PSYCH 694 Week 3 Industrial and Organizational Psychology Example

Forty Percent of Our Medical Assistants Leave Each Year: What an I-O Psychologist Would Study and Change

[Student Name]

University of Phoenix

PSYCH/694: Specialty Areas in Applied Psychology

Week 3 Assignment

[Instructor Name]

[Date]

The health center, its staff and all figures are composites written for a model paper; research findings come from the sources listed.

In my first paper for this course, I listed burnout among our medical assistants as one of five problems in our waiting room. This week I examine it through industrial and organizational psychology, the specialty that applies psychological science to work.

The Problem

Our health center employs about thirty-five medical assistants, who bring patients back to exam rooms, record vital signs, give vaccines and manage referrals. Last year fourteen left, a turnover rate of forty percent. Each departure costs an estimated six thousand dollars in recruiting, onboarding and overtime for those who stay, and physicians report that vacancies slow clinics and frustrate patients. Exit interviews mention workload, schedule changes and feeling "invisible."

What I-O Psychologists Do

I-O psychology studies people at work, from how organizations select and train employees to how leadership, motivation and culture affect performance and well-being. Unlike general human resources practice, it rests on measurement and research: I-O psychologists test whether a hiring method predicts performance or whether an intervention actually reduced turnover. Many practice with master's degrees in organizations and consulting firms; doctoral I-O psychologists also teach and conduct research.

Why People Leave

Griffeth et al. (2000) meta-analyzed research on the antecedents and correlates of employee turnover. Among the strongest predictors were job satisfaction, organizational commitment, comparing one's job with available alternatives and thoughts and intentions about quitting, which typically come just before leaving. Pay and pay satisfaction had only modest relationships with turnover, while factors such as relationships with supervisors and coworkers, role clarity and promotion chances contributed. Previous absences and lateness also predicted later departures, suggesting a pattern of gradual withdrawal.

These findings suggest our center should not assume a raise will solve the problem. Exit interviews point to satisfaction and commitment, workload, unpredictable schedules and feeling unseen, which an I-O approach would examine directly.

Who Gets Hired

Schmidt and Hunter (1998) reviewed eighty-five years of research on methods used to select employees. General mental ability tests had high validity for predicting job performance, and work sample tests and structured interviews, where each applicant faces identical job-based questions rated against fixed standards, predicted about as well. Unstructured interviews predicted noticeably less well. Some methods widely used in practice, such as years of education and reference checks, showed weak validity, and combining a mental ability test with a structured interview or an integrity test produced the strongest predictions.

Our center hires medical assistants through informal conversations with clinic managers, essentially unstructured interviews. An I-O approach would introduce structured interviews with questions about handling a busy clinic, a distressed patient or a scheduling conflict, along with a short work sample, such as taking vital signs and entering them correctly.

We have been hiring medical assistants with the least predictive method available and then wondering why so many leave.

Engagement and Results

Harter et al. (2002) meta-analyzed data from nearly eight thousand business units in thirty-six companies. Units with higher employee satisfaction and engagement had better customer satisfaction, productivity and profit, lower employee turnover and fewer accidents, and the relationships generalized across companies. The authors judged the links big enough to be worth acting on.

For our center, the relevant outcomes are turnover and patient experience. Clinic teams where medical assistants feel engaged should show lower turnover and better patient satisfaction scores, which we already collect.

What the Center Will Do

With help from an I-O psychologist at the local university, the center plans four changes. First, stay interviews with current medical assistants, asking why they stay and what would tip them toward leaving, a direct measure of the predictors the turnover meta-analysis identified. Second, a structured hiring process with standard questions, set standards for rating each answer and a work sample. Third, a realistic job preview, a short video and shadowing hour showing the pace and demands of the job before candidates accept, which helps those who would not fit opt out early. Fourth, an annual engagement survey, with results discussed by each clinic team.

Evaluating the Changes

The center will track monthly turnover, especially in the first ninety days, compare performance ratings of medical assistants hired under the new process with earlier hires and examine engagement scores alongside patient satisfaction by clinic team. A year of data will show whether the changes worked.

What I Learned About the Specialty

Before this week, I thought of I-O psychology as far from patient care. But the medical assistants who leave take relationships with patients with them, and the ones who stay carry the load. Improving their work is, indirectly, improving care, and the specialty's emphasis on evidence and measurement fits a health center that already tracks clinical outcomes.

What the Stay Interviews Found

The first round of stay interviews, conducted with twenty medical assistants by someone outside their reporting line, sharpened the picture. Sixteen said the most frustrating part of the job was learning their schedule only a few days ahead, leaving them scrambling to line up child care or second jobs. Twelve said that physicians rarely acknowledged their work, and eleven said they had no path to advance short of leaving to train as nurses. Only five named pay as their main concern. Several said they stayed because of coworkers, which suggests that team relationships are a strength to protect.

Career Paths as a Retention Tool

One finding pointed to a change the center had not considered. Medical assistants who want to grow have nowhere to go inside the center, so ambition becomes a reason to leave. An I-O psychologist would recognize this as a problem of job design and career structure. The center is now considering a senior medical assistant role, with responsibility for training new hires and coordinating a clinic team, with help paying tuition for anyone hoping to pursue nursing while continuing to work part time.

A Day With the I-O Psychologist

I spent part of a day with the university I-O psychologist as she met with clinic managers. Much of her work was translation: turning a manager's sense that "the new ones don't last" into a question that data could answer, such as whether early departures differ by clinic or by hiring manager. She spent as much time designing measures as recommending changes, which is the clearest difference I have seen between I-O psychology and well-meaning management advice.

Limits

Turnover in our region also reflects housing costs and competition from hospitals that pay more. I-O interventions cannot change the labor market. They can change what happens inside our walls, and the stay interviews suggest that schedules, recognition and a path to advance matter more to our staff than a small raise would.

Conclusion

I-O psychology offers our health center research on why people leave, which hiring methods predict success and how engagement relates to results. Applying it means listening to current staff, hiring with structure and measuring whether changes reduce turnover.

References

Griffeth, R. W., Hom, P. W., & Gaertner, S. (2000). A meta-analysis of antecedents and correlates of employee turnover: Update, moderator tests, and research implications for the next millennium. Journal of Management, 26(3), 463-488. https://doi.org/10.1177/014920630002600305

Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: A meta-analysis. Journal of Applied Psychology, 87(2), 268-279. https://doi.org/10.1037/0021-9010.87.2.268

Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124(2), 262-274. https://doi.org/10.1037/0033-2909.124.2.262