How my colleagues help me achieve happiness, health, and productivity in careers: An 18-week 4-wave dyadic study

Word count (excluding figures and references): 1000


How we stay healthy, happy, and productive in our careers today is immensely different from our parents!

Older generations devote their lives to employment stability, whereas we willingly move among organizations and develop multiple career paths to satisfy the need for self-growth and personal achievements. Managing careers is now uncertain and complex as we must constantly realize our career goals and ensure employability in the turbulent labor market to achieve health, happiness, and productivity across the lifespan – the notion referred to as career sustainability [1].

The world’s ongoing unpredictable and rapid socio-economic changes have put more pressure on sustainable careers. For example, the COVID 19 has made millions unemployed, and those who remain experience increasing burnout and depression, which is and continues to be tremendously costly to individual flourishing, organizations’ effectiveness, and society if no prompt intervention is made. Thus, fostering career sustainability is a growing concern for all. However, we find it meaningful to focus on young professionals who might be at risk of diminished career sustainability from the start because they lack the competencies to navigate their careers at the time of graduation.

Therefore, this study aims to promote career sustainability of young professionals (age ≤ 35) working in European countries.

What we know and not know

Individual health, happiness, and productivity in their careers are and continue to be primarily individual responsibilities. However, recent conceptual papers have argued that although career sustainability starts with the individual, it also depends on multiple stakeholders, such as coworkers and spouses[1-2]. Empirical research has offered limited insight into this issue[1].

What is known is that experiences/resources can cross over between individuals via interaction. This means colleagues’ beneficial resources can be transferred to individuals and help develop individual sustainable careers. If colleagues transmit harmful resources, individual careers might be negatively affected. This notion is even more interesting and essential when employees are required to make increased interaction for team-based work, thus creating more chances for the career crossover, either positive or negative, to happen. As the current research does not sufficiently address the influence of colleagues on individual sustainable careers, this raises a question:

How, why, and under which conditions could colleagues contribute to establishing healthy, happy, and productive careers?

What we do

Building on the recent conceptual papers[1-2], we test several hypotheses (Figure 1) concerning the interaction between employees and coworkers to uncover their inter-influence on building each other’s sustainable careers. We consider career competencies as a career resource that can cross over to the other person and contribute to perceived employability – an indicator of career sustainability. We examine career mentoring as the “how” mechanism of this process and collegial relationship quality as the condition that strengthens the career crossover.

What we learn

Theoretical contribution: By considering the role of coworkers in individual careers over 18 weeks, we respond to the research call to adopt a systematic and dynamic approach to career sustainability. We expect to provide initial evidence of the relevance of coworkers to individual careers and shed light on the career crossover. We aim to identify a set of specific mentoring behaviors that explain career sustainability. While past research finds communication frequency moderates the crossover process, we expect the collegial relationship quality to strengthen the crossover.

Practical contribution: Our findings provide workers and organizations with knowledge to build career sustainability at work. The study insights could increase the effectiveness of the current organizational interventions against employee dysfunction by suggesting employers design programs that involve coworkers as active actors in employees’ careers. Organizations should create networking/team-building events aimed at promoting mentoring and the quality of collegial relationships.

Contribution to Prolific: Prolific participants’ longitudinal attrition rates are scarcely reported in two single-source short-and-long-term studies[3-4]. With a dyadic 18-week 4-wave design, our study will be the first to provide preliminary data on the Prolific attrition rate of multisource 4-wave studies over the medium term for scholars to consider crowdsourcing on Prolific.


This is an 18-week 4-wave longitudinal dyadic study (Figure 2). The study design enables us to minimize measurement errors and biases, and increase our predictive capacity of the proposed causality.

Analysis Plan

Since dyadic data are not independent, we analyze our data with the Actor-Partner Interdependence Model. Due to the hierarchical nature of our data, we run a multilevel analysis - with repeated measurements as the first level, individuals as the second level, and the dyads as the third level - on MPLUS to test the hypotheses.

Data Collection

Data will be collected via Qualtrics surveys.

Scenario 1: Employees and their coworkers are Prolific members. Both participants will be invited to two different surveys based on the procedure outlined on the Prolific blog.

Scenario 2: Only employees are registered on Prolific. Employees are invited via Prolific to do the first survey. Upon completion, they are asked to forward the second survey’s link to their coworkers.

To minimize the attrition rate, we reward greater financial compensation per wave only to dyads with dyadic completion.

Sample Size and Costs

Power analysis for the three-level model with dyads=200 using the optimal design program (Level 1, N=1600; Level 2, N=400; Level 3, N=200) resulted in values higher than .80, suggesting adequate power. Thus, our target sample size in Wave 4 is 200 dyads.

We use the retention rate of previous studies as a reference point for our sample size estimation[5]. A similar design and setting study reports a retention rate of 58%[6].

In Wave 1, we need 200x(100/58)^3 ≈ 1026 employees.


We assume 25% of coworkers are Prolific members. To recruit 200 dyads, we need £7303.63 + £7303.63*25% ≈ £9,130 . Non-Prolific coworkers’ participation will be reimbursed on our tight budget.

In sum, we ask for a grant of £9,130 for this study.


This study has been pre-registered:

Our university has a publication deal with the Dutch VSNU: we publish open access to the best-fitting peer-reviewed journal. Our data are FAIR (Findable, Accessible, Interoperable, and Reusable) and will be archived on a digital repository DataVerseNL for 10 years.


[1] De Vos, A., Van der Heijden, B. I., & Akkermans, J. (2020). Sustainable careers: Towards a conceptual model. Journal of Vocational Behavior, 117, 1-13. doi:10.1016/j.jvb.2018.06.011

[2] Van der Heijden, B., De Vos, A., Akkermans, J., Spurk, D., Semeijn, J., Van der Veldek, M., & Fugate, M. (2020). Sustainable careers across the lifespan: Moving the field forward. Journal of Vocational Behavior, 117.

[3] Palan, S., & Schitter, C. (2018). Prolific. ac—A subject pool for online experiments. Journal of Behavioral and Experimental Finance, 17, 22-27.

[4] Kothe, E., & Ling, M. (2019). Retention of participants recruited to a one-year longitudinal study via Prolific.

[5] Ployhart, R. E., & Ward, A. K. (2011). The “quick start guide” for conducting and publishing longitudinal research. Journal of Business and Psychology, 26 (4), 412-422.

[6] Westman, M., Bakker, A. B., Roziner, I., & Sonnetnag, S. (2011). Crossover of job demands and emotional exhaustion within teams: a longitudinal multilevel study. Anxiety, Stress, & Coping, 24 (5), 561-577. doi:10.1080/10615806.2011.558191

This is quite interesting.


it is interesting

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Thank you @Atanaska_Donkova. I’m glad you like my paper!

Sounds very interesting!

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Awesome👌 good job!

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Thank you @Kadija_Khatun for your interest in my proposal :slight_smile:

Thank you @Catherine_Vergara! Happy to have you read my proposal!

Interesting and practical research, and the study design is really well thought out. Good luck!


Looks very interesting. All the best

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Thank you for your comment :smiley: Yes, we indeed put many thoughts in our design as it’s the core of the quality of any study.

The field of organizational behavior mostly applies cross-sectional designs that collect data at one single point in time. However, the cons of this method are that it assumes variables are static, thus not capturing change over time and quite often leading to inaccurate conclusions. Longitudinal designs, by collecting data at multiple measurement times, address this problem, increase confidence in making causality inferences, and therefore, are the design that is highly recommended by many high-quality journals.

The time lag of 6 weeks between each wave is also meaningful as it is long enough for the hypothesized processes to happen but short enough for the relationships not to be inflated by the effects of unexpected life events. We also did lots of research on how to promote longitudinal participation and found out that there is a significantly higher retention rate in longitudinal studies that offer greater rewards for each later wave than studies that offer unchanged incentives. Unlike self-rating longitudinal studies, dyadic ones like our study are likely to experience a much lower retention rate. Thus, receiving funds is extremely crucial to the success of our project.

Wish us all the best :wink:!


Thank you @Sundus_Noor_Saba. Fingers crossed :crossed_fingers: