Impact of Shift-Work on Psychosomatic Health Among Nurses Working in Rotating and Day Shift: A Cross-Sectional Study in India

Study design and setting

This study employed a cross-sectional, comparative research design to examine the impact of shift work on psychosomatic health among nurses. The study specifically compared psychosomatic symptoms between nurses engaged in rotating shifts and those working regular day shifts.

The research was conducted across both government and private hospitals located in northern India, providing a heterogeneous sample that reflects diverse institutional work environments and scheduling practices.

Sample and sampling technique

A total of 384 registered nurses were recruited using convenience sampling. The required sample size was calculated using Cochran’s formula [41] for an unknown population proportion, assuming a 95% confidence level and 5% margin of error. Nurses included in the study were classified into two main groups: 1) shift-working nurses, including those engaged in rotating or non-rotating night shifts; and 2) non–shift-working nurses, defined as those employed in standard fixed day shifts.

Eligibility criteria required participants to be actively employed as nursing professionals for at least six months in either a government or private hospital. Nurses who were on leave or had a history of diagnosed psychiatric or chronic medical illness were excluded to minimize confounding variables.

Convenience sampling was used, which introduces the possibility of selection bias, as nurses who volunteered may differ systematically from those who declined, potentially affecting the generalizability of findings. However, this approach was chosen to ensure that nurses from different hospitals (government and private), departments, and shift schedules were included, thereby enhancing the diversity of the sample. While not a strictly purposive sampling strategy, the convenience-based recruitment facilitated purposive representation across varied work contexts.

Instruments for data collection

Data were collected using a structured questionnaire comprising two sections: 1) demographic and professional profile: information on age, gender, marital status, years of experience, type of hospital, title of job, and shift schedule was obtained; and 2) psychosomatic symptom assessment: the PHQ-15 was used to assess the severity of psychosomatic symptoms. The PHQ-15 is a validated self-report tool that captures 15 somatic symptoms commonly associated with psychological distress, including fatigue, gastrointestinal problems, sleep disturbances, pain, and cardiovascular symptoms [34]. Each item is rated on a 3-point scale (0=not bothered, 1=bothered a little, 2=bothered a lot), with higher scores indicating greater symptom severity.

Data collection procedure

After obtaining institutional permission, data were collected through face-to-face administration of the questionnaire during duty hours or break periods and through online Google Forms to ensure convenience and minimize disruption. Participation was voluntary and confidential.

Statistical analysis

After the completion of data collection, all responses were coded and entered into a Microsoft Excel spreadsheet for initial organization and cleaning prior to statistical analysis. Data were analyzed using SPSS Statistics version 22 (IBM Corp.). Descriptive statistics (frequency, percentage) were used to summarize demographic and clinical characteristics. Categorical variables were summarized using absolute frequencies and corresponding percentages. Chi-square tests were conducted to compare psychosomatic symptoms between shift and non-shift workers. Further, logistic regression analysis was used to determine the association between the type of shift and the likelihood of experiencing each of the 15 individual psychosomatic symptoms. Statistical significance was set at p<0.05.

Ethical considerations

This study was conducted as part of a PhD research project. Before data collection, ethical clearance was obtained from the Institutional Human Ethics Committee of Lovely Professional University (LPU), LPU/IEC-LPU/2024/3/5, India. All procedures involving human participants were performed by the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments.

Participants were fully informed about the purpose of the study, and informed consent was obtained from each participant before the administration of the questionnaire. Participation was entirely voluntary, and nurses were assured that their decision to participate or withdraw at any stage would not affect their professional standing. Strict confidentiality and anonymity of the collected data were maintained throughout the research process. The information gathered was used solely for academic purposes, specifically for the completion of the researcher’s postgraduate thesis.

Reliability analysis

To assess the internal consistency of the psychosomatic symptom scale used in this study, Cronbach’s alpha was computed for the 15 items of the PHQ-15. The reliability analysis yielded a Cronbach’s alpha of 0.867, indicating good internal consistency among the items. This suggests that the PHQ-15 scale is a reliable tool for assessing psychosomatic symptoms within the sample of Indian nursing professionals included in this study. Each item contributed positively to the overall reliability, and no single item, if deleted, improved the alpha significantly, affirming the coherence of the 15-item structure in this context.

This high level of internal consistency supports the use of the PHQ-15 for further statistical analyses, including comparisons across shift work groups and assessment of symptom-level prevalence. The reliability observed is consistent with prior studies validating the PHQ-15 in occupational and clinical populations [34].

Since the majority of the study variables were categorical, descriptive analysis was conducted using frequencies and percentages. Table 1 summarizes the demographic characteristics of the nursing professionals (n=384) included in the study.

Table 1.

Demographic characteristics of participants

The majority of participants were female (73.2%), and nearly half were below 30 years of age (49.0%), followed by those aged 30–40 years (35.7%). In terms of educational qualifications, 52.3% of the nurses held a BSc nursing degree, while 32.8% had completed general nursing and midwifery (GNM), and 12.5% held an MSc in nursing.

With regard to income distribution, 38.0% of participants reported earning less than ₹25,000 per month, while 24.0% earned between ₹25,000–50,000, and 22.9% between ₹50,000–100,000. A smaller proportion (15.1%) earned more than ₹100,000 monthly.

In terms of marital status, 51.6% were unmarried, and 48.4% were married. Regarding professional designation, a large majority (79.7%) were working as nursing officer, followed by senior nursing officers (8.6%), and other supervisory or administrative roles such as assistant nursing superintendent (ANS) (5.2%), nursing superintendent (NS) (4.9%), and deputy nursing superintendent (DNS) (1.6%).

Shift-related characteristics

Descriptive analysis of shift-related variables is presented in Table 2. A majority of participants were employed in government hospitals (45.8%), followed by those in private hospitals (27.9%) and other healthcare settings (26.3%). Most nurses (70.8%) reported being engaged in shift work, while the remaining 29.2% were not involved in shift-based schedules.

Table 2.

Shift-related characteristics of participants

With regard to work schedule types, over half of the respondents (53.9%) worked three-shift rotations, 14.3% worked two-shift rotations, and 31.8% followed non-traditional or irregular schedules. In terms of shift duration, the largest proportion of nurses (44.8%) reported working 6-hour shifts, followed by 8-hour shifts (35.1%), other durations (11.5%), and 12-hour shifts (8.6%).

Distribution of psychosomatic symptom levels

As shown in Table 3, the psychosomatic symptom burden among nurses was assessed using the PHQ-15 instrument. Based on total scores, 36.7% of participants fell in the medium symptom category, while 35.9% had low symptom levels, and 27.3% reported high levels of psychosomatic symptoms. These findings suggest a considerable proportion of nursing professionals are experiencing moderate to severe somatic complaints, potentially influenced by their work schedules and shift engagement.

Table 3.

Distribution of psychosomatic symptoms (PHQ-15 categories) among nurses

Symptom severity of psychosomatic complaints (PHQ-15 items)

Each of the 15 somatic symptoms assessed using the PHQ-15 was categorized into severity levels: “Not bothered at all,” “Bothered a little,” and “Bothered a lot.” Table 4 presents the item-wise distribution of symptom severity among the study participants.

Table 4.

Distribution of PHQ-15 symptoms by severity among nurses (n=384)

Notably, the most frequently reported symptoms were nausea/indigestion (84.6%), constipation or loose bowels (83.9%), and tiredness/low energy (75.3%) in the “bothered a little” category. A considerable proportion also reported trouble sleeping (27.1%), back pain (26.6%), and tiredness (24.7%) as “bothered a lot.” Symptoms such as chest pain, fainting spells, and problems during sex were least frequently reported in the “bothered a lot” category. These findings reflect varying degrees of psychosomatic symptom burden among nurses, possibly related to occupational stressors and shift patterns.

Association between shift work characteristics and psychosomatic symptom severity

A series of chi-square tests was conducted to examine the association between shift work-related variables and psychosomatic symptom severity (categorized as low, medium, and high based on PHQ-15 scores) seen in Table 5.

Table 5.

Association between shift work characteristics and psychosomatic symptom severity (PHQ-15 categories)

Association of individual psychosomatic symptoms among nurses in different settings

To examine which psychosomatic symptoms were more prevalent among nurses working in different settings, a series of chi-square tests was conducted between work setting (government hospital, private hospital, and other institutions) and each of the 15 individual PHQ symptom items. The analysis revealed statistically significant associations for several symptoms (Table 6).

Table 6.

Association between individual PHQ-15 psychosomatic symptoms and work characteristics among nurses (n=384)

Notably, significant associations were found for stomach pain (χ²=11.41, df=2, p<0.01), back pain (χ²=11.46, df=2, p<0.01), problems with menstruation (χ²=43.48, df=8, p<0.01), headache (χ²=30.25, df=4, p<0.01), problems during sex (χ²=13.79, df=4, p=0.01), constipation or diarrhea (χ²=7.04, df=2, p=0.03), low energy or fatigue (χ²=31.09, df=2, p<0.01), and trouble sleeping (χ²= 25.69, df=4, p<0.01). These findings suggest that nurses employed in government hospitals reported a higher prevalence of these symptoms compared to those working in private or other healthcare settings.

On the other hand, symptoms such as body pain, chest pain, dizziness, fainting spells, heart racing, shortness of breath, and nausea/indigestion did not show statistically significant differences across work settings (p>0.05).

Association between engagement in shift work and individual psychosomatic symptoms

To determine whether engagement in shift work is associated with individual psychosomatic symptoms, item-wise chi-square tests were conducted for all 15 items of the PHQ-15 (Table 6). The results revealed that nurses engaged in shift work reported significantly higher frequencies of several psychosomatic symptoms. Specifically, significant associations were found for stomach pain (χ²(1)=8.81, p<0.01), back pain (χ²(1)=12.22, p<0.001), body pain (χ²(2)=8.90, p<0.01), headaches (χ²(2)=6.21, p<0.05), nausea or indigestion (χ²(1)=10.10, p<0.01), tiredness or low energy (χ²(1)=6.38, p=0.01), and trouble sleeping (χ²(2)=9.85, p=0.01). These findings suggest that shift-working nurses are more prone to experience these symptoms than their non-shift counterparts.

However, other symptoms such as chest pain, dizziness, fainting spells, heart palpitations, shortness of breath, problems during sex, menstrual difficulties, and bowel-related issues (e.g., constipation or diarrhea) did not show statistically significant differences between shift-working and non-shift-working groups (p>0.05). This suggests that while some psychosomatic complaints are linked with shift work engagement, others may be more universally experienced or influenced by other factors.

Association between work schedule type and PHQ-15 psychosomatic symptoms

Chi-square analyses were conducted (Table 6) to examine whether different work schedule types (fixed, rotating, and night shifts) were associated with the prevalence of individual psychosomatic symptoms measured using the PHQ-15. Item-wise analyses indicated that work schedule type was significantly related to several psychosomatic complaints (Table 6).

Highly significant associations (p<0.001) were observed for stomach pain (χ²(2)=19.40), back pain (χ²(2)=13.84), headaches (χ²(4)=27.21), chest pain (χ²(4)=20.97), constipation or diarrhoea (χ²(2)=15.32), low energy/tiredness (χ²(2)=18.43), and trouble sleeping (χ²(4)=19.95). These findings suggest that irregular or non-standard work schedules may contribute substantially to gastrointestinal discomfort, musculoskeletal pain, fatigue, and sleep-related difficulties among nurses.

In addition, statistically significant associations were identified for nausea or indigestion (χ²(2)=10.56, p=0.01) and fainting spells (χ²(4)=10.41, p=0.03), whereas menstrual-related problems (χ²(8)=15.21 p=0.06) are not significant. These findings suggest that variations in work schedules may be associated with certain autonomic psychosomatic symptoms.

Conversely, symptoms such as general body pain, dizziness, heart pounding or racing, shortness of breath, and problems during sexual activity did not demonstrate statistically significant differences across work schedule categories (p>0.05), suggesting that these symptoms may be less sensitive to variations in shift patterns.

Overall, the results underscore the crucial role of work schedule organization in influencing psychosomatic health outcomes among nursing professionals, particularly in relation to symptoms such as sleep disturbances, fatigue, pain, and gastrointestinal issues.

Predictors of psychosomatic symptom severity: the role of shift work and workplace characteristics

A multinomial logistic regression was conducted to examine the effects of shift work engagement, work schedule type, shift duration, and workplace setting on psychosomatic symptom severity among nursing professionals, using the PHQ-15 symptom categories: low, medium, and high (Table 7). The low symptom category was specified as the reference group.

Table 7.

Multinomial logistic regression predicting psychosomatic symptom severity

The overall model was statistically significant compared to the null model, χ²(18)=32.89, p=0.017, indicating that the set of predictors reliably distinguished between the levels of psychosomatic symptoms. The model explained approximately 9.3% of the variance in psychosomatic symptom categories as indicated by the Nagelkerke pseudo R².

Likelihood ratio tests revealed that work schedule type (χ²(4)=12.05, p=0.017) and workplace setting (χ²(4)=10.59, p=0.032) significantly improved model fit, while engagement in shift work (χ²(2)=3.99, p=0.136) and shift duration (χ²(8)=4.31, p=0.828) did not contribute significantly.

In terms of predicting high psychosomatic symptoms (compared to low), nurses working under three-shift schedules were three times more likely to report high symptoms (OR=3.02, 95% CI [1.11, 8.25], p=0.031), while those with irregular or “other” shift schedules were more than five times as likely (OR=5.22, 95% CI [1.77, 15.45], p=0.003). Furthermore, nurses employed in other types of healthcare settings (e.g., NGOs, specialty clinics) were significantly less likely to report high symptoms compared to those in private hospitals (OR=0.415, 95% CI [0.19, 0.93], p=0.032).

When comparing medium symptoms to low, most predictors were not statistically significant. However, a marginal effect was found for nurses working in government hospitals, who were nearly twice as likely to report medium symptoms (OR=1.83, 95% CI [0.99, 3.39], p=0.054), suggesting a trend toward increased psychosomatic burden in that group.

Shift work engagement (Yes/No) showed a non-significant trend for both medium and high symptom groups (p=0.091 and p=0.093, respectively), and shift duration (6-hour, 8-hour, 12-hour) showed no significant association with psychosomatic symptom category in any comparison (p>0.5).

These findings suggest that the type and pattern of work schedule play a more critical role in predicting psychosomatic symptom burden than shift length or general shift engagement, highlighting the importance of schedule design in occupational health planning.

The multinomial logistic regression findings underscore the importance of work schedule design and workplace setting as predictors of psychosomatic symptom severity among nurses. While shift engagement and shift duration did not emerge as significant predictors, the strong association of irregular and three-shift schedules with high psychosomatic symptoms aligns with global evidence that erratic schedules disrupt circadian stability and exacerbate fatigue, sleep disturbances, and somatic complaints [32,42]. This finding supports the growing argument that the structure and predictability of work schedules, rather than the mere presence or length of shifts, have a more profound effect on health outcomes.

The observed trend of greater symptom burden among nurses in government hospitals also reflects the contextual challenges of Indian healthcare systems, where high patient–nurse ratios and inadequate staffing persist despite national norms. Previous studies have reported that workload intensification, especially in public hospitals, contributes to heightened psychosomatic complaints and burnout among nurses [43]. Thus, the results highlight that occupational health interventions must not only address circadian misalignment but also incorporate organizational reforms such as workload redistribution and adequate staffing.

Importantly, the non-significant effect of shift duration suggests that policies focusing solely on reducing shift length may not sufficiently safeguard nurse well-being. Instead, chronobiology-informed scheduling approaches that consider stability, forward rotation, and adequate rest opportunities between shifts may offer more sustainable benefits [13,14].

Nonsignificant findings and their implications

While several psychosomatic symptoms showed significant associations with work schedules and engagement in shift work, a subset of symptoms did not demonstrate statistically significant relationships. For instance, body pain (item 3), dizziness (item 7), fainting spells (item 8), heart palpitations (item 9), and shortness of breath (item 10) yielded non-significant chi-square results across most comparisons. These findings suggest that not all somatic complaints among nurses are directly attributable to shift work or circadian disruption.

Previous research supports this variability. Trinkoff et al. [44] noted that musculoskeletal pain and dizziness may be more strongly linked to ergonomic demands, patient handling, and environmental stressors rather than to shift patterns per se. Similarly, Vedaa et al. [49] emphasized that individual factors such as resilience, physical fitness, and coping strategies often mediate the relationship between shift schedules and symptom presentation. The lack of association for palpitations and shortness of breath in the present study may also reflect the multifactorial nature of these symptoms, which are influenced by pre-existing cardiovascular or respiratory conditions [50] and not solely by occupational stressors.

This finding aligns with previous studies suggesting that the quality and timing of shifts may exert a greater influence on health than their absolute duration [42,51]. Nurses working in rotating or irregular shifts may experience circadian misalignment, which has been shown to disrupt sleep and metabolic regulation, whereas longer but more predictable shifts may allow for partial adaptation [19]. The lack of significance for cardiovascular-type symptoms (e.g., palpitations, chest pain) is also noteworthy. Prior research indicates that such symptoms often have multifactorial origins, including lifestyle behaviors, baseline anxiety, and underlying medical conditions, which may obscure their relationship with shift work [32,52].

These non-significant findings emphasize that not all domains of psychosomatic health are equally influenced by shift work. They highlight the importance of investigating moderating factors such as individual resilience, coping strategies, and organizational supports. Future longitudinal studies incorporating both somatic and psychological measures (e.g., anxiety, depression, coping scales) would help clarify these complex interrelationships.

Furthermore, the elevated symptom burden among nurses employed in government hospitals compared to those in private or other settings may be attributed to systemic factors such as staffing shortages, heavier caseloads, or limited institutional support [25,30]. These contextual factors can compound the impact of shift work, further exacerbating physical and mental health outcomes.

The study also reinforces the psychometric robustness of the PHQ-15 scale, with a Cronbach’s alpha of 0.867, indicating good internal consistency. This supports the use of PHQ-15 in future occupational health research in India, particularly in resource-constrained settings where brief yet valid tools are needed.

The present findings align with concerns regarding workload and staffing pressures in India. Nurse-to-patient ratios often fall short of recommended norms, especially in government hospitals where patient inflow is higher and resources limited. While guidelines propose ratios of 1:6 in general wards and 1:1–1:2 in intensive care settings, actual practice frequently deviates due to chronic shortages [37]. In addition, time-and-motion analyses highlight that patient dependency levels justify closer to a 1:1.2 ratio in critical care [37,38]. Previous surveys reveal that more than 80% of Indian nurses perceive workload as a major contributor to occupational stress, and shift-working nurses disproportionately report gastrointestinal issues, back pain, hypertension, and disturbed sleep [38,43]. These contextual realities likely compound the psychosomatic symptom burden we observed, particularly among government hospital nurses, reinforcing the need for policy-level interventions.

Limitations of the study

Despite its significant findings, this study has several limitations that warrant consideration. First, the cross-sectional design precludes any causal inferences between shift work and psychosomatic symptoms. Longitudinal or prospective cohort studies would be necessary to confirm whether shift work leads to psychosomatic distress over time, or whether individuals with higher baseline vulnerability are more likely to report symptoms. While associations were observed, the temporal direction of these relationships cannot be confirmed, and reverse causality remains a possibility.

Second, data were collected using self-reported instruments, including the PHQ-15, which may be subject to response bias, such as social desirability or recall inaccuracies. Participants may have underreported or overreported symptoms based on personal perceptions, mood at the time of survey completion, or fear of professional consequences. Although the PHQ-15 is a validated and reliable tool for assessing somatic symptom severity, it does not differentiate between psychosomatic or functional complaints and symptoms arising from underlying medical conditions [33]. Thus, some reported symptoms may reflect organic illnesses rather than occupational stressors or shift work per se. To minimize this limitation, we excluded participants with known chronic medical ailments at the time of data collection. Furthermore, the PHQ-15 identifies symptoms that persist for more than four weeks [34], thereby reducing the likelihood of capturing transient or short-term complaints unrelated to work patterns.

Third, the study relied on convenience sampling from selected hospitals, which limits the generalizability of findings. The sample, though sizable (n=384), may not fully represent the broader nursing population across India, especially those in rural or smaller healthcare settings.

Fourth, while the PHQ-15 offers a reliable assessment of psychosomatic symptoms, it does not differentiate between functional and organic causes of symptoms. Consequently, some reported complaints may stem from medical conditions unrelated to occupational stress or shift work.

Fifth, important confounding variables such as chronotype, sleep quality, coping mechanisms, and organizational factors (e.g., staffing ratio, administrative support) were not controlled in this study. Their omission may limit the depth of interpretation regarding the pathways through which shift work affects psychosomatic health.

Lastly, gender-specific health concerns, such as menstrual issues, were explored but not stratified by gender, which may dilute the interpretability of certain results—particularly as these symptoms are biologically constrained to a subset of participants.

Future research should consider longitudinal designs, stratified sampling, and multivariate models that incorporate biological, psychosocial, and environmental moderators to better understand the complex relationship between shift work and nurses’ health.

This study did not directly measure staffing adequacy, nurse-to-patient ratios, or patient dependency levels. Given that Indian hospitals often operate below recommended norms and with significant variability between government and private sectors, incorporating workload measures could have provided a more nuanced understanding of how staffing interacts with shift schedules to influence psychosomatic health. Future studies should integrate objective workload indicators to strengthen causal inferences.

Conclusion

This study provides compelling evidence that shift work significantly influences psychosomatic symptom severity among nursing professionals. A considerable proportion of participants reported moderate to high levels of somatic complaints, particularly those engaged in rotating or irregular work schedules. Key symptoms such as headaches, gastrointestinal discomfort, fatigue, and sleep disturbances were more prevalent among shift workers compared to those on fixed schedules. These findings align with prior research indicating that circadian disruption and inconsistent work patterns contribute to heightened physiological stress and symptom manifestation [32,53,54].

Furthermore, chi-square analyses revealed significant associations between specific shift characteristics—such as engagement in shift work, work schedule type, and working hours—and various psychosomatic indicators. These results underscore the urgent need for shift-sensitive health monitoring systems and institutional strategies to mitigate adverse outcomes in healthcare workers [10].

Given the critical role of nurses in patient care delivery, prioritizing their well-being is not only a matter of occupational health but also of healthcare quality and safety. Implementation of chronobiologically informed scheduling and stress-reduction programs may help reduce symptom burden and improve job satisfaction and retention [55].

In conclusion, shift work emerges as a salient occupational stressor associated with psychosomatic distress in nurses. Addressing this issue requires an integrated approach involving organizational policy reform, individualized shift planning, and continued research to explore underlying mechanisms and long-term outcomes.

This study adds to the growing literature on occupational health by documenting the significant burden of psychosomatic symptoms among nurses working in shifts. The strong associations between shift work and specific somatic complaints highlight the urgent need for organizational policies that prioritize shift design, rest periods, and supportive work environments. Future interventions should consider chronobiological principles to align work schedules with individual chronotypes, potentially mitigating the health risks associated with shift work.

Future directions

Beyond observational and longitudinal research, future investigations should examine intervention strategies that integrate chronobiological principles with staffing reforms. In the Indian context, this could include piloting flexible or chronotype-informed shift schedules alongside the enforcement of safe nurse-to-patient ratios as recommended by national guidelines [56,57]. Interventional trials assessing the combined effect of staffing adequacy and schedule design on psychosomatic health would provide stronger evidence for sustainable workforce policies.

While observational designs highlight important associations, interventional research is needed to test actionable strategies. Chronobiology-informed scheduling has shown promise in reducing circadian misalignment by aligning work hours with individual chronotypes, using forward-rotating shifts (day–evening–night), and limiting consecutive night duties [10,56,58]. Such strategies have been linked to improved sleep quality, reduced fatigue, and lower psychosomatic symptom burden. Organizational reforms are equally critical. These include enforcing safe nurse-to-patient ratios, as recommended for Indian healthcare settings [37], and implementing workload redistribution through supportive staffing policies. Institutional measures such as protected rest breaks, fatigue risk management systems, and wellness programs focusing on sleep hygiene and coping strategies may also mitigate health risks [1,51,59]. In the Indian context, pilot trials combining chronobiology-informed scheduling with staffing reforms in high-volume government hospitals would be especially valuable. Evaluating these interventions could provide robust evidence for institutional and national policy changes aimed at safeguarding nurse well-being and sustaining care quality.