|Year : 2020 | Volume
| Issue : 2 | Page : 69-79
Effect of COVID-19 Home Confinement on Family Well-Being
Rooban Thavarajah1, Anusa Arunachalam Mohandoss2, Kannan Ranganathan1
1 Department of Oral and Maxillofacial Pathology, Ragas Dental College and Hospital, Affiliated to The Tamil Nadu Dr. MGR Medical University, Chennai, India
2 Marundeeswara Oral Pathology Services and Analytics, Chennai, India
|Date of Submission||02-Jul-2020|
|Date of Acceptance||31-Aug-2020|
|Date of Web Publication||16-Feb-2021|
Dr. Rooban Thavarajah
Department of Oral and Maxillofacial Pathology, Ragas Dental College and Hospital, Affiliated to The Tamil Nadu Dr. MGR Medical University, 2/102, East Coast Road, Uthandi, Chennai-600119
Source of Support: None, Conflict of Interest: None
Introduction: Home confinement (HC) due to Corona Virus Disease-19 (COVID-19) creates changes in family dynamics. A survey tool was developed based on existing tools to measure the changes in family attachment, bonding, changeability, and interaction during HC. The aim was to capture the changes in family well-being in a defined cohort of dentists and observe the role of sociodemographic factors in such a change. Material and Methods: A new tool “home containment mediated family improvement index (HCMFII)” was developed, pretested, and used for measuring the changes in family well-being. The survey intended to capture the basic demographic details along with HCMFII. This was developed as a Google form and circulated among Indian dentists for 72 hours from 29 May to 1 June. Descriptive statistics, measures of association, and one-way analysis of variance (ANOVA) were used to identify the difference between the demographic factors and HCMFII scores. P ≤ 0.05 was taken as significant. Result: In the 72 hours, 213 Indian dentists completed the survey. Of them, 37 (17.4%) had negative HCMFII scores, 56 (26.3) in neutral, and 120 (56.3%) with a positive outlook during HC compared to pre-COVID-19 situation. The mean HCMFII score was 53.9 ± 14. Age (P = 0.02), marital status (P < 0.00), children (P < 0.001), and income (P = 0.01) were significant factors influencing the scores. Discussion and Conclusion: A new tool to capture familial well-being in chrono-environment in presented. One of the two dentists perceived better family well-being, whereas one of the four perceived no change. Cause of concern is that one of the eight dentists still continue to have more disagreement-discordance than before HC and lesser family well-being. Extension of this index study would help to gauge the family well-being during HC and institute better modes of familial engagement to change the course of the pandemic.
Keywords: COVID-19, domestic violence, family bonding, family well-being, interaction, lockdown, mental health
|How to cite this article:|
Thavarajah R, Mohandoss AA, Ranganathan K. Effect of COVID-19 Home Confinement on Family Well-Being. J Orofac Sci 2020;12:69-79
|How to cite this URL:|
Thavarajah R, Mohandoss AA, Ranganathan K. Effect of COVID-19 Home Confinement on Family Well-Being. J Orofac Sci [serial online] 2020 [cited 2021 Aug 3];12:69-79. Available from: https://www.jofs.in/text.asp?2020/12/2/69/309581
| Introduction|| |
The novel severe acute respiratory syndrome coronavirus-2 is the etiological agent of the Corona Virus Disease-19 (COVID-19) pandemic. It has become a global health challenge due to its contagiousness and associated morbidity and mortality. As of June 15, 2020, COVID-19 has affected 8.02 million people globally causing 0.44 million deaths. In a bid to contain the spread of COVID-19 and prevent death, most of the countries have imposed “lockdown” or home confinement (HC). HC mandates staying indoors and working from home. The intent is to contain the spread of COVID-19 infection. COVID-19 has effect on personal, social, and physical (illness, hospitalization, lack of physical exercise) domains. There has been an impact on all aspects of normal life, including finance (loss/reduced income, increased expenses, unemployment, financial insecurity), restricted access to food and essentials, education (closure of school, alteration of examination), and mental health (fear, anxiety, distress, depression, less social contact, loneliness).,, Issues pertaining to substance abuse and domestic violence were projected to raise with HC.,,, Globally, the incidence of domestic violence is about 10% to 35% in nonpandemic situation. There are no reports on the dynamics or changes in the familial well-being and interaction during HC.
The broad definition of a family is that it is a unit of two or more persons united by marriage, blood, adoption, or consensual union, in general consisting of a single household, interacting and communicating with each other. It forms an essential, basic unit of the society and is used in this context in this study. Family well-being and functioning are important contributors for individual’s quality of life. Interaction among members of a family is complex in psychosocial domains, such as cohesion, expressiveness, conflict, independence, achievement orientation, intellectual-cultural orientation, active recreation orientation, moral-religious dimension, organization, and controlled interaction with society. Till date, there is no universally accepted measure that has captured family dynamics in entirety. Survey instruments in this field are being continuously improvised with a goal to capture and assess a particular trait or a domain. A few instruments tend to view family functioning as a whole, whereas others compartmentalize it. Some instruments have a clinical or therapeutic context, whereas others are for mass screening purposes. Clinicians and researchers usually administer surveys pre- and postintervention to measure the success of their intervention.,,,, Survey instruments have been used to identify various domains, such as family bonding, adaptation, changeability, and interaction. However, till date there is no instrument that captures domains of family bonding, adaptation, changeability, and interactions after a critical societal event such as HC. In light of this lacunae, we have attempted to formulate a survey instrument that captures the alteration in family dynamics in a postcritical societal adverse event due to the COVID-19 pandemic in a selected cohort.
Dentists are an integral part of the health care profession. Dental practice has been limited to emergency during current “lockdown” to curtail disease-spreading, aerosol-producing procedures. Dentists are under acute mental distress during this HC. This distress stems from fear of contagion, stigma associated with treating COVID-19 patients, concern for self/family well-being, unrealistic public perception, anxiety of encountering a COVID-19 infected patient, personal protective equipment availability, financial implications, and heightened need for infection control procedures., The increased pervasive stress due to COVID-19 in community and dentistry specific stress in HC has the potential to affect family interaction and dynamics. We hypothesize that COVID-19 HC has impacted the dynamics of familial well-being of dentists significantly.
| Material and Methods|| |
Family environment and interaction among family members is dynamic. It evolves with time and challenges. Our questionnaire was constructed using previously validated questionnaires of Survey of Family Environment-Japan (SFE-J), Family Environment Scale (FES), and Family Attachment and Changeability Index (FACI8) for a cross-sectional cohort.,,, We retained the family internal environment system (among family members); however, we limited questions that concern family external system. All questions were studied in their chrono-environment, which is a time framework that compares the past to present to future, that is, from pre-COVID-19 to present. The pooled questions were refined following discussion with professional colleagues to remove redundant questions. In all, 14 questions from FACI8, 6 from SFE-J, and 2 from FES were collated to form 22-question-containing survey instrument.
As face-content validity assessment could not be done, virtual pilot assessment was done on a convenience sample comprising 32 dentists representing 32 families. They were provided with a link containing all written information and consent was obtained. Reliability analysis had a Cronbach α of 0.74 and Cronbach α based on standardized items was 0.923. After obtaining the recorded response to the questionnaire, one of the authors Rooban Thavarajah (TR) debriefed the respective respondents and obtained comments concerning the content, readability, and overall impression of the questionnaire. Repeated revisions (32 interviews) of the items and instrument were performed with each subsequent debriefing. In all, three questions removed, four added, and five modified, making the final questionnaire with 23 questions. This final version of the questionnaire was named home containment mediated family improvement index (HCMFII).
HCMFII measures family internal environment in domains of changeability (a degree of flexibility of family members’ relationships with each other; seven questions), attachment (an enduring, strong, positive affectionate connection to family member(s) developing over years; seven questions), bonding (is the love, care, and concern that respondent feels and are unique to relationship with other family member(s); six questions), and interaction (a process by which two or more family members affect each other by action, verbal or nonverbal communication; three questions) in HC chrono-environment. Twenty-two questions concerned past to present and one captured ideation for present to future. This self-administered form takes a maximum of 4 minutes to complete. All the answers were evaluated on a 5-point Likert scale, with 0 indicating “strongly disagree”, 2 being neutral, and 4 being “strongly agree”. There were three questions (two on attachment and one on interaction) in reverse format, for ensuring consistency, as the survey was intended to be administered in electronic format. In all, the maximum possible score was 92 and minimum −12. Calculation of the overall scores or scores broken down by domains was obtained as a sum. Higher scores indicate betterment in family relationship with HC, whereas a lower score would be the reverse. An overall score of 46 means that there were no change with HC in HCMFII. The maximum-minimum-neutral for domains were: changeability: 28-0-14; attachment: 28-(-8)-14); bonding: 24- 0-12, and interaction: 12-(-4)-6. The HCMFII scores in chrono-environment were categorized as negative (score ≤40), neutral (41–52), and positive (≥53) to assess the situation of well-being in family compared to pre-HC.
This research met the guidelines and was approved by the institutional review board of the corresponding author’s institution. This survey was conducted from May 29 and lasted till June 1, 2020 in the Phase 4 and 5 of Indian COVID-19 lockdown transition, with both days inclusive. Survey was done exclusively in self-reportable form in English, designed using Google forms, and the link was shared among dentists in various closed social media platforms using snowball sampling technique. Anonymity was ensured, and no personal identification was collected. Participation was on voluntary basis. The demographics of gender, age group in years (>35, 35–44, 45–54, ≥55 years), current domicile, marital status (married/unmarried/separated/widowed), dental practice characteristics, mode of employment in dentistry (student/exclusive practice/exclusive academics/combined), annual income (in Indian rupee − below 5/5-10/10-15/15-20/>20 lakhs) were collected. Details of marriage, spouse occupation, and family structure (nuclear/joint family) were collected. The HCMFII was administered after consent.
The participants were questioned about their expectation at start of HC about possibility of increase in discordance-disagreement frequency (DDF) in the family. The response was categorized as yes (increased DDF), not sure, and no increase in DDF. The reality of DDF at the time of attempting the survey was also asked. Respondents categorized reality of DDF as increased or decreased or no change. The HCMFII was administered and response (total HCMFII and domain) scores formed the outcome variable.
The link to Google form was kept open for 72 hours. All data thus collected were downloaded in Excel format. The data were then entered and analyzed using Statistical Package for Social Services software (IBM Corp. Released 2016. IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM Corp). Reliability of the HCMFII was performed by reliability analysis. Descriptive statistics, mean ± standard deviation (SD), (minimum-maximum; range; inter-quartile range [IQR]) for continuous variables, and proportions for categorical variables were calculated. Comparison of expectation about discordance/disagreement within family at the start of the HC and the reality by the various sociodemographic factors was assessed by χ2 test. Comparison between the expectation and reality was also assessed by the χ2 test. The reliability analysis was carried out by calculating Cronbach α and Cronbach α based on standardized items. One-way analysis of variance (ANOVA) test was employed to identify the difference in mean ± SD with 95% confidence interval (CI) by various sociodemographic factors for the HCMFII and its domains. Similarly, the one-way ANOVA was performed for expectation and reality of DDF was also performed. The categorized HCMFII scores were compared with sociodemographic factors, DDF expectation, and reality using χ2 test. P ≤ 0.05 was considered statistically significant.
| Results|| |
In all, 236 participants attempted the survey. Of them, 23 declined to consent and did not participate in the survey. Two hundred and thirteen dentists completed the survey and formed this study group. Of this, only 179 (84%) were willing to share their income details. For this parameter, only scores of 179 were considered. Of the 213, 112 (48.5%) were males, 153 (71.8%) were >44 years of age, 182 (85.5%) were married, 122 (52.8%) living in joint family, 99 (46.5%) had two children, 61 (34.1%) had a combined family annual income between 5 and 10 lakhs, 129 (60.6%) were the only dentists in the family, and 85 (39.9%) indulged in academics and practice [Table 1].
|Table 1 Expectation about discordance-disagreement in family at start of home confinement versus reality by sociodemographic of the study population|
Click here to view
The distribution of the dentists among sociodemographic parameters in terms of expectation and reality of DDF in HC was studied using χ2 test. Family structure had a difference that was statistically significant (P = 0.005) [Table 1]. On comparing expectation DDF with the real DDF, there was statistical significance. Among those who experienced more DDF than usual (n = 37), 14 (37.8%) had expected the DDF to be less, 11 (29.7%) were not sure, and 12 (32.4%) believed that DDF would be more. This difference was statistically significant (P = 0.001) [Figure 1].
|Figure 1 Expectation Vs Reality of frequency of discordance- disagreement among family members in COVID-19 Home confinement Period|
Click here to view
For the 23-item questionnaire, the Cronbach α was 0.888 (based on the standardized item as 0.897) and if any item is deleted, the Cronbach α turned less or equal. The mean ± SD [minimum to maximum; range; IQR] HCMFII score was 53.85 ± 13.97[1-78; 77; 14.5]. The same for various domains were attachment (12.3 ± 4.63[-4 to 20; 24;6]), bonding (18.05 ± 4.73[0 to 24; 24; 7], changeability (20.4 ± 5.36[0 to 28; 28; 7]), and interaction (3.1 ± 1.87[-3 to 8; 11; 2]).
There were 37(17.4%) in negative HCMFII scores, 56(26.3%) in neutral, and 120(56.3%) with a positive outlook in family well-being during HC compared to pre-COVID-19 situation. [Table 2] shows the sociodemographic factors, DDF reality, and expectation compared by the HCMFII categories. The proportion of dentists with positive family well-being was observed among middle-aged dentists (P = 0.02), married dentists (P = 0.01), and those with children (P = 0.002). The reality of DDF showed that 57 dentists who had positive HCMFII scores had less DDF than usual, 12 having more, and 51 having neutral scores. This difference was statistically significant (P < 0.001).
One-way ANOVA analysis of HCMFII scores with sociodemographic parameters revealed that the age group (P = 0.016), marital status (P = 0.001), number of children (P < 0.001), combined annual income (P = 0.01), and the mode of dentistry (P = 0.037) were significant [Table 3]. [Table 4] and [Table 5] show the mean difference among sociodemographic parameters in four domains of the HCMFII. In the attachment domain, annual income of the household was significant (P = 0.04). For bonding, age group (P = 0.007), marital status (P = 0.001), number of children (P < 0.001), income (P = 0.025), and mode of dentistry (P = 0.002) were significant. For the changeability, the age (P = 0.023), marital status (P = 0.001), number of children (P = 0.002), and income (P = 0.032) were significant. For the interaction, only marital status (P = 0.025) and number of children (P = 0.029) were statistically significant.
|Table 3 Home containment mediated family improvement index scores by sociodemographic parameters using one-way analysis of variance|
Click here to view
|Table 4 Attachment and bonding domain scores by sociodemographic parameters of study population|
Click here to view
|Table 5 Changeability and interaction domain scores by sociodemographic parameters of study population|
Click here to view
The mean HCMFII and its domain scores were compared within the expectation as well as reality of DDF. The HCMFII and its domain scores were not statistically significant in expectation group, whereas for the reality, all the domains and HCMFII were highly significant (P < 0.001) [Table 6].
|Table 6 One-way analysis of variance test result showing the mean difference between outcome measures in terms of expectation about discordance/disagreement frequency at start of home confinement and reality|
Click here to view
| Discussion|| |
HC during COVID-19 pandemic resulted in a majority of the families spending more time together. The familial dynamic changes during HC have not been reported till date. It is established that when facing adversity, individual and familial psychosocial dynamics change, for example, individuals can turn more supportive or become self-centered., Family dynamics can be potentially harnessed to favor societal and social behavioral change for the community management of COVID-19 spread. This manuscript was designed as a survey-screening tool to capture the alteration of familial dynamics in the domains of attachment, changeability, interaction, and bonding. The survey tool was based on designs of previously published tools and a pilot survey that was tested among Indian dentists. As there is no precedence to the pandemic, the survey tool could not be compared against any other literature.
None of the studied sociodemographic parameter proportions were statistically significant for DDF expectation before the start or while taking the survey, except family structure in reality. Those in nuclear families had lesser than usual DDF in family during HC, as seen in [Table 1]. This trend has been previously reported. One-in-eight (n = 27, 12.7%) had more DDF than the pre-COVID-19 HC. Of this, 12 (32.4%) had anticipated increase in DDF, 11 (29.7%) were not sure, and 14 (37.8%) had not anticipated this increase in DDF. This difference between the less and no change in DDF was statistically significant, indicating that a significant number of respondents had perceived the situation wrongly. This emerged as a first clue that familial dynamics have been significantly altered due to HC. The next evidence comes from [Table 2], indicating sociodemographic factors of age, marital status, and children had an influence on the HCMFII categories and the effect of familial well-being with HC. One of the two dentists perceived better scores with HCMFII, whereas one-in-four perceived no change in their family well-being [Table 2].
The HCMFII and its domain scores were studied for influence by other factors. The sociodemographic parameters showed statistical difference among age group, marital status, children, annual family income, the number of dentists in the same family, and the mode of dentistry practiced with statistical significance.
The role of gender in influencing HCMFII and its domains was studied. The absence of significance in HCMFII and its domains between genders was a significant finding. When stressed, males generally respond with a “flight or fight”, whereas females are associated with “tend and fend”. Biobehavioral mechanism are suggested to underlie behind this tend-and-fend pattern that works through the attachment-caregiving system. However, in the present study, we failed to notice such a difference and this needs further study.
Age influenced the HCMFII scores. Older respondents had higher HCMFII scores. Marital status has a significant impact on the HCMFII scores and is in line with previous studies on familial interaction. This is again higher when the respondents have children. This is in agreement with previous reports on similar lines., Joint families were believed to be a source of immense support, especially in stressful situation by increasing the bonding and providing resilience., However, we could not find any statistical significance in terms of family structure, though in DDF the reality differed significantly for this factor [Table 1]. This diverse finding needs further investigations. The HCMFII scores differed between family incomes, indicating that money is a critical factor that still continues to influence the level of interaction, bonding, and attachment to other family members. Mode of dentistry has a bearing on the stress and this is also reflected in this study,,,, [Table 2].
An attempt was to identify the role of each domain being influenced by sociodemographic parameters. Attachment domain was not influenced by any factor except income levels. Attachment is a long process and takes time. As the HC was short (∼60 days), probably it has not provided sufficient time to capture the alteration in the attachment level among family members or recall bias could have contributed to this phenomenon. Lack of sufficient sensitivity of the questions to capture attachment alteration is another possibility. However, as the domain has been used successfully to capture alteration in familial attachment, it can be ruled out. Attachment is a complex factor and needs more time to happen, especially in stressful situations such as COVID-19 HC. With increase in family income, higher family attachment scores are seen. As affluence increases, the family tends to spend time together and this may have contributed to the difference in scores.,,, In all probabilities, this difference could have persisted even before HC [Table 3].
Bonding between family members is expected to happen when they share more time together. However, this is influenced by age, marital status, children, income, and mode of dentistry practiced. Highest bonding score are shown by middle aged. This age, in Indian family setup, is associated with other significant factors such as marital status and children.,, Being a family increases the paternal, maternal bonding with their children. As there is increase in children from none to one to two, the bonding score increases, indicating the children play an important role in family bonding. Similarly, as income increases, the bonding score increases. When financial security is achieved, the financial worries are removed, paving more free time to be spent and bonded with children. Hence, the boding domain scores increase.,, Mode of dentistry has an important influence on the family bonding. Dental postgraduate students are known to have high levels of stress and the HC would have amplified the same, leading to least bonding with family members. Those dentists who pursue academics and practice show less bonding scores possibly, as their energy is demanded on two fronts compared to exclusive practitioners or academicians,,,, [Table 4].
Older respondents demonstrated that with age they secure higher changeability scores. With adversity, older people react better with family as in line with previous studies. Similarly, married people have higher scores than others, indicating that respondents have changed or readily adapt to situation better than others during HC. When the respondents have children, they have accommodated more during the HC. This changeability again is dependent on the income of the family as well as the coping mechanism.,, Interaction with family is highest among married and those with children. Possibly, dentists have spent more time with their family than ever before, which is reflected in this score. Similar results are being reported ,, [Table 5].
HCMFII score and its domain scores did not differ by the expectation of the DDF while all the domains were significant for the reality [Table 6]. This could reflect two facts − one that the dentist family dynamics in reality have changed than expected. Second, the survey instrument has been able to capture the changes accurately. When the DDF were less than usual, they had more scores in all domains and HCMFII followed by no change group and least score when the DDF were higher than normal. This is expected as the response varies among families, especially when facing adversity, in reality.
The family is a culturally sanctioned social institution. It is at the family, the basic orientation of survival and social life are transferred. Hence, it is considered as the basic unit of life. Most of the children learn and refine the value of individual/societal norms from their family. Increase in studied values of attachment, bonding, interaction, and changeability for better indicates that the family well-being is increased, though in this current anthropocene old values have given ways to newer dimensions, values, and models., The HC induced by COVID-19 has provided a chance to rediscover, reinvent, and introspect the familial bonding, attachment, interaction, and changeability. The results of the study show that majority of respondents were having better familial relationship in terms of bonding, changeability, and interaction.
The results of this study indicate that 176 (82.6%) dentists had no change or less than usual DDF compared to pre-COVID-19. The same number of respondents felt positive changes in the family as reflected by the HCMFII scores [Table 1]. As reflected by the scores in subgroups of the mode of profession and the number of dentists in the family, it could be safely assumed that this survey tool is not dentist specific; rather, it can be employed for any individual or critical event, but in chrono-environment. The role of external environment in causing psychological stress has not been studied. Factors such as job, risks associated with it, income instability, and infection spread in neighborhood could precipitate stress and play a vital role in resiliency of the family unit. Possibly an additional, complementary questionnaire could be developed to address the influence of this factor. The study identifies that though most of the dentists feel that their family interaction, changeability, and bonding have altered for betterment, attachment domain has not seen much improvement during the HC. Possibly long-term effect may show the degree of improvement of this domain. The cause of concern is that still one of the eight dentists experiences increased DDF and has poor scores of HCMFII scores.The reason for choosing dentists as a study population was to get a more homogeneous cohort. The reason for avoiding external family environment was not only to mitigate factors such as financial, educational, and medical-related issues, but also to prevent the spillover effect of routine work-to-home and home-to-work stress. This factor is often ignored in dental professional well-being studies. These stresses need to be accounted, as they contribute to a spectrum of health needs, including the psychosocial attributes (such as conflict between the roles as a family member and profession). These effects may be productive (role enhancement) or counterproductive (role strain). The factors identified to influence familial well-being are much similar to those of various other previous studies in different well-being context.
The result of this study has to be construed keeping in mind that the design is cross-sectional and done during the time of pandemic and among a relatively small, smartphone-handling, highly literate sample. This sample could not be representative of the population. Additionally, the limitations in online surveys, particularly those in which the response rate is not known, with outliers and other confounding factors pose challenge., The inherent complexity of family dynamics and Indian societal setup needs to be factored in. These limitations underline the need for further studies with a larger sample size and accounting for more sociodemographic factors. Future studies have to take these limitations into account.
| Conclusion|| |
The acute psychological challenges posed by COVID-19 and HC are widely being reported. There are changes in familial well-being domains. Family well-being is a determinant to societal, social behavioral changes that can impact spread of COVID-19. We propose a new tool to capture family well-being in a time-related environment. This tool has shown that the domains of changeability, bonding, and interaction have improved with HC in majority of the respondents, while the attachment domain does not show significant improvement statistically. Age, income, number of children, and family structure (joint/nuclear) are important factors influencing the family well-being. This tool would be valuable in a heterogeneous population too. Once validated, the policy makers can identify vulnerable populations to provide need-based psychological aid to create better family life for citizens.
The authors thank Dr N. Azhagarasan MDS and management of Ragas Dental College and Hospital for their continuous support and encouragement during this COVID-19 pandemic. We thank all the participants for their time.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Klompas M. Coronavirus disease 2019 (COVID-19): protecting hospitals from the invisible. Ann Intern Med 2020;172:619‐20.
Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis 2020;20:533-4. doi: 10.1016/S1473-3099(20)30120-1. Epub 2020 Feb 19. Erratum in: Lancet Infect Dis. 2020 Sep;20(9):e215. PMID: 32087114; PMCID: PMC7159018; Factual Data from https://coronavirus.jhu.edu/map.html
[Last accessed 16.5.2020].
Wang G, Zhang Y, Zhao J, Zhang J, Jiang F. Mitigate the effects of home confinement on children during the COVID-19 outbreak. Lancet 2020;395:945‐7.
Dong L, Bouey J. Public mental health crisis during COVID-19 pandemic, China. Emerg Infect Dis2020;26:1616-8. doi: 10.3201/eid2607.200407. Epub 2020 Jun 21. PMID: 32202993; PMCID: PMC7323564.
Ramasubramanian V, Mohandoss AA, Rajendhiran G, Pandian PRS, Ramasubramanian C. Statewide survey of psychological distress among people of Tamil Nadu in the COVID-19 pandemic. Indian J Psychol Med 2020;42:368-73. doi:10.1177/0253717620935581 PMCID: PMC7375356.
Usher K, Bhullar N, Durkin J, Gyamfi N, Jackson D. Family violence and COVID-19: increased vulnerability and reduced options for support. Int J Ment Health Nurs 2020;29:549-52. doi: 10.1111/inm.12735. Epub 2020 May 7. PMID: 32314526; PMCID: PMC7264607.
Armitage R, Nellums LB. Substance misuse during COVID-19: protecting people who use drugs. Public Health 2020;183:63. doi: 10.1016/j.puhe.2020.05.010. Epub 2020 May 13. PMID: 32405098; PMCID: PMC7218358.
van Gelder N, Peterman A, Potts A, O’Donnell M, Thompson K, Shah N, Oertelt-Prigione S. Gender and COVID-19: reducing the risk of infection might increase the risk of intimate partner violence. EClinicalMedicine 2020;21:100348. doi: 10.1016/j.eclinm.2020.100348. PMID: 32292900; PMCID: PMC7151425.
Flury M, Nyberg E, Riecher-Rössler A. Domestic violence against women: definitions, epidemiology, risk factors and consequences. Swiss Med Wkly 2010;140:w13099. doi: 10.4414/smw.2010.13099. PMID: 20853195.
Sharma R. The family and family structure classification redefined for the current times. J Fam Med Primary Care 2013;2:306-10.
Pritchett R, Kemp J, Wilson P, Minnis H, Bryce G, Gillberg C. Quick, simple measures of family relationships for use in clinical practice and research. A systematic review. Fam Pract 2011;28:172‐87.
Boyd CP, Gullone E, Needleman GL, Burt T. The family environment scale: reliability and normative data for an adolescent sample. Fam Process 1997;36:369‐73.
Botha F, Booysen F. Family functioning and life satisfaction and happiness in South African households. Soc Indic Res 2014;119:163-82.
McCubbin HI, Thompson AI, Elver KM. Family attachment and changeability index 8 (FACI8). In: McCubbin HI, Thompson AI, McCubbin MA (Eds.), Family Assessment: Resiliency, Coping and Adaptation: Inventories for Research and Practice. 1st ed. Madison: University of Wisconsin 1996. p. 725-51.
Hohashi N, Honda J. Development and testing of the survey of family environment (SFE): a novel instrument to measure family functioning and needs for family support. J Nurs Meas 2012;20:212‐29.
Farooq I, Ali S. COVID-19 outbreak and its monetary implications for dental practices, hospitals and healthcare workers. Postgrad Med J 2020; postgradmedj- 2020-137781. doi:10.1136/postgradmedj-2020-137781. Epub ahead of print. PMID: 32245754.
Nair AKR, Karumaran CS, Kattula D, Thavarajah R, Mohandoss AA. Stress levels of Indian endodontists during COVID-19 pandemic. Rev Cubana Estomatol 2020;57:e3445.
Bavel JJV, Baicker K, Boggio PS et al.
Using social and behavioural science to support COVID-19 pandemic response. Nat Hum Behav 2020;4:460‐71.
Converse BA, Risen JL, Carter TJ. Investing in karma: when wanting promotes helping. Psychol Sci 2012;23:923‐30.
Savani K, Rattan A. A choice mind-set increases the acceptance and maintenance of wealth inequality. Psychol Sci 2012;23:796‐804.
Samanta T. The joint family and its discontents: interrogating ambivalence in intergenerational relationships. Asian Popul Stud 2019;15:28-46.
Taylor SE, Klein LC, Lewis BP, Gruenewald TL, Gurung RA, Updegraff JA. Biobehavioral responses to stress in females: tend-and-befriend, not fight-or-flight. Psychol Rev 2000;107:411‐29.
Prime H, Wade M, Browne DT. Risk and resilience in family well-being during the COVID-19 pandemic. Am Psychol 2020;75:631-43. doi: 10.1037/amp0000660. Epub 2020 May 21. PMID: 32437181.
Torres AP, Marshall MI, Sydnor S. Does social capital pay off? The case of small business resilience after Hurricane Katrina.J Contigencies Crisis Manag 2019;27:168-81.
Alani A, Bishop K, Djemal S. The influence of specialty training, experience, discussion and reflection on decision making in modern restorative treatment planning. Br Dent J 2011;210:E4.
Knipe D, Maughan C, Gilbert J, Dymock D, Moran P, Gunnell D. Mental health in medical, dentistry and veterinary students: cross-sectional online survey. BJPsych Open 2018;4:441‐6.
Singh P, Aulak DS, Mangat SS, Aulak MS. Systematic review: factors contributing to burnout in dentistry. Occup Med (Lond). 2016;66:27‐31.
Collin V, Toon M, O’Selmo E, Reynolds L, Whitehead P. A survey of stress, burnout and well-being in UK dentists. Br Dent J 2019;226:40‐9.
Bretherton I. Attachment and bonding: from ethological to representational and societal perspectives. In: Van Hasselt VB, Herson M (Eds.), Handbook of Social Development. 1st ed. New York: Plenum 1992. p. 133-55.
Sutton TE. Review of attachment theory: familial predictors, continuity and change, and intrapersonal and relational outcomes. Marriage Fam Rev 2019;55:1-22.
Thomas PA, Liu H, Umberson D. Family relationships and well-being. Innov Aging 2017;1:igx025. doi: 10.1093/geroni/igx025. Epub 2017 Nov 11. PMID: 29795792; PMCID: PMC5954612.
Wu W, Stephens M, Du M, Wang B. Homeownership, family composition and subjective wellbeing. Cities 2019;84:46-55.
D’Cruz P, Bharat S. Beyond joint and nuclear: the Indian family revisited. J Comp Fam Stud 2001;32:167-94.
Bhat AK, Dhruvrajan R. Ageing in India: drifting intergenerational relations, challenges and options. Ageing Soc 2001;21:621-40.
Vitaliano PP, DeWolfe DJ, Maiuro RD, Russo J, Katon W. Appraised changeability of a stressor as a modifier of the relationship between coping and depression: a test of the hypothesis of fit. J Pers Soc Psychol 1990;59:582‐92.
Ungar M. Varied patterns of family resilience in challenging contexts. J Marital Fam Ther 2016;42:19‐31.
Wang C, Pan R, Wan X et al.
Immediate psychological responses and associated factors during the initial stage of the2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health 2020;17:1729.
Varshney M, Parel JT, Raizada N, Sarin SK. Initial psychological impact of COVID-19 and its correlates in Indian Community: an online (FEEL-COVID) survey. PLoS One 2020;15:e0233874.
Hochschild AR. When work becomes home and home becomes work. In: Henslin JM (Ed.), Life in Society: Readings to Accompany Sociology, a Down-to-Earth Approach. 8th ed. Boston: Pearson; 2007. p. 169-78.
Fernandes GC, Boehs AE, Denham SA, Nitschke RG, Martini JG. Rural families’ interpretations of experiencing unexpected transition in the wake of a natural disaster. Cad Saude Publica 2017;33:e00161515.
Chandola T, Martikainen P, Bartley M et al.
Does conflict between home and work explain the effect of multiple roles on mental health? A comparative study of Finland, Japan, and the UK. Int J Epidemiol 2004;33:884‐93.
Deaton A. Income, health, and well-being around the world: evidence from the Gallup World Poll. J Econ Perspect 2008;22:53‐72.
Burke M, Hodgins M. Is ’Dear colleague’ enough? Improving response rates in surveys of healthcare professionals. Nurse Res 2015;23:8‐15.
Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. Am J Pharm Educ 2008;72:43.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]