Original Research

Enhancing goal attainment through solution-focused cognitive-behavioural coaching incorporating neuroscientific principles

Sarah Johnson, Dirk J. Geldenhuys

Received: 20 Jan. 2026; Accepted: 05 June 2026; Published: 17 Aug. 2026

Copyright: © 2026. The Authors. Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Orientation: This article explores enhancing goal attainment through solution-focused cognitive-behavioural (SF-CB) coaching incorporating neuroscientific principles.

Research purpose: The study aimed to develop and explore the contribution of integrating neuroscience principles into an SF-CB coaching framework on goal attainment.

Motivation for the study: While goal-setting is well established as a means of supporting personal and professional success, limited research has integrated neuroscientific principles into coaching practice. Solution-focused cognitive-behavioural coaching can be adapted using neuroscience to enhance goal attainment.

Research approach/design and method: This interactive qualitative study, within a social constructionist paradigm, explored the impact of integrating neuroscientific principles into an SF-CB coaching framework on goal attainment. A purposive sample of five participants took part in coaching sessions using the newly developed DANIEL framework, which integrated solution-focused, cognitive-behavioural and neuroscientific principles. Data were then collected and analysed using interactive qualitative analysis methodology.

Main findings: Emotional intelligence was the primary driver of goal attainment, enabling self-awareness and emotional regulation needed to set and pursue meaningful goals. An agile mindset supported goal attainment by fostering adaptability and learning, while skills orientation supported continuous development.

Practical/managerial implications: Result orientation emerged as the primary outcome, motivating focused, deliberate action towards goal attainment.

Contribution/value-add: This research contributes to coaching and industrial and organisational psychology by combining solution-focused and cognitive-behavioural approaches, informed by neuroscience, to enhance goal attainment. It provides practical insights to enhance coaching effectiveness in personal and organisational contexts and supports future research in neuroscience-informed coaching.

Keywords: neuroscience; solution-focused coaching; cognitive-behavioural coaching; goal attainment; DANIEL framework; emotional intelligence; interactive qualitative analysis.

Introduction

Human behaviour is inherently goal-directed. Goals (ideas of future, desired end states) function as regulators of action by directing attention, mobilising effort, increasing persistence and encouraging the development of strategies for achievement (Locke & Latham, 1990). Various psychological (e.g. motivation, self-efficacy and commitment) and cognitive processes (e.g. attention, planning and self-regulation) influence goal attainment (Bandura, 1991; Locke & Latham, 2002). Setting goals has been shown to enhance motivation, improve performance, facilitate self-regulation, boost confidence and promote both personal and professional growth (Hesketh, 2001; Locke & Latham, 2019). A goal sets the foundation for an individual’s plan, increasing awareness of what they aim to achieve and providing a structured approach for doing so. Clear goals help individuals measure progress, stay motivated, overcome procrastination and stay on track, ultimately contributing to an individual’s level of personal and professional success (Dik et al., 2019). The most effective goal-setting strategies include specificity, difficulty and acceptability. Goals that are specific, difficult (but achievable) and personally meaningful (acceptability) are motivating and likely to result in higher levels of performance (Coultas et al., 2011). Coaching plays an important role in assisting individuals to develop such goals, structuring relevant information in a way that facilitates behavioural change, enhances goal attainment and promotes overall well-being (Grant, 2015). Bandura’s (1991) social cognitive theory offers a framework for understanding goal-directed behaviour. He argues that self-regulatory systems lie at the heart of purposeful human action, driven by forethought and internal standards. Through coaching, clients engage these self-regulatory systems, turning cognitive representations of future states into present motivators. This aligns with the solution-focused and cognitive-behavioural approach, where clients are supported to envision desired outcomes and develop proactive strategies to achieve them. Solution-focused cognitive-behavioural (SF-CB) coaching integrates core principles from two distinct psychological approaches: solution-focused brief therapy (SFBT) and cognitive-behavioural therapy (CBT) (Cavanagh & Grant, 2010; Grant, 2017). Solution-focused brief therapy is a short-term, goal-directed approach that focuses on individuals’ existing strengths and future possibilities rather than past problems (De Shazer, 1985; De Shazer et al., 2007; Grant, 2017), thereby allowing greater emphasis to be placed on solutions and future possibilities rather than becoming fixated on past difficulties. This forward-looking perspective fosters a more optimistic and constructive outlook (Lightfoot, 2014). Cognitive-behavioural therapy focuses on identifying and restructuring maladaptive thought patterns (Beck, 2021). It provides individuals with tools to recognise unhelpful beliefs and modify the behaviours and cognitive processes that hinder their goals (Beck, 2021; Hofmann et al., 2012). For example, CBT techniques such as cognitive restructuring support rational thinking and self-regulation (Beck, 2021), essential for achieving and sustaining behavioural change. While SFBT focuses on constructing solutions and CBT focuses on correcting dysfunctional thought patterns, SF-CB coaching leverages the strengths of both. This integrated approach helps individuals clarify future-oriented goals while also addressing cognitive and emotional patterns that may hinder progress (Grant, 2015). However, SF-CB coaching generally places less emphasis on exploring emotional processing or the influence of unresolved psychological issues on goal attainment, which may fall outside its practical, goal-focused scope (Lightfoot, 2014). Therefore, while SF-CB coaching proves effective for many, individuals presenting with psychological challenges may require more therapeutic-derived or -based interventions facilitated by competent coaches with insight into psychology and psychotherapy (Kilburg, 2000; Stout-Rostron, 2012). Insights from neuroscience research suggest the brain’s capacity for change, particularly regarding emotional and cognitive regulation in goal pursuit (Boyatzis & Jack, 2018; Doidge, 2007, 2015). This suggests that targeted coaching interventions may contribute to lasting cognitive and behavioural changes by engaging specific neural circuits associated with executive function, emotional regulation and motivation.

Research purpose and objectives

Incorporating neuroscience principles in understanding and changing behaviour, and hence in practising therapy, counselling and coaching, is still in its infancy (Rock, 2006), but is gaining momentum (Habermacher et al., 2014; Keen & Geldenhuys, 2025; Rock, 2006). It is argued in this study that SF-CB coaching, which is based on the integration of solution-focused and cognitive-behavioural principles, already represents a step towards an integrative coaching perspective. Incorporating neuroscientific principles may further refine the model.

Furthermore, empirically exploring the contribution of the study to participants’ goal attainment may contribute to the development of coaching psychology, a discipline that is still in its infancy. These arguments are based on the premises that the functioning of the human brain underpins all human behaviour (Rossouw, 2014), that applying neuroscience does not give preference to any single school of thought in psychology, and that there is a recent quest for interdisciplinarity in human sciences (Geldenhuys, 2022; Siegel et al., 2021). This study aims to refine SF-CB coaching by incorporating neuroscientific principles to enhance goal attainment over time, thereby providing a foundation for the development of more effective coaching interventions and empirical studies.

Literature review

The solution-focused cognitive-behavioural approach to coaching

Solution-focused cognitive-behavioural coaching integrates principles from solution-focused coaching and cognitive-behavioural coaching to support goal attainment through a structured, strengths-based and future-oriented process (Grant, 2013, 2017). It emphasises identifying what is working, constructing preferred outcomes and translating these into practical next steps, while also addressing the cognitive and behavioural patterns that may hinder progress. Drawing on cognitive-behavioural theory, SF-CB coaching assumes that goal attainment is enhanced when clients understand the reciprocal links between their environment, thoughts, emotions and behaviours, and learn to restructure unhelpful cognitions and behaviours that interfere with performance (Grant, 2017). Within cognitive-behavioural coaching, the coach and client typically clarify session objectives, identify the problem to be addressed and develop solution pathways using evidence-based strategies such as cognitive restructuring and goal-setting (Beck, 2021; Neenan & Palmer, 2001; Palmer & Williams, 2013; Williams et al., 2010). Grant (2001, p. 49) emphasises goal-setting as the ‘foundation of successful self-regulation’. Many cognitive-behavioural coaching (CBC) models, such as those described by Neenan and Palmer (2001) and Palmer and Williams (2013), incorporate Locke and Latham’s (1990, 2002) goal-setting theory, guiding clients to establish goals that are specific, measurable, achievable, relevant and time-bound (SMART). Overall, SF-CB coaching combines solution-building momentum with cognitive-behavioural tools to facilitate adaptive change and goal-directed performance (Grant, 2017).

Advantages of the solution-focused cognitive-behavioural approach

The integration of solution-focused and cognitive-behavioural methodologies into SF-CB coaching addresses the above limitations by combining the strengths of both approaches.

Contemporary coaching literature increasingly supports integrative models that blend cognitive-behavioural, solution-focused and positive psychology principles to enhance client outcomes (Dias et al., 2017).

This integration provides a balanced framework that enables clients to resolve underlying cognitive and behavioural obstacles while maintaining a positive, goal-directed mindset (Grant, 2017). Clients can explore and resolve underlying issues (a strength of cognitive-behavioural coaching) while also identifying and building on their existing strengths and resources to achieve future goals (a strength of solution-focused coaching). Solution-focused cognitive-behavioural coaching encourages a holistic view encompassing past, present and future perspectives, supporting enhanced self-awareness and sustained goal-directed behaviour.

Research suggests SF-CB coaching enhances performance, reduces stress and builds resilience by equipping clients with practical tools to manage cognitive distortions while leveraging inherent strengths and resources (Grant, 2017). Moreover, the approach fosters self-regulation and goal attainment by helping clients define clear, specific goals and develop actionable pathways that combine cognitive restructuring and solution-building strategies (Cavanagh & Grant, 2010).

Central to SF-CB coaching is client empowerment, which positions clients as experts in their own lives and encourages ownership of goals and solutions, with the coach acting as a collaborative facilitator (Grant, 2001; Grant & Cavanagh, 2007). The framework’s flexibility allows coaches to tailor their methods to individual needs, employing more intensive cognitive-behavioural techniques when required, or emphasising solution-focused momentum to sustain progress. In practice, SF-CB coaching typically involves clarifying the client’s goal, identifying existing strengths and resources, exploring cognitive or behavioural obstacles, generating solution pathways, supporting action and reviewing progress (Grant, 2017).

In summary, SF-CB coaching offers a theoretically sound and empirically supported framework that bridges the gap between problem-focused approaches (e.g. identifying and restructuring maladaptive cognitions) and solution-focused approaches (e.g. identifying strengths and constructing preferred outcomes). By integrating their complementary strengths, it overcomes individual limitations and supports clients in achieving lasting personal growth, enhanced performance and resilience (Cavanagh & Grant, 2010; Grant, 2001, 2017).

Neuroscience as a foundation for coaching practice

Applied neuroscience provides a scientific framework for assessing, expanding and refining theories and even proposing new models and practices related to human functioning (Geldenhuys, 2020). Advances in brain research have deepened our understanding of the neural processes associated with thought, emotion, motivation and behaviour, offering a biological basis for interventions aimed at meaningful and sustainable change (Boyatzis & Jack, 2018; Walter et al., 2009). Within this study, neuroscience serves as a conceptual lens for evaluating and enhancing SF-CB coaching by linking psychological processes to underlying neurobiological mechanisms. A key contribution of neuroscience to coaching lies in demonstrating that experience and focused attention can modify neural functioning, often referred to as self-directed neuroplasticity (Rock & Page, 2009; Schwartz et al., 2005). Through structured reflection and behavioural experimentation, coaching can therefore support adaptive learning and sustained change by reinforcing functional patterns of thinking, feeling and acting (Arden, 2019; Brann, 2022; Siegel, 2020).

Neuroscience framework

Neuroscience provides a useful lens for understanding how coaching supports goal attainment by linking common coaching processes (reflection, emotional regulation, planning and behavioural follow-through) to large-scale brain network dynamics. One framework often used to understand these dynamics is the triple-network model, which describes the coordinated activity of three large-scale brain systems: the Executive Network (EN), the Default Mode Network (DMN) and the Salience Network (SN). The interaction of these networks is considered central to mental flexibility, emotional regulation and goal-directed behaviour (Arden, 2019; Bressler & Menon, 2010). In coaching, effective goal pursuit typically requires flexible switching between these functions: meaning-making and self-referential reflection (DMN), prioritising what feels relevant and emotionally salient (SN) and translating insight into structured action through planning and self-regulation (EN) (Arden, 2019; Beaty et al., 2015; Brann, 2022; Buckner & Carroll, 2007; Menon & Uddin, 2010). The sections below outline how each network is conceptually relevant and how these functions are applied within SF-CB coaching to support goal attainment.

Executive network

The EN, also referred to as the central executive or task-positive network, is engaged during cognitively demanding tasks and supports goal-directed behaviour through functions such as attention control, working memory, planning, decision-making and response inhibition (Arden, 2019; Beaty et al., 2015; Lesage & Stein, 2016; Menon & Uddin, 2010). Arden (2019, p. 36) describes the EN as the brain’s ‘central executive’, highlighting its role in maintaining present-moment awareness and translating task demands into purposeful action.

Executive network functioning is strengthened when individuals experience psychological safety and sufficient internal stability, enabling them to adapt effectively to challenges arising from external demands (Arden, 2019; Geldenhuys, 2020; Grawe, 2007). In contrast, reduced EN activation has been associated with difficulties in attention and decision-making and lower resilience, whereas optimal activation supports improved planning and goal pursuit (Arden, 2019; Dahlitz, 2015; Geldenhuys, 2020). Drawing on these findings, the EN can be understood as supporting the translation of insight into structured action through planning, goal-setting and self-regulation within SF-CB coaching (Arden, 2019; Brann, 2022; Grant, 2017).

Default-mode network

The DMN, sometimes described as the storytelling brain, is associated with self-referential thinking, autobiographical reflection and sense-making (Arden, 2019; Buckner & Carroll, 2007; Martinez-Conde et al., 2019; Menon & Uddin, 2010). It is engaged during internally directed cognition such as imagining the future, recalling past experiences and constructing narratives that help individuals interpret their experiences and anticipate what may happen next (Arden, 2019; Bear et al., 2016; Willner et al., 2013).

The DMN supports ‘mental time travel’, but is typically downregulated during demanding, goal-directed tasks when executive control is required (Arden, 2019, p. 40; Bressler & Menon, 2010). In supportive contexts, sharing autobiographical stories can promote insight and new perspectives (Arden, 2019; Boyatzis et al., 2015; Garnett et al., 2022; Jack et al., 2013). However, excessive co-activation of the DMN and SN under perceived threat may contribute to intrusive rumination and sustained negative inward focus (Arden, 2019; Buckner et al., 2008; Garnett et al., 2022; Geldenhuys, 2020; Willner et al., 2013). Disrupted DMN connectivity (e.g. following trauma) may impair narrative processing and self-reflection (Arden, 2019). Drawing on these findings, the DMN can be understood as supporting reflective processes such as autobiographical exploration, perspective-taking and meaning-making within SF-CB coaching (Arden, 2019; Brann, 2022; Grant, 2017).

Salience network

The SN, sometimes referred to as the ‘feeling network’, supports the detection and prioritisation of emotionally significant stimuli and bodily sensations, directing attention and behaviour towards stimuli that are perceived as most relevant to current goals or concerns (Arden, 2019, p. 32; Bressler & Menon, 2010). By integrating interoceptive signals with emotional appraisal, the SN shapes motivated decision-making, influencing whether individuals approach or disengage (Arden, 2019; Menon & Uddin, 2010). Importantly, the SN helps coordinate switching between the DMN and EN, depending on task demands and environmental cues, supporting cognitive flexibility, emotional regulation and adaptive behaviour (Arden, 2019; Beaty et al., 2015; Bressler & Menon, 2010; Menon & Uddin, 2010). When SN functioning is disrupted (e.g. through over-activation, under-activation, or stress-related impairment), difficulties may present as hyperarousal, emotional detachment, intrusive rumination, reduced flexibility or impaired motivation (Arden, 2019; Geldenhuys, 2020; Lanius et al., 2015; Menon & Uddin, 2010). Drawing on these findings, the SN can be understood as supporting the identification of what is most relevant or motivating for the client, guiding attention towards goal-relevant cues and priorities within SF-CB coaching (Arden, 2019; Brann, 2022; Grant, 2017).

Overall, the neuroscience literature provides a conceptual basis for understanding SF-CB coaching as an applied change process that supports learning, regulation, adaptation and sustainable goal-directed change (Arden, 2019; Brann, 2022).

The optimal functioning brain

Optimal functioning of each network and a balanced, coordinated activation between the different networks are important for optimal functioning (Arden, 2019; Cozolino, 2017; Siegel, 2020). Integration implies top-down and left-right integration between and within the different networks (Cozolino, 2017). During optimal functioning, the activation of the DMN assists in providing stability by reflecting on the past and envisioning the future, while the activation of the EN creates the capacity to dynamically engage with the challenges of the environment in the present moment. The SN serves as a ‘switch’ between these two networks by determining the relevance and urgency of dealing with outside challenges or personal needs.

Considering the above, incorporating neuroscience principles in coaching implies the use of psychological interventions that will facilitate optimal brain functioning. For example, the goal-focused orientation of SF-CB coaching (Grant, 2015; Passmore & Oades, 2014) can ‘facilitate the capacity to defer immediate gratification in the service of long-term planning and goal-directed behaviors’ (Arden, 2019, p. 158). Similarly, coaching strategies that foster positive emotional states can stimulate brain regions in the SN that are associated with intrinsic motivation, reinforcing both effort and perseverance (Arden, 2019; Boyatzis & Jack, 2018; Grawe, 2007).

The DANIEL Method

The DANIEL method was developed by the author for the purposes of this study as an original, structured application of SF-CB coaching informed by neuroscientific principles. The acronym DANIEL refers to the six phases developed for this study: Define goal, Activate strengths, Navigate obstacles, Innovate solutions, Evaluate progress and Learn and adjust. The six-phase iterative cycle of the DANIEL method is presented in Figure 1. The method draws on established solution-focused coaching, cognitive-behavioural coaching, neuroscience-informed coaching and applied neuroscience literature (Arden, 2019; Brann, 2022; Cavanagh & Grant, 2010; Grant, 2017), and was designed to support personal, professional and functional goal attainment within coaching contexts.

FIGURE 1: The six-phase iterative cycle within the DANIEL method.

Although presented sequentially, the DANIEL method is conceptualised as an iterative coaching approach rather than a linear process. The phases reflect a cycle of goal orientation, self-regulation, experimentation, reflection and adjustment, consistent with the view that change is recursive rather than linear (Cavanagh & Grant, 2010; Kolb, 1984; Siegel, 2020). In broad neuroscientific terms, the method is designed to support flexible coordination between reflection and meaning-making, attention to what is emotionally salient, and goal-directed planning and execution, which are commonly associated with large-scale brain network dynamics (Arden, 2019; Brann, 2022; Bressler & Menon, 2010). As such, the DANIEL method functions as a structured yet flexible framework that guides goal-focused coaching while accommodating the dynamic nature of change.

Each phase is described below in terms of its coaching purpose, the SF-CB processes applied and the neuroscience-informed rationale for how the phase supports goal attainment.

Define goal clarifies the client’s goals, values and preferred outcomes. In this phase, solution-focused practices are used to articulate a preferred future and identify available resources, while cognitive-behavioural questioning explores beliefs, assumptions and interpretations that may influence perception, motivation and readiness for action (Beck, 2021; Grant, 2013, 2017). The neuroscience-informed rationale is that clear and personally meaningful goals increase motivational salience and support goal-directed planning and follow-through (Arden, 2019; Cozolino, 2020).

Activate strengths mobilises strengths, intrinsic motivation and positive affect to build momentum. In this phase, solution-focused amplification of what is already working is combined with cognitive-behavioural reinforcement of self-efficacy and behavioural commitment (De Shazer & Berg, 1997; Neenan & Dryden, 2013). The neuroscience-informed rationale is that positive affect, reward-based learning and approach motivation support sustained engagement and goal-directed activation (Cozolino, 2020; Fredrickson, 2001).

Navigate obstacles supports clients to identify obstacles, reframe challenges and develop adaptive coping strategies. In this phase, solution-focused questioning is used to open possibilities, while cognitive-behavioural techniques such as thought monitoring, cognitive restructuring and skills-building support reduced avoidance and persistence under challenge (Beck, 2021; Ochsner & Gross, 2008). The neuroscience-informed rationale is that emotional regulation and cognitive reframing can support a shift from threat-based reactivity towards more approach-oriented responding (Arden, 2019; Brann, 2022).

Innovate solutions encourages experimentation and the testing of workable, self-authored solutions. In this phase, solution-focused discovery is combined with cognitive-behavioural experiments to translate insight into action. The neuroscience-informed rationale is that flexible coordination between executive control, reflective simulation and salience detection supports adaptive problem-solving and the testing of new behavioural pathways (Beaty et al., 2015; Menon & Uddin, 2010).

Evaluate progress involves evaluating outcomes, noticing what is working and identifying required adjustments. In this phase, cognitive-behavioural feedback loops and evidence-based reflection are combined with solution-focused attention to progress and scaling (Jackson & McKergow, 2007, as cited in Cavanagh & Grant, 2010; Palmer, 2011). The neuroscience-informed rationale is that feedback and recognition of progress support learning, persistence and adaptive adjustment (Arden, 2019).

Learn and adjust consolidates learning and supports maintenance through reflection, repetition and meaning-making. In this phase, cognitive-behavioural maintenance principles are combined with solution-focused coaching to reinforce change through sustaining narratives that embed learning into personal identity and future action (De Shazer & Berg, 1997; Neenan & Dryden, 2013). The neuroscience-informed rationale is that repeated practice supports experience-dependent learning, strengthening more durable patterns of thought and behaviour over time (Doidge, 2015).

The conceptual alignment between the neural network functions and phases of the DANIEL method is presented in Table 1.

Research design

Research approach

This study employed a qualitative exploratory research design, adopting a social-constructionist perspective and using interactive qualitative analysis (IQA) for the collection of data. According to Northcutt and McCoy (2004), IQA acknowledges power dynamics between participants and the researcher, with participants, referred to as ‘constituents’ in IQA, taking an active role in the generation, collection and analysis of their own data through various IQA protocols. Interactive qualitative analysis is a qualitative methodology that provides a structured, accountable and systematic framework for inquiry, making it well-suited for research focused on how phenomena are socially constructed and for developing a theory that captures the systemic nature of the phenomenon under investigation (Northcutt & McCoy, 2004). Interactive qualitative analysis empowers participants to both generate and interpret data, with the researcher facilitating the process (Bargate, 2014; Northcutt & McCoy, 2004).

Research strategy

The research strategy for this study began with a structured coaching process, followed by a focus group, individual semi-structured interviews and follow-up interviews.

Participants engaged in four coaching sessions via Microsoft Teams scheduled weekly over a period of 4–6 weeks. Four sessions were used to provide a focused, time-bound coaching process aligned with the brief, goal-directed nature of SF-CB coaching and the research timeframe. The focus group facilitated the concurrent collection and analysis of data, with the emerging affinities (themes) guiding the content of the individual semi-structured interviews. These semi-structured interviews were used to validate the focus group findings (Northcutt & McCoy, 2004) and contributed to achieving data saturation. In line with IQA methodology, saturation was indicated by the recurrence of affinities and the absence of substantively new themes during the iterative data collection and analysis process. The relatively homogeneous sample supported depth of exploration within a shared context, enabling the identification and validation of stable patterns across participants (Northcutt & McCoy, 2004), offering additional depth and insight into the group-level processes as well as individual experiences (Fusch & Ness, 2015).

Follow-up interviews were conducted approximately 3 months after the initial semi-structured interviews to examine the sustainability of the coaching outcomes.

Research method

Research setting

The research was conducted at The Cowshed in Pretorius Park, Pretoria. This location was chosen for its neutrality, proximity to the participants and ease of access via common navigation systems.

Research participants and sampling methods

A purposive sampling method was used to select participants, referred to as ‘constituents’ in IQA terminology (Northcutt & McCoy, 2004). Participants were professionals working within applied psychological contexts, with most having backgrounds in psychometrics. In IQA, participants are selected as ‘constituents’ (representatives of a shared constituency) due to their direct engagement with the phenomenon being studied and their role in co-constructing meaning through the research process (Northcutt & McCoy, 2004). This participatory approach supports the systematic identification and validation of themes within the group. As Hood (2016) explains, qualitative research typically involves small samples due to the in-depth and intensive nature of the analysis. The goal is to gain a thorough understanding of the phenomenon rather than to generalise to a larger population, with the research being inductive and emergent (Dworkin, 2012). A total of five participants were involved in the study, participating in all stages, including the coaching sessions, focus group discussions, semi-structured interviews and a follow-up interview. This allowed for a comprehensive exploration of their experiences, with each stage building upon insights gathered from the previous one. All participants were female. One of the participants was between 25 years and 30 years of age, two were between 36 years and 40 years, and two were between the ages of 41 years and 45 years.

Coaching sessions

Neuroscientific principles were incorporated practically through the DANIEL method by structuring the coaching process to support emotional regulation, focused attention, motivation, behavioural experimentation, feedback and learning consolidation. For example, participants were guided to clarify personally meaningful goals, identify strengths and resources, reframe obstacles, experiment with adaptive actions, evaluate progress and consolidate learning through reflection and adjustment. Neuroscience therefore informed the structure and facilitation of the coaching process, rather than being measured directly as a neurological outcome.

Each participant engaged in four virtual, individual coaching sessions weekly over a 4–6-week period, with each session lasting approximately 60 min. Four sessions were used to provide a focused, time-bound coaching process aligned with the brief, goal-directed nature of SF-CB coaching and the research timeframe. Brief neuroscience-informed explanations were also incorporated where relevant, using accessible language to help participants understand how emotional activation, focused attention and self-regulation may influence goal clarity, decision-making and follow-through.

Approximately 3 months later, participants took part in an individual follow-up interview to discuss the sustainability of the coaching outcomes. This interview explored the actions participants had taken since the coaching phase, changes in goal status, unexpected challenges encountered and the strategies used to address them. It also invited participants to reflect on the perceived effectiveness of the DANIEL method in supporting goal attainment over time. Follow-up reflections were gathered through a structured post-coaching questionnaire and interview questions focused on goal progress, perceived changes, challenges encountered and strategies used after the coaching sessions. These follow-up reflections provided insight into participants’ longer-term cognitive, behavioural and goal-related changes, as well as the sustainability of the coaching outcomes.

Data collection methods

In line with the IQA protocol, data collection was carried out in two phases: a focus group followed by individual semi-structured interviews (Northcutt & McCoy, 2004). In the focus group, participants (constituents) reflected on the phenomenon using an issue statement (‘What comes to mind when you think about how coaching has helped you reach your goals?’) and generated and clustered ideas into affinities. They then explored perceived influence relationships among the affinities, which informed the development of the systems influence diagram (SID). The researcher facilitated the process to support participant-led meaning-making and minimise undue influence. The second phase consisted of individual semi-structured interviews designed around the affinities (or themes) identified during the focus group. These interviews deepened interpretation by linking the group-generated system to participants’ individual experiences. Consistent with IQA methodology, the focus group phase supports the co-construction of affinities, which are then explored and refined during the individual semi-structured interviews. This sequential design enables participants to reflect on and elaborate their perspectives, thereby strengthening the validity of the emergent system (Northcutt & McCoy, 2004). To explore sustainability, follow-up interviews were conducted approximately 3 months later to examine whether changes associated with the coaching process were maintained over time. Participants were assigned unique identifiers (e.g. ‘P1’, ‘P2’) to protect anonymity, and verbatim extracts from focus group and interview data were included to support the findings.

Data recording

The coaching sessions, focus group and individual semi-structured interviews were recorded using a digital voice recorder. Additionally, the adhesive notes generated during the focus group were displayed on a wall for the entire group to view.

Strategies employed to ensure data quality and integrity

Northcutt and McCoy (2004, p. 17) assert that IQA is particularly advantageous for theory, both in terms of generating and testing it, offering a structured, accountable and rigorous approach to qualitative research. The involvement of participants in the thematic analysis, to identify, analyse and report patterns (themes) within the data, together with the confirmation of themes during the individual semi-structured interviews, created a perfect platform for triangulation (Northcutt & McCoy, 2004).

Data analysis

Affinities

Once the group had clarified what each response meant, participants were asked to identify recurring ideas and points of overlap (themes and/or commonalities) across the various responses. This process, known as inductive coding, aimed to organise the data into thematic groups and identify affinities (points at which categories and topics began to emerge) (Northcutt & McCoy, 2004, p. 98). The affinities were then worked through in discussion and progressively refined until the group agreed that each affinity description reflected the intended meaning. The group then generated titles or headings that accurately described the essence of each affinity. The researcher recorded a brief description that represented the general content and meaning of each affinity, as collectively defined by the group (Northcutt & McCoy, 2004). Four affinities and their respective descriptions were identified by the focus group (see Table 2).

Theoretical coding

Interactive qualitative analysis uses theoretical coding to identify the causal (influence) relationships among the affinities. In this phase, participants determine what they perceive to be the cause-and-effect relationship (influences) between the affinities within a system (Northcutt & McCoy, 2004, p. 149). When a direct relationship is identified between the affinities, participants are then asked to determine the direction of influence. There are three possible relationships: if A influences B, it is illustrated as A→B; if B influences A, it is illustrated as A←B; and if participants believe there is no relationship, it is represented as A<>B. For example, if participants perceived emotional intelligence (EI) to influence agile mindset (AM), the relationship was recorded as EI→AM. It is important to note that participants are not evaluating the strength of the relationship, but merely its existence and direction (Human-Vogel & Van Petegem, 2008). The Pareto principle was used to identify the most influential relationships among the potential causal links for analysis (Northcutt & McCoy, 2004), enabling the prioritisation of those relationships that contribute most substantially to system variance while reducing analytical complexity.

This principle assumes that a small proportion of relationships accounts for the majority of system variance (Northcutt & McCoy, 2004, p. 158). In this study, the selected relationships reflected those accounting for up to 80.0% of the variance, while less influential relationships were excluded from further analysis.

Interrelationship diagram

The creation of an interrelationship diagram (IRD) was the initial step in the broader process of rationalising the system (Northcutt & McCoy, 2004, p. 170). After calculating the delta values (Δ), representing the difference between the number of outgoing (‘outs’) and incoming (‘ins’) relationships for each affinity, the affinities are sorted in descending order of delta frequency to identify the relative drivers (causes) and outcomes (effects) within the system (Human-Vogel & Van Petegem, 2008; Northcutt & McCoy, 2004), as shown in Table 3. An affinity with a high positive delta value, characterised by a greater number of ‘outs’ than ‘ins’, is considered the primary driver. The primary driver is a significant cause, influencing numerous other affinities without being influenced by any. The secondary driver is a relative cause or influence on other affinities. Circulators or pivots occur when an affinity has an equal number of ‘ins’ and ‘outs’. An affinity with a high negative delta value, with many ‘ins’ but no ‘outs’, is identified as the primary outcome. The primary outcome (a significant effect) is influenced by multiple affinities but does not affect others, whereas the secondary outcome represents a relative effect (Northcutt & McCoy, 2004).

Table 3 presents the IRD, where the numbered columns (1–4) correspond to the affinities listed on the left. The vertical numbering reflects the ordering of affinities based on their delta (Δ) values rather than their original sequence. Arrows indicate the direction of influence between affinities, with upward arrows representing a directional relationship from the row affinity to the column affinity, and leftward arrows indicating the inverse. This table provides the analytical basis for the driver and outcome classifications presented in Table 4.

Systems influence diagram

In the final phase of the focus group data analysis, an SID was developed to visually represent the system of affinities and their relationships, as shown in Table 4. The SID represents the system of drivers and outcomes by mapping affinities and their directional relationships (Northcutt & McCoy, 2004). The numbering indicates the relative ranking of affinities based on their delta (Δ) values (highest to lowest), rather than their original sequence.

Given the complexity of the initial SID, redundant links were removed following the IQA rationalisation process (Northcutt & McCoy, 2004, p. 37), whereby links that duplicated indirect relationships (i.e. where a relationship could be explained through intermediary affinities) were eliminated based on delta (Δ) ordering to produce a clearer and more interpretable representation.

The resulting uncluttered SID, shown in Figure 2, functions as a mind map of the relationships between affinities and was subsequently adapted into a more linear format for use in the second phase of the IQA process, which consisted of the individual semi-structured interviews.

FIGURE 2: Uncluttered linear system influence diagram.

Reporting

The key findings from the focus group and individual semi-structured interviews are detailed in the following section. To enhance the depth of the analysis, the researcher incorporated verbatim extracts from both the focus group discussions and the individual semi-structured interviews. Participants were assigned unique identifiers (e.g. ‘P1’, ‘P2’) to maintain clarity and ensure anonymity throughout the reporting process.

Results

Four affinities were generated in the focus group, which participants used to create a mental framework of their lived experience through both inductive and deductive reasoning. By arranging the affinities in descending order of delta, drivers (causes) and outcomes (effects) were identified within the system. The resulting SID represents the theory developed by the group (Northcutt & McCoy, 2004) and is presented as the streamlined linear SID in Figure 2.

The uncluttered linear SID was presented during the semi-structured interviews to facilitate discussion and link the group’s collective insights with participants’ individual perspectives. These interviews did not constitute a new phase of data collection, but provided interpretive depth by enabling participants to reflect on the personal meaning of the affinities and their interrelationships (Northcutt & McCoy, 2004).

Primary driver: Emotional intelligence

Emotional intelligence was identified as the primary driver of goal attainment and is regarded as the ‘fundamental cause’ or ‘source of influence’ within the system (Northcutt & McCoy, 2004, p. 32). As a primary driver, EI influences other affinities within the system, but is not influenced by them. Participants associated EI with ‘self-awareness’, ‘self-regulation’ and ‘empathy’, emphasising that the ability to recognise and understand one’s own emotions affects how individuals approach problem-solving and goal attainment. P1 stated that:

‘You must obviously have self-insight, self-awareness. You need to know how to manage yourself in order to set your goals.’ (P1, 25–30 years, assessment practitioner)

Participants also described EI as central to identifying meaningful goals and sustaining effort towards them. P3 (P3, 36–40 years, industrial psychology and business practitioner) explained that understanding what they were feeling and thinking helped clarify ‘what your goal needs to be’, particularly when goals were emotionally grounded (e.g. family-related goals). Although some participants initially expressed uncertainty about the relationship between EI and an AM, the group agreed that EI was the stronger driver. As P4 noted:

‘Even though you have to adapt, you have to be aware of what you need to change. It doesn’t help that you know you need to change something, but you’re not aware of what.’ (P4, 41–45 years, HR and assessment practitioner)

Secondary driver: Agile mindset

Agile mindset emerged as the secondary driver. Secondary drivers are relative causes (or influences) on affinities in the system, which are determined when there are both ‘outs’ and ‘ins’, but with a higher number of ‘outs’ than ‘ins’ (Northcutt & McCoy, 2004). Participants described AM using terms such as ‘adaptability’, ‘resilience’ and ‘sustainability’, emphasising the ability to adjust when plans change or setbacks occur. P5 stated:

‘Resilience and sustainability are almost the same thing, and you have to be adaptable because things will go wrong in trying to achieve a certain goal.’ (P5, 41–45 years, independent assessment practitioner)

Participants consistently described EI and AM as closely connected, with EI supporting persistence and AM supporting adjustment. As P2 summarised:

‘[An] agile mindset will get you to the goal. Emotional intelligence will keep you going.’ (P2, 36–40 years, assessment and business practitioner)

Secondary outcome: Skills orientation

Skills orientation (SO) was identified as the secondary outcome. A secondary outcome reveals a relative effect in the system and is recognised when there are both ‘ins’ and ‘outs’, but there are more ‘ins’ than ‘outs’ (Northcutt & McCoy, 2004). The group retained SO as a stand-alone affinity, despite it initially containing only two descriptors (‘techniques’ and ‘practical’), because these were seen as capturing the essence of skills actively used to achieve goals.

Participants expressed mixed views about the importance of skills. P1 (P1, 25–30 years, assessment practitioner) acknowledged that while skills play a role, they may not always be the most significant contributor, whereas P3 emphasised skills development as a way to improve outcomes and satisfaction with the approach taken, stating:

‘If you don’t have the right tool to get something done, you can then go learn it to get a better result.’ (P3, 36–40 years, industrial psychology and business practitioner)

Primary outcome: Results orientation

Results orientation (RO) was identified as the primary outcome. A primary outcome is characterised by having many ‘ins’ but no ‘outs’, meaning that it is influenced by multiple affinities but does not exert any influence on them (Northcutt & McCoy, 2004). Participants described RO as the point at which motivation, emotional management, adaptability and skills translate into measurable progress and follow-through. P1 (P1, 25–30 years, assessment practitioner) linked RO to practical goal methods, stating that using techniques such as SMART helped to ‘get to the goal’.

Participants also described RO as connected to skills development and evidence of change. As P3 stated:

‘You want to have evidence that you did something or changed something to reach something new which you weren’t happy with before.’ (P3, 36–40 years, industrial psychology and business practitioner)

Participant reflections on the coaching process and follow-up

Participants described the coaching phase as strengthening self-awareness and emotional readiness before goal execution. As P3 noted:

‘The beginning part of it is all more human-oriented. It’s all about the person, what you’re feeling, thinking, who you are, what you are, etc.’ (P3, 36–40 years, industrial psychology and business practitioner)

Participants also described reframing as important for adaptive goal pursuit. Reflecting on early coaching sessions, P4 stated:

‘That first day or the first session […] you just guided me to realise why it is worthwhile. […] changing your mindset about how you see things, maybe looking at it from a different perspective.’ (P4, 41–45 years, HR and assessment practitioner)

During the follow-up interviews conducted approximately 3 months after the coaching sessions and initial semi-structured interviews, participants reported that their original goals generally remained relevant, although progress was moderated by contextual constraints such as workload, time-management challenges, setbacks and self-doubt. Participants emphasised continued effort and adjustment, which aligned with the drivers and outcomes identified through the SID:

‘… life happens, so just adjust and move with it’ (P5, 41–45 years, independent assessment practitioner)

Discussion

The purpose of this study was to enhance goal attainment through SF-CB coaching incorporating neuroscientific principles. The focus on goal attainment was informed by the central role of goals in coaching and self-regulation, as well as the need for structured approaches that support clients not only to define goals, but also to regulate emotions, respond adaptively to obstacles and sustain follow-through over time. The study therefore aimed to conceptualise and apply a structured coaching framework that integrates SF-CB processes with neuroscientific principles through the DANIEL method.

Emotional intelligence emerged as the primary driver of goal attainment, shaping participants’ readiness to engage meaningfully with goal definition and sustained follow-through. Consistent with established models of EI, self-awareness and emotion regulation support motivation, resilience and adaptive responding under challenge (Goleman, 1995; Gross, 2002; Mayer & Salovey, 1997, Salovey & Mayer, 1990). Within the DANIEL method, this driver was most evident in Define goal and Activate strengths, where clients connected goals to values and internal resources.

From a neuroscience perspective, this can be understood as improved integration between executive processes involved in deliberate goal-setting and salience processes that register emotionally meaningful cues, supporting intrinsically meaningful commitment rather than compliance-based goal pursuit (Beaty et al., 2015; Bressler & Menon, 2010; Menon & Uddin, 2010). This emphasis on experienced meaning aligns with evidence that meaning is constructed through individuals’ interpretations of purpose, values and goals in context (Geldenhuys & Johnson, 2021).

Agile mindset emerged as the secondary driver. An AM is characterised by adaptability, experimentation and learning in response to uncertainty, rather than rigid persistence with ineffective plans (Eilers et al., 2022; Hrishikesh, 2024). Within the DANIEL method, this was most evident in Navigate obstacles and Innovate solutions, as reflected in participants’ accounts of reframing setbacks as feedback and adapting their approaches in response to changing circumstances. From a neuroscience perspective, small wins, timely feedback and perceived control can strengthen approach-oriented persistence through reinforcement learning processes, supporting continued effort despite ambiguity or obstacles (Lesage & Stein, 2016; Schultz, 2015; Wise, 2004). In this sense, setbacks are interpreted as feedback rather than failure and are used to guide the next adaptive action.

Skills orientation emerged as the secondary outcome, reflecting the development and refinement of competencies required for sustained progress (Ericsson et al., 1993). In the DANIEL method, this outcome aligned closely with Learn and adjust, where reflection and iterative improvement supported capability building over time. From a neuroscience perspective, repeated practice and feedback support experience-dependent learning and the consolidation of more functional behavioural routines (Arden, 2019; Brann, 2022; Kempermann, 2015).

Results orientation emerged as the primary outcome, reflecting a stronger focus on measurable progress, persistence and deliberate self-regulation towards goal attainment (Locke & Latham, 2002; Schunk, 2005). In the DANIEL method, this outcome aligned most directly with Evaluate progress and was further supported by Learn and adjust, where progress monitoring and iterative refinement strengthened follow-through. From a neuroscience perspective, regular review of outcomes provides contingent feedback that supports value-updating and the refinement of goal-directed action over time (Schultz, 2015; Wise, 2004). Overall, the findings suggest that for some clients, coaching may need to begin by strengthening emotional awareness, regulation and psychological safety before more structured goal-setting and execution work is emphasised, consistent with bottom-up, neuroscience-aligned change processes (Badenoch, 2008; Kryza-Lacombe et al., 2021; Miller, 2016; Siegel, 2020).

Integration across data sources and sustainability

Across the focus group, individual semi-structured interviews and 3-month individual follow-up interviews, participants’ accounts were broadly consistent with the system of drivers and outcomes identified in the IQA results. Reflections at follow-up indicated that goals generally remained relevant, while progress was shaped by contextual constraints such as time pressure, workload and setbacks. These accounts suggest that the change processes described in this study appear to be sustained beyond the immediate coaching period for some clients, and they highlight the potential value of ongoing support or follow-up sessions to maintain momentum when contextual demands are high.

Implications for practice

The findings highlight how integrating neuroscience with SF-CB coaching can strengthen goal attainment by attending to both emotional readiness and structured goal-directed action. Several practical implications for coaching practice emerge.

Emotional readiness as a foundation for goal work

Given that EI emerged as a primary driver of goal attainment, coaches can benefit from attending to clients’ emotional awareness, regulation and psychological safety before engaging in structured goal-setting. This includes brief psychoeducation on how emotions and attention influence decision-making, as well as grounding or reflective practices to support readiness for goal-directed work. In practice, this may involve beginning coaching sessions with reflective check-ins, emotional labelling, grounding exercises or questions that help clients identify what feels most important before moving into goal-setting.

Application in organisational and professional contexts

The integrated framework can be applied in organisational settings to support leadership development, performance and change initiatives. By fostering EI, adaptability and iterative learning, coaching can contribute to greater agility and resilience in individuals and teams. For example, the framework could be used in leadership or professional development coaching to help individuals clarify meaningful goals, reframe barriers, identify adaptive actions and review progress over time.

The emphasis on evaluation, learning and adjustment underscores the value of a longer-term developmental perspective. In practice, this may include scheduled follow-up sessions, progress reviews, reflective journalling or action-learning tasks that help clients consolidate learning, maintain progress and adjust strategies as their goals evolve.

Overall, these implications suggest that SF-CB coaching informed by neuroscience can enhance coaching effectiveness by aligning interventions with how individuals regulate emotion, learn from experience and sustain goal-directed change.

Limitations

Several limitations should be considered when interpreting the findings. The study utilised a single focus group comprising five participants, which limited opportunities for comparison across different focus groups. The findings are also based on the experiences and perspectives of participants within a specific context, which may limit transferability to other coaching environments or to individuals with different levels of experience or expertise. Contextual factors such as organisational culture, resource availability and individual readiness for change may influence the implementation and effectiveness of the model. Finally, the application of neuroscientific principles to coaching remains an emerging field. As such, the findings are limited by the current understanding of how neuroscience directly informs coaching practices, requiring further empirical research.

Recommendations for future research

Future studies should involve larger, more diverse samples to provide a more comprehensive understanding of the application of the framework across different coaching contexts and populations. Research could also explore how the framework can be adapted for group coaching.

Conclusion

This study explored the integration of neuroscientific principles into SF-CB coaching through the DANIEL method to enhance goal attainment. The findings suggest that emotional intelligence, agile mindset, skills orientation and results orientation work together to support emotional regulation, adaptive action, learning and sustained goaldirected change.

Acknowledgements

This article is based on research originally conducted as part of Sarah Johnson’s doctoral thesis titled ‘Enhancing Goal Attainment Through Solution-Focused Cognitive-Behavioural (SF-CB) Coaching Incorporating Neuroscientific Principles’, submitted to the Department of Industrial and Organisational Psychology, University of South Africa in 2026. The thesis was supervised by Dirk J. Geldenhuys. The manuscript has since been revised. The original thesis is not yet publicly available.

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Sarah Johnson: Writing – original draft. Dirk J. Geldenhuys: Supervision. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication and take responsibility for the integrity of its findings.

Ethical clearance for the study was obtained from the University of South Africa, Department of Industrial and Organisational Psychology Ethics Review Committee (Ref. no. 4470), prior to participant recruitment. All participants provided informed consent. Participants were informed that participation was voluntary and of their right to withdraw from the study at any stage without explanation or penalty, and confidentiality and anonymity were assured.

Consistent with the IQA methodology, participants were actively involved in the generation and analysis of data (Northcutt & McCoy, 2004) through the focus group and individual semi-structured interviews, supporting the integrity and trustworthiness of the findings.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

The data that support the findings of this study are available from the corresponding author, Sarah Johnson, upon reasonable request.

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

References