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Consulting Psychology Journal: Practice
and Research
FACILITATING SUCCESSFUL BEHAVIOR CHANGE: BEYOND
GOAL SETTING TO GOAL FLOURISHING
Kenneth Nowack
Online First Publication, April 17, 2017. http://dx.doi.org/10.1037/cpb0000088
CITATION
Nowack, K. (2017, April 17). FACILITATING SUCCESSFUL BEHAVIOR CHANGE: BEYOND GOAL
SETTING TO GOAL FLOURISHING. Consulting Psychology Journal: Practice and Research.
Advance online publication. http://dx.doi.org/10.1037/cpb0000088
FACILITATING SUCCESSFUL BEHAVIOR
CHANGE: BEYOND GOAL SETTING TO
GOAL FLOURISHING
Kenneth Nowack
Envisia Learning, Inc., Santa Monica, California
Most successful coaching engagements encourage clients to start, increase, decrease,
modify, or stop behaviors that contribute to their effectiveness and performance on the
job (Fogg, n.d.). Successfully sustaining new or altered behaviors over time until they
become a habit is even more difficult (Nowack, 2009). Goal intentions (e.g., “I want to
be a more participative and involvement-oriented leader”) have been found in a recent
meta-analysis to be a weak predictor of acquiring new habits and account for approxi-
mately 28% of the variance in successful behavior-change efforts (Gollwitzer &
Sheeran, 2006). Translating insight in coaching engagements to deliberate, varied, and
ongoing practice has been shown to be associated with long-term successful behavior
change (Nowack & Mashihi, 2012). This paper reviews current issues and best practices
in goal intentions, goal striving, and goal flourishing to maximize coaching success with
clients.
Keywords: goal striving, goal setting, implementation intentions, behavior change,
habits
Goal setting and the initiation of new behaviors and sustaining them over time is particularly
challenging for most individuals. However, we are all creatures of habit. In fact, on the basis of
experience-sampling diary studies using student and community samples, approximately 45% of
everyday behaviors tend to be repeated in the same location almost every day (Neal, Wood, &
Quinn, 2006; Wood & Rünger, 2016). It is surprising to note that people report a heterogeneous set
of actions that vary in habit strength each day, including diverse and established behaviors such as
exercise, eating, and daily activities (Wood, Quinn, & Kashy, 2002; Wood, Tam, & Guerrero, 2005).
This paper will attempt to summarize current evidence and practice behind goal intentions, goal
setting/planning processes, and goal striving resulting in successful creation of new habits (goal
flourishing) by addressing six important questions (see Figure 1). Initially, it will be useful to define
specific characteristics of coaching goals and then present important factors associated with goal
flourishing, including some common myths about goal striving and giving up/quitting goals.
Recent neuroscience research provides both a framework for understanding the resistance to
initiating new habits and the challenges around goal flourishing. For example, there appears to be
broad and meaningful individual differences in our motivation to try new behaviors, a willingness
to take risks, and a tendency to seek novel and intense experiences (Holmes, Hollinshead, Roffman,
Correspondence concerning this article should be addressed to Kenneth Nowack, Envisia Learning, Inc.,
2208 6th Street, Santa Monica, CA 90405. E-mail: ken@envisialearning.com
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Consulting Psychology Journal: Practice and Research © 2017 American Psychological Association
2017, Vol. 0, No. 999, 000– 000 1065-9293/17/$12.00 http://dx.doi.org/10.1037/cpb0000088
1
Smoller, & Buckner 2016). Using magnetic resonance imaging (MRI), Holmes et al. (2016)
measured the size of particular regions of the brain for each participant and measured self-reported
traits associated with sensation-seeking and impulsivity as well as alcohol, tobacco, and caffeine
usage. The strongest links occurred in brain areas related to the ability to regulate emotions and
behavior most strongly associated with the anterior cingulate and middle frontal gyrus. Changes in
those brain structures also significantly correlated with participants’ self-reported tendency to act on
impulse and with heightened use of alcohol, tobacco, or caffeine.
Current research suggests that availability and type of social support (Chiaburu, Van Dam, &
Hutchins, 2010; Martin, 2010; Orehek & Forest, 2016) as well as regulation of emotions are equal
to, or even more important than, cognitions in predicting both intention and initiation of new habits
(Lawton, Conner, & McEachan, 2009). These findings imply an important role for coaches in
considering the social-support climate of clients, helping them to manage their emotional reactions
and consequences for engaging in behavioral-change efforts as well as assessing “readiness to
change” stages that are associated with successful behavior change.
For example, one of the purposes of using 360-degree feedback in coaching interventions is to
provide information to coaches to illuminate strengths as well as potential areas for development
(Bracken, Rose, & Church, 2016; Nowack & Mashihi, 2012). Some negative reactions to such
feedback might actually be motivating for successful behavior change (Atwater & Brett, 2005), but
neuroscience research provides answers about why “underestimators” (whose self-ratings are more
critical than the ratings of their observers) or those who interpret the feedback as judgmental or
hurtful are disengaged and lack motivation to change behavior (Woo, Sims, Rupp, & Gibbons,
2008). In addition, interpersonal judgment and social evaluation tend to elicit strong stress reactions,
with cortisol levels in one’s system being elevated 50% longer when the stressor is interpersonal
versus impersonal (Dickerson & Kemeny, 2004). As a result, individuals who negatively interpret
feedback and experience emotional hurt, rejection, and pain tend to have both blunted motivation to
initiate behavior change and diminished readiness for creating implementation intentions that are
crucial for successful behavior change. Fortunately for practitioners, there are some individual-
change models that help optimize understanding, acceptance, and action that are based on feedback
to ensure successful behavior change.
Six Important Quesons about Goal Seng, Goal Striving, and Goal Flourishing
1. What are the key characteriscs of goals?
2. If goal intenons aren’t generally effecve to facilitate behavior change what works beer?
3. Goal striving: When are clients most movated?
4. How long does it take for new habits to form?
5. When should clients “hold” and when should they “fold” in goal striving?
6. Does pracce make perfect?
Figure 1. Six questions about goal setting.
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2 NOWACK
Building on the process models of feedback and change by Gregory, Levy, and Jeffers (2008),
Koroleva (2016), and London and Smither (2002), I have proposed a more specific individual
behavioral-change model that draws heavily on evidence-based research in the health-psychology
and behavioral-medicine literature (see Figure 2). The 3-E model of individual behavior change
(Enlighten, Encourage, and Enable; Nowack, 2009) represents a merging of recognized individual
behavioral-change theories and models, including the theory of planned behavior (Ajzen, 1991),
self-efficacy and social– cognitive theory (Bandura, 1977), the health-belief model (Becker, 1974),
the transtheoretical model of change (TTM; Prochaska & Velicer, 1997), and extension of the
elements of goal-setting theory and performance posited by Locke and Latham (2002). Each of these
theories and models should be useful to all coaches who are attempting to influence both insight/
awareness and successful behavior change with their clients.
Successful coaching engagements foster both self-efficacy and self-management of clients (Joo,
2005; Grover & Furnham, 2016). Self-management theorists agree upon two important components
that involve cognitive, emotional, and behavioral challenges in goal flourishing (i.e., the successful
adoption and targeted results of goal pursuits): goal setting and goal striving (Mann, De Ridder, &
Fujita, 2013). Goal setting (Fogg Behavior Grid; Fogg, 2012) typically involves two concepts—the
valence of behaviors (start, increase, decrease, stop, do differently) and frequency (one time,
sometime, and all of the time). Goal striving typically involves the implementation of actions and
behaviors related to goals that have been set, redefining goals during the pursuit, managing lapses
from distractions, and dealing with loss of energy or resources that interferes with successful
accomplishment. Although often temporal, there are situations in which reappraisal of goals often
follows perceived or real obstacles and challenges (e.g., if the goal is unrealistic or resources needed
to accomplish the goal change, such as for financial reasons).
Clients tend to initially identify goals (Koestner, Lekes, Powers, & Chicoine, 2002) in which
they have an intrinsic stake (“What is in it for me?”) and when they perceive what others expect or
desire of them (e.g., 360-degree-feedback results by one’s boss or direct reports to change specific
leadership practices). Self-determination theory (Deci & Ryan, 1985), readiness to change
(Prochaska & Velicer, 1997), the 3-E model of individual change (Nowack, 2009), and other related
models all suggest that a client’s level of motivation and self-efficacy is a critical predictor of
successful goal adoption, maintenance, and adherence over time.
Hierarchy of goals also shape what clients will focus on. For example, if a specific goal (e.g.,
deploying a stress-management technique such as mindfulness meditation) competes with another
goal (e.g., spending more time with one’s children after work) based on finances, time, or energy,
then clients are unlikely to maintain it over time (Riediger & Freund, 2004). Therefore, helping
clients to explore both inhibitors and promoters of goals would appear to be a useful exercise by
coaches to facilitate goal completion and success. In addition, research by Kruglanski and colleagues
(2002) suggests that when client goals have more than one payoff, clients are more likely to pursue
• Accurate
Insight
• Identifying
Signature
Strengths
• Ideal Self vs.
Real Self
Enlighten
• Motivation
• Self-Efficacy
• Skill Building
•Goal
Implementation
Encourage
• Practice Plans
• "Nudge"
Reminders
• Social Support
• Relapse
Prevention
• Evaluation
Enable
Figure 2. Enlighten, Encourage, and Enable individual change model.
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3BEYOND GOAL SETTING TO GOAL FLOURISHING
all of them because doing so maximizes the outcome with the same effort (e.g., soliciting and
accepting feedback from direct reports might simultaneously increase engagement of employees
while enhancing perceived agreeableness as a personality trait of the leader).
What Are the Key Characteristics of Goals?
There are several important characteristics that directly influence the goal pursuit that individuals
engage in (Koo & Fishbach, 2010). Some of the most important characteristics include difficulty
(e.g., easy vs. challenging), proximity of the end state (e.g., short term vs. long term), number of
goals to tackle at one time (e.g., single vs. multiple), type of goal (e.g., learning vs. performance),
and motivational mindset (e.g., avoidance vs. approach). Each of these five characteristics of goals
will be briefly described here.
Easy Goals Versus Challenging/Stretch Goals
Previous studies have traditionally emphasized that goals should not be overly ambitious as
exemplified by the SMART goal acronym, which suggests that goals should be specific, measurable,
attainable, realistic, and timely (Latham, 2003). However, current research suggests that challenging
goals lead to greater effort, focus, and persistence than moderately difficult or easy goals and that
SMART goals might not be very effective in fully operationalizing the complexity needed for
deliberate practice (Nowack, 2015). Such “big, hairy, audacious goals,” or BHAGs, help provide a
clear vision of what is to be measured and evaluated at the end of a large-scale behavior-change
effort (Collins, 1999).
It has also been suggested that people who perceived their goal as difficult to attain reported
higher positive emotion, an increase in job satisfaction, and perceptions of occupational success
(Latham & Locke, 2006). In fact, there is some evidence that difficult and unrealistic goals might
actually inspire, rather than interfere with, goal pursuit (Latham & Locke, 2013; Linde, Jeffrey,
Finch, Ng, & Rothman, 2004). Other research suggests that difficulty of a coaching goal does not
appear to impact how successful the coaching engagement actually is in terms of overall goal
attainment (Sonesh et al., 2015).
Consider the following implications for coaching: Some researchers argue that lowering the
difficulty of goals, rather than enhancing motivation, is the desired strategy for successful behavior
change (Fogg, 2012). In summary, encouraging clients to set challenging goals is more likely to
stimulate initial readiness to change. However, when faced with obstacles or challenges, reducing
barriers to achieving goal success by modifying their difficulty might be a good strategy to follow
for clients in coaching engagements (Fogg, 2012).
Short-Term Focus Versus Long-Term Focus
Goals are often distinguished by how far forward they project into the future. Schunk (2001)
suggests that short-term goals are achieved more quickly and result in higher motivation and better
self-regulation than more distant or long-term goals. Furthermore, research suggests that if long-
term goals must be established, subdividing or “chunking” them into more manageable tiny actions
or steps can produce greater benefits (i.e., goal attainment).
The time frame for completion needs to be reasonable for goals to be attained (Latham & Locke,
2006). However, individuals are more likely to maintain goals in the face of obstacles and challenges
when more time remained for goal pursuit than when less time remained (Schmidt & Deshon, 2007),
suggesting that for shorter-term goals, experiencing setbacks early will not necessarily lead to
extinction of the initial goal. In addition, people who wrote out their short-term goals, shared their
commitment to complete the goals with others, and communicated progress with others were
approximately 33% more successful than those who did not document their goals, share intent, and
communicate progress with others (Matthews, 2012). Finally, a single focus on the goal without
having a specific backup plan appears to be predictive of goal achievement given a longer time
frame to accomplish desired results (Shin & Milkman, 2016).
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4 NOWACK
Consider the following implications for coaching: For most coaching engagements, clients
should be encouraged to focus on specific and short-term goals and the underlying steps and
behaviors to facilitate progress and success. Building in tracking and monitoring systems (Harkin et
al., 2016; Webb, Joseph, Yardley, & Michie, 2010) and encouraging clients to share their intentions
with goal mentors might also be useful strategies to optimize successful achievement of both
short-term and long-term goals (Cole-Lewis & Kershaw, 2010; De Leon, Fuentes, & Cohen, 2014;
Fanning, Mullen, & McAuley, 2012; Mashihi & Nowack, 2013).
Single Goals Versus Multiple Goals
Behavior-change efforts are typically individualistic, based on a myriad of individual and environ-
mental factors, and tend to be progressive, regressive, or even static (Nowack, 2009). Mixed
evidence supports the argument that multiple simultaneous efforts (e.g., behaviors planned to
improve multiple competencies at the same time) tend to be equal or even more effective than
focusing on single goals because they reinforce quick benefits (Achtziger, Gollwitzer, & Sheeran,
2008; Hyman, Pavlik, Taylor, Goodrick, & Moye, 2007). On the other hand, several studies suggest
that focus on a single implementation intention might be superior to multiple goal intentions (Dalton
& Spiller, 2012). Additional research extends these findings by showing that formulating multiple
plans in the service of the same goal is also not beneficial (Verhoeven et al., 2013).
Consider the following implications for coaching: Individuals can accomplish more than one
goal at a time, assuming that these goals do not conflict with each other in some way (Locke &
Latham, 2002). As such, coaches should raise realistic concern about overall success when clients
express an interest in working simultaneously on multiple goals in their initial contracting agreement
or throughout the coaching engagement. For example, rather than making multiple implementation
intentions at once, a phased approach might be more successful. In this way, one new behavioral
goal or habit could be targeted with an implementation intention first, and only when the new desired
behavior has been reached, according to some metric of agreed-up improvement by the coach and
client, might a new goal be addressed.
Learning Goals Versus Performance Goals
An individual’s goal orientation and personality can accurately describe the goals that they choose
and the methods used to pursue those goals (DeShon & Gillespie, 2005). A performance versus
learning characteristic of goals (Elliott & Dweck, 1988) involves the achievement of a specific
standard (e.g., performance goal such as “lose 15 pounds”) as opposed to the development of a
specific skill (e.g., learning goal such as “acquiring the skill to practice mindfulness meditation”).
Instead of focusing on the end result, a learning goal focuses attention on the discovery of effective
strategies, skills, or techniques to attain and sustain desired results (Seijts, Latham, Tasa, & Latham,
2004). Latham and Locke (2013) argued that it is best to set a learning goal when an individual lacks
the ability to perform the task and to set a performance (outcome) goal when the person has the
ability to attain a desired level of performance.
When trying to accomplish a learning goal, the individual will learn to master all of the
necessary skills that are associated with acquiring that goal. In the process, he or she may ask for
feedback and reflect on progress to master whatever it takes to learn the new skill. On the other hand,
trying to attain a specific performance goal can place additional cognitive demands that could
interfere (e.g., choking) with goal accomplishment (e.g., Beilock, Carr, MacMahon, & Starkes,
2002).
Consider the following implications for coaching: Performance goals can be appropriate when
the necessary skills to perform a task are already mastered and the primary focus is to exert more
effort to reach a higher level of performance. Seijts, Latham, Tasa, and Latham (2004) found that
individuals with learning goals demonstrated the following advantages over those with performance
goals:
1. They took the time necessary to acquire the knowledge to effectively perform the task and
to analyze the task-relevant information that was available to them.
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5BEYOND GOAL SETTING TO GOAL FLOURISHING
2. They showed an increase in self-efficacy as a result of the discovery of appropriate
strategies for task mastery. Other research supports the notion that learning goals are
especially effective in enhancing self-efficacy and self-regulation (Schunk, 2001).
3. They had a significantly higher commitment to their goals than did those with a perfor-
mance goal.
It is a good idea to set up goals that will allow your clients to focus on mastering the skills
necessary to perform a new behavior as well as goals that target specific outcomes. For instance, a
client may have a performance goal of creating a more productive team or losing a specific amount
of weight. However, by establishing a learning goal, the client would focus on acquiring the skills
to build a high-performance team or to maintain a healthy weight in order to ensure that the targets
or outcomes are successfully accomplished.
Avoidance Goals Versus Approach Goals
Goals that clients have can either be focused on securing desired outcomes (approach goals) or they
can target avoiding unwanted outcomes (avoidance goals). Avoidance goals, aiming to eliminate an
undesired end state (e.g., “avoid being overly controlling in my staff meetings”), tend to have more
ambiguous strategies associated with them and should not typically be used (Carver & Scheier,
1982).
Because approach goals tend to be more effective than most avoidance goals, one strategy for
behavior-change interventions is to encourage clients to redefine any avoidance goals into approach
goals (e.g., “be more participative and listen more to my staff during our meetings before I suggest
my own ideas”). In addition, people are more likely to engage in an approach goal when they have
set a low-high range goal (e.g., lose 2 to 4 pounds this week) versus when they have set a
single-number goal (Scott & Nowlis, 2013). Coaches should consider encouraging their clients to
utilize more low-high range goals when appropriate for specific desired behaviors.
Consider the following implications for coaching: With some goals, clients may be able to use
a “substitution goal” (e.g., “in meetings, soliciting suggestions and input from others instead of
expressing my own ideas and opinions”) or a different goal for which the avoidance goal is
instrumental (e.g., “seeking input and then summarizing the ideas of others” is instrumental for “not
being seen as being an overly directive or authoritative leader”). The Fogg Behavior Grid (Fogg,
2012) offers a comprehensive typology of strategies and drivers for coaches to use with their clients,
focusing on either approach goals (start doing, doing more, or doing differently) or avoidance goals
(stop doing or doing less), and it provides examples for when the end result is one time (e.g., run
a marathon), sometimes (i.e., situational or periodic), or all of the time (i.e., become an ongoing
behavioral ritual).
If Goal Intentions Are Not Generally Effective to Facilitate Behavior Change,
What Works Better?
Research suggests that attempts to change people’s intentions alone may not always result in
successful maintenance of behavior over time (Lawton et al., 2009). Many people express a strong
desire and intent to become more effective and to try new behaviors, but often they never really
initiate or sustain a new change for very long (e.g., relapse). Some research suggests that the
perceived importance of the goal (i.e., concern for the desired end point of the behavioral change)
might be the best predictor of those who will initiate new behaviors (whether they keep it up or not).
On the other hand, the individual factors of self-efficacy, perceived control, and being clear about
the disadvantages (i.e., the cons of behavioral change) are stronger predictors of clients who
successfully maintain new behaviors over time (Rhodes, Plotnikoff, & Courneya, 2008).
In general, clients are most strongly committed to goals that are desirable (attractive) and
attainable (Oettingen et al., 2009). However, neither of these factors guarantees that these judgments
translate into actual practice (Oettingen & Gollwitzer, 2007). Several studies provide evidence that
cognitively contrasting a desired future state with impeding reality (mental contrasting) effectively
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6 NOWACK
increases motivation and commitment to implement a goal (Gallo, Cohen, Gollwitzer, & Oettingen,
2013; Oettingen, Marquardt, & Gollwitzer, 2012; Oettingen et al., 2009).
These studies suggest that a structured approach to comparing and contrasting future success
versus realistic barriers determines the energy that will be used to commit and pursue personal/
professional goals. Simply, coaches could help clients directly reflect and compare their vision of a
desired future (e.g., enhanced professional performance or adopting new behaviors) with the current
situation that may hinder goal pursuit and success (e.g., barriers, temptations, and obstacles). This
technique appears to be consistent with “self-talk” motivational-interviewing strategies used to
enhance readiness to change (e.g., Passmore, 2007) and comparing the “real” versus “ideal” self in
the intentional-change model posited by Boyatzis and Akrivou (2006).
In summary, intentions to change behavior are weak predictors of actual behavior change
(Nowack, 2015). However, the use of implementation intentions (practice plans) appears to be
significantly more robust (Gollwitzer & Sheeran, 2006). A meta-analysis involving more than 8,000
participants in 94 independent studies revealed a medium-to-large average effect size (d⫽0.65) of
implementation intentions on goal achievement in various domains (e.g., interpersonal, environ-
mental, health) on top of the effects of mere goal intentions (Conner & Higgins, 2010; Gollwitzer
& Sheeran, 2006). These findings provide coaches with a specific approach to contracting and
supporting goal initiation to translate them into ongoing practice plans using an if-then model with
clients (See Figure 3). As such, implementation intentions are defined as if-then plans that have been
shown to cause sustained changes in behavior and acquisition of new habits (Gollwitzer & Sheeran,
2009).
The “if” part of the goal is the trigger or cue and the “then” part of the goal is a statement of
the specific behavior desired to be modified (e.g., stop, start, do more, do less). Some habit triggers
will be situation-based (e.g., “When I feel anxious, I will practice mindfulness meditation to calm
me down” or “When I notice the other person speaking, I will seek to understand what is being said
before I share my own ideas”) and others will be time-based (e.g., “When it is Monday, Wednesday,
and Friday morning at 7:00 a.m. for the next month, I will attend my 50-min yoga class” or “At each
weekly staff meeting, I will solicit the ideas of my staff and summarize them before sharing my own
thoughts and suggestions”). Both types might be relevant to use depending on the specific goal being
targeted. Fogg (2012) and Nowack (2015) have suggested that one of the most potent triggers is
pairing a new behavior with an existing habit (e.g., if a client has a routine in the morning that is
already established, then it is easier to link a new behavior to that existing habit).
Studies show that the “if” component of implementation intentions facilitates the accessibility
of situations, and linking “if” with “then” automates the behavioral response specified in the “then”
Goal Intention
Example
Practice Plan
Example
“To stay calm in
anxiety producing
situations”
“If my heart starts to
race, then I will
begin using my
mindfulness
breathing technique
and focus on how
relaxed I begin to
feel”
Figure 3. Practice plan/implementation intention example.
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7BEYOND GOAL SETTING TO GOAL FLOURISHING
component (Gollwitzer & Sheeran, 2009). Implementation intentions are powerful for coaches to
use with clients because they systematically facilitate deliberate practice to ensure both neuroplas-
ticity and long-term goal success (Conner & Higgins, 2010; Mashihi & Nowack, 2013).
Goal Striving: When Are Clients Most Motivated?
Models such as the Transtheoretical Behavior Change Model (TTM; Prochaska & Velicer, 1997)
suggest that clients are ready to change when they are ready to change. The TTM refers to readiness
stages of differential motivation with respect to both goal initiation and striving (e.g., precontem-
plation to maintenance stages). With respect to goal striving, clients have already moved through
contemplation, preparation, and action stages, but not all clients have the motivation to continue
with their goal pursuits despite some progress being made. In practice, client motivation typically
varies, so what do we know about when clients are most motivated in a cycle of goal initiation and
striving?
In general, the most common indicator for a subjective evaluation of a “best day at work” is
perceived progress in a goal by an individual or team (Amabile & Kramer, 2011). Amabile and
Kramer (2011) investigated a total of 26 project teams composed of 238 individuals who were asked
to report daily on moods, motivations, perceptions of the work environment, what work was
accomplished, and what events stood out in their mind (nearly 12,000 diary entries). Steps forward
(progress) occurred on 76% of people’s best mood days and setbacks on only 13% of those days.
Therefore, progress— even a small step forward—was highly correlated with the number of days
employees reported being in a good mood, although causality between mood and progress was not
possible to discern in this study (Amabile & Kramer, 2011). Nonetheless, this finding and the
research of others (e.g., Fogg, 2012) suggest that coaches should emphasize and reinforce tiny steps
of progress by their clients to maintain a high level of motivation and positive affect throughout the
course of a coaching engagement.
When clients work toward goals they monitor their progress in two ways—what they have
achieved so far and how much they have left to do. It appears that clients switch between the
methods depending on how close they are to reaching a goal. Research with university students
asked to pursue a specific goal (e.g., correcting errors in an essay) showed that students were
less motivated halfway through the tasks, which likely reflects the point where they switch their
focus from how much they achieved to how much they had left to do (Bonezzi, Brendl, & De
Angelis, 2011). Despite the widely accepted belief that motivation to reach a goal increases as
clients approach the desired end state, these findings suggest that this is not always the case and this
very much depends on the standard of reference used to monitor progress.
Client motivation within coaching engagements typically follows a U-shaped pattern such that
motivation is highest at the beginning and end of a goal pursuit rather than in the middle (Bonezzi
et al., 2011; Touré-Tillery & Fishbach, 2011, 2012). Because beginning and end (vs. middle)
positions with respect to goal setting are often arbitrarily determined, one thing coaches can do with
clients is to reduce the length of the “middle” by dividing goal pursuits into subgoals requiring
smaller actions and dates to follow up. This should increase the likelihood that clients will continue
to successfully maintain their efforts toward goal completion. Taken together, these studies suggest
motivation is most likely to fluctuate most in the middle of goal striving (i.e., slacking is more likely
in the middle of a goal pursuit); therefore, this is the optimum time for coaches to explore new ways
to enhance the readiness-to-change level of their clients to avoid potential derailment or outright
failure.
How Long Does It Take for New Habits to Form?
One important outcome in coaching engagements and leadership-development initiatives is suc-
cessful habit and behavior change based on targeted goals of the client. Neuroscience research
provides practitioners with a better understanding about how long it takes, on average, for new
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8 NOWACK
behaviors to become comfortable and automatic. It is important to point out that there is a difference
between changes at the neural level (neuroplasticity) and resulting behaviors becoming more
efficient and leading to visible performance outcomes that are meaningful for clients (Kleim &
Jones, 2008).
For example, the posterior hippocampus (visual-spatial memory center) in London taxi-cab
drivers has been shown to increase in size with years of experience (Woollett, Spiers, & Maguire,
2009), extensive piano practicing has been associated with enhanced plasticity of white-matter areas
of the brain (Bengtsson et al., 2005), adults attending a juggling course showed detectable changes
in brain structure within 3 months (Draganski et al., 2004), and short-term practice of mindfulness
meditation has resulted in significant changes in the brain measured by functional magnetic
resonance imagery (fMRI; Tang, Hölzel, & Posner, 2015). However, previous and current practice
of new behaviors is required to translate observable neural change into skill improvement and actual
health benefits.
To illustrate, doctors who have previous video-game experience and currently report playing
games make significantly fewer endoscopic surgical errors than surgeons who have no previous
video experience (Rosser et al., 2007). Finally, in a waiting-list control study using objective
measures of autoimmune lesions, clients with multiple sclerosis practicing a comprehensive stress-
management program demonstrated significantly less development of disease (exacerbations and
new lesions), but no evidence of subsequent improvement was observed when clients discontinued
using these coping techniques 26 weeks after the study (Mohr et al., 2012). At a practical level,
getting clients to “start” new habits and behaviors does appear to create significant and observable
neural change, but unless the behavior is maintained, it is unlikely that the advantages will be
translated into enhanced performance (“use it or lose it”).
Research by Lally, Van Jaarsveld, Potts, and Wardle (2010) suggests that new behaviors can
become automatic, on average between 18 and 254 days, but it depends on the complexity of what
new behavior a client is trying to put into place as well as their personality. They studied volunteers
who chose to change an eating, drinking, or exercise behavior and tracked them for success.
Participants completed a self-report diary, which they entered on a website log, and were asked to
try the new behavior each day for 84 days. For the habits, 27 chose an eating behavior, 31 a drinking
behavior (e.g., drinking water), 34 an exercise behavior, and 4 did something else (e.g., meditation).
Analysis of all of these behaviors indicated that it took 66 days, on average, for this new behavior
to become automatic and natural. The range was anywhere from 18 to 254 days (median 66 days).
The mean number of days varied by the complexity of the habit: drinking ⫽59 days, eating ⫽65
days, and exercise ⫽91 days.
Additional research suggests that interleaving (mixing up deliberate practice) results in even
greater skill performance and success than merely repeating new behaviors over and over (Lin et al.,
2013). A substantial body of research has established that interleaving (defined as practicing
different skills in quick succession) significantly improves both learning and performance in
students and adults (e.g., Rohrer, 2012; Rohrer, Hedrick, & Steershick, 2015).
Therefore, creating new habits requires tremendous self-control and emotional regulation to
reach a limit of self-reported automaticity for performing an initially new behavior. Taken together,
practitioners should consider that translating a goal into a new habit for most clients might take
longer than expected (approximately 2 months or more of deliberate practice) assuming that clients
have an appropriate motivation level for readiness to change throughout a coaching engagement. As
a result, shorter-term coaching engagements and complex behavior-change efforts might require
greater repetition and diversity of practice (interleaving) to demonstrate effectiveness.
When Should Clients “Hold” and When Should They “Fold” in Goal Striving?
Research in both health and organizational psychology suggests that several five-factor models
(FFMs) are significantly associated with goal initiation, goal striving, and successful behavior
change over time (Hampson & Friedman, 2008; Kern & Friedman, 2008; Lyubomirsky, King, &
Diener, 2005; Smither, London, & Reilly, 2005). For example, a review of the training-transfer
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9BEYOND GOAL SETTING TO GOAL FLOURISHING
literature by Zu Knyphausen-Aufsess, Smukalla, and Abt (2009) suggested that learners who are
higher in emotional stability and more extroverted are most likely to maximize training success in
terms of knowledge acquisition and skill improvement over time.
It seems both intuitive and reasonable that persistence and drive would generally be associated
with goal striving and successful behavior change. In a series of studies by Angela Duckworth and
colleagues, individuals demonstrating “grit” were more likely to be successful in both academic and
job-related goals and measures of performance (Duckworth, Peterson, Matthews, & Kelly, 2007).
Grit (defined as passion and perseverance for long-term goals) accounted for an average of 4% of
the variance in success-outcome measures (e.g., educational attainment among two samples of
adults [N⫽1,545 and N⫽690], academic GPA among Ivy League undergraduates [N⫽138], and
retention in two classes of U.S. Military Academy, West Point, cadets; Duckworth et al., 2007).
However, a recent meta-analysis by Credé, Tynan, and Harms (2016) found that grit, as
typically measured, appears to be only moderately correlated with diverse performance and retention
outcomes and is strongly confounded with the construct of conscientiousness. Their results, based
on 584 effect sizes from 88 independent samples representing 66,807 individuals, suggest that the
true utility of the grit construct may solely be due to perseverance, which overlaps with FFM
measures of conscientiousness (Credé et al., 2016). As such, continuing in the face of goal challenge
and pressure (i.e., “holding”) would appear to be generally advantageous for successful goal
attainment and maximized by those high in grit, achievement orientation, and drive (i.e., consci-
entiousness)— until it is not.
According to several studies, quitting (“folding”) may be a better coping strategy for the
well-being of clients when facing unattainable goals. In a series of studies, psychologists Gregory
Miller and Carsten Wrosch have found that people who feel comfortable quitting when faced with
unattainable goals may have better mental and physical health than those who persevere and push
themselves to succeed (Wrosch, Miller, Scheier, & Brun de Pontet, 2007; Wrosch, Scheier, &
Miller, 2013). These findings build on their previous research, which found that those persistent
individuals experienced higher levels of an inflammatory protein called C-reactive protein (an
indicator of inflammation) and increased cortisol (Miller & Wrosch, 2007). Given that chronic
inflammation represents a risk factor for various diseases (e.g., heart disease; Miller, Chen, & Zhou,
2007), these findings provide evidence for another mechanism potentially linking goal disengage-
ment, psychological well-being, and physical-health outcomes.
As such, effort and persistence are not always the most adaptive responses to the experience of
goal-related obstacles and challenges. On the basis of these findings, coaches might be more
supportive for clients, in the face of unattainable goals, to actually disengage and explore goal
reengagement. In fact, goal-disengagement and goal-reengagement capacities are typically not
strongly correlated with each other, making it possible for practitioners to emphasize both behaviors
(Wrosch, Scheier, Carver, & Schulz, 2003). Support for this perspective is provided by King and
Hicks (2006), who investigated how individuals cope with lost opportunities and mistaken expec-
tations and their association with health, happiness, and personality development. The happiest
individuals acknowledged loss, did not spend much time ruminating on the past, and more easily
disengaged from failure and “what might have been” in the past. Overall, they were more likely to
be focused on and committed to current goals, passions, and life activities (King & Hicks, 2006).
Does Practice Make Perfect?
Most coaches and clients resonate with the old saying that “practice generally makes perfect.” As
such, it is commonly accepted that individual differences in performance reflect differences in the
amount of deliberate and accumulated practice (activities that are structured and repetitive to
enhance effectiveness in any domain). Or, at least if you do something long and hard enough, then
you will likely become an expert.
In fact, there is a big difference between “experts” and those “who are expert” in what they do
(Ericsson, 2007). In a 1996 book coedited by Anders Ericsson and others titled The Cambridge
Handbook of Expertise and Expert Performance, two of the authors concluded that great perfor-
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10 NOWACK
mance comes mostly from two things: regularly obtaining concrete and constructive feedback and
deliberate practice with difficult tasks (Ericsson, 1996a, p. 4). For example, the authors found that
the best skaters spent 68% of their practice doing really hard jumps and routines compared with
those who were less successful (they spent only about 48% of their time doing the same difficult
things). Ericsson (1996b) defined “deliberate practice” to mean focused, structured, serious, and
detailed attempts to get better. That means it has to be challenging and difficult (i.e., practicing the
most difficult tasks).
In two other studies, Ericsson, Krampe, and Tesch-Romer (1993) recruited musicians from
different levels of accomplishment and asked them to retrospectively estimate the amounts of time
per week they had engaged in deliberate practice. Group averages were highest for the most
accomplished musicians. On average, the “best” violinists had accumulated more than 10,000 hr of
deliberate practice, compared with less than 8,000 hr for the “good” violinists and not even 5,000
hr for the least accomplished “teachers.” Ericsson et al. (1993) concluded that “individual differ-
ences in ultimate performance can largely be accounted for by differential amounts of past and
current levels of practice” (p. 392).
Brooke Macnamara and her colleagues from Princeton University recently conducted the largest
review and meta-analysis of studies exploring the relationship between deliberate practice and
performance in several domains (Macnamara, Hambrick, & Oswald, 2014). Their research also tests
the widespread “10,000-hour rule” popularized in several books (Colvin, 2008; Gladwell, 2008) that
suggests that it takes 10,000 hr of practice to become an expert in any given skill domain. Their
research included 111 independent samples, with 157 effect sizes and a total sample of 11,135
participants (Macnamara et al., 2014). They explored the deliberate practice and performance
relationship in various domains and two sets of factors. The first factor was based on the
predictability of a task or how often the behavior might be expected to be performed (e.g., handling
an aviation emergency to running each day) and the second was how the previous research was
conducted and how practice was actually measured (e.g., recall or log).
Their findings contradict the popular urban myth and claim that individual differences in
expertise and performance are largely accounted for by the amount of deliberate practice a person
engages in over time. In fact, the percentage of variance accounted for by deliberate practice in five
specific domains was as follows: games 26%, music 21%, sports 18%, education 4%, and profes-
sions less than 1% (Macnamara et al., 2014). Even in the most widely studied domains of expertise
research (music and chess), deliberate practice does not appear to adequately explain individual
differences in performance (Hambrick et al., 2014).
A subsequent meta-analysis (Macnamara, Moreau, & Hambrick, 2016) focused on the perfor-
mance of elite athletes to test the premise that individual differences in sports performance largely
reflect individual differences in accumulated amount of deliberate practice (Ericsson, 2007).
Overall, deliberate practice accounted for 18% of the variance in sports performance. However, the
contribution differed depending on skill level. Most important, deliberate practice accounted for
only 1% of the variance in performance among elite-level performers.
Deliberate practice explained a similar amount of variance in performance for youth as it did for
adult athletes (19% vs. 15%), and higher skill was independent of starting age (Macnamara et al.,
2016). Taken together, the popular myth of the requirement for 10,000 hr to become expert is clearly
not supported by research evidence, suggesting that genetic influence and other factors might
account for the unexplained variance in performance (e.g., with athletes it might be ease of
accumulating muscle mass or cortical motor control associated with superior coordination).
Certainly, deliberate practice is a necessary, but not sufficient, condition to explain individual
differences in skills, and it appears that more variance is not explained by deliberate practice than
what is explained by it. From a practitioner perspective, these results suggest the importance of
considering other broad factors that may contribute to individual differences in competence and
expertise (e.g., cognitive ability, personality, peer support, and genetic predisposition). For example,
across a wide range of piano-playing skill, deliberate practice accounted for less than half of the
variance (45.1%) in sight-reading performance (Meinz & Hambrick, 2011). However, working
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11BEYOND GOAL SETTING TO GOAL FLOURISHING
memory capacity (which is highly stable and largely heritable) added incremental validity and
explained an additional 7.4% variance of performance above and beyond deliberate practice.
In addition, another study explored the popular 10,000 “rule” by examining associations
between musical ability and practice (rs⫽.18 –.36) in 10,500 Swedish twins (Mosing, Madison,
Pedersen, Kuja-Halkola, & Ullén, 2014). Findings from this study suggest that practice does not
always make perfect if you do not have the minimal capabilities and the proper mindset to begin
with. Surprisingly, associations between music practice and music ability were predominantly
genetic, and, contrary to the researcher’s hypothesis, nonshared environmental influences did not
contribute. Genetic influences on hours of practice were substantial, explaining 69% of the variance
in males and 41% in females, with additional shared-environmental influences in females (21%).
Music abilities were moderately heritable, ranging between 12% and 61% (Ullén, Mosing, Holm,
Eriksson, & Madison, 2014). Finally, using a sample of more than 850 twin pairs, Hambrick and
Tucker-Drob (2015) found, after controlling for music practice, that there was a statistically
significant genetic effect on music accomplishment.
Although it seems reasonable to predict that anyone who engages in thousands of hours of
deliberate practice will develop a high level of skill in any field, it appears that our basic skills and
abilities may actually limit the ultimate level of performance that can be attained. Genes and
environment are both important for essentially any behavior, and practice is no exception. However,
there is a strong indication that extreme environmentalist models of performance and expertise (e.g.,
“practice is everything”) are likely to be just an urban myth (Nowack, 2015; Plomin, Shakeshaft,
McMillan, & Trzaskowski, 2014).
Coaches and consultants should encourage clients to practice new skills until they become
comfortable and automatic, but they should be cognizant of the limits of deliberate practice in
realistically converting “competent jerks” into “loveable stars” on the job. Evidence is convincing
that not all clients we work with can change very much despite deliberate and accumulated practice
(Hambrick et al., 2014). In practical terms, the magnitude of behavior change expected and required
by organizations that hire coaches to help employees change behavior may, at times, be both
unrealistic and unattainable for some.
Conclusion
In general, there has been a lack of attention in both research and practice to exploring ways to
successfully help clients initiate and sustain new behavior in training and coaching interventions
(Bracken et al., 2016; Joo, 2005; London & Smither, 2002; Mashihi & Nowack, 2013). On the basis
of the current neuroscience and behavioral research, coaches and consultants should consider the
following suggestions for optimizing goal setting and successful behavior change with their clients.
Skydiving Is Not Advised for Those Who Have a Tendency to Fail
Despite common edicts from psychologists, educators, and parents that perseverance and relentless
pursuit of goals optimize work and life success and well-being, recent research actually suggests a
curvilinear pattern. In fact, some lifetime failure has been shown to be associated with optimal
well-being (Seery, 2011; Seery, Leo, Lupien, Kondrak, & Almonte, 2013). Popular concepts such
as grit (Duckworth et al., 2007) appear to reinforce a “never quit” philosophy despite evidence of
only modest associations with diverse performance outcomes and conceptual overlap with consci-
entiousness (Credé et al., 2016). In fact, failure in accomplishing goals should not be viewed as a
weakness in clients, and terminating the pursuit of unrealistic or unattainable goals might actually
prove to be a better strategy in terms of physical health and psychological well-being (Miller &
Wrosch, 2007; Wrosch et al., 2013).
Practice Makes Better (Not Perfect)
More statistical variance in expertise and successful performance is not explained by deliberate
practice than is explained. Deliberate practice is merely a necessary, but not sufficient, condition for
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12 NOWACK
skill competence and significant performance improvement, whether behavioral or mental (Pascual-
Leone, Amedi, Fregni, & Merabet, 2005; Pascual-Leone et al. 1995). What needs to be carefully
considered is the investment of time, energy, and money compared to other factors such as readiness
to change and physical, cognitive, and psychological abilities that might limit successful goal
attainment and high performance (Macnamara et al., 2016). Even with the most motivated clients,
meta-analytic research suggests only small to modest effect sizes for skills-based outcomes,
implying that not all clients are capable of significant changes in behavior (Jones, Woods, &
Guillaume, 2016).
Goal Intentions Are Not the Same As Practice Plans
Wanting to change, often observed as stating intentions through goals, does not necessarily ensure
nor predict successful change. Motivated clients with a readiness to change will have the greatest
success translating stated goals into practice plans (Gollwitzer & Sheeran, 2006). Using if-then
intention methods for goal implementation with clients maximizes goal striving, completion, and
success. The “if” part of implementation intentions refers to the trigger or cue for implementing
desired behavior and can be existing habits, time, or specific situations such as meetings with others
(Fogg, 2012). Coaches should enhance the use of regular practice plans with their clients to facilitate
maximum neuroplasticity through varied deliberate practice for approximately 60 to 90 days,
depending on the complexity of the desired target behavior, resulting in unconscious competence
required for higher levels of comfort, skill enhancement, and performance (Lally et al., 2010).
Goals Come in Different Sizes but, like Shoes, Should Fit the Client
If you go to any coffee shop, you can typically order a variety of different “sizes” of your favorite
drink. Goals also can be described as having different “sizes” and features, so being precise with the
goals of your client will maximize goal success. Fogg (2012) has summarized a behavioral grid of
15 different goal options that help guide coaches and clients to focus on the best direction addressing
their interest and needs (e.g., goals resulting in behaviors to do one time, sometime, or all of the time
that might include doing things more frequently, less frequently, differently, starting something new,
or stopping an existing behavior). It is important that clients be specific in defining the type of goal
and frequency of adoption they desire in order to ensure the possibility of goal striving and
successful achievement.
Adopt Strategies to Optimize Goal Success but Avoid Backup Planning
Motivation and commitment to goals are indeed prerequisites for client success in attempting to
develop new habits and adhere to goals. Kruglanski, Pierro, and Sheveland (2011) found that
thinking about additional strategies for achieving a given goal indeed increases commitment to that
goal. However, it is easy to confuse our clients by encouraging them to create strategies to
accomplish stated goals instead of urging them to contemplate and develop backup plans in the
possible face of failure.
Backup plans, or secondary goals, should not be confused with relapse-prevention strategies
used effectively for abstinence-oriented goals related to addiction (Marlatt & Gordon, 1980).
Relapse prevention classifies factors contributing to relapse into two categories: proximal determi-
nants (high-stress situations, coping skills, outcome expectancies) and covert antecedents (e.g.,
urges/cravings, social interactions increasing relapse). Using a cognitive– behavioral framework,
relapse prevention helps the client recognize and prepare for high-stress situations in which a lapse
or total relapse is likely (Larimer, Palmer, & Marlatt, 1999).
Although making a backup plan may provide practical and emotional benefits in the face of
uncertainty, the value may come at a higher cost than previously understood. Results from three
studies suggest that the act of reflecting on a backup plan has harmful effects on goal accomplish-
ment (Shin & Milkman, 2016). This research suggests that reflecting on or generating backup plans
may actually reduce the probability of successful goal attainment by dampening the initial goal
desire (note that goal success that is based on pure luck or innate skill will not be affected). Clients
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13BEYOND GOAL SETTING TO GOAL FLOURISHING
who are mindful of their goal(s) and stated target behavior(s) will be optimally successful, but
challenging clients to come up with alternative or backup plans might actually interfere with
subsequent goal success.
Insight and Motivation Are Only Necessary, but Not Sufficient, Conditions for
Successful Goal Attainment and Performance Improvement
Not all clients who are self-aware and motivated will successfully change behavior or become more
effective on the job (Bacon & Spear, 2003; Chiaburu & Marinova, 2005; Glasgow et al., 2014;
Mashihi & Nowack, 2013). In a recent comprehensive review of coaching studies (Grover &
Furnham, 2016), nearly all studies investigating the impact of coaching on goal attainment were
found to have positive overall results as well as a significant association with enhancing self-efficacy
in clients. However, very few positive associations appear to support a relationship between
coaching and actual improvement in job performance (Grover & Furnham, 2016).
From both a research and practice perspective, it is important to distinguish between proximal
outcomes (e.g., enhanced resilience, self-awareness, skills acquisition) and distal outcomes (e.g.,
retention, performance) and to identify which ones are realistic and possible with specific behavior-
change interventions such as coaching. Finally, based on 360-degree-feedback studies with coach-
ing, effect sizes for observed behavior change are typically modest, suggesting that organizations
need to be realistic about the magnitude of behavior change to expect even when clients are highly
motivated (Nowack & Mashihi, 2012; Smither et al., 2005).
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Received October 27, 2016
Latest revision received February 2, 2017
Accepted February 5, 2017 䡲
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