organisational performance. It enhances well being and reduces stress as well as helping coachees to move towards a more transformational style of leadership. Despite methodological difficulties in evaluating the impact of coaching, further well designed evaluation research is required if the true impact of coaching on different aspects of performance is to be demonstrated.
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Objectives: This paper describes a preliminary attempt to evaluate executive coaching for 10 members who are on a High Potential Development Scheme within the Ministry of Defence (MoD). Design: A multi-method approach was taken which comprised the use of questionnaires to survey scheme member’s perceptions, a Return on Investment (ROI) study and a follow-up of members to determine their success in gaining promotion. Results: The analysis showed that all 10 who had been coached rated their experience positively. All rated their own progress within the Development Scheme as High and in particular they perceived it was their leadership skills that had benefited. A preliminary ROI calculation also indicated that the benefits exceeded the costs. Other benefits included promotion, broader leadership skills, and skills transfer within the MoD. Conclusions: The results indicate that within the context of the Development Scheme coaching provides a potential financial ROI. The findings also show that coaching impacts positively on scheme members such that they are highly committed to demonstrating and exhibiting leadership behaviours and that there is some evidence of a broader impact on the Department as a whole with generalised skills transfer.