The research, published in the open-access journal Discover Social Science and Health by Mainak Ghosh and Susmita Mukhopadhyay, set out to solve a problem that has hampered the field since the term quiet quitting entered popular vocabulary. Although the phenomenon — formally defined as a sustained limitation of discretionary effort while employees continue to perform their required duties — has been widely discussed, its possible causes have rarely been prioritised in a rigorous, structured way within Indian healthcare settings. Rather than guessing which factors matter most, the team assembled a panel of senior healthcare experts and asked them to weigh the evidence themselves.

The methodological backbone of the study was a two-stage design combining a modified Delphi process with the analytic hierarchy process, a structured decision-making technique originally developed for complex multi-criteria choices. The researchers began with a systematic literature review that identified 23 candidate drivers of quiet quitting, spanning individual, job-related, and organisational domains. These candidate factors were then put before a panel of 23 senior healthcare experts, who worked through four successive Delphi rounds, refining and narrowing the list based on collective judgement.

The retention criteria were deliberately strict. For a driver to survive the Delphi stage, the panel’s median rating had to reach at least eight on the study’s rating scale, and the standard deviation across experts could not exceed 1.00 — a statistical guarantee that the group was not merely divided but genuinely converging. Eleven of the original 23 drivers met these thresholds, forming a distilled set of expert-validated factors that ranged from workload and staffing issues to recognition, autonomy, and organisational support.

The second stage converted consensus into a ranking. Fifteen of the experts went on to complete pairwise comparisons in the analytic hierarchy process, judging each driver against every other in terms of relative importance. Their individual judgements were aggregated using an equal-weight geometric mean, a technique that prevents any single voice from dominating the group result. The mathematical rigour of the exercise was verified through consistency ratios: all 15 individual comparison matrices satisfied the conventional threshold of a consistency ratio at or below 0.10, and the aggregated group matrix achieved a consistency ratio of just 0.0605, indicating that the experts’ judgements were coherent rather than arbitrary.

The resulting hierarchy is both intuitive and sobering. Burnout and Emotional Exhaustion emerged as the highest-ranked perceived driver, carrying a priority weight of 0.2217. Work–Life Imbalance followed closely at 0.1998, and Understaffing and Resource Constraints came third at 0.1277. Together, these three factors accounted for 54.92 percent of the total priority weight — meaning that, in the eyes of experienced healthcare professionals, more than half of the explanation for quiet quitting in Indian healthcare lies in the relentless depletion of the workforce’s physical and emotional reserves and the structural conditions that cause it.

What makes the findings particularly compelling is the extraordinary level of agreement among the experts. The Kendall’s coefficient of concordance, a statistical measure of how closely multiple raters align, reached 0.9602 — a value so close to unity that it suggests near-unanimous prioritisation. The researchers stress-tested this consensus in several ways. Leave-one-expert-out analyses, in which the ranking was recalculated after removing each participant in turn, preserved the complete group ranking every time. Bootstrap resampling, which repeatedly re-estimated the ranking from random subsamples, placed Burnout and Emotional Exhaustion first in 90.55 percent of samples. Even more remarkably, every professional subgroup within the panel produced the same complete rank order, indicating that doctors, administrators, and other senior professionals read the situation identically.

The technical strength of the design matters because prioritisation exercises in organisational research are often criticised for producing unstable or panel-dependent results. By combining a convergent Delphi stage with the multiplicative weighting logic of the analytic hierarchy process, and by validating the outcome with concordance statistics, sensitivity analyses, and resampling, Ghosh and Mukhopadhyay have built a case that their ranking reflects a durable expert consensus rather than a statistical fluke. The study also followed formal ethical safeguards, with approval from the Institute Ethics Committee of IIT Kharagpur granted before recruitment, informed consent from every participant, and full voluntariness of participation in line with the Declaration of Helsinki.

The practical implications reach directly into hospital management. The authors argue that because burnout and work-life imbalance dominate the expert hierarchy, they should form the first tier of any intervention strategy. But the third-ranked driver — understaffing and resource constraints — suggests that individual-level wellness programmes alone will not suffice. Instead, the study points toward an integrated approach in which hospitals connect staffing decisions, scheduling reform, workload control, managerial support, and protected recovery time into a single coherent policy framework. A mindfulness workshop, in other words, cannot compensate for a chronic staffing shortfall; the drivers of silent disengagement are systemic, and the response must be too.

The researchers are careful to delineate the boundaries of what their study can claim. The findings represent expert priorities — the considered judgements of senior healthcare professionals about which factors matter most — and do not establish causal effects. Whether reducing burnout actually reduces quiet quitting in Indian hospitals is a question for future empirical work, ideally longitudinal studies that track discretionary effort as working conditions change. Still, in a sector where coordination, continuity, and voluntary support directly shape the quality and safety of care, knowing where the experts would aim first is a valuable map. As quiet quitting continues to spread from social media discourse into the daily reality of overstretched health systems worldwide, this study offers Indian healthcare leaders a data-driven starting point: protect the workforce’s energy and time, and the quiet withdrawal of effort may begin to reverse.

Subject of Research: Expert prioritisation of the perceived drivers of quiet quitting in Indian healthcare organisations using a modified Delphi method and analytic hierarchy process.

Article Title: Expert prioritisation of perceived drivers of quiet quitting in Indian healthcare organisations

Article References: Ghosh, M., & Mukhopadhyay, S. (2026). Expert prioritisation of perceived drivers of quiet quitting in Indian healthcare organisations. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00493-5

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00493-5

Keywords: quiet quitting, healthcare, burnout, work-life imbalance, understaffing, Delphi method, analytic hierarchy process, Indian hospitals, employee disengagement, workforce management, emotional exhaustion, hospital management