This was a cross-sectional study in which we employed a mixed-methods approach for data collection. The technique of triangulating two sets of findings can improve comprehension and increase the reliability of conclusions. Data collection was undertaken during February-April 2024 at a tertiary cancer care hospital in Bhubaneswar, Odisha.

From the four tertiary cancer care hospitals in Bhubaneswar city, we purposively selected one, reaching out to all clinically diagnosed cancer patients attending outpatient services or admitted between February and April 2024. Caregivers above the age of 18, directly related to the cancer patient, who had provided care at least for 3 months and consented to participate, were included in the study. The final sample consisted of 230 caregivers. Additionally, ten caregivers were selected through purposive sampling for conducting in-depth interviews.

Quantitative data collection

A semi-structured interview schedule was developed, comprising of two sections: a) socio-demographic details; and b) standardized tools to assess anxiety, depression, and stress. Questions for anxiety, depression and stress were adapted from two questionnaires namely, the Hospital Anxiety and Depression Scale (HADS) and Perceived Stress Scale (PSS). HADS is a widely recognized self-report tool for emotional distress, commonly used in oncology and other somatic disease settings. ¹⁸ It consists of 14-items with seven questions related to depression and seven related to anxiety, each valued from 0 to 3. Therefore, the overall score varied from 0 to 21 for each category. Caregivers responded through a 4-point scale (from 0 to 3) referring to their explicit experiences within the past week. An analysis of the two subscales revealed that total scores of 0-7 indicate a normal case, 8-10 a borderline case, and 11-21 an abnormal case. ¹⁹ The 10-item Perceived Stress Scale is a self-reported tool used to measure psychological stress experienced over the past 30 days. ²⁰ The scale consists of four positive items (items 4, 5, 7 and 8) that measure an individual’s ability to manage current stressors (also known as positive stress, perceived efficacy or perceived control) and six negative items (items 1, 2, 3, 6, 9 and 10) that evaluate feelings of lack of control and negative reactions (negative stress, perceived helplessness or perceived stress). ²¹ Responses are rated on a 5-point Likert scale, from (never) to 4 (very often). The four affirmative answers are reverse-coded, with higher scores corresponding to more stress. Scores of 0-13 indicate low stress, 14-26 suggest moderate stress, and 27-40 representing high perceived stress. The total PSS-10 score ranges from 0 to 40. ²²

Qualitative data collection

Ten in-depth interviews (IDI) were conducted to explore the factors contributing to mental health challenges among caregivers of cancer patients in a tertiary care hospital of Bhubaneswar. A tailor-made interview guide was meticulously developed, translated into local language, field-tested and contextualised before use. Each interview lasted for about 30-40 minutes. The questions included information regarding personal background, emotional impact, social support, impact on personal life, communication with healthcare providers, financial constraints and supportive services.

The quantitative data collected was entered into Excel sheet and analysed by using R 4.2.2 software. ²³ It’s an open-access software for statistical analysis and data visualization. HADS and PSS score distributions were used to determine the prevalence of stress, anxiety and depression among caregivers. Descriptive statistics were presented as mean ± standard deviation (SD) and frequency (%), as applicable. Pearsons’s chi-squared test and regression analysis were performed to examine associations between socio-demographic factors and caregivers’ psychological distress. For qualitative data, translations and verbatim transcriptions were imported into Atlas.ti 8 for analysis. Thematic framework analysis was employed involving steps such as data familiarization, coding and thematic grouping for interpretation of results. ²⁴

Sociodemographic characteristics

Among the 230 study participants, 54.7% were aged 18-29 years, 24.3% were 30-39 years, 14.3% were 40-49 years and 6.5% were over 50 years. The majority were female respondents (53.5%) with males comprising 46.5%. 2.17% of the respondents had no education, 6.9% had primary level of education, 13.04% had secondary education, 57.3% were graduates, and 20.4% had post-graduate degrees. Employment status showed that 66% were employed, 31.4% were unemployed and 3.6% were retired. Duration of accompaniment was 6-12 months for 77.4% of participants, 13-24 months for 21.7%, and over 24 months for 0.86%. Caregiving status revealed that 41.7% were the sole caregivers of their patient, while 58.3% were not. Additionally, 45.6% families had insurance coverage, 54.3% did not, and 57.3% had a Biju Swasthya Kalyan Yojana (BSKY) health card, while 42.7% did not ( Table 1).

Among 230 participants, 126 (54.7%) had normal anxiety levels, 47 (20.4%) had borderline abnormal levels, and 57 (24.7%) had abnormal anxiety levels. For the ease of analysis, those with borderline abnormal and abnormal levels were considered as “CASE” OR “Anxious” resulting in an overall anxiety prevalence of 45.2%. For depression, 130 (56.5%) participants were at a normal level, 48 (20.8%) had borderline abnormal levels, and 52 (22.6%) had abnormal levels. Participants with borderline abnormal and abnormal levels were considered as “CASE” OR “Depressed”, leading to an overall depression prevalence of 43.4%. Likewise, for stress 127 (55.2%) participants reported low stress, 98 (42.6%) reported moderate stress, and 5 participants reported high perceived stress. Those with moderate and high perceived stress were categorized as “Stressed” resulting in an overall prevalence of moderate to high perceived stress at 44.8% translating to 103 participants, as shown in Table 2.

As shown in Table 3, with a p-value < 0.05 indicating statistical significance, age, gender, religion, caregiver status, insurance coverage, and duration of accompaniment were all significantly associated with anxiety, depression and stress. For instance, females showed higher anxiety levels than males (p < 0.001), while being the only caregiver was strongly associated with elevated anxiety levels (p < 0.001). BSKY insurance coverage was significantly associated with lower anxiety (p = 0.002).

For depression, the duration of accompaniment (time as a caregiver) was significantly associated with depression (p = 0.019), particularly among those who had been caregiving for 6-12 months. Being the only caregiver was also strongly associated with higher depression (p < 0.001). Age was significantly associated with stress levels (p = 0.003), and again being the sole caregiver was strongly associated to higher stress (p < 0.001).

There were no significant associations between mental health status and marital status, education level, employment status, economic status, insurance coverage, or number of household members. Although these findings were not statistically significant at the conventional level, they suggest potential trends that should be explored further ( Table 3).

A stepwise logistic regression model was performed to identify factors contributing to caregiver stress, anxiety and depression. The analysis revealed that among the basic characteristics gender, religion, BSKY coverage, and being the only caregiver were significant predictors of anxiety. For depression, the significant predictors were duration of accompaniment and being the only caregiver. For stress, being younger and being the only caregiver were significant predictors. However, further Regression analysis indicated that all the other variables lost significance and showed no association, except for being the only caregiver, which remained a significant predictor of caregivers’ psychological distress ( Table 4).

In-depth interviews were conducted with ten caregivers aged 29-62 years, with an equal number of males and females. Most had completed undergraduate or postgraduate education, while two had no formal education. Six were employed, while the others were either unemployed, retired, or had left their jobs for caregiving. The analysis of data extracted from the interviews revealed emergence of the following themes, highlighting key aspects of their experiences and perspectives.

Many participants reported that caregiving significantly impacted their personal lives and well-being. They often neglected their own needs, feeling overwhelmed by the demands of caregiving. This dependency placed a heavy psychological strain on them. For some, particularly those who were the sole caregivers, it was emotionally draining, leaving them frequently exhausted and stressed. A few of the participants mentioned experiencing changes in their own health or well-being due to care-giving.

The level of responsibility among participants varied, with some bearing more duties than others, depending on the patient’s condition and the number of people involved in their care. Caregiving included various tasks such as attending doctor’s appointments, managing medications, overseeing diet, and handling the patient’s daily activities. Additionally, as this shift in responsibility sometimes occurred suddenly, many respondents found it exceptionally stressful and demanding to manage these responsibilities.

For most participants, caring for a cancer patient had a profound emotional impact. Witnessing a loved one’s suffering brought intense grief, fear, and frustration along with overwhelming responsibilities and uncertainties of their situation. However, there were also moments of hope and gratitude for the time spent together. This daily struggle between feeling powerless and finding the strength to help provided a sense of purpose and fulfilment amidst the emotional turmoil. For a few, the diagnosis felt like the end of life as they knew it, making the experience particularly stressful and challenging.

Some participants in our study expressed gratitude for the support they received from family and friends. They appreciated various forms of assistance, including financial help, as well as emotional support, understanding, motivation, and encouragement. Practical aid, such as neighbours helping with chores and providing guidance on treatment options, was also highly appreciated. Despite the challenges of caregiving, the presence of a supportive network made it easier for participants to manage their daily responsibilities.

While many participants expressed gratitude for the support they received from friends and family, some felt disappointed and helpless due to the lack of support. These individuals faced significant difficulties and had to cope with the situation entirely on their own, managing all caregiving responsibilities without assistance. This lack of support exacerbated the emotional and practical challenges they encountered, highlighting the disparities in caregiving experiences.

A few participants with low incomes faced significant financial hardships, struggling to afford prescriptions, medical supplies, and treatment co-pays. They often had to choose between paying for healthcare and other essential expenses like rent or groceries. However, they did receive some assistance through BSKY health cards. Among middle-income caregivers, most had health insurance, but out-of-pocket costs such as deductibles and co-pays still strained their budgets. Additionally, taking leave from work to care for their loved ones resulted in a loss of income, further adding to their financial stress.

Many participants initially faced challenges in understanding where to seek medical care and how to navigate the healthcare system, but over time, their communication with healthcare providers improved. A few participants, struggled to comprehend medical terminology and navigate the complex healthcare system. This lack of understanding ultimately caused confusion about caregiving among caregivers. Some participants, valued open communication with their team of doctors and actively sought updates on treatment plans and prognoses.

This study has some inherent limitations. Firstly, the sample size, primarily drawn from a single healthcare facility, limits the generalizability of our findings. To enhance the robustness and applicability of these findings, future research should consider conducting longitudinal studies on larger and more diverse population cohorts. Expanding participant recruitment across various settings and regions would further strengthen the study’s generalizability. Additionally, this study did not account for certain pertinent factors contributing to caregiver distress such as relationship with the patient, availability of financial support, physical strain, family background, and social support. Addressing these factors in future research will offer a more comprehensive understanding of caregiver well-being. Lastly, our analysis was confined to data collected within two-month timeframe, highlighting the need for further investigation to explore the long-term impacts of the factors studied.