| Literature DB >> 33541721 |
Nidhi Patni1, Arati Hota2, Ayushi Patni3, Pragya Misra2.
Abstract
In the unprecedented times of Corona Pandemic (CP), each individual is facing uncertainty and stress. Presence of cancer during these times compounds the troubles. The changing scenario of consultation and treatment during pandemic, logistic issues, dwindling finances and fear are making a negative impact on the mental health of cancer patients. In a qualitative analysis conducted in a tertiary oncology hospital from 1st June to 6th July on the recently diagnosed or under treatment cancer patients. The face to face interview was conducted using a semi structured questionnaire specific to Cancer amid CP, General Anxiety Disorder Item Scale 7 and Physical Health Questionnaire 9 (PHQ-9). There were total 294 patients, mean age around 51 years with a male female ratio of 3:2, 40% were suffering from head and neck malignancy. There was a delay initiating cancer treatment in 22.4% of patients and three fourths of them attributed it to CP. Almost 80% of patients perceived that pandemic has adversely affected their treatment and 50% thought they would have had a better chance of cure. Half of our cohort stated that due to social distancing and usage of masks, there is a communication gap between them and the doctors. They also felt that now, with decreased nonverbal communication; they felt lack of empathy. 14.9% patients were more concerned about corona pandemic as compared to malignancy. This study is about the challenges and perspective of cancer patients during the CP. It indicates a need for more systematic and patient friendly approach by the regulatory authorities, hospital management and staff. Timely intervention of those under stress is recommended more frequently during CP.Entities:
Keywords: Cancer; Corona pandemic; Mental health; Psychological impact
Mesh:
Year: 2020 PMID: 33541721 PMCID: PMC7669237 DOI: 10.1016/j.currproblcancer.2020.100671
Source DB: PubMed Journal: Curr Probl Cancer ISSN: 0147-0272 Impact factor: 3.187
Socio-demographic analysis.
| N (%age) | Mean | Mode | Standard deviation | ||
|---|---|---|---|---|---|
| Gender distribution | |||||
| Female | 117 (39.80%) | ||||
| Male | 177 (60.20%) | ||||
| Age wise distribution | 51•33 | 55 | 12•71 | ||
| Young Adults (18-35 yrs.) | 35 (11.90%) | ||||
| Middle age adults (36-55 yrs.) | 149 (50.68%) | ||||
| Older adults (>55yrs.) | 110 (37.41%) | ||||
| Marital status | |||||
| Married | 267 (90.82%) | ||||
| Unmarried | 12 (4.08%) | ||||
| Widow | 13 (4.42%) | ||||
| Separated | 2 (0.68%) | ||||
| Domicile | |||||
| Rural | 150 (51.02%) | ||||
| Urban | 144 (48.98%) | ||||
| Education | |||||
| Illiterate | 56 (19.05%) | ||||
| Primary | 66 (22.45%) | ||||
| Secondary | 83 (28.23%) | ||||
| Graduate | 53 (18.03%) | ||||
| Post Graduate | 36 (12.24%) | ||||
| N (%age) | |||||
| Employment status (before) | Employment status (present) | ||||
| Retired | 40 (13.60%) | Retired | 43 (14.63%) | ||
| Service | 46 (15.65%) | Service | 25 (8.50%) | ||
| Business | 41 (13.95%) | Business | 21 (7.14%) | ||
| Farming | 39 (13.27%) | Farming | 29 (9.86%) | ||
| House Wife | 89 (30.27%) | House Wife | 93 (31.63%) | ||
| Daily Labour | 28 (9.52%) | Daily Labour | 1 (0.34%) | ||
| Unemployed | 7 (2.38%) | Unemployed | 79 (26.87%) | ||
| Others (Student, Priest) | 4 (1.36%) | Student | 3 (1.02%) | ||
| Family Structure | |||||
| Joint | 195 (66.33%) | ||||
| Nuclear | 99 (33.67%) | ||||
| Economic status | |||||
| Below Poverty Line (BPL) | 23 (7.82%) | ||||
| Lower Income Group (LIG) | 101 (34.35%) | ||||
| Middle Income Group (MIG) | 142 (48.30%) | ||||
| Higher Income Group (HIG) | 28 (9•52%) | ||||
Fig. 1Qualitative data analysis - patient's perspectives on corona pandemic.
Psychological distress among cancer patients.
| Overall – N (%age) | Male – N (%age) | Female – N (%age) | |
|---|---|---|---|
| GAD – 7 | |||
| Mean | 6•06 | 6•05 | 6•07 |
| Mode | 0 | 0 | 0 |
| Standard Deviation | 4•65 | 4•54 | 4•83 |
| Severity | |||
| Minimal (0-4) | 134 (45.57%) | 82 (46.33%) | 52 (44.44%) |
| Mild (5-9) | 75 (25.51%) | 47 (26.55%) | 28 (23.93%) |
| Moderate (10-14) | 76 (25.85%) | 41 (23.16%) | 35 (29.91%) |
| Severe (15-21) | 9 (3.06%) | 7 (3.95%) | 2 (1.71%) |
| PHQ – 9 | |||
| Mean | 6.48 | 6.57 | 6.36 |
| Mode | 0 | 5 | 0 |
| Standard deviation | 4.73 | 4.63 | 4.89 |
| Severity | |||
| Minimal (1-4) | 113 (38.44%) | 63 (35.59%) | 50 (42.74%) |
| Mild (5-9) | 101 (34.35%) | 65 (36.72%) | 36 (30.77%) |
| Moderate (10-14) | 64 (21.77%) | 41 (23.16%) | 23 (19.66%) |
| Moderately Severe (15-19) | 13 (4.42%) | 7 (3.95%) | 6 (5.13%) |
| Severe (20-27) | 3 (1.02%) | 1 (0.56%) | 2 (1.71%) |
Comparative analysis of anxiety & depression (moderate to severe) with socio demographic variables.
| Gender | |||
| Female | 37 (43.53%) | 31 (38.75%) | |
| Male | 48 (56.47%) | 49 (61.25%) | |
| Domicile | |||
| Rural | 41 (48.24%) | 39 (48.75%) | |
| Urban | 44 (51.76%) | 41 (51.25%) | |
| Marital Status | |||
| Married | 76 (89.41%) | 73 (91.25%) | |
| Unmarried | 5 (5.88%) | 3 (3.75%) | |
| Divorce | 1 (1.18%) | .. | |
| Widow | 3 (3.53%) | 4 (5.00%) | |
| Education | |||
| Illiterate | 12 (14.12%) | 11 (13.75%) | |
| Primary | 15 (17.65%) | 20 (25.00%) | |
| Secondary | 30 (35.29%) | 24 (30.00%) | |
| Graduate | 15 (17.65%) | 16 (20.00%) | |
| Post Graduate | 13 (15.29%) | 9 (11.25%) | |
| Age grouping | |||
| Yong Adults (0-35 yrs) | 12 (14.12%) | 7 (8.75%) | |
| Middle Age Adults (36-55 yrs) | 50 (58.82%) | 44 (55.00%) | |
| Older Adults (56 and Above) | 23 (27.06%) | 29 (36.25%) | |
| Family structure | |||
| Joint | 59 (69.41%) | 58 (72.50%) | |
| Nuclear | 26 (30.59%) | 22 (27.50%) | |
| Economic status | |||
| BPL | 6 (7.06%) | 10 (12.50%) | |
| LIG | 34 (40.00%) | 28 (35•00%) | |
| MIG | 38 (44.71%) | 37 (46.25%) | |
| HIG | 7 (8.24%) | 5 (6.25%) | |