City St George's Organisational Psychology Group Blog

By Maria Alejandra Mussfeldt Rizzo (24-25)

Work–life balance has become one of the biggest challenges facing employees today (Brough et al., 2022; Kalliath & Brough, 2008). It is common for employees to go home after a long day only to find out that work has followed them back through emails, unrealistic deadlines, and the constant pressure of unfinished work (Kelly et al., 2020; Maslach, 2003). At the same time, family and personal responsibilities, and the need for rest continue to demand attention. This ongoing struggle to meet the expectations of both work and personal life can have a serious impact on how satisfied people feel in their jobs (Kossek et al., 2011; Haar et al., 2014).

Most existing research on work-life balance has focused on developed Western countries, where supportive labour policies are more common (Eiffe, 2021; Lapuerta et al., 2011). But in places like Ecuador, long working hours, limited flexibility, and traditional gender expectations often shape people’s experiences in ways that aren’t usually studied (Idrovo Carlier et al., 2012; Chioda, 2016). My research set out to compare these two contexts. My aim was to understand how culture and workplace practices influence both work-life balance and job satisfaction. 

I conducted an online survey with 133 employees across both countries. The survey asked how satisfied they felt with work-life balance, how often work interfered with family, whether they had flexibility to take time off, and how frequently they were contacted about work outside (ISSP, 2012; ISSP, 2024). I also asked participants about work centrality, meaning how important work was to their identity (Paullay et al., 1994; Kanungo, 1982). For some people, work is the most important thing in their lives and gives them a lot of meaning. For others, it is not a main priority (Moser & Ashforth, 2021).

Employees who were more satisfied with their work-life balance also reported being more satisfied with their jobs (Haar et al., 2014; Noda, 2020). When people felt that work was constantly interfering with their family or personal responsibilities, their job satisfaction dropped. However, those who felt supported in managing both roles were more positive about their jobs and more engaged with their roles. Moreover, this did not mean that balance was less important. Even the most work-focused individuals experienced lower satisfaction when balance was poor, suggesting that valuing work does not make someone immune to the strain of competing demands.

The differences between genders were not as obvious as expected. Nevertheless, cultural context was important. Women in Ecuador reported worse work-life balance than men, reflecting strong traditional gender roles and expectations (Chant, 2002; Basham, 1976). Many felt they could not find balance because of this double responsibility, also referred to as the “double burden” (Horner, 1990; Berniell et al., 2023). The difference between men and women was smaller in Spain, potentially because of more progressive policies and changing ideas about mutual parental responsibility (Escobedo & Wall, 2015). It is interesting that there were not any statistically significant differences in overall job satisfaction between men and women, but the results still show how cultural expectations affect how employees feel about balance (Meeussen & Van Laar, 2018).

Work-life balance is not just a personal issue for employees to solve. It is a workplace issue that directly affects job satisfaction, wellbeing, and productivity (Greenhaus & Beutell, 1985; Allen et al., 2013). Organisations who ignore this can risk having employees who are disengaged, stressed, and unhappy (Maslach, 2003). Organisations who take it seriously will see better moods, engagement, and stronger performance (Boamah et al., 2022).

Companies can take real steps to help. One way is to set clear rules about working hours and limit after-hours communication to what is necessary (De Bloom et al., 2015). Studies show that workers who can properly disconnect come back more motivated and productive. Flexible work arrangements are another valuable tool (Lewis, 2003; Wheatley, 2017). Allowing employees to adjust their hours or location helps them balance responsibilities, lowers stress, and increases satisfaction. It is equally important to offer inclusive parental leave and childcare support, especially to help women who often face greater family responsibilities (Haas & Rostgaard, 2011; Bainbridge & Townsend, 2020). Making sure that both mothers and fathers can take time off without stigma encourages equal sharing of responsibilities and supports long-term gender equality at work (Grotto & Andreassi, 2024).

Organisations should also encourage employees to use their annual leave and disconnect fully during holidays (Schwartz & McCarthy, 2010). Coverage systems, where coworkers share duties, can reduce the anxiety of work piling up while people are away (Randell et al., 2010). Lastly, managers need to recognise that not all employees see work as the most important thing in their lives. Some thrive on career development opportunities, while others value flexibility more (Eccles, 2009). Tailoring support to these differences can make workplaces more inclusive and supportive (Anttila et al., 2015).

The comparison between Spain and Ecuador shows why context matters (Idrovo Carlier et al., 2012). Policies and workplace cultures cannot simply be copied from one country to another without considering cultural expectations (Aycan, 2008). In Spain, laws protect workers, but culture can sometimes make it hard to benefit fully (La Barbera & Lombardo, 2019). In Ecuador, policies are less developed, and traditional values mean women in particular still face greater difficulties (Chioda, 2016). One-size-fits-all solutions rarely work. Strategies need to be adapted to cultural and gender dynamics to foster real balance and satisfaction (Brown et al., 2021).

My research confirms that work-life balance is related to job satisfaction for both men and women and across different cultures (Haar et al., 2014). It also shows that valuing work highly can make people happier at work, but this does not replace the need for balance (Mannheim et al., 1997). By supporting employees to meet both professional and personal demands, organisations can improve satisfaction, engagement, and long-term performance (Brough et al., 2022). In a world where stress, burnout, and disengagement are common, supporting work-life balance is a necessity (Maslach, 2003). Every company should remember that when work-life balance gets better, so does job satisfaction.

References

Allen, T. D., & Finkelstein, L. M. (2014). Work–family conflict among members of full-time dual-earner couples: An examination of family life stage, gender, and age. Journal of Occupational Health Psychology, 19(3), 376–386.

Allen, T. D., Herst, D. E., Bruck, C. S., & Sutton, M. (2000). Consequences associated with work-to-family conflict: A review and agenda for future research. Journal of Occupational Health Psychology, 5(2), 278–308.

Allen, T. D., Johnson, R. C., Kiburz, K. M., & Shockley, K. M. (2013). Work–family conflict and flexible work arrangements: Deconstructing flexibility. Personnel Psychology, 66(2), 345–376.

Anttila, T., Oinas, T., Tammelin, M., & Nätti, J. (2015). Working-time regimes and work-life balance in Europe. European Sociological Review, 31(6), 713–724.

Aycan, Z. (2008). Cross-cultural approaches to work-family conflict. In K. Korabik, D. Lero, & D. Whitehead (Eds.), Handbook of work-family integration (pp. 353–370). Academic Press.

Bainbridge, H. T., & Townsend, K. (2020). The effects of offering flexible work practices to employees with unpaid caregiving responsibilities. Human Resource Management, 59(5), 483–495.

Basham, R. (1976). Machismo. Frontiers: A Journal of Women Studies, 1(2), 126–143.

Berniell, I., Berniell, L., de la Mata, D., Edo, M., & Marchionni, M. (2023). Motherhood and flexible jobs: Evidence from Latin American countries. World Development, 167, 106225.

Boamah, S. A., Hamadi, H. Y., Havaei, F., Smith, H., & Webb, F. (2022). Striking a balance between work and play: The effects of work–life interference and burnout on faculty turnover intentions and career satisfaction. International Journal of Environmental Research and Public Health, 19(2), 809.

Brough, P., Timms, C., Chan, X. W., Hawkes, A., & Rasmussen, L. (2022). Work–life balance: Definitions, causes, and consequences. In T. Theorell (Ed.), Handbook of socioeconomic determinants of occupational health (pp. 473–487). Springer.

Brown, H., Kim, J. S., & Faerman, S. R. (2021). The influence of societal and organizational culture on the use of work-life balance programs: A comparative analysis of the United States and the Republic of Korea. The Social Science Journal, 58(1), 62–76.

Chant, S. (2002). Researching gender, families and households in Latin America. Bulletin of Latin American Research, 21(4), 547–575.

Chioda, L. (2016). Work and family: Latin American and Caribbean women in search of a new balance. World Bank Group.

De Bloom, J., Kinnunen, U., & Korpela, K. (2015). Recovery processes during and after work: Associations with health, work engagement, and job performance. Journal of Occupational and Environmental Medicine, 57(7), 732–742.

Eccles, J. (2009). Who am I and what am I going to do with my life? Personal and collective identities as motivators of action. Educational Psychologist, 44(2), 78–89.

Eiffe, F. (2021). Eurofound’s reference framework: Sustainable work over the life course in the EU. European Journal of Workplace Innovation, 6(1), 67–83.

Escobedo, A., & Wall, K. (2015). Leave policies in Southern Europe: Continuities and changes. Community, Work & Family, 18(2), 218–235.

Grotto, A. R., & Andreassi, J. K. (2024). When it’s better than expected: A quasi-experimental study of firm-provided paid parental leave and employee organizational commitment. The International Journal of Human Resource Management, 36(1), 80–102.

Greenhaus, J. H., & Beutell, N. J. (1985). Sources of conflict between work and family roles. Academy of Management Review, 10(1), 76–88.

Haas, L., & Rostgaard, T. (2011). Fathers’ rights to paid parental leave in the Nordic countries. Community, Work & Family, 14(2), 177–195.

Haar, J. M., Russo, M., Suñe, A., & Ollier-Malaterre, A. (2014). Outcomes of work–life balance on job satisfaction, life satisfaction and mental health: A study across seven cultures. Journal of Vocational Behavior, 85(3), 361–373.

Horner, M. (1990). The changing challenge: From double bind to double burden. New England Journal of Public Policy, 6(1), 47–64.

Idrovo Carlier, S., Leon Llorente, C., & Grau, M. (2012). Comparing work-life balance in Spanish and Latin-American countries. European Journal of Training and Development, 36(2/3), 286–307.

ISSP. (2012). Family and Changing Gender Roles IV Questionnaire. International Social Survey Programme.

ISSP. (2024). International Social Survey Programme source questionnaire.

Kanungo, R. N. (1982). Measurement of job and work involvement. Journal of Applied Psychology, 67(3), 341–349.

Kelly, M., Soles, R., Garcia, E., & Kundu, I. (2020). Job stress, burnout, work-life balance, well-being, and job satisfaction among pathology residents and fellows. American Journal of Clinical Pathology, 153(4), 449–464.

Kossek, E. E., Pichler, S., Bodner, T., & Hammer, L. B. (2011). Workplace social support and work–family conflict: A meta‐analysis clarifying the influence of general and work–family‐specific supervisor and organizational support. Personnel Psychology, 64(2), 289–313.

La Barbera, M., & Lombardo, E. (2019). “The long and winding road”: A comparative policy analysis of multilevel judicial implementation of work–life balance in Spain. Journal of Comparative Policy Analysis, 21(1), 9–24.

Lewis, S. (2003). Flexible working arrangements: Implementation, outcomes, and management. International Review of Industrial and Organizational Psychology, 18, 1–28.

Macdonald, S., & MacIntyre, P. (1997). The generic job satisfaction scale: Scale development and its correlates. Employee Assistance Quarterly, 13(2), 1–16.

Mannheim, B., Baruch, Y., & Tal, J. (1997). Alternative models for antecedents and outcomes of work centrality and job satisfaction of high-tech personnel. Human Relations, 50(12), 1537–1562.

Maslach, C. (2003). Job burnout: New directions in research and intervention. Current Directions in Psychological Science, 12(5), 189–192.

Meeussen, L., & Van Laar, C. (2018). Feeling pressure to be a perfect mother relates to parental burnout and career ambitions. Frontiers in Psychology, 9, 2113.

Moser, J. R., & Ashforth, B. E. (2021). My network, myself: A social network approach to work-based identity. Research in Organizational Behaviour, 41, 100155.

Noda, H. (2020). Work–life balance and life satisfaction in OECD countries: A cross-sectional analysis. Journal of Happiness Studies, 21(4), 1325–1348.

Paullay, I. M., Alliger, G. M., & Stone-Romero, E. F. (1994). Construct validation of two instruments designed to measure job involvement and work centrality. Journal of Applied Psychology, 79(2), 224–228.

Randell, R., Wilson, S., Woodward, P., & Galliers, J. (2010). Beyond handover: Supporting awareness for continuous coverage. Cognition, Technology & Work, 12(4), 271–283.

Schwartz, T., & McCarthy, C. (2010). The way we’re working isn’t working: The four forgotten needs that energize great performance. Simon & Schuster.

Snir, R., & Harpaz, I. (2004). Attitudinal and demographic antecedents of workaholism. Journal of Organizational Change Management, 15(5), 520–536.

Wheatley, D. (2017). Employee satisfaction and use of flexible working arrangements. Work, Employment and Society, 31(4), 567–585.

A study on how perfectionism affects career decision-making and anxiety in students

By: Lior Tweg (24-25)

Deciding on which career path to go down is a challenge faced by many students, but for perfectionists, it can be even more emotionally exhausting and high-pressure. Many different factors will influence a student’s choice-both individual and circumstantial (Savickas, 2002; Chen et al., 2023; Rudolph et al., 2019). In today’s digital age, it becomes even harder to avoid comparison to peers and feelings of inadequacy and anxiety, despite the individual’s own successes (Chakraborty, 2024). Influences of social media will mean an individual with perfectionistic tendencies already will experience heightened pressure to perform and make the “perfect” career choices. What is supposed to be an exciting time in a student’s life-entering the professional world, becomes one riddled with anxiety and negative emotions. 

A brief history of Perfectionism:

The definition of perfectionism is striving for flawlessness, having high personal standards for performance and being concerned over mistakes and expectations of parents (Flett & Hewitt, 2002). The concept of perfectionism has often been seen in terms of being “good” or “bad”, and the different definitions used in research has not helped decide whether perfectionism is positive or negative (Stoeber & Otto, 2006). Instead, it is better understood as a layered concept, which can be both positive and negative depending on the individual’s experience of it. The original research paper framing perfectionism as a complex concept, made up of different types of perfectionism was from Hamachek (1978), who argued perfectionism has two types: adaptive and maladaptive. These different types had different experiences associated with them, such as having high but realistic standards for adaptive perfectionists, while maladaptive perfectionists battle constant dissatisfaction and fragile self-esteem. Different distinctions between types of perfectionism have since expanded to account for whether the behaviours are directed outward or towards oneself (Hewitt & Flett, 1991), multiple different elements (Frost et al., 1990), as well as more recently, introducing a new model that can be applied to individuals from different cultures and backgrounds (Smith et al., 2016; Rahman et al., 2025).

This study

To understand how perfectionistic students experience career decision-making and anxiety in light of their tendencies, we interviewed nineteen Master’s students and one recently-graduated Undergraduate student about their experiences. The participants’ ages ranged from 22-47 and had a variety of different educational and occupational backgrounds. 

Findings

Through analysis of the interview data, we found that participants mentioned having high standards and wanting things to go according to the way they planned, and feeling distressed when this did not happen. Furthermore, participants mentioned procrastinating, either putting off tasks by doing something unrelated (yet still productive, such as cleaning) or something purely for comfort (such as watching a favourite TV show). Perfectionistic students mentioned wanting to show their superiors at work that they were capable in order to maintain a positive reputation, but also potentially to gain financial security (in the form of bonuses or better salaries). In their academic lives, the students mentioned the heightened pressure they faced to perform and get the best grades possible, while also mentioning that being in charge of their own schedules and timings increased their perfectionistic tendencies as they only relied on themselves. When asked about their job search experiences, participants mentioned struggling to find the “right fit”, either due to feelings of being underqualified or waiting for the “perfect” job, or due to feelings of indecisiveness. The students also mentioned that while on their hunt for jobs, the emotions associated with pre-and post-applications. During the pre-application phase, participants mentioned overthinking and anticipatory anxiety, causing them to spend extra time and devote extra energy into the application process. While post-application was riddled with rumination and threats to self-worth if they were rejected. 

What this means/Future directions

This research shows the importance of understanding lived perspectives of students in an understudied population (predominantly Master’s students), as they may feel heightened pressure and distress when choosing their career path compared to a non-perfectionist population. Understanding the way perfectionist students experience this stage of life can help us help them in future, by encouraging universities and other institutions to provide specialised careers advice and more effective coping strategies for students who experience career anxiety and distress (Kang et al., 2020). By aiding those students to overcome their internal challenges and understand that rejections and ambiguities are a natural part of choosing a career path, as well as knowing nothing needs to be permanent, this may help students with perfectionistic tendencies to alleviate some of their stress and see it for what it could be—a time full of promising potential. 

Final summary

In summary, the study showed that students with perfectionistic tendencies spoke of having high standards, but procrastinating on tasks sometimes, wanting to be seen as competent and gain financial security and recognition, while also balancing demands of their studies, such as having control over their schedule. When applying for jobs, these students mentioned feeling demoralised when receiving rejections, while some people said they were put off from applying if they did not feel they met all the criteria in the job applications, or did not apply because they were waiting for the perfect fit. Higher education institutions and careers services could help alleviate the added pressure students put themselves under (often unprovoked and unnecessarily) by helping students face these internal challenges and by helping them understand this is a natural part of the job search process.­

Blog References

Chakraborty, A. (2024). Navigating Career Anxiety in the Modern Age: Understanding Its Roots and Remedies. International Journal of Interdisciplinary Approaches in Psychology, 2(1), 13-24.

Chen, H., Liu, F., & Wen, Y. (2023). The Influence of College Students’ Core Self-evaluation on Job Search Outcomes: Chain Mediating Effect of Career Exploration and Career Adaptability. Current Psychology, 42(18), 15696–15707. https://doi.org/10.1007/s12144-022-02923-4 

Flett, G. L., & Hewitt, P. L. (2002). Perfectionism and maladjustment: An overview of theoretical, definitional, and treatment issues. In G. L. Flett, & P. L. Hewitt (Eds.), Perfectionism: Theory, research, and treatment (pp. 5-31). American Psychological Association. https://doi.org/10.1037/10458-001 

Frost, R. O., Marten, P., Lahart, C., & Rosenblate, R. (1990). The dimensions of perfectionism. Cognitive therapy and research, 14(5), 449-468.

Hamachek, D. E. (1978). Psychodynamics of normal and neurotic perfectionism. Psychology: A Journal of Human Behavior, 15(1), 27–33.

Hewitt, P. L., & Flett, G. L. (1991). Perfectionism in the self and social contexts: Conceptualization, assessment, and association with psychopathology. Journal of Personality and Social Psychology, 60(3), 456-470. https://doi.org/10.1037/0022-3514.60.3.456

Kang, M., Lee, J., & Lee, A. (2020). The effects of college students’ perfectionism on career stress and indecision: Self-esteem and coping styles as moderating variables. Asia Pacific Education Review, 21(2), 227-243. https://doi.org/10.1007/s12564-019-09609-w

Rahman, S. N., Allen, L. K., & Natoli, A. P. (2025). Predictive Invariance of the Big Three Perfectionism Scale (BTPS) Across Race when Predicting Mistake Rumination. Journal of Psychoeducational Assessment, 07342829251334269.

Rudolph, C. W., Zacher, H., & Hirschi, A. (2019). Empirical developments in career construction theory. Journal of Vocational Behavior, 111, 1–6. https://doi.org/10.1016/j.jvb.2018.12.003 

Savickas, M. L. (2002). Career Construction: A Developmental Theory of Vocational Behavior. In D. Brown (Ed.), Career Choice and Development (4th ed., pp. 149–205). Jossey-Bass. 

Smith, M. M., Saklofske, D. H., Stoeber, J., & Sherry, S. B. (2016). The big three perfectionism scale: A new measure of perfectionism. Journal of Psychoeducational Assessment, 34(7), 670-687. https://doi.org/10.1177/0734282916651539

Stoeber, J., & Otto, K. (2006). Positive conceptions of perfectionism: Approaches, evidence, challenges. Personality and social psychology review, 10(4), 295-319.

By Benjamin Finbow (24-25)

Reports suggests that nearly a quarter of all UK employees will have left their roles voluntarily by the end of 2025. This reads more than just a statistic, this is a costly drain of resources and finances, let alone the affect that this has on a teams morale, for graduates who often see their graduate scheme as a strategic step into the professional world, the retention risk is even higher. 

Hiring graduates into your company is a huge investment! On average companies spend upwards of £5000 on a graduate, before a single day of training or the managers’ lost time is factored in. Immense resources are poured into developing this young talent pipeline through these graduate schemes, yet so often these graduates do not stay beyond their graduate scheme.

So, what’s going wrong?

If companies are offering competitive salaries, what makes these early in career, talented individuals, look to leave so early?

This study looked to answer this very question, by sitting down with 12 graduates on graduate schemes across different business sectors, including finance, defence, automotive and recruitment to understand their experiences as to why they would stay. 

The findings were clear and powerful. A good salary was an important factor for many of the graduates; however it is rarely the main reason that they stay.  The real drivers of why people stay tended to be far more human centric. Below are the main experiences that the graduates reported. 

1. The psychological contract: a broken promise makes for broken trust

Before the graduate even signs the physical contract, an unspoken agreement is formed. In the academic world this is called the “psychological contract”, but this can just be thought of as a collection of promises and expectations set during the interview process. 

According to the graduates in this study, this is where the companies first go wrong, recruiters often find themselves over promising on exciting career development, hands-on-training and a fantastic work-life balance. However, once the graduate is in the position and these promises aren’t met, the trust in the graduate scheme is ruined – the psychological contract, broken. 

The study heard directly from graduates whose trust was broken: 

• One participant spoke to how they were promised a 6-month training program with rotations throughout the business, just to be told when they arrived that it was 2 months with no rotations at all. 
• Another was lured in by the recruiter on the promise of upwards of £100,000 in commission, only to be told when they arrived that no-one has ever made that much in their first year. 

When the psychological contract is broken, it’s not just disappointment for the graduate, it feels like a breach of their trust in the company. Once the trust is gone, good luck getting it back! 

• Where am I going here? 

You might think that career planning is an issue for people in their 30s and 40s, however, this study found how important career development planning is from day one for the graduates, they don’t just want a job – they need clear guidelines and a trajectory! 

Non-negotiable: A clear career path 

The graduates who were happiest on their schemes and most likely to stay were those who could see a clear path forward in their careers. One of the participants spoke excitedly about a linear progression from “assistant to underwriter to senior underwriter”. Another participant appreciated the clearness of their company policy, “Five years until you get a promotion, if you don’t get it then you’re not going to get it ever” – while harsh this did provide clear trajectory. 

In complete contrast, graduates at companies without a clear structure felt lost and ready to leave. They expressed fears of being “stuck in middle management”, or felt their career would be “stunted” if they stayed too long. One summed up their future slightly bleakly “I don’t really know, I guess I just won’t be a graduate at the end of the 18 months”. 

Learning cannot be an afterthought 

Aligned with a clear career path is the need for quality training to help the gradates progress. The most positive experience came from companies that truly invested in learning. One graduate described their scheme as “one continuous cycle of learning”, where the company would pay for “any course, be it sporting , professional or literally any scope of things”. 

However, many participants reported a frustrating conflict. They were told training was essential but were given no time during the workday to get it done. Instead, they were expected to learn on their own time, which meant that the training either wasn’t done or it was done with very minimal effort. 

• The old saying rings true: You don’t quit a job, you quit your boss 

The single biggest influence on a graduates day-to-day experience is their direct line manager. This relationship, more than any company policy, determines whether the graduate feels supported, valued and engaged.

A good manager is a game changer: 

• Hold regular meetings and be invested in the success of your graduate 
• Provide actionable feedback that actually helps the graduate improve 
• Make them feel valued! Listen to what they have to say 
  

Conversely, a poor or absent manager was a major cause for graduate dissatisfaction.  One participant revealed “We’re supposed to have a weekly or bi-weekly meeting, my manager hasn’t set one up this year”, with another participant saying “You just have to assume you’ve done a good job” because feedback was non-existent. 

So, how do you keep your graduates?

1. Draw a clear map – graduates need to see the journey ahead.
   
   Don’t let them try and figure it out and don’t leave it to chance. Create clear career ladders that show exactly what it takes to get to the next level. In addition to this, add a competency framework that outlines the specific skills they need to develop 
   
2. Protect their time to learn – not just a login to an eLearning platform!
   
    Block out time in their calendars specifically for training and development. Treat it as a core part of their job, not an extra task to be squeezed in at home. 
   
3. Train your managers!
   
   The most impactful change you can make is to train your manager. Teach them how to give useful feedback, how to mentor and how to support someone at the beginning of their career. Even, consider reverse mentoring to make the graduates feel heard and allow them to share their expectations with the graduate schemes.  

Graduate schemes are a brilliant investment in your talent of tomorrow, don’t waste them!  

By Paige Williams (24-25)

The existing body of literature focusing on career success is often based on older generations whose careers more typically follow clear, linear steps up the career ladder. Generation Z (‘Gen Z’, 1997-2012), however, is joining the workforce during a time marked by shifting norms, technological advancements, and a general sense of instability (Francis & Hoefel, 2018). More modern studies focusing on Gen Z indicate that the generation prioritizes different things for a number of reasons (Schroth, 2019). By understanding how Gen Z is currently operating at work, as well as the existing career theories, frameworks, and ideas, we can piece together Gen Z’s motivations and priorities in terms of ‘career success’.

Prior research distinguishes objective and subjective markers of career success, showing they are linked but unique in their own ways (Ng et al., 2005). Contemporary frameworks, such as Hall’s (2004) protean and Arthur’s (1994) boundaryless career, predict a stronger emphasis on values and autonomy than pay and title, but psychological lenses such as Deci and Ryan’s (2000) Self-Determination Theory, Demerouti el al.’s (2001) Job Demands-Resources, and Kristof’s (1996) Person-Organization Fit explain the importance of objective gains in the chase of subjective ends. Current research, however, lacks the breadth and depth of qualitative research, as many are completed with surveys as opposed to first-person narratives. We also know less about the specific competencies and conditions Gen Z believes they need in order to achieve their version of career success. Guided by this gap, this study asks a simple question with complex implications: How does Gen Z conceptualize career success?

Three focus groups, each consisting of 11 recruited participants, were conducted to answer the research question. Semi-structured interviews were run alongside photo elicitation, in which each participant was asked to bring an image that represented their conceptualization of career success (see the figure to the right for the images). From these conversations, three main themes (each with its own subthemes) were developed to explain how Gen Z defines career success.

1. Career Success as Well-being First: The first major theme developed is career success represented by prioritizing well-being over more traditional success markers, especially when individuals feel supported in and out of the workplace. Participants described success in felt, everyday terms: coming home without dread, having energy for life, and being treated as a whole person.
2. Career Success as Financial Gain: How Much is Enough?: The majority of participants associated monetary gain with career success, but the degree to how much money is desired varied among participants. Some had dreams of ‘being super rich one day’ and owning $300 million penthouses in New York City, while others found success in ‘get[ing] what I want without having to look at the price tag’. Across accounts, money was treated as instrumental; valued for what it enables (security, options, comfort), not as an end in itself.
3. Career Success as the Freedom to Choose: The third dimension of career success, according to the Gen Z participants, is having genuine control and freedom; whether it be time and place of work, over the pace and shape of roles, and/or over the path their careers take. Pauline simply stated, ‘I like freedom within my job’. Instead of being framed as an unrealistic, unrestricted freedom, the freedom was presented as manageable choices: enough control to balance work and life and to adjust when opportunity arises or values change.

Traditional, objective markers of success, such as pay, title, or promotion mattered because they enabled the subjective conditions participants counted as success. When forced to trade off, participants protected their well-being, livability, and agency and rejected opportunities that would threaten those conditions even if they promised higher status or income.

Implications

• Gen Z individuals need to define their ‘enoughness’
  • Set a concrete baseline for things like income, benefits, and scheduling that removes chronic stress from these factors. Writing down what ‘enough’ is is a beneficial skill that can be worked on and revisited throughout entire careers. As people change so do priorities, so constantly knowing and working on one’s ‘enough’ can help sustain success throughout all stages of careers.
• Run a Jobs Demands-Resources audit on any roles/offers
  • By knowing what features of the workplace may be obstacles instead of enhancers, contracts can be drawn up more efficiently and conversations around changes in the workplace can be more structured and evidence-based. A good offer/environment is one with a resource-demand balance, if not excess resources. This skill is not only helpful when negotiating contracts, but also throughout the role. Keep the audit alive and renegotiate when the balance feels off.
• Design a positive work environment that enables choice and supports relational goals
  • Offer time/location autonomy alongside clear deliverables and objectives to keep the flexibility within healthy, enforceable boundaries.
  • Monitor JD-R at the team level and adjust staffing or objectives before the overload leads to chronic strain.
  • Train and select for humane management, as well as have a form of checks and balances in the workplace.
  • Support the relational goals of their Gen Z employees by having systems in place that support familial obligations when needed (paid parental leave, job protection, caregiving leave)

The Way Forward

Looking forward, two key design changes can be made to extend this study. First, researchers should test the same question across subgroups of Gen Z (gender, culture, socioeconomic status) and individuals following non-traditional career paths (apprenticeships, community college, gig work, entrepreneurship). Doing so would clarify which themes generalize and where they may vary systematically. Second, adopt mixed-methods, longitudinal designs. Pairing the focus groups with solo interviews with additional diary entries to track how daily conditions change how career success is conceptualized would contribute richer data to analyze.

In closing, Gen Z’s conceptualization of career success is not anti-tradition/objectivity; it is using tradition to shape and mold to modern, subjective markers of success. Success is having the resources and autonomy to build a sustainable, values-aligned career, and the freedom to change when feeling stagnant or unsuccessful.

References

Arthur, M. B. (1994). The boundaryless career: A new perspective for organizational inquiry.

Journal of Organizational Behavior, 15, 295-306. https://doi.org/10.2307/259107

Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and

the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.

https://doi.org/10.1207/S15327965PLI1104_01

Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job

demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499–512.

https://doi.org/10.1037/0021-9010.86.3.499

Francis, T., & Hoefel, F. (2018). ‘True Gen’: Generation Z and its implications for companies.

McKinsey & Company.

Hall, D. T. (2004). The protean career: A quarter-century journey. Journal of Vocational

Behavior, 65(1), 1–13. https://doi.org/10.1016/j.jvb.2003.10.006Kristof, A. L. (1996). Person-organization fit: An integrative review of its conceptualizations,

measurement, and implications. Personnel Psychology, 49(1), 1–49.

https://doi.org/10.1111/j.1744-6570.1996.tb01790.x

Ng, T. W. H., Eby, L. T., Sorensen, K. L., & Feldman, D. C. (2005). Predictors of objective and

subjective career success: A meta-analysis. Personnel Psychology, 58(2), 367–408.

https://doi.org/10.1111/j.1744-6570.2005.00515.x

Schroth, H. (2019). Are you ready for Gen Z in the workplace? California Management Review,

61(3), 5–18. https://doi.org/10.1177/0008125619841006

By Lola Goldstein (24-25)

Gen-Z are facing a mental health crisis unlike any previous generation. Research shows that one in six Gen-Z experience depression and two in five experience anxiety, while the overall incidence of psychological distress has almost doubled in comparison to the two generations before. At the same time, Gen-Z consistently ranks mental health as one of the most pressing issues facing their generation, making it an issue that organisations cannot afford to ignore.

Born between 1996 and 2012, Gen-Z were the first generation to grow up with smartphones in hand. While this brought new opportunities, it also disrupted critical developmental experiences, including by limiting social learning and increasing sleep deprivation, ultimately resulting in significant changes in mental health. The first iPhone was released in 2007, and most homes had access to social media by 2012. This coincided with a peak in mental illness, with rates of teen depression more than doubling between 2010 and 2015. However, these mental health challenges have not been left behind in adolescence but now shape Gen-Z’s working lives, creating severe implications for employers.

Employee well-being has received growing attention in recent years, with organisations acknowledging the far-reaching impact this can have. Work well-being involves both the physical and psychological health of employees in the workplace. Low employee well-being can be highly costly for organisations, resulting in higher turnover intentions, reduced retention, absenteeism and presenteeism. On the other hand, organisations that invest in well-being can experience productivity gains of up to 20%, as employees who handle workplace stress better show greater levels of creativity, engagement, and innovation. Therefore, investing in employee well-being is not just ethically important, it also creates a competitive edge. 

Gen-Z already make up 27% of the workforce, and by 2035, they are projected to be the most dominant cohort. Therefore, it is crucial that organisations understand what drives this generation’s well-being at work. 

The Study

This research set out to explore various contributors to Gen-Z’s work well-being in order to determine which are the most important. These results provide valuable insights that can help organisations to direct their resources more effectively, supporting the well-being of this generation while strengthening organisations as a whole.

Several workplace factors were explored with established links to employee well-being including: a combination of high job demands and low job control (job strain), social support, and an imbalance between the effort expended at work and rewards received. Factors specifically associated with Gen-Z were also investigated, including work-life balance, the alignment between an individual and their job (person-job fit), the alignment between individuals and organisations (person-organisation fit), and psychological safety. 

To establish these findings, 104 Gen-Z employees (aged 20-29) were recruited to compete and online survey assessing their levels of work well-being and scores on each workplace factor. 

What the Research Found

The results were clear: the strongest predictors of Gen-Z’s work well-being were person-job fit, person-organisation fit and social support. After these was work-life balance, followed by psychological safety. Meanwhile, traditional stressors like high job demands and low job control or imbalances between effort and reward were less influential for this generation. Interestingly, working in the education sector is also linked to higher well-being among Gen-Z employees.

What This Means for Organisations

These findings emphasise the vital role of “fit” for Gen-Z’s well-being, highlighting the need for harmony beteen an employee and their work environment. By putting energy into improving this alignment, organisations are likely to see positive improvements in the well-being of these employees.

To enhance person-job fit, organisations should ensure they are matching their Gen-Z employees with roles that reflect their skills, abilities and interests. This can be done through recruitment and selection processes that prioritise this alignment, helping to place people where they can thrive. On-the-job training should also be tailored to help employees to meet the required skills for the role, further promoting person-job fit. 

Person-organisation fit can also be improved through the hiring process, including by clearly and openly communicating the organisation’s mission, values, and culture to candidates in order to attract employees with similar priorities. For instance, showcasing corporate social responsibility efforts that go beyond typical business goals can attract Gen-Z candidates who are looking for meaningful work. 

The results also highlight the importance of creating supportive work environments. This can be achieved through initiatives as mentoring programmes, peer networks, and management practices that provide guidance, feedback, and encouragement. Providing this kind of social support can help employees combat job stress and is therefore a powerful way to improve Gen-Z’s work well-being.

Beyond these three essential elements, work-life balance is also another valuable focus for organisations, given its key role in supporting Gen-Z’s work well-being. This generation are thought to have re-defined work-life balance, viewing this as an integration of professional and personal life that enhances their psychological well-being, rather than treating them as completely separate entities. Therefore, organisations can help maintain this balance by providing more flexible work options, like hybrid or remote arrangements, along with clear boundaries around work-related communication.  

Why It Matters

Overall, these findings points to generational nuances in the predictors of work well-being, specifically highlighting the importance of “fit” and social support for this generation. This reflects Gen-Z’s greater emphasis on intrinsic motivators, such as meaning and values alignment, as well as positive relationships at work, over more traditional drivers like financial rewards alone. Therefore, this provides a useful guide for organisations looking to improve the well-being of the newest generation to enter their workforces. Organisations that understand and act on these priorities are likely to see notable improvements in the well-being of their Gen-Z employees, ultimately strengthening their organisation as a whole. 

By James Holden (24-25)

Artificial Intelligence (AI) is transforming workplaces at an astonishing pace. Tools like ChatGPT, Microsoft Copilot, and automated decision-making systems are reshaping how we recruit, communicate, and measure performance. For some employees, these tools feel exciting and liberating. For others, they spark anxiety, confusion, or fear of being replaced.

As organisations race to adopt AI, an important question arises:  what does the introduction or increasing use of AI mean for the wellbeing of employees?

This research explored this question by looking at flourishing, a broad measure of workplace wellbeing. Flourishing is more than the absence of stress; it is about employees feeling good and functioning well: being engaged, connected to others, finding meaning in what they do and being able to grow and contribute at work. In today’s competitive landscape, flourishing employees are more innovative, more productive, collaborate more and are more likely to stay. In short, flourishing isn’t a “nice to have”, it’s vital for organisational success.

But flourishing is under pressure in the age of AI. The very tools designed to make work easier can create new kinds of stress, often called  technostress. This research examined how AI-related technostress affects workplace flourishing, and whether personality plays a role in how employees cope with it.

The stress side of AI

When we think of ‘stress at work’, we might imagine long hours or difficult bosses. But technology itself can be a major stressor. AI brings some unique challenges:

• Techno-complexity  – when systems feel confusing, constantly changing, or difficult to master.
• Techno-insecurity  – when people fear that AI could replace their job or devalue their skills.
• Techno-overload  – when technology speeds up the pace of work and volume of information, creating pressure to do more in less time.

Most of us have felt at least one of these recently. Learning a new system that seems baffling. Wondering if AI will make your role redundant. Or feeling pressured to be ‘always on’ because technology never rests.

This study set out to see whether these stressors predict lower flourishing at work, and whether some people are more vulnerable than others.

Personality matters

Psychologists often point out that stress is not just about what happens to us, but how we interpret and react to it, thus this study looked at  neuroticism, one of the “Big Five” personality traits. People high in neuroticism tend to experience negative emotions more strongly and worry more about potential threats.

What the research covered

Almost 200 working adults in the UK from a broad range of industries  were surveyed and asked three simple things:

1. how much they were  flourishing at work  (feeling good and functioning well),
2. how much  AI-related pressure  they felt in three areas—complexity  (hard to learn),  insecurity  (fear of being replaced), and  overload  (AI pushing the pace), and
3. their  personality, focusing on  neuroticism  (tendency toward worry/negative emotion).

Everyday background factors like  age, education, income comfort, industry, and  risk tolerance  (how comfortable people feel taking risks) were also recorded. Then standard statistical models were run to see what actually predicts flourishing, and whether neuroticism  changes  the impact of those AI pressures. 

What were the results

• No direct AI-pressure hit to flourishing. When the background factors, were accounted for, none of the three AI-related stressors (techno-complexity, techno-insecurity, or techno-overload) directly predicted lower flourishing.

• Personality mattered. People higher in neuroticism reported lower flourishing overall. Meanwhile, people with higher risk tolerance  reported  higher flourishing. These were  direct  links with flourishing (i.e. how people felt and functioned at work); they weren’t tied to higher or lower AI stress per se.

• No “amplifier” effect.  When it was tested whether neuroticism  amplified  the impact of different AI-related technostressors, it didn’t. The interaction terms were not significant.  

In short: in this mixed UK sample, current AI pressures didn’t knock flourishing down, but who you are (especially lower neuroticism and higher risk tolerance) did relate to how well you felt you were thriving at work.  

Why this matters for organisations

A common assumption is that “AI stress will undermine wellbeing.” These data suggest: not necessarily—at least not for flourishing. Flourishing reflects resources such as support, meaning, growth, and connection. Removing stressors is helpful, but it is often  not sufficient; flourishing grows where resources are deliberately built.

• If your goal is to protect flourishing, don’t focus only on “removing stressors.” Instead, build resources around people and teams (e.g. clarity, support, autonomy, learning, recognition). These are the soil flourishing grows in.  

• Neuroticism  is a reliable risk flag for lower flourishing. That doesn’t mean “the person is the problem”; it means they’ll benefit more from  predictability, reassurance, and quick access to support. 

• Risk tolerance  looks like a quiet  asset. People comfortable with uncertainty tend to  flourish more  during change. Harness that, without glorifying unnecessary risk.  

Practical steps leaders can take (now)

1. Resource first, tech second.
   Pair AI rollouts with  short, targeted training, easy help channels, and  manager check-ins. Don’t just deploy tools, deploy  support. 

2. Tune your comms to different people.
   • For employees higher in worry/uncertainty: give  clear roadmaps, timelines, and “what this means for your role” briefings; signpost  emotion-regulation/mindset micro-skills  (10–15 minutes is enough).
   • For higher risk-tolerance staff: involve them in  early pilots  as  AI champions  and co-designers.  

3. Protect boundaries.
   AI can speed everything up. Set norms for  notification management, response times, and  right-to-disconnect practices so pace doesn’t quietly become overload.  

4. Make flourishing visible.
   Track simple, actionable indicators (e.g.,  learning progress,  team belonging,  manager support). Celebrate  human strengths (e.g. judgement, empathy, creativity), so people feel valued alongside AI.  

Final thought

AI is here to stay, but its people impact is not fixed. In this study,  AI didn’t automatically erode flourishing. What mattered more was the  human side: stable dispositions like neuroticism and risk tolerance, and the  resources  organisations provide. If leaders invest in clarity, capability, and care, employees can keep flourishing, even as AI evolves. That’s not just good for people; it’s good strategy.

By Ellyn Murakami (24-25)

Why is this study important?

Organisations continue to navigate volatile, uncertain, complex, and ambiguous (VUCA) challenges, such as globalisation, digitisation, and health crises, which require leaders to adapt and exhibit new behaviours to motivate and mobilise others effectively (Lawrence, 2013). However, perceptions of how well leadership development initiatives equip leaders to handle such complexities are consistently low. In 2014, McKinsey found only 7% of senior leaders believed they were developing global leaders effectively, and, similarly, Deloitte found only 13% of organisations thought they had done a quality job training their leaders (Gurdjian et al., 2014; Schwartz et al., 2014). These numbers are alarming considering that in 2018, it was estimated that organisations spent $370 billion on leadership development solutions globally with the USA alone spending $169 billion (Training Industry, 2020). Whilst there has been a surge of scientific interest in leadership development over the last 20 years, the field remains underdeveloped compared to the general leadership field (Day, 2024). Thus, this study aims to identify the enablers and barriers to effective leadership development in the 21st century.

What was found?

            17 individuals from seven industries were interviewed to explore their experiences of leadership development initiatives. To ensure diverse perspectives, participants were recruited across three roles: commissioners (clients of leadership development vendors), providers (E.g., consultants, in-house leadership development professionals, etc.), and participants of leadership development programmes. 

            Six themes were identified, representing the complexity of effective leadership development in the 21^st century (see Figure 1.) Effective leadership development works as a system, influenced by what happens before, during, and after a programme. Success also depends on having a well-designed measurement plan and on the wider organisational context.

Figure 1

Themes, subthemes, and illustrative quotes.

Note: Green text represents enablers and red text represents barriers. 

1. Leadership Development System

Participants consistently emphasised that leadership development works best when treated as a system, not just a course. This means it is crucial to consider what happens before, during, and after programme, how success is measured, and the organisation’s context. In this view, development is more of an ecosystem and ongoing process than a one-off classroom event.

2. Before a Leadership Development Programme

Common barriers to effective leadership development before a programme starts are not properly diagnosing the organisation’s strategy and leadership gaps and requiring participation. Without this, programmes feel disconnected from strategy, may not address the organisation’s needs, and participants may not know why they’re there. Also, requiring attendance also undermines motivation, which can negatively affect the whole group.

3. During a Leadership Development Programme

Three main enablers stood out during programmes:

1. In-person cohorts over time: participants shared that building trusting relationships and having sufficient time during and between sessions to learn, connect, and reflect were pivotal in making learning stick. 
2. Self-awareness: almost everyone cited this as the most impactful skill to learn and as a prerequisite for future leadership growth.
3. Experiential learning: challenging projects where participants applied new skills were seen as the most effective.

4. After a Leadership Development Programme

Many participants shared the importance of ongoing support after leaving the classroom. They noted that learning often fizzles due to not having enough time to continue applying and unsustained accountability, whether that comes from themselves, the programme, their leader, or the organisation. Participants also suggested check-ins, bite-sized follow-up workshops, or alumni meetups as ways to keep momentum going.

5. Measurement Plan

            Designing a measurement plan for leadership development initiatives is necessary to evaluate their effectiveness; however, this is rarely done and is challenging. Participants highlighted the importance of identifying key metrics and measuring a baseline, followed by immediate and longer-term evaluation to determine the lasting impact.

6. Context of the Organisation

Many participants emphasised that organisational culture and leadership behaviours strongly impact their development. Without support from managers or when leaders fail to model the behaviours participants are learning, development efforts quickly lose traction. Conversely, when senior leaders participate in and sponsor initiatives, it signals priority, builds a common language, and reinforces change.

What does this mean?

The study found that leadership development is most effective when approached as a holistic system with enablers and barriers at every stage before, during, and after programmes, and within the measurement plan and organisational context. Based on these findings, leadership development systems can be classified into four types. The programme and the organisational context are crucial because participants reported spending most of their working lives embedded in the organisational context, with only limited time devoted to formal programmes. As a result, even well-designed programmes may not compensate for an unsupportive organisational environment, just as a strong context may be insufficient to make up for a poorly designed programme. This interdependence is illustrated in Figure 2, which depicts four leadership development system types.

Figure 2

Leadership Development System Types

Becoming aware of which leadership development system type an organisation fits is the first step in identifying what needs to change to develop leaders most effectively. The development of an assessment would allow organisations to identify their type. If they are not in the optimal zone, this evaluation can highlight the weak components that need improvement and offer solutions.

What can organisations do going forward?

Organisations should approach leadership development holistically to ensure the most effective use of the time and money invested. Specifically, some recommendations are:

• Participants in leadership development systems should integrate new behaviours and leadership goals into their personal development plans to maintain priority and ensure accountability.
• Managers should support their team members’ leadership development by encouraging participation in growth opportunities, protecting time to practise new skills, and reinforcing accountability by sharing feedback.
• Managers and organisational leaders should model desired behaviours by participating in and sponsoring leadership development systems.
• Organisations should partner with Organisational Psychologists to diagnose needs and design, implement, and evaluate leadership development initiatives.

            In summary, the study found that leadership development is most effective when approached as a holistic system. This allows organisations to prioritise enablers and address barriers at every stage before, during, and after programmes, and within the measurement plan and organisational context. Viewed this way, leadership development becomes more than individual programmes: it becomes a system that helps leaders and organisations reach their full potential.

References

Day, D. V. (2024). Developing leaders and leadership: Principles, practices, and processes (First). Palgrave Macmillan Cham. https://doi.org/10.1007/978-3-031-59068-9

Gurdjian, P., Halbeisen, T., & Lane, K. (2014). Why leadership development programs fail. https://www.mckinsey.com/~/media/mckinsey/featured%20insights/leading%20in%20the%2021st%20century/why%20leadership%20development%20programs%20fail/why%20leadership%20development%20programs%20fail.pdf?shouldIndex=false

Lawrence, K. (2013). Developing leaders in a VUCA environment. http://www.execdev.unc.edu

Schwartz, J., Bersin, J., & Pelster, B. (2014). Global human capital trends 2014 – Engaging the 21st-century workforce. https://www.deloitte.co.uk/makeconnections/assets/pdf/global-human-capital-trends-2014.pdf

Training Industry, Inc. (2020). The size of the training industry. https://trainingindustry.com/wiki/learning-services-and-outsourcing/size-of-training-industry/

By Alice Wallace (24-25)

Introduction 

Burnout remains one of the biggest challenges in healthcare, with more than one in three professionals reporting symptoms during their careers (Nagarajan et al., 2024). Long hours, emotional demands, and exposure to distressing situations place heavy strain on staff – reducing clinical judgement and increasing the risk of errors (Matsuo et al., 2022). These pressures highlight the need to support the workforce, with artificial intelligence (AI) emerging as a transformative tool for improving efficiency, accuracy, and patient outcomes (Amann et al., 2020). AI is already making tangible contributions across healthcare. It has demonstrated high accuracy in diagnosing a range of conditions: hypertension, diabetes, Alzheimer’s disease, and several cancers. Beyond diagnostics, AI is advancing precision medicine by tailoring treatments to patient’s genetic and lifestyle choices (Huang et al., 2018). 

Despite these benefits, adoption of these nuanced technologies is not a linear process. Uptake depends on the people who must work with AI in demanding environments. Many healthcare staff report concerns about ethics, accountability, and risk (Warrington & Holm, 2024); these perceptions can strongly shape willingness to engage with AI (Choudhury, 2022). Dingel et al. (2024) found that higher perceptions of risk were linked to lower willingness to adopt AI-enabled decision support systems. While these concerns highlight important organisational challenges, it is important to consider the personal resources clinicians bring to their roles. Individual factors such as occupational self-efficacy (i.e., the confidence clinicians have in their ability to manage complex challenges) can shape how staff respond to new technologies (Rigotti et al., 2008). Kuper et al. (2025) found that clinicians with greater confidence in their own judgement were less likely to rely on AI when classifying skin images as benign or malignant – suggesting that confidence may reduce willingness to engage with technological support. 

Building on the current research, this study seeks to answer two key questions: (1) How does perceived risk affect clinicians’ willingness to use AI; and (2) Does occupational self-efficacy impact this relationship?

Methods

This research was conducted as part of a MSc in Occupational Psychology at City, University of London. A total of 125 participants took part, consisting of both qualified healthcare professionals (i.e., Nurses, Paramedics, and Psychiatrists) and students completing their clinical placements (i.e., Nursing, Midwifery, and Medicine). Recruitment was carried out using several online platforms: Facebook, Instagram, LinkedIn, and Reddit). Additional recruitment took place through university channels, via student and staff mailing lists. 

The study was hosted online, where participants completed three main questionnaires: risk perception (i.e., concerns about safety or errors), willingness to use AI (i.e., intentions to adopt these tools), and occupational self-efficacy (i.e., confidence in managing workplace challenges). To ensure the results were reliable, several other factors that might influence attitudes towards AI was also considered: age, gender, clinical experience, student status, risk aversion, technology literacy, and AI literacy. Including these controls helped rule out alternative explanations and provided a clearer picture of the psychological factors most relevant to AI adoption. 

Results

Approximately one-third of participants (31.2%) reported using AI in their clinical practice or placement, suggesting that widespread integration of these tools is relatively still limited. The results highlighted four key factors that influenced these individuals’ willingness to adopt AI in their practice…

• Student status: Students were significantly more willingness to use AI compared to professionals. This suggests that openness to these technologies may vary across stages of professional development. 
• AI literacy: This captures individuals’ awareness and understanding of how AI systems operate. Here, clinicians and participants with higher levels of AI literacy were more willing to adopt these tools in their practice. 
• Technology resistance: The measure incorporates a reluctance towards adopting new technologies. The findings showed that participants with higher technology resistance were less willing to engage with AI. 
• Risk perception: This reflects how individuals evaluate the potential dangers or uncertainties associated with AI. Participants who had higher risk perceptions of AI were less willing to use these tools in practice.

Discussion 

The findings of this study reinforced that the psychological and organisational factors play an important role in shaping AI adoption within healthcare settings. Risk perception emerged as an important predictor: clinicians and students who viewed AI as uncertain or unsafe were less inclined to adopt these technologies. This is consistent with wider evidence showing that in high-stakes environments such as healthcare, potential losses often carry more weight than possible gains (Kahneman & Tversky, 1979). In practice, this reflects a professional culture that prioritises patient safety and accountability (Warrington & Holm, 2024). 

Alongside risk, AI literacy emerged as the strongest influence on willingness to adopt these technologies in clinical practice. These findings extend previous work with nursing students, where Sumengen et al. (2024) demonstrated that AI literacy was an important factor influencing willingness – the present study extends these findings to a wider range of healthcare professions. Additionally, students were more willing to adopt that compared to current healthcare professionals. This suggests that openness to these technologies seems to vary at different stages of an individual’s professional development. These findings highlight the need for structured training that develops individuals’ confidence and competence in using AI, ensuring that both current and future professionals are adequately supported. 

Contrary to expectations, higher occupational self-efficacy was linked to reduced willingness to adopt AI. This finding suggests that clinicians who are more confident in their own judgement are less willing to rely on AI, as they place greater trust in their own expertise than in external technological support. While self-efficacy is usually seen as a protective resource that fosters resilience (Bandura, 2001), in this context it may inadvertently limit openness to innovation. 

Together, these findings highlight that adoption ultimately depends on the interplay of psychological resources, professional identity, and organisational culture. Addressing an individual’s perceptions of risk, enhancing AI literacy, and embedding supportive organisational practices are important here. By prioritising these factors, healthcare systems can foster the meaningful integration of AI that strengthens rather than undermining clinical practice.

Blog references

Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. I. (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-01332-6

Bandura, A. (2001). Social Cognitive Theory: an Agentic Perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1

Choudhury, A., Asan, O., & Medow, J. E. (2022). Effect of risk, expectancy, and trust on clinicians’ intent to use an artificial intelligence system — Blood Utilization Calculator. Applied Ergonomics, 101, 103708. https://doi.org/10.1016/j.apergo.2022.103708

Dingel, J., Kleine, A., Cecil, J., Sigl, A., Lermer, E., & Gaube, S. (2024). Predictors of Healthcare practitioners’ intention to use AI-Enabled Clinical Decision Support Systems (AI-CDSSS): A Meta-Analysis based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Preprint). Journal of Medical Internet Research. https://doi.org/10.2196/57224

Huang, C., Clayton, E. A., Matyunina, L. V., McDonald, L. D., Benigno, B. B., Vannberg, F., & McDonald, J. F. (2018). Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy. Scientific Reports, 8(1). https://doi.org/10.1038/s41598-018-34753-5

Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263. https://doi.org/10.2307/1914185

Küper, A., Lodde, G. C., Livingstone, E., Schadendorf, D., & Krämer, N. (2025). Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: an Experimental Online Study Among Dermatologists (Preprint). Journal of Medical Internet Research, 27, e58660. https://doi.org/10.2196/58660

Matsuo, T., Yoshioka, T., Okubo, R., Nagasaki, K., & Tabuchi, T. (2022). Burnout and its associated factors among healthcare workers and the general working population in Japan during the COVID-19 pandemic: a nationwide cross-sectional internet-based study. BMJ Open, 12(11), e064716. https://doi.org/10.1136/bmjopen-2022-064716

Nagarajan, R., Ramachandran, P., Dilipkumar, R., & Kaur, P. (2024). Global estimate of burnout among the public health workforce: a systematic review and meta-analysis. Human Resources for Health, 22(1). https://doi.org/10.1186/s12960-024-00917-w

Rigotti, T., Schyns, B., & Mohr, G. (2008). A short version of the Occupational Self-Efficacy Scale: Structural and Construct Validity across five countries. Journal of Career Assessment, 16(2), 238–255. https://doi.org/10.1177/1069072707305763

Sumengen, A. A., Subasi, D. O., & Cakir, G. N. (2024). Nursing students’ attitudes and literacy toward artificial intelligence: a cross-sectional study. Teaching and Learning in Nursing. https://doi.org/10.1016/j.teln.2024.10.022

Warrington, D. J., & Holm, S. (2024). Healthcare ethics and artificial intelligence: a UK doctor survey. BMJ Open,14(12), e089090. https://doi.org/10.1136/bmjopen-2024-089090

By Dela Glevey (24-25)

When you think about getting ready for work, what’s on your mind? Picking an outfit? Checking your diary for the day ahead? For many Black women, one of the first questions is: what will my hair say about me today?

That might sound small, but it’s not. Hair, particularly Black hair, is never “just hair”. It is loaded with identity, heritage and culture. While in the workplace, it can also be a source of judgement, bias and daily stress. Recent research has set out to explore how Black British women navigate their hair choices, professional image and identity at work, here’s what the latest study finds.

Why Hair Matters at Work

To understand why hair matters, we need to step back. For centuries, Eurocentric styles have been pushed as the standard of beauty. In workplaces these standards have shaped what it means to be “professional”. Straight, sleek hair is seen as neutral, tidy and respectable. While natural Afro-textured styles (braids, twists, Afros, locs etc) are seen as unruly, distracting and “unprofessional”.

The evidence backs this up. The Black British Voice project (2023) found almost all respondents (98%) felt pressure to change themselves in the workplace, including hair, to “fit in”. The Broken Ladders Report (2022) found a quarter of women of colour had to alter their hair at work. While, research has shown natural styles are rated less professional or employable than straight styles by hiring managers (Donahoo, 2022; Koval & Rosette, 2020; De Leon, 2023).

These findings highlight what many Black women already know: hair is never just about style. It influences how they are seen, how they feel and the opportunities available to them.

The study

Despite growing recognition of hair bias in the US, there is a vast lack of UK focused research. To address this, 15 Black British women working across industries took part in interviews and a photograph exercise. Participants shared two photos: one when they felt “most like me” and one where they felt “most professional”.

The contrast was powerful. The simple exercise highlighted the tension between showing up as themselves, using words around authenticity and confidence in the “most like me” map, while words use for the “professional” photo spoke to pressures to conform to workplace expectations.

Figure 1 “Most like me” (top) and “Most professional” (bottom) word clouds

From the interviews three overall themes were developed- Spheres of Influence, Strategic Styling and Navigating the Personal Journey. However, two main overarching ideas stood out: the daily managing of hair and identity and the longer “hair journey” across their careers.

Finding 1: Managing hair and Identity

The first key finding was the sheer amount of thought and energy that went into managing hair on a daily basis. The women described a constant balancing act, managing external perceptions and internal anxieties. Interviews, client meetings or senior audiences often shaped their styling decisions, with Eurocentric looks favoured to minimise risk of questions, touching and doubts over their credibility. This daily management was rarely about preference, instead a strategy for avoiding negative stigma, stereotypes or unwanted attention. In practice hair became a tool of impression management, understood to remove hurdles and allow them to stand out for their work. Echoing Social-Identity Based Impression Management (SIM;Roberts, 2005), which describes how people from marginalised groups manage aspects of their identity to “fit in.”

The cost of managing, however, was high. Participants spoke of planning hairstyles weeks in advance, sticking to consistent and predictable ‘office safe’ looks, or dealing with the constant low-level anxiety of wigs slipping or curls frizzing. This drained energy that could otherwise be used on their work.

Finding 2: The “Hair Journey”

Beyond daily management, women also described a longer “hair journey” across their careers. Early in their careers, most adopted conservative, Eurocentric styles as a form of protection. Straightened or tied-back hair was viewed as the safest way to establish credibility and avoid being singled out.

But over time many women described a shift. With greater seniority, life experience, or personal turning points, they began to embrace authenticity. For some, this gave them freedom to wear natural styles, feeling they had earned the right to wear their hair naturally. Others mentioned milestones such as parenthood, a new job, relocation or even the pandemic as moments which inspired them to reconsider hair choice.

The sectors they worked in also mattered. Finance and fashion were described as stricter, with unwritten Eurocentric norms, while teaching and creative fields were seen as more open. This suggests both workplace culture and career stage shape how black women feel. Supporting what Black Feminist Thought (BFT;Collins, 2009) proposes, these choices are not just personal but shaped by wider systems. What is seen as “professional” is not neutral, but rooted in whiteness and many women describe having to unlearn this thinking and rebuild confidence in their natural selves.

Practical Implications

So, what can you do with all this? For Black women, these strategies shouldn’t be necessary, but supportive networks can help ease the burden of code-switching and build confidence. For colleagues, respect boundaries, avoid intrusive questions and challenge bias when you see them. For leaders, step up and use your influence to model inclusion. For organisations, review your policies, train managers and hiring teams on hair bias, ensure representation and co-design solutions appropriate for your workplace. Why not make a visible first step and adopt the Halo Code. The goal? Workplaces where Black women don’t need to second-guess their hair and can turn up authentically.

Conclusion

This study showed for Black Women hair is not just about style, it is central to their identity, confidence and how professionalism is judged. The findings highlight two key threads: the daily effort of managing their hair and the longer “hair journey” over their career. Both reflect how Eurocentric pressures still shape workplace expectations. While the findings support SIM and BFT they also suggest there is an emotional weight not fully captured by either theory. Making space for this issue will not only allow Black women to show up fully, but in doing so create more inclusive, creative and productive workforces.

References

Black British Voice Project. (2023). In Black British Voice (pp. 1–104). University of Cambridge. https://www.bbvp.org/

Collins, P. H. (2009). Black Feminist Thought: Knowledge, Consciousness, and the Politics of Empowerment. Routledge. https://doi.org/10.4324/9780203900055

De Leon, M. (2023). Workplace Hair Acceptance Report. In https://www.worldafroday.com/wp-content/uploads/2023/09/Workplace-Hair-Acceptance-Report-2023.pdf.

Donahoo, S. (2022). Working with style: Black women, black hair, and professionalism. Gender, Work & Organization, 30(2), 596–611. https://doi.org/10.1111/gwao.12838

Gyimah, M., Azad, Z., Begum, S., Kapoor, A., Ville, L., Henderson, A., & Dey, M. (2022). Broken Ladders: The myth of meritocracy for women of colour in the workplace. Fawcett Society and Runnymede Trust. https://cdn.prod.website-files.com/61488f992b58e687f1108c7c/628cf1924ac4e10b1ba8917b_Fawcett%20%26%20Runnymede%20Trust%20-%20Broken%20Ladders%20(final).pdf

Halo Collective. (n.d.). Hair Discrimination in Workplace. Halo Collective. Retrieved September 2025, from https://www.halocollective.co.uk/halo-workplace

Koval, C. Z., & Rosette, A. S. (2020). The Natural Hair Bias in Job Recruitment. Social Psychological and Personality Science, 12(5), 194855062093793. https://doi.org/10.1177/1948550620937937

Roberts, L. M. (2005). Changing Faces: Professional Image Construction In Diverse Organizational Settings. Academy of Management Review, 30(4), 685–711. https://doi.org/10.5465/amr.2005.18378873

By Archie Allen (24-25)

Artificial Intelligence (AI) is no longer a futuristic concept, it is here, shaping how organisations work, make decisions, and compete. From automating repetitive tasks to enhancing data-driven insights, AI has the potential to transform entire industries. But as organisations rush to adopt these tools, an equally important question arises: what kind of leadership do we need in this new era?

That was the central focus of my research. For my MSc dissertation, I interviewed twelve senior leaders and leadership development professionals across industries, from healthcare to finance to technology, to explore what human leadership looks like in the AI era. The answers were clear: leadership needs to become more human than ever.

Why leadership needs to change

AI adoption is happening at speed. Unlike past technological revolutions that unfolded over decades, today’s shift is taking place in just a few years. Leaders are navigating uncharted territory: employees are unsure about how AI will affect their roles, organisations face ethical dilemmas around fairness and transparency, and many people are simply overwhelmed by the pace of change. My research shows that what people most want from leaders today is not more data or more certainty, but more honesty, empathy, and human connection.

What was the research?

To answer the research questions, what human competencies are required to lead in the AI era, and why are they necessary, I conducted twelve in-depth interviews with senior leaders and leadership experts. The participants ranged from Chief HR Officers and Managing Directors to organisational psychologists and leadership consultants. Together, they represented decades of experience leading teams and shaping leadership development. The interviews were analysed using reflexive thematic analysis, which looks for patterns of meaning across conversations. From this, three themes emerged that capture the essence of human leadership in the AI era: human leadership, relational leadership, and visionary leadership.

Theme 1: Human Leadership

The first theme centred on integrity, empathy, and credibility. Participants described transparency as vital, even when the message is difficult. Employees want leaders who show up as real people, not polished robots. Empathy was also seen as critical, helping leaders respond to the mix of excitement, fear, and resistance that AI often generates. Finally, many warned against letting AI erode credibility. Leaders who rely too heavily on AI-generated communication risk appearing inauthentic and losing trust. The message is clear: in a world where machines process information faster than us, credibility comes from staying unmistakably human.

Theme 2: Relational Leadership

The second theme focused on how leaders relate to others. Humility was described as a powerful quality. Leaders who admitted uncertainty or mistakes were seen as strengthening connection rather than weakening authority. This vulnerability encouraged others to be open too, creating a culture of learning rather than fear. Psychological safety was also seen as essential. In the context of AI, employees need reassurance that experimenting, failing, and asking questions are not only allowed but expected. Leaders who modelled openness and normalised mistakes created the conditions for innovation and adaptability.

Theme 3: Visionary Leadership

The final theme highlighted the role of vision. When vision was meaningful, it helped anchor people during disruption by connecting daily work to a bigger, human purpose. Leaders who could tell this story reduced anxiety and built trust. But when vision was absent, employees were left to fill the gaps with their own narratives, often fuelled by fear and uncertainty. The lesson is that leaders do not need to have all the answers, but they do need to provide a sense of direction that feels steady, human, and hopeful.

Why these findings matter for organisations

The success of AI adoption depends not just on the technology itself, but on how people respond to it. If employees feel anxious, excluded, or silenced, they are less likely to engage with new systems. But if they feel heard, supported, and inspired, they are more willing to experiment, adapt, and innovate. This means organisations need to rethink how they prepare their leaders. Leadership development should make empathy, humility, and ethical communication core priorities, not optional extras. Building psychological safety should be treated as a deliberate leadership practice, one that allows teams to learn and adapt without fear. And leaders must remain present in their communication, ensuring that human tone and visibility are not lost when supported by AI tools.

Bringing theory into practice

Much leadership theory already points to these ideas, emotional intelligence, authentic leadership, transformational vision. What this research shows is that in the AI era, these are not luxuries but necessities. As machines take on more technical and cognitive tasks, the distinct value of human leadership lies in things AI cannot replicate: empathy, integrity, humility, and the ability tocreate shared meaning. Put simply, the more AI we have in the workplace, the more human our leaders need to be.

Conclusion

My dissertation set out to answer two questions: what are the human leadership competencies required in the AI era, and why are they necessary? The findings suggest that employees are looking for leaders who show up with honesty and empathy, who build trust and collaboration through humility and psychological safety, and who provide grounded and meaningful direction in uncertain times. AI will keep evolving, but these human needs remain constant. For organisations, the practical takeaway is clear: technology alone does not guarantee success. What makes the difference is leaders who bring a distinctly human presence, leaders who can connect, communicate, and create meaning in ways no machine ever could.