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Coaching: An International Journal of
Theory, Research and Practice
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The power of coaching: a meta-analytic
investigation
Shirley C. Sonesha, Chris W. Coultasb, Christina N. Lacerenzac,
Shannon L. Marlowc, Lauren E. Benishekd & Eduardo Salasc
a Institute for Simulation & Training, University of Central Florida,
Orlando, FL, USA
b Leadership Worth Following, LLC, Irving, TX, USA
c Department of Psychology, Rice University, Houston, TX, USA
d Armstrong Institute for Patient Safety and Quality, Johns Hopkins
University School of Medicine, Baltimore, MD, USA
Published online: 25 Aug 2015.
To cite this article: Shirley C. Sonesh, Chris W. Coultas, Christina N. Lacerenza, Shannon L.
Marlow, Lauren E. Benishek & Eduardo Salas (2015): The power of coaching: a meta-analytic
investigation, Coaching: An International Journal of Theory, Research and Practice, DOI:
10.1080/17521882.2015.1071418
To link to this article: http://dx.doi.org/10.1080/17521882.2015.1071418
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The power of coaching: a meta-analytic investigation
Shirley C. Sonesh
a
*, Chris W. Coultas
b
, Christina N. Lacerenza
c
,
Shannon L. Marlow
c
, Lauren E. Benishek
d
and Eduardo Salas
c
a
Institute for Simulation & Training, University of Central Florida, Orlando, FL, USA;
b
Leadership Worth Following, LLC, Irving, TX, USA;
c
Department of Psychology, Rice
University, Houston, TX, USA;
d
Armstrong Institute for Patient Safety and Quality, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
(Received 12 March 2015; accepted 29 June 2015)
Coaching is defined as a one-to-one relationship in which the coach and coachee
work together to identify and achieve organisationally, professionally, and
personally beneficial developmental goals. However, it is often unclear what the
relative effects of coaching are on specific coaching outcomes. We adopt meta-
analytic techniques to investigate the predictive power of coaching on coach–
coachee relationship outcomes, and coachee goal-attainment outcomes. Our
findings suggest that coaching has stronger effects on eliciting relationship
outcomes with the coachee than goal-attainment outcomes. Moreover, of the
goal-attainment outcomes, coaching has the strongest effect on behavioural
changes as opposed to attitudinal changes. Sample type, study design,
background of the coach, and number of coaching sessions all emerged as
significant moderators. Implications of these findings are discussed.
Keywords: coaching; executive coaching; working alliance; coach–coachee
relationship; goal attainment
Practice points
.The current paper is relevant to a broad spectrum of practice areas as the studies
included in the meta-analysis represent coaching relationships in multiple indus-
tries and contexts (e.g. MBA and executive coaches).
.Our paper departs from the reliance on specific coaching techniques as the expla-
natory mechanism behind coaching effectiveness. It explores the relative effects
of general coaching, characteristics of the coach, the coachee, and the coaching
sessions on both relationship and goal-attainment outcomes, which has never
been meta-analytically investigated. Moreover, it explores the effect of relation-
ship outcomes on goal-attainment outcomes. This serves as a necessary first step
towards determining the role of the coach–coachee relationship as a mechanism
through which coaching works.
.Tangible implications for practitioners include the following: practitioners need
to foster the development of a healthy, social relationship with their coachees; if
attitudinal outcomes are the goal of the coaching relationship, practitioners need
to work harder to achieve these outcomes as they are harder to develop in
© 2015 Taylor & Francis
*Corresponding author. Email: ssonesh@ist.ucf.edu
Coaching: An International Journal of Theory, Research and Practice, 2015
http://dx.doi.org/10.1080/17521882.2015.1071418
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comparison to behavioural outcomes; practitioners need to keep in mind the
type of coachee they are coaching –coaches should collect longer term goal-
attainment information for executive coachees in comparison to student
coachees.
The power of coaching: a meta-analytic investigation
Executive coaching has been described as a ‘catalyst for personal growth and corpor-
ate change’(Axsmith, 2004, p. 1). In addition to indirectly engendering organisational
outcomes, coaching enables business leaders to become self-aware and obtain a deeper
understanding of the effects of their language and actions (Sherman & Freas, 2004).
Executive coaching is formally defined as a ‘one-on-one relationship between a pro-
fessional coach and an executive (coachee) for the purpose of enhancing coachee’s be-
havioral change through self-awareness and learning, and thus ultimately for the
success of individual and organization’(Joo, 2005, p. 468). Executive coaching has
impacted the corporate world in a positive way. The International Coaching Federa-
tion (2009) demonstrated that 70% of coachees report an improvement in job perform-
ance, 72% in communication skills, and 61% in business management. Furthermore,
86% report a positive return on investment (ROI) and 96% indicate that they would
repeat the coaching process. Grant, Curtayne, and Burton (2009) conducted a ran-
domised controlled study and found that coaching resulted in increases in goal attain-
ment, resilience, and workplace well-being, and decreases in depression and stress.
Researchers also argue that executive coaching is an ‘effective method of leadership
development’(Kombarakaran, Yang, Baker, & Fernandes, 2008, p. 78), and a
recent meta-analysis examining the role of coaching on five individual level coachee
outcomes provides promising evidence that coaching is an effective intervention in
organisations (Theeboom, Beersma, & van Vianen, 2013).
Coaching entails a collaborative process of learning and behavioural change,
making key constructs from the teams, training, learning, and motivational/behav-
ioural change literature bases particularly salient. Similarities between coaching and
training suggest parallel process-based models involving (1) a facilitator (trainer, train-
ing system, or coach), (2) content or techniques, (3) a learner, trainee, or coachee, (4)
an organisational context, and (5) proximal and distal outcomes.
Despite evidence that coaching works (Theeboom et al., 2013) and provides ROI
(De Meuse, Dai, & Lee, 2009), there is much debate about the specific competencies,
qualifications, and conceptualisations of effective coaching (Peterson, 2011). More-
over, academic and practitioner reviews have noted that despite the popularity of
coaching in industry, peer-reviewed empirical work is scarce (Bono, Purvanova,
Towler, & Peterson, 2009; Feldman & Lankau, 2005). Although coaching research
has increased and improved, a significant portion remains uncontrolled, anecdotal,
and lacking theoretical foundation (Dagley, 2006; Grant, 2013).
The coaching relationship is argued to be the primary explanatory mechanism under-
girding the differential effectiveness of different coaching engagements (Hooijberg &
Lane, 2009; Joo, 2005; Kowalski & Casper, 2007;McNally&Lukens,2006), yet the
specific interpersonal (e.g. trust, rapport, and chemistry) and intrapersonal variables
(e.g. information processing and motivation changes) that precede successful coaching
outcomes have, until recently, been relatively unexplored (Feldman & Lankau, 2005).
2S.C. Sonesh et al.
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Nonetheless, recent works have responded to calls (Boyatzis, Smith, & Van Oosten, 2015;
Kampa-Kokesch & Anderson, 2001) for more research examining the effects of the
coaching relationship on coaching results (Boyce, Jackson, & Neal, 2010; Gessnitzer &
Kauffeld, 2015; Ianiro & Kauffeld, 2014; Ianiro, Lehmann-Willenbrock, & Kauffeld,
2014; Ianiro, Schermuly, & Kauffeld, 2013; Passmore & Fillery-Travis, 2011). The
importance of the coaching relationship raises a fundamental question –why? What is
it about the coaching relationship that facilitates desirable coaching outcomes? Is it
increased motivation or deeper commitment to goal setting? Or might there be a more
complex phenomenon underlying the coaching-outcome connection? Fillery-Travis
and Lane (2006) suggested that it is of paramount importance to address these questions
and determinewhich mechanisms can foster effective coaching outcomes. To achieve this
aim, it is necessary to understand the relative effects of coaching on emergent relationship
phenomena between a coach and coachee.
Ultimately, the objectives of this meta-analysis are threefold. The first objective is
to systematically explore the relative effects of coaching on relationship outcomes that
emerge between the coach and coachee, and what specific relationship outcomes
coaching elicits. The second objective is to explore the relative effects of coaching
on goal-oriented coaching outcomes (e.g. behavioural change, attitudinal change,
and cognitive change), and which types of coaching outcomes are most strongly
affected by coaching. The third objective is to meta-analytically explore the relation-
ship between the coach–coachee relationship and coachee goal-oriented outcomes.
Goal-attainment coachee outcomes
According to goal setting theory, goals improve performance by ‘directing energy and
attention, mobilising energy expenditure or effort, prolonging effort over time (persist-
ence) and motivating the individual to develop relevant strategies for goal attainment’
(Locke, Shaw, Saari, & Latham, 1981, p. 145). As such, goal setting is a critical part of
developmental initiatives (Salas & Cannon-Bowers, 2001). In fact, executive coaching
is a goal-focused process (Grant, 2006). Goal attainment is achieved when coachee
performance is goal appropriate so has become a fundamental dependent variable
in coaching research (e.g. Spence, 2007). Empirical evidence supports the notion
that coaching leads to goal attainment (e.g. Grant et al., 2009). For instance, Grant
(2008) conducted a repeated-measures experiment and found coaching increases
goal attainment, cognitive hardiness, and insight, and reduces anxiety.
Relationship outcomes
Coaching shares construct space with mentoring and therapy/counselling (Feldman &
Lankau, 2005) in that the facilitator-recipient relationship is thought to be a key deter-
minant of intervention effectiveness by eliciting changes in the client (Gassmann &
Grawe, 2006; McKenna & Davis, 2009). The relationship between therapist and
patient (or coach and coachee) is evaluated along a number of dimensions such as
respect, openness, and affect (DiGiuseppe, Leaf, & Linscott, 1993; Horvath &
Symonds, 1991; Saltzman, Luetgert, Roth, Creaser, & Howard, 1976). Relationship
forms the medium and context by which specific coaching inputs (e.g. feedback, chal-
lenging questions) are delivered (Baron & Morin, 2009; Horvath & Symonds, 1991).
Coaching: An International Journal of Theory, Research and Practice 3
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Executive coaching is characterised by a series of one-on-one conversations, or ses-
sions, between a coach and a coachee (de Haan, 2012). During these sessions, a quality
relationship based on trust, support, and safety is established, thereby enabling the
coachee to better learn from and reflect on their experiences (de Haan, 2012; Joo,
2005). The establishment of a relationship between a coach and coachee leads to
desired outcomes (Baron & Morin, 2009; Horvath & Symonds, 1991). In fact, some
researchers argue that the quality of the coaching relationship represents ‘not just a
critical success factor, but the critical success factor in successful coaching outcomes’
(Bluckert, 2005, p. 336). Once a quality relationship is built, the coachee is more apt to
take risks associated with positive change, learning, and development (Bluckert, 2005).
The link between coaching relationships and outcomes has been identified both in
theory (Kemp, 2008) and empirical research (e.g. de Haan, Duckworth, Birch, &
Jones, 2013; Woerkom, 2010). De Haan et al. (2013) investigated 156 coach–
coachee pairs and found the coaching relationship to be a significant mediator
between inputs (i.e. self-efficacy) and desired outcomes. Similarly, Boyce et al.
(2010) demonstrated that the coaching relationship variables of trust, rapport, and
commitment led to the attainment of targeted coaching outcomes. Moreover, execu-
tives’perceptions of outcomes were significantly related to perceptions of relationship
factors. Empirical results from a similar dyadic field study conducted by Baron and
Morin (2009) also suggest that the executive coaching relationship mediates the
relationship between the presence of coaching and desired outcomes. In another
study, 84% of coachees identified the quality of their relationship with their coach
as the critical ingredient to their success (McGovern et al., 2001). In addition, multiple
reviews outlining the state of the field (MacKie, 2007; Passmore & Fillery-Travis, 2011;
Passmore & Gibbes, 2007) identify the impact of coaching relationships on goal
attainment. As such, it is critical to examine the ways coaching impacts desired out-
comes and the coaching relationship.
A testable model of coaching and its outcomes
By extracting core principles and key variables from the existing coaching literature
and conceptually similar fields, we have developed a conceptual model for understand-
ing the effectiveness of executive coaching interventions. Coaching involves pro-
fessional development (Van Velsor & Leslie, 2001) and is related to the learning,
teaching, and training disciplines. Naturally, there are key differences between these
domains (Feldman & Lankau, 2005), but the Baldwin and Ford (1988) training effec-
tiveness and transfer model offers a helpful starting point to guide the structure of the
proposed coaching effectiveness model. The major distinction between coaching and
training (and what makes coaching akin to therapy) is the centrality of the coach–
coachee relationship to coaching outcomes (Feldman & Lankau, 2005; McKenna &
Davis, 2009). For this reason, we place the coaching relationship as the most proximal
coaching outcome, dynamically emerging from an interaction of coach and coachee
inputs, coaching techniques, and organisational variables. This emergent coaching
relationship serves to influence the development of further proximal and distal out-
comes (e.g. goal setting, goal attainment). The idea that coaching is essentially a
matter of input-process-output is neither new nor creative –indeed, Ely et al. (2010)
reviewed the coaching literature and have identified many of these same concepts.
However, the explicit modelling and parsing apart of coaching inputs, relationship
4S.C. Sonesh et al.
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variables, and immediate coaching outcomes constitutes a contribution to the coach-
ing literature because it allows for the testing of causal linkages within any given
coaching intervention. Existing models of coaching tend to link coaching inputs to
coaching outcomes without discriminating the theoretical ‘distance’between inputs
and outcomes or suggesting causal mediating variables (Carey, Philippon, & Cum-
mings, 2011; Grant, 2007; Joo, 2005; Mackie, 2007). As a result, our model is more
methodologically sound (Ajzen, 1996), and will provide a scalable foundation for
future research to be developed and tested.
In this meta-analysis, we explore the current state of the empirical literature on
executive coaching and test the meta-analytic links between key constructs within
our proposed model (see Figure 1). Specifically, we explore the direct effect of coach-
ing on relationship outcomes and coachee goal-attainment outcomes, as well as the
role that the coach–coachee relationship plays on influencing goal-attainment out-
comes. By theoretically linking coaching with proximal relationship outcomes and
distal goal-attainment and coachee outcomes, we provide a more unified understand-
ing of the predictive power of coaching, as opposed to solely exploring the goal-attain-
ment outcomes of interest.
Moderators of coaching effectiveness
This meta-analysis sought to determine whether study characteristics impact coaching
outcomes. Several researchers have criticised the use of data collected within labora-
tories for lacking ‘relevance for understanding the “real world”’ (Falk & Heckman,
2009, p. 535) due to unrepresentative student samples and unrealistic settings. Field
Figure 1. A model of the predictive power of coaching.
Coaching: An International Journal of Theory, Research and Practice 5
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studies using executive coachee samples may show lower effect sizes due to the diffi-
culty associated with collecting results-oriented outcomes over time, whereas the
control afforded by laboratory studies may produce stronger results. In response, we
took an exploratory approach to determine whether study sample moderates the
relationship between coach behaviours and coaching outcomes, and coach–coachee
relationship and coaching outcomes. Study design is another factor that may influence
results (Theeboom et al., 2013). We explored whether primary studies utilising
repeated-measures designs (i.e. single group, pretest vs. posttest), independent
groups designs (i.e. control vs. treatment groups), a combination of both designs
(i.e. treatment vs. control group, pretest vs. posttest), or correlational designs influence
the direction or magnitude of the examined relationships.
Broadly speaking, researchers and practitioners understand what works in coach-
ing, but debate specifics, such as the importance of professional certification and the
advantages of coach professional background (e.g. psychology vs. business) (Bono
et al., 2009). In response, we investigate whether the role of the coach and their
level of expertise affect the coach–coachee relationship and coaching outcomes, as
some studies argue that more experience is not necessarily better (Solomon,
DiMarco, Ohlson, & Reece, 1998). Finally, because Theeboom et al.’s(2013) meta-
analysis did not, we explore whether the number of coaching sessions moderates the
examined relationships.
As the empirical research on executive coaching and coaching in general is
nascent, this meta-analysis seeks to provide an initial foundation upon which future
empirical investigations and practical advancements in coaching can be based. By elu-
cidating the relative effects that coaching has on relationship outcomes and perform-
ance-oriented goal-attainment outcomes and the specific coaching behaviours and
techniques that contribute to those outcomes, we can begin to better understand
which mechanisms and coaching characteristics contribute to targeted effects. While
previous meta-analyses have examined whether coaching generally works (Theeboom
et al., 2013), this is the first to differentiate between relationship and behavioural out-
comes, while determining the relative effects of coaching. These aims further the field’s
understanding regarding the how and why of executive coaching effectiveness.
Methods
Search methodology
We searched the following databases: PsycINFO, Business Source Premier, Human
Resources abstracts, and PsycARTICLES, from January 2000 to December 2014,
using the keywords ‘coaching’,‘leadership coaching’, and ‘business coaching’com-
bined with ‘correlation’,‘survey’,‘sample’,or‘experiment’. Additionally, we manually
searched the International Journal of Evidence Based Coaching & Mentoring for rel-
evant primary studies. Our search returned 2123 articles. After removing duplicates
and non-coaching articles, 874 remained.
Inclusion/exclusion criteria
To be included in the meta-analysis, primary studies must have examined leadership,
business, or executive coaching. Studies that explored life, managerial, or peer coach-
ing were excluded. Moreover, studies needed to empirically investigate the
6S.C. Sonesh et al.
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relationships in our model and report data appropriate for conversion to a common
metric, Cohen’sd. Twenty-four studies totalling 26 independent samples met these cri-
teria and were included in the meta-analysis (see Figure 2).
Coding procedures
Three trained individuals coded a subset of the articles together until 100% inter-rater
reliability was achieved. Two individuals coded each remaining article to ensure
quality and accuracy. Coding discrepancies were resolved via discussion. Each of
the included studies was coded across eight categories: (1) study design (e.g.
repeated-measures [pre-posttest design]; independent groups [treatment vs. control
groups]; independent groups and repeated measures; correlational), (2) coach’s back-
ground (e.g. psychology; non-psychology), (3) coach’s level of expertise, which we
dichotomised due to the infrequency of primary studies reporting this information
(e.g. novice, expert), (4) the number of coaching sessions provided to the coachee,
(5) sample type (e.g. undergraduates, MBA students, executive coachees, non-execu-
tive coachees, and coaches), (6) the behaviours/techniques employed in coaching
(e.g. goal setting, 360 feedback, challenging questions, behavioural observation, role
play, etc.), (7) relationship variable outcomes (e.g. trust, credibility, working alliance,
information sharing, rapport, communication, conflict, openness, and psychological
safety), and (8) goal-oriented coaching outcomes and conceptualisations of coaching
effectiveness which we categorised into (a) generic behavioural change (e.g. improved
job performance, technical skills, leadership skills, impact and influence), (b) work-
related attitude change (e.g. motivation, self-efficacy, motivation to transfer coached
skills), (c) personal-related attitude change (e.g. reduced stress, happiness), (d) career
Figure 2. Search strategy used for the inclusion of studies in the meta-analysis.
Coaching: An International Journal of Theory, Research and Practice 7
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outcomes (e.g. promotion, career satisfaction), (e) interpersonal/socio-emotional out-
comes (e.g. improved relations with others), (f) cognitive outcomes (e.g. self-awareness,
strategic thinking, emotional intelligence), and (g) satisfaction with coaching. Finally,
we coded for sample size, measure reliability, and effect size metrics.
Analysis
Original article effect sizes were transformed to a repeated-measures Cohen’sd, which
represents the standardised difference between pre- and post-coaching outcomes,
using Hedges and Olkin’s(1985) approach to meta-analysis. This conservative tech-
nique allows for statistical corrections of artifactual sources of variance (Borenstein,
Hedges, Higgins, & Rothstein, 2009). To avoid overestimating the population effect
size given our small sample, we calculated Hedges’gfrom Cohen’sd. Hedges’gis
still interpreted as the mean difference expressed in standard deviation units but
applies a simple correction to avoid overestimates (Hedges, 1981). A random effects
model was used to conduct the meta-analysis and all effect sizes were weighted by
the reciprocal of the sampling variances (Hedges & Olkin, 1985). Qtests were con-
ducted in order to test for homogeneity (i.e. evaluated on a chi-square distribution
with k–1 degrees of freedom; Hedges, 1982).
When relationships between coach–coachee relationships and coachee outcomes
were reported, we focused on the mean corrected correlations and the confidence inter-
vals around the mean. This approach followed Hunter and Schmidt’s(2004) guidelines
so all correlations were corrected for attenuation in the predictor and criterion vari-
ables. The software used for the analysis was comprehensive meta-analysis developed
by Borenstein, Hedges, Higgins, and Rothstein (2005).
Results
Table 1 reports the results of the meta-analyses examining the influence of coaching on
several coaching outcomes and relationship outcomes. The first objective of our meta-
analysis was to determine the impact of coaching interventions on outcomes that
emerge from the coach–coachee relationship. To assess this, we examined the
impact of coaching on overall relationship outcomes, which was significant (g=
0.32, 95% CI [0.27, 0.38]), as indicated by the exclusion of 0 in the 95% confidence
interval. To examine more specific coaching relationship outcomes, we assessed the
influence of coaching on the generic coach–coachee relationship (g= 0.33, 95% CI
[0.17, 0.49]), which was significant. However, the effect of coaching on working alli-
ance was not significant (g= 0.40, 95% CI [−.02, 0.80]), as indicated by the inclusion
of 0 in the 95% confidence interval. In summary, our findings indicate that coaching
positively and significantly influences the coach–coachee relationship.
The second objective of this meta-analysis was to assess the impact of coaching on
goal-oriented coaching outcomes as well as to examine which outcomes are most
strongly affected. In the aim of addressing this goal, we assessed the impact of coach-
ing on overall coachee outcomes. The effect size was significant (g= 0.10, 95% CI
[0.10, 0.11]); however, coaching had a significantly larger effect on relationship out-
comes in comparison to coachee outcomes, as evidenced by the non-overlapping
95% confidence intervals (Ng, Eby, Sorensen, & Feldman, 2005). Examining more
granular outcomes within this category, coaching had a significant impact on
8S.C. Sonesh et al.
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Table 1. Meta-analytic results.
Variable kN dHedge’sgSE %Var
95% CI
LL UL Q
Relationship outcomes 6 580 0.324 0.321 0.000 0.000 0.267 0.376 2286.04*
Generic coach–coachee relationship 3 385 0.332 0.330 0.081 0.007 0.171 0.489 342.774*
Working alliance 3 195 0.399 0.391 0.208 0.043 −0.017 0.799 287.675*
Coachee outcomes 40 3756 0.108 0.100 0.002 0.000 0.100 0.107 172,709.93*
Goal attainment 6 216 0.218 0.206 0.055 0.003 0.099 0.314 1869.635*
Behavioural change 10 2350 0.192 0.188 0.020 0.000 0.149 0.227 48,430.793*
Work-related attitude change 11 524 0.186 0.175 0.016 0.000 0.145 0.206 10,541.589*
Personal attitude change 5 149 0.077 0.072 0.003 0.000 0.066 0.078 23,563.984*
Improved relations with others 3 84 0.124 0.115 0.062 0.004 −0.006 0.237 3069.875*
Overall satisfaction with coaching 2 173 0.399 0.391 0.124 0.015 0.149 0.634 48.063*
Cognitive change 2 153 0.220 0.217 0.175 0.031 −0.125 0.560 299.384*
Task performance 1 107 0.368 0.365 0.017 0.000 0.332 0.399 0.000
Organisation outcomes 1 52 0.284 0.280 0.009 0.000 0.262 0.298 0.000
Notes: k, number of samples; N, sample size; d, Cohen’sdin a repeated-measures metric; SE, standard error; %Var, per cent of variance accounted for by sampling error; CI,
confidence interval; LL, lower limit; UL, upper limit; Q, chi-square test for the homogeneity of true correlations across studies.
*p< .001.
Coaching: An International Journal of Theory, Research and Practice 9
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general goal attainment (g= 0.21, 95% CI [0.10, 0.31]), behavioural change (g= 0.19,
95% CI [0.15, 0.23]), work-related attitude change (g= 0.18, 95% CI [0.15, 0.21]), and
personal attitude change (g= 0.07, 95% CI [0.07, 0.08]). Interestingly, coaching had a
significantly stronger impact on the majority of coachee outcomes as compared to per-
sonal attitude change, indicated by the non-overlapping 95% confidence intervals (Ng
et al., 2005). Findings also indicated a significant effect of coaching on overall satis-
faction with coaching (g= 0.39, 95% CI [0.15, 0.63]), although this result must be
interpreted with caution, given the associated low number of primary studies (indi-
cated by k) included in the analysis. The effect of coaching on improved relations
with others, most often the coachees’subordinates, was not significant (g= 0.12,
95% CI [−0.01, 0.24]). Additionally, coaching did not significantly improve cognitive
change outcomes (g= 0.22, 95% CI [−0.13, 0.56]), but this finding must also be inter-
preted with caution, given the small number of primary studies included in the analy-
sis. In summary, these findings demonstrate that coaching significantly impacts goal-
oriented coaching outcomes, fostering positive change.
In exploration of the third objective, the effect of the coach–coachee relationship on
coachee outcomes, mean corrected correlationswere examined. While based ononly two
studies, and therefore should be interpreted with caution, results suggest that the coach–
coachee relationship, working alliance in particular, does significantly correlate with
overall goal-attainment coachee outcomes (r= 0.463, CI [0.418, 0.445]) (see Table 3).
Sample type
To assess the moderating effect of sample type, additional analyses were conducted.
Table 2 summarises these analyses. The findings indicate that sample type was a sig-
nificant moderator of the effectiveness of coaching on goal-oriented coaching out-
comes. Specifically, overall goal-oriented coaching outcomes were more significantly
improved in undergraduate students (g= 1.00, 95% CI [0.38, 1.61]) than in either
executive coachees (g= 0.10, 95% CI [0.09, 0.11]) or non-academic, non-executive
coachees (g= 0.10, 95% CI [.10, .11]). There were not a sufficient number of
primary studies to warrant comparison across sample type for relationship outcomes.
Design type
Results of the design type moderator analysis suggest that the study design does mod-
erate the effect of coaching on coaching outcomes. However, the repeated-measures
confidence interval overlaps with the independent groups’confidence interval,
suggesting that there is not a significant difference between repeated measures or inde-
pendent groups designs. The number of primary studies was too low (k< 3) to examine
the moderating effect of design type on relationship and organisational outcomes.
Coach background
While there were not a sufficient number of primary studies to run comparative sub-
group analyses of coach background (i.e. psychology or non-psychology background)
on relationship outcomes, the results suggest that non-psychology coaches are effective
in eliciting positive relational outcomes (g= 0.284, 95% CI [0.082,0.504]). Results
suggest that coach background is a significant moderator of coachee outcomes,
such that a mix of psychology and non-psychology coaches are more effective
10 S.C. Sonesh et al.
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Table 2. Moderator analyses.
Moderator variable kN dHedge’sgSE %Var
95% CI
QLL UL
Sample type
Relationship outcomes 6 580 0.324 0.321 0.000 0.000 0.267 0.376 2286.04
Undergraduates 0 0 –––––– –
MBA students 0 0 –––––– –
Executive coachees 1 73 0.290 0.287 0.011 0.000 0.266 0.308 0.000
Non-executive coachees 0 –– – – – – – –
Coaches 0 –– – – – – – –
Both coaches and coachees 5 507 0.323 0.321 0.028 0.001 0.265 0.376 1808.443
Coachee outcomes 40 3756 0.108 0.100 0.002 0.000 0.100 0.107 172,709.93
Undergraduates 2 367 0.999 0.995 0.312 0.098 0.383 1.607 6.939
MBA students 0 0 –– –– – – –
Executive coachees 19 999 0.102 0.098 0.002 0.000 0.094 0.101 57,719.286
Non-executive coachees 14 2151 0.106 0.103 0.003 0.000 0.097 0.109 65,378.825
Coaches 0 0 ––––– –
Both coaches and coachees 5 239 0.255 0.250 0.056 0.003 0.141 0.360 852.137
Organisation outcomes 1 52 0.284 0.280 0.009 0.000 0.262 0.298 0.000
Undergraduates 0 ––––––– –
MBA students 1 52 0.284 0.280 0.009 0.000 0.262 0.298 0.000
Executive coaches 0 –– – – – – – –
Non-executive coachees 0 ––––––– –
Coaches
Both coaches and coachees 0 ––––––– –
Study design type
Relationship outcomes
Repeated measures 3 112 0.293 0.284 0.108 0.012 0.082 0.503 625.332
Independent groups 0 ––––––– –
(Continued)
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Table 2. Continued.
Moderator variable kN dHedge’sgSE %Var
95% CI
QLL UL
Correlational 1 156 0.617 0.614 0.048 0.002 0.522 0.711 0.00
Repeated measures and independent groups 0 ––––––– –
Coachee outcomes
Repeated measures 8 300 0.234 0.227 0.024 0.001 0.187 0.281 1700.383
Independent groups 4 570 0.53 0.527 0.143 0.020 0.249 0.810 313.844
Correlational 1 13 0.167 0.156 0.004 0.000 0.159 0.174 0.000
Repeated measures and independent groups 7 2031 0.128 0.124 0.008 0.000 0.112 0.144 61,483.597
Organisational outcomes
Repeated measures 0 ––––––– –
Independent groups 1 52 0.284 0.28 0.009 0.000 0.265 0.302 0.000
Correlational 0 ––––––– –
Repeated measures and independent groups 0 ––––––– –
Number of coaching sessions
Relationship outcomes
1–3 2 39 0.298 0.287 0.247 0.061 −0.186 0.783 143.869
4–60––––––– –
7–9 1 156 0.617 0.614 0.048 0.002 0.522 0.711 0.000
10–12 0 ––––––– –
13–15 0 ––––––– –
15+ 1 73 0.29 0.287 0.011 0.000 0.269 0.311 0.000
Coachee outcomes
1–3 4 404 0.17 0.169 0.024 0.001 0.122 0.217 879.092
4–6 6 718 0.099 0.097 0.004 0.000 0.091 0.107 117,170.666
7–9 1 38 1.84 1.802 0.446 0.199 0.965 2.715 0.000
10–12 0 ––––––– –
13–15 0 ––––––– –
15+ 2 200 1.407 1.392 1.401 1.962 −1.339 4.152 5.334
Organisational outcomes
1–30––––––– –
12 S.C. Sonesh et al.
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4–60––––––– –
7–90––––––– –
10–12 1 52 0.284 0.28 0.009 0.000 0.265 0.302 0.000
13–15 0 ––––––– –
15+ 0 ––––––– –
Coaches vocational background
Relationship outcomes
Psychology 0 ––––––– –
Non-psychology 3 112 0.293 0.284 0.108 0.012 0.082 0.503 625.332
Mix 0 ––––––– –
Coachee outcomes
Psychology 3 297 1.411 1.393 0.863 0.746 −0.281 3.104 27.7
Non-psychology 2 81 1.385 1.362 1.429 2.042 −1.416 4.186 5.537
Mix 3 1182 0.089 0.087 0.041 0.002 0.009 0.169 11,509.591
Organisational outcomes
Psychology 0 ––––––– –
Non-psychology 0 ––––––– –
Mix 1 52 0.284 0.28 0.009 0.000 0.265 0.302 0.000
Coaches expertise
Relationship outcomes
Novice 3 112 0.293 0.284 0.108 0.012 0.082 0.503 625.332
Expert 1 156 0.617 0.614 0.048 0.002 0.522 0.711 0.000
Mix of novice and expert 0 ––––––– –
Coachee outcomes
Novice 3 138 0.36 0.35 0.136 0.019 0.093 0.628 96.700
Expert 5 1507 0.148 0.147 0.028 0.001 0.093 0.202 166.079
Mix of novice and expert 1 11 0.066 0.061 0.001 0.000 0.065 0.067 0.000
Organisational outcomes
Novice 0 ––––––– –
Expert 1 52 0.284 0.28 0.009 0.000 0.265 0.302 0.00
Mix of novice and expert 0 ––––––– –
Notes: k, number of samples; N, sample size; d, Cohen’sdin a repeated-measures metric; SE, standard error; %Var, per cent of variance accounted for by sampling error; CI,
confidence interval; LL, lower limit; UL, upper limit; Q, chi-square test for the homogeneity of true correlations across studies.
Coaching: An International Journal of Theory, Research and Practice 13
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(g= 0.087, 95% CI [0.009, 0.169]), than coaches solely with a psychology (g= 1.393
95% CI [−0.281, 3.104]) or non-psychology background (g= 1.362, 95%CI [−1.416,
4.186]). There were not a sufficient number of primary studies to examine the moder-
ating effect of coach background on organisational outcomes.
Coach expertise
Sub-group analyses indicate that coach expertise is not a moderator of the relationship
between coaching and coachee outcomes. Novices (g= 0.136, 95% CI [.093, .628]) are
as effective as experts (g= 0.308, 95% CI [0.093, 0.202]) in achieving coachee goal-
attainment outcomes, as evidenced by overlapping confidence intervals that do not
cross zero. There was not a sufficient amount of primary studies to examine the mod-
erating effect of coach expertise on relationship outcomes or organisational outcomes.
Number of coaching sessions
Finally, there was a significant moderating effect of the number of coaching sessions
provided to coachees on coachee outcomes. Specifically, it was found that 1–3 coach-
ing sessions had a stronger effect on coachee outcomes (g= 0.169, 95% CI[0.122,
0.217]) than 4–6 coaching sessions (g= 0.097, 95% CI [0.091, 0.107]). Having 7–9
coaching sessions was superior (g= 0.446, 95% CI [0.965, 2.715]), but this finding
was based on only 1 primary study. There were not a sufficient number of studies to
examine the moderating effects of number of coaching sessions on relationship or
organisational outcomes.
Discussion
The main purpose of this study was to investigate the relative effects of coaching on
variables highly salient to how coaching effectiveness is conceptualised. We found
that coaching is an effective tool contributing to positive coach–coachee relationships
and that coaching is effective in improving coachee behaviours and attitudes.
Coaching had a significant positive effect on coachee behavioural change,
suggesting that coaching is effective in improving coachee leadership skills, job
performance, and skills development. Moreover, coaching significantly improved coa-
chee’s personal and work-related attitudes. These include improvement in coachee self-
efficacy, motivation to transfer coached skills to the job, stress reduction, and commit-
ment to the organisation. These attitudes are critical to goal-attainment and coachee
behavioural change, as research has shown that work-related attitudes such as self-
Table 3. Meta-analytic effect size between coach–coachee relationship and coachee outcomes.
IV DV kN r
Corr
r
% var
RM
95% CI
range
Relationship (working
alliance)
Coachee
outcomes
2 186 .432 .463 .783 .418 .445
Notes: k, number of samples; N, sample size; r, correlation; Corr r, corrected correlation; %Var, per cent of
variance accounted for by sampling error; 95% CI, confidence interval.
14 S.C. Sonesh et al.
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efficacy, commitment to the organisation, and satisfaction are strong predictors of
improved job performance (Bandura, 1997; Grant & Greene, 2004; Anderson, Kra-
jewski, Goffin, & Jackson, 2008).
Interestingly, cognitive outcomes (e.g. coachee self-awareness and strategic think-
ing) were not significantly improved by coaching. It is likely that this was not signifi-
cant because only two studies explored these outcomes. While generally not the
primary focus of coaching, cognitive outcomes are important in changing the ways
coachees approach their work and promote behavioural change, and ultimately con-
tribute to improved job performance, (Goleman, 2001; Sy, Tram, & O’Hara, 2006)
and even subordinate job performance (Moshavi, Brown, & Dodd, 2003). Similarly,
coachees’relationships with their colleagues and subordinates did not significantly
improve as a result of coaching, though this result should be interpreted with
caution as it is based on a low number of primary studies (k= 3). This highlights
the need for additional work exploring the impact of coaching on these outcomes in
order to obtain a deeper understanding of the effects of coaching.
Our findings also suggest that coaching is an effective developmental tool to
elicit positive coach–coachee relationship outcomes. In fact, of all the outcomes
examined in this meta-analysis, coaching had the strongest effect on relationship
outcomes. While working alliance was not significantly improved, it has long
been used in the field of psychotherapy, as it refers to the quality and strength of
the collaborative relationship between a client and his/her psychotherapist
(Bordin, 1979). In coaching relationships, relationship building is crucial as it con-
tributes to joint goal setting and greater engagement in working on coaching tasks.
It has been shown in previous work that working alliance plays a role in coaching
outcomes (Baron & Morin, 2009), and the findings of this meta-analysis show that
coaching does in fact elicit this bond between coach and coachee. Research suggests
that transformational coaches are more likely to elicit a strong working alliance
(Sun et al., 2013), but there was not enough evidence in the literature to meta-
analyse this effect. Nonetheless, the results suggest that the emergent relationship
between a coach and coachee may be an important mechanism through which
coaching goals are achieved. While the primary studies included in this meta-analy-
sis did not allow for a robust meta-analytic investigation of the effect of coaching
relationship on coaching outcomes, there is literature that supports this link
(Bennett, 2006; de Haan, 2008; Gessnitzer & Kauffeld, 2015; Gregory & Levy,
2010,2011; Gyllensten & Palmer, 2007; Ting & Riddle, 2006). As such, we
suggest that future research conduct a meta-analytic structural equation model
(SEM) analysis (Cheung & Chan, 2005) to more fully test the proposed conceptual
mediating model presented in this manuscript.
Coaches should adopt a person-centred approach (Rogers, 1951,1959,1961;
Barrett-Lennard, 1998) to coaching whereby the coach approaches the coachee with
the assumption that he/she is his/her own best expert and respects self-determination
(Grant, 2004). By doing so, the coach can build a positive relationship and simul-
taneously leverage the emergent relationship to facilitate the attainment of goal-
oriented coaching outcomes.
Another notable finding is that coachee behavioural change improvements were
found to be significantly larger than attitudinal changes. This is a promising finding con-
sidering that behavioural change is the most common objective of coaching engage-
ments. This evidence lends support for the continued use of and investment in
Coaching: An International Journal of Theory, Research and Practice 15
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coaching programmes at the academic and executive levels. However, because the
sample type was a significant moderator of coaching effectiveness, coaches should be
mindful of how and when they measure coaching effectiveness. Specifically, coachee
outcome effect sizes were significantly larger for undergraduate student samples than
executive coachee samples. This suggests that executive coaches might take longer to
behaviourally or attitudinally manifest their coaching outcomes than students who
often have more immediate opportunities to prove performance (e.g. exams). Moreover,
field samples are often operating in more dynamic environments riddled with potential
confounds (Luthans, Luthans, Hodgetts, & Luthans, 2001) which likely attenuated the
meta-analytic results for executive coachee samples. Executive coaches, as opposed to
academic coaches, may need to collect longer term goal attainment data to accurately
determine whether the coachee has attained his/her goals.
The results of the number of coaching sessions moderator analysis suggest that
more coaching sessions are not necessarily better for achieving coachee outcomes. It
seems likely that session quality is more important than quantity. The findings point
to a potential ‘sweet spot’or curvilinear relationship of coaching sessions, where
too many sessions might lead to burn-out and frustration, while too few may not be
sufficient to achieve goals. The most appropriate number of coaching sessions may
also depend on the complexity and difficulty of the coaching goals. Future research
should explore these questions using qualitative techniques to more fully capture
the optimal number of coaching sessions.
The results of the background and level of expertise of the coach moderator analy-
sis suggested that for coaching outcomes, it is not necessary to have an expert coach
but rather have one who has a good mix of both business and psychology backgrounds.
These findings address the raging debate (Bono et al., 2009; Brotman, Liberi, & Wasy-
lyshyn, 1998; Diedrich & Kilburg, 2001; Kampa-Kokesch & Anderson, 2001) over the
qualifications necessary to be a coach and speak to the merits of being balanced in the
way one approaches a coaching engagement.
Limitations and future research
While we found significant effects, the field of coaching continues to lack substantial
empirical research. Our meta-analysis explored the changes that coachees experience
as a result of a coaching intervention. While it provides an insight into the relative
effects of coaching, we were unable to explore specific relationship constructs (e.g.
emergence of trust; rapport; shared understanding) or specific goals due to a lack of
primary studies. Moreover, we were unable to explore the moderating effects of pro-
posed variables due to the low frequency with which primary articles report such infor-
mation. Consequently, research examining these questions should be conducted and
empirical work should be explicit in reporting the specific coaching behaviours
used, as well as the characteristics of the coaching sessions and the coach and
coachee themselves. This will enable more robust, systematic examinations to be con-
ducted, such as meta-analytic SEM (Cheung & Chan, 2005). Future studies should
seek to explore the question of what relational attributes are most important for pre-
dicting coachee goal-attainment outcomes. Specifically, the field of coaching would
benefit from work seeking to answer the following questions: (1) To what extent is
coaching effectiveness attributable to positive shifts in coachees’relational and psycho-
logical states? (2) What specific coach behaviours contribute to a strong positive
16 S.C. Sonesh et al.
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coach–coachee relationship? (3) What coach behaviours, strategies, and techniques
contribute to successful coaching engagements?
While our paper describes relationship outcomes as the most proximal outcome that
should ultimately predict goal-attainment coachee outcomes, due to a low number of
primary studies, we were unable to run a meta-analytic SEM to test this link. Future
research should leverage the process-based models (e.g. Baldwin & Ford, 1988),
which are more methodologically sound (Ajzen, 1996) than existing models of coach-
ing. Generally, most models of coaching link coaching inputs to coaching outcomes
without accounting for the theoretical ‘distance’between inputs and outcomes or
suggesting causal mediating variables (Carey, Phillippon, & Cummings, 2011; Grant,
2007; Joo, 2005; Mackie, 2007). Future work should seek to identify more mediating
mechanisms through which these relationships occur, enabling better understanding
of the conditions under which coaching fosters targeted outcomes.
Moreover, future work should continue to examine how proximal coaching
outcomes (e.g. working alliance) might contribute to or elicit more distal coaching
outcomes (e.g. coachee promotion). For example, many primary studies examined
self-efficacy, commitment to the organisation, and career satisfaction as their depen-
dent variables, while others looked at terminal outcomes like coachee promotion.
As the empirical research on coaching continues to grow, future work could leverage
meta-analytic SEM techniques (Cheung & Chan, 2005) to explore the relative fitof
models that explore the temporal nature of relationships between coach and
coachee behaviours, relational processes (e.g. trust, information sharing, and
working alliance), proximal attitudinal outcomes (e.g. commitment, self-efficacy,
and satisfaction), and distal behavioural (e.g. job performance and leadership
ability), organisational, and career-related outcomes (e.g. promotion). Other fruitful
areas for research include comparing different coaching techniques. For example,
assessing the effects of coachee psychological characteristics, and coach inputs such
as experience, background, and licensure would yield useful information with practical
implications. Furthermore, echoing other researchers (Bolch, 2001;MacKie,2014),
we emphasise several methodological issues that need to be addressed, such as the
lack of longitudinal investigations and the fact that most studies exclusively rely on
self-report data. There is much work left to be done to achieve a full understanding
of the coaching process and its effects, but the preliminary findings are promising.
Coaching should continue to be leveraged as a resource to promote various coachee
outcomes in a variety of industries, contexts, and settings.
Acknowledgements
The views expressed in this work are those of the authors and do not necessarily reflect the
organisations with which they are affiliated or their sponsoring institutions or agencies.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was supported by funding from the Society for Human Resource Management
(SHRM) Foundation [Contract number 162] to the University of Central Florida.
Coaching: An International Journal of Theory, Research and Practice 17
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Supplemental data
Supplemental data for this article can be accessed here.
Notes on contributors
Shirley Sonesh is an organisational psychologist and postdoctoral
research scientist at the Institute for Simulation and Training, at the Uni-
versity of Central Florida. Dr Sonesh obtained her doctorate in organis-
ational behaviour at the A.B. Freeman School of Business at Tulane
University. While at Tulane, Dr Sonesh’s research focused on expatriate
knowledge transfer in multi-national organisations. Currently, she con-
ducts coaching research, research investigating the effects of teamwork
and team-based training in the field of medicine, the effects of telemedi-
cine on teamwork and patient safety, among other healthcare related
initiatives. Shirley also consults organisations on how to improve train-
ing, teamwork, cultural change, and selection processes. Dr Sonesh has
co-authored a number of published articles in the fields of medical
team training, training evaluation, and simulation in healthcare. She
has been invited to a number of national and international conferences
to present her research related to these fields.
Chris Coultas graduated from the Universityof Central Florida (UCF) in
2014 with a Ph.D. in Industrial/Organisational Psychology. While at
UCF, Chris worked at the Institute for Simulation and Training, under
Dr Eduardo Salas, where he conducted research on teams, training,
culture, leadership, leadership development, and coaching. Chris has
published works in Small Groups Research and Consulting Psychology
Journal, as well as book chapters on training and leadership, and has pre-
sented at numerous conferences. Chris also has a Master’s in Industrial/
Organisational Psychology from UCF, as well as Bachelor of Science
degrees from Liberty University in Religion and Counseling Psychology.
In addition to providing consulting services to clients, Chris leverages his
expertise in research methods and data analysis to provide insights and
breakthrough interventions to proactively address current and future
client needs.
Christina N. Lacerenza is currently pursuing a doctoral degree in Indus-
trial/Organisational (I/O) Psychology at Rice University. Current projects
include identifying an optimal team composition for team performance,
identifying factors influencing training effectiveness, scale development
and validation, team training program development, and identifying
effective executive coaching behaviours. As an I/O Psychologist, Christi-
na’s mission is to utilise innovative techniques to improve the overall
effectiveness, performance, and well-being of individuals and teams
within firms.
18 S.C. Sonesh et al.
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Shannon L. Marlow is a doctoral student in the Industrial/Organisational
Psychology programme at Rice University. Shannon earned a B.S. in Psy-
chology with a minor in Statistics from the University of Central Florida
in 2013. Her research interests primarily include team processes, with a
particular focus on team training, virtual teams, and performance.
Lauren E. Benishek is an organisational psychologist and postdoctoral
research fellow in the Department of Anesthesiology and Critical Care
Medicine at the Johns Hopkins School of Medicine who holds an appoint-
ment with the Armstrong Institute for Patient Safety and Quality. Dr
Benishek’s stream of research focuses on workplace behaviour and inter-
ventions for improving patient safety and quality healthcare. Her special-
ties include teamwork culture, processes, and performance, individual and
team training development and evaluation, and enhancing training effec-
tiveness. At the time of publication, she has co-authored 10 peer reviewed
articles, 1 book chapter, 1 book, and 30 invited talks and conference pre-
sentations in these areas.
Eduardo Salas is a professor and Allyn R. & Gladys M. Cline Chair in
Psychology at Rice University. Previously he was trustee chair and pro-
fessor of Psychology at the University of Central Florida. He also
holds an appointment as Program Director for Human Systems Inte-
gration Research Department at the Institute for Simulation & Training.
Dr Salas has co-authored over 300 journal articles and book chapters and
has co-edited 15 books. He is on/has been on the editorial boards of
Journal of Applied Psychology,Personnel Psychology,Military Psychol-
ogy,Interamerican Journal of Psychology,Applied Psychology: An Inter-
national Journal,International Journal of Aviation Psychology,Group
Dynamics, and Journal of Organizational Behavior and is past Editor of
Human Factors journal. His expertise includes helping organisations on
how to foster teamwork, design, and implement team training strategies,
facilitate training effectiveness, manage decision-making under stress,
develop performance measurement tools, and design learning environ-
ments. He is currently working on designing tools and techniques to mini-
mise human errors in aviation, law enforcement, and medical
environments. He has consulted to a variety of manufacturing, pharma-
ceutical laboratories, industrial and governmental organisations. Dr
Salas is a fellow of the American Psychological Association (SIOP and
Division 21), the Human Factors and Ergonomics Society. He received
his Ph.D. degree (1984) in industrial and organisational psychology
from Old Dominion University.
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