Learnings from Conducting Online Surveys in India During the COVID-19 Pandemic

doi:10.21203/rs.3.rs-4823050/v1

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Learnings from Conducting Online Surveys in India During the COVID-19 Pandemic

https://doi.org/10.21203/rs.3.rs-4823050/v1

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When traditional research data collection methods were stalled due to the COVID-19 driven large-scale lockdown across India, it led to a sharp rise in the use of digital platforms to collect research data. In 2020, we launched three online surveys (including cross-sectional and longitudinal surveys) aimed at understanding the mental health concerns and needs of different populations in India. This paper presents the learnings from conducting these surveys and highlights the experience of our team with respect to different phases of the studies such as conceptualisation, development, recruitment, and dissemination. Our key findings are that: collaboration with relevant organisations was the most effective method for mass dissemination and recruitment; despite an aim of wide recruitment, survey recruitment came primarily from known networks; if aiming for recruitment via significant social media dissemination, then translation into regional languages was not effective on its own; and the visual design, user interface, and ease of language play a key role in making the survey accessible, inclusive, and easy to navigate. Based on these learnings, we present recommendations for the planning and execution of online surveys in low-resource settings.

Online Surveys

India

COVID-19 Pandemic

mental health

methodological learnings

On 25 March, 2020, a nationwide lockdown was announced in India due to the rapid increase in the number of COVID-19 cases. Social distancing and restricted movement became the new ‘normal’ for citizens, both nationally and globally. In India, the lockdown introduced prohibitive guidelines including the suspension of public transportation; closing of educational institutions, workplaces, and entertainment centres; and a ban on any form of social, political, or religious gathering. Unexpectedly and overnight, individuals were compelled to shift their lives ‘online’ and rely on digital media for their regular activities such as education, work, hobbies, and connecting with loved ones. In the research community, conventional data collection methods that necessitated in-person interactions like interviews, focus group discussions (FGD), pen and paper administration of surveys, were paused for the foreseeable future or at least until the pandemic was under control.

At the same time, there was a global call to action defining research priorities for COVID-19, with a focus on mental health, social cohesion, and connectedness (1). This resulted in a sudden rise in online surveys to explore the psychosocial impact of the pandemic (2). Online surveys offered a unique opportunity to continue data collection in lieu of face-to-face methods that were paused to prevent the spread of COVID-19. Online surveys are also an inexpensive and quick method to collect real-time data for emergency responses, such as the one mandated by a pandemic (3).

Prior to the pandemic, India already faced a significant burden of mental health issues. It was essential to explore the mental health impacts of the pandemic to ensure that policymakers and healthcare providers can develop targeted interventions and allocate resources effectively to support the mental well-being of the population. Responding to the evolving situation and with the goal of understanding mental health impacts of the pandemic on the Indian population, we launched three online surveys as follows: (a) My Wellness and COVID-19 (WAC), to examine the mental health and social effects resulting from social isolation in India due to COVID-19; (b) Young People’s Health Survey (YPHS), to understand the prevalence of anxiety, depression, substance use, and dating violence in young people between the ages of 18–24 years; and (c) Heal Well India (HWI), to examine how the mental health of healthcare workers was impacted during the pandemic. Copies of all three are provided in a supplementary file.

The data from these surveys are in the process of being analysed and written up for publication. This paper specifically focuses on a number of issues and challenges that arose in the undertaking of these and draws together the learnings that we have acquired as a result of overcoming those challenges. In the following sections, we summarise some of the methodological decisions that we took, outline the issues that arose related to these decisions, and how the resulting challenges were overcome. We end by outlining recommendations for those undertaking similar work in the future.

WAC (and later HWI) were designed as longitudinal studies (repeat surveys) whereas the YPHS was designed as a cross-sectional survey for online administration. The surveys were hosted on REDCap (Research Electronic Data Capture) and linked to a dedicated website. All three surveys received ethical approval from the Institutional Review Board of the host institution. Each survey assessed eligibility before the consenting process and directed participants to the information sheet and consent form for that study. Different sociodemographic variables were collected based on the survey population and intended use. Each survey included a set of standardised tools to obtain data pertaining to specific domains relevant to each study. Our recruitment strategy for all three surveys was multi-modal, primarily online, due to COVID-19. The response rates for the surveys were between 25–40%. Once lockdown restrictions were relaxed, in-person recruitment was conducted in Goa and Bhopal, targeting remote areas where participants may not have had the means or digital access to complete an online survey.

Synthesis of learnings

Given the intervals between the release of each of the three surveys, the subsequent surveys were informed by insights and findings from the preceding ones. Throughout the study, learnings were systematically documented into a ‘log of learnings’, during weekly project management meetings. Dissemination strategies, particularly digital approaches, were regularly evaluated. For instance, website and social media analytics were monitored to assess both the accessibility and comprehensibility of the content.

Once the recruitment period for the three online surveys was closed, the survey team, composed of early career researchers and data managers, came together to share their experiences and overall insights, which were then consolidated and added into the ‘log of learnings’. This process involved synthesising learnings from each study as well as identifying favourable outcomes and roadblocks common across surveys. Suggestions and feedback collected over a period of time from other team members (interns and host institution’s youth advisory board) who had contributed to the survey design and/or implementation were also factored in.

A few mutual challenges emerged, such as plateaued recruitment one-month post-launch, issues with REDCap (software), the initial determination of the appropriate questionnaire length and so on. It was also helpful to explore which strategies worked the best for the intended target audience. For example, the YPHS garnered the highest number of completed responses because online dissemination was an effective method to reach a young audience (18–24-year-olds). For both WAC and HWI, a revised dissemination strategy that was less reliant on digital methods was introduced to better reach the intended target groups.

The learnings, challenges, and potential solutions arising from team members’ experiences were a mix of both generalisable, and contextual, insights. Relevant findings from the ‘log of learnings’ are incorporated into the ‘results’ section below.

Between 2020-21, three online surveys were launched to gather data regarding the mental health impacts of the pandemic. The details of the surveys are described in Table 1.

Table 1

Survey details
Survey	My Wellness and COVID-19 Survey (WAC)	Young People’s Health Survey (YPHS)	Heal Well India Survey (HWI)
Aim	To examine the mental health and social effects resulting from social isolation in India due to COVID-19	To understand the prevalence of anxiety, depression, substance use, and dating violence in young people between the ages of 18–24 years	To examine how the mental health of healthcare workers was impacted during the pandemic
Type	Longitudinal	Cross-sectional	Longitudinal
Audience	1) Anyone above the age of 18 years 2) Indian citizens 3) Currently residing in India	1) Young people between the ages of 18–24 years 2) Indian citizens 3) Currently residing in India	1) Healthcare professionals above the age of 18 years 2) Indian citizens 3) Currently residing in India
Variables explored	Current Covid-19 status; caregiving responsibilities; access to essential goods; knowledge about Covid-19; time spent in home-based activities; patterns of home-based activities; and differences in life since Covid-19 were assessed	Substance use; common mental disorders; physical activity and sports engagement; prevalence and patterns of dating violence and risky behaviours	Experiences, fears, and concerns about COVID-19; trust in the workplace and formal; anxiety, depression, and substance use-related problems; prevalence of Posttraumatic Stress Disorder; resilience
Target sample size	1275	1800	2000
Reach (attempted responses)	1404	3409	648

In this section we describe the challenges faced in conducting the surveys and mitigation strategies deployed in response.

Dissemination and recruitment

In the first month after the launch of each survey, rigorous dissemination was undertaken through social media platforms (e.g., Instagram, Facebook, Twitter), newsletters, emails, and WhatsApp. Typically, the disseminated messages included a brief note about the survey, eligibility criteria, and the survey link. These messages were tailored to each platform – for example, colourful and interactive graphics were developed for social media and messenger apps whereas text-based information was shared via email.

Since each survey targeted a different set of populations, we created a database of our existing networks within those populations. Tapping into known contacts and snowballing from there seemed to be the most effective strategy across surveys. We observed a spike of eighty to hundred responses within the first month post-launch, as a result of active sharing of survey links within personal and professional networks. However, once our personal networks were exhausted, the recruitment numbers started to plateau.

Another strategy adopted by the team was cold emailing relevant stakeholders and organizations. Barring a few exceptions, we did not receive any interest or responses through cold emailing. Paid advertisements on social media were deployed to enhance recruitment efforts, which facilitated greater visibility of the surveys but did not lead to a significant increase in recruitment numbers.

Launched in the middle of the first lockdown, the WAC survey was well-received since online activities were at an all-time high during that time period. Gradually, the response rate declined. Participant feedback suggested that the survey was too lengthy (it took at least 20 minutes to complete). The pandemic also evolved rapidly, and survey questions that were relevant during the first lockdown were no longer relatable at follow up data collection 8–12 months down the line. For example, questions like ‘time spent doing home-based activities’ were appropriate during the lockdown and were perceived to be no longer relevant once the lockdown was lifted.

Another recruitment technique used was to disseminate information about and a link to the survey through an advert in a local newspaper. This technique was intended to disseminate the survey to a larger audience which may not be present on social media platforms but were consumers of traditional media. However, no discernible spike in recruitment was observed immediately after this strategy was deployed.

For the YPHS, we mobilised our advisory board consisting of nineteen young people from across the country to disseminate the survey within their networks. Collaborations with youth-led and youth-centric organizations in the socio-development sector helped us garner the highest number of responses when compared to other recruitment strategies. Three ways in which these collaborations worked were: (a) the collaborating organization shared our survey within their networks through social media, email, and WhatsApp; (b) the collaborating organization circulated our survey to their networks on the condition that we amplified their work on our own digital platforms. For example, we shared the link to an online survey conducted by a collaborating organization on our social media channels, and they reciprocated by circulating our survey within their networks; (c) paid collaborations with organizations, which included partnering with an organization with access to a vast network of our survey’s target audience. This collaboration was formalised through a contract agreement specifying the deliverables and terms of payment. The first two strategies provided a momentary boost in responses and greater visibility for the surveys on digital platforms. The third led to a much more substantial boost; we engaged in a paid collaborated with Yuvaa [Yuvaa.co.uk], a youth engagement media platform in India, resulting in the generation of over 900 responses in about four months from a diverse sample of young people, which we may not have been able to reach otherwise. Yuvaa’s Youth Champions widely disseminated the YPHS links across their university networks. A unique code (such as YUVAA01) accompanied the links, which enabled the data manager to track the responses from Yuvaa’s network on the backend. We ensured that participants’ identity was kept confidential and only accessible to the data manager.

Once the lockdown restrictions were relaxed and lifted after the second wave of the pandemic, we conducted in-person dissemination of the online survey. This involved circulating the survey link and QR code during in-person interactions with potential participants at events such as college workshops. For remote areas with limited network connectivity in two states where we had available staffing, in-person assisted administration was used. This involved enabling the participants to take the survey on a project-owned digital tablet or completing a paper-pencil questionnaire.

During in-person workshops with college students in one state, the link and QR code for YPHS was shared using a PowerPoint slide, and printed brochures and stickers. This dissemination strategy enabled us to recruit young participants from that state, a sample that was not adequately covered during online dissemination.

For the HWI survey, a comprehensive database was created including audiences such as government and private hospitals, public health organizations, medical colleges and associations, physical and mental healthcare professionals, Accredited Social Health Activists (ASHA workers), and social media influencers working in the healthcare sector. The survey link was emailed in a staggered manner to one audience group each week. Most of these audience networks included new contacts and as mentioned earlier, cold emailing did not yield many results. In fact, the HWI survey received the least number of responses as compared to the other two surveys, possibly due to the fact that healthcare professionals were exceptionally preoccupied during the pandemic. However, in-person assisted administration using digital or paper-pencil questionnaires helped us gather more responses from remote areas in the state.

Translation

English versions of the surveys were created relatively speedily following the initial idea for each survey, and the preliminary work in developing the questions. However, translating a lengthy questionnaire into Indian regional languages such as Hindi, Marathi, and Konkani was considerably time-consuming. It was challenging for our in-house team to find the most appropriate translation of words which were not culturally equivalent such as ‘psychosocial’ and ‘well-being’, into regional languages. One solution attempted was to hire an external agency for translation, however, the coordination and proofreading required from our team led to a delay in our timelines. This meant that each survey translated into regional languages could only be launched a few months after the English one, thereby delaying recruitment for regional language versions.

Ideally, one may launch all translated versions of the survey at the same time, however, we chose to deploy a staggered approach as we did not want to lose time considering the evolving nature of the COVID crisis. Hence, we released versions that were ready to go, to prioritise data collection as soon as possible, during the pandemic.

Despite developing translated versions of the survey to make it more accessible, it was found that 99% of the participants chose to respond in English. Potential reasons may be that a large number of the population with access to digital technology in India are English-speaking.

Survey format

The format of the surveys – including factors such as length, visual appearance, order of questions, and ease of navigation - played a crucial role in determining survey completion. The format was workshopped with sample participants and community advisors (e.g. youth advisors), both within and outside the host institution, before the launch of each survey. When the surveys were active, our team also monitored the points at which participants were dropping off.

Feedback from both these sources informed iterative revisions to the format and design. For example, with one survey, the length of the survey was flagged during the review, and it was recommended to add progress bars, page numbers, interactive messages and memes to encourage participants to finish the survey. It was also noted that the survey ‘landing page’ was extremely text-heavy, which might have potentially discouraged a participant from continuing beyond that page. Hence, the first screen of the survey was modified to include crisp information along with a link to the detailed information sheet.

Follow-ups

Follow-ups were designed to study the impact of the pandemic at different time points. As such, only the two surveys collecting data related to the pandemic (the WAC and HWI) involved follow-ups. For WAC, after completing baseline, follow-ups were sent to participants monthly for 12 months; and then later at 6 and 12 months post the pandemic. For HWI, follow-ups were sent to participants at 3, 6, 12 months post the completion of baseline.

The follow-up surveys were shorter in length as compared to the baseline, and were tested within the team to optimize for time required to complete, relevance of questions, and language comprehension. However, there was a gradual decline in response rates for the follow-up surveys, especially for WAC, perhaps because the follow-ups were too frequent.

It was a challenge for our data team to coordinate the follow-ups, and required a few rounds of trial and error and manually scheduling follow-ups before automated follow-ups could be streamlined.

There were several software glitches while sending follow-up surveys, requiring multiple rounds of troubleshooting with the global REDCap support team. Managing data across three surveys in several regional languages with multiple follow-ups became increasingly complex for the data team. To simplify and systematize the process, the task was divided such that one team member was managing follow-ups for only one survey, under the supervision of the data manager.

Software and data management

REDCap (Research Electronic Data Capture) is a secure, web-based application for building and managing online surveys and databases. It was developed in the United States at Vanderbilt University in 2004 for academic and non-profit use in health research, quality assurance, and health service management (4). It was important to the survey team that the tool we used ensured data security and privacy of participant information, hence REDCap was chosen to host our three online surveys since it was HIPAA (Health Insurance Portability and Accountability Act) compliant – this is a USA-based Act, but has also become an International standard. REDCap also was chosen because it offered various unique features: for example, REDCap was able to record participant journeys through the surveys, thus, allowing us to monitor points where participants were dropping off. Also, multiple languages could be embedded within a single survey in REDCap, thereby, allowing the participant to switch to their preferred language easily by clicking a small button in the application.

The major challenge while using REDCap was the lack of accessible and prompt customer support. Since our team was using the platform for the first time, adequate and timely support was required to navigate it. However, the only option to access help was to join a Global forum on a Zoom call, organized once a week in a different time zone. This was inconvenient as the forum was held close to midnight in Indian Standard Time (IST), and as it was only weekly, quick troubleshooting was not possible.

To enable quick problem-solving, the data team used online tools and resources to gain proficiency in operating REDCap. One of our team members was also familiar with using REDCap, which facilitated the setup of the tool. Additionally, an external expert was consulted on a needs-basis to provide troubleshooting support.

Two issues that came up while using this software were occasional server outages thereby preventing participants from taking the survey; and us facing several glitches while automating the follow-up surveys on REDCap, eventually having to manually send the follow-ups to hundreds of participants. This increased the amount of resources and labour required from our small, resource-constrained team.

This paper presents the learnings and challenges from deploying three online surveys, each with a different target population, in resource-constrained settings during COVID-19.

There is ample evidence related to the impact of COVID-19 on individual mental health and well-being, across both HICs and LMICs. However, there are limited global and LMIC-based studies describing the process, learnings, and challenges of conducting research during the pandemic. Hence, our paper bridges a significant gap in the literature pertaining to the process of conducting research during global crises such as the COVID-19 pandemic.

In summary, although the surveys were designed for a pan-India audience and disseminated through various online platforms, recruitment came primarily from known networks. Collaborating with relevant organizations was the most effective method for mass dissemination and recruitment. Translation of the questionnaires was intended to increase accessibility of the surveys in a diverse country like India, however, it did not lead to greater recruitment. Our findings indicate that translations into regional languages must be accompanied by targeted dissemination strategies to enhance uptake. It was also found that survey design was crucial in ensuring the engagement of participants. We recognised that the visual design, user interface, and ease of language play a key role in making the survey accessible, inclusive, and easy to navigate for the target audience.

It is possible that disseminating within known networks led to higher recruitment because the personal appeal may have generated more curiosity and motivation. Unknown contacts, especially those who may not know about or be interested in contributing to health research, did not have much incentive to open the survey link. Perhaps introducing an incentive, monetary or otherwise, could have enhanced motivation to complete the survey.

There is possibility of a potential bias in these samples, as most of the respondents were directed to the surveys after they were disseminated within known networks. Additionally, the English language surveys receiving the highest number of responses may have skewed the sample to represent a more English-speaking population.

During COVID-19, higher prevalence of online fatigue was reported, referring to fatigue associated with a massive use of technology (5). Since most activities during the lockdown were conducted digitally, both survey fatigue and online fatigue may have impacted the uptake of the surveys. This phenomenon was observed globally and reported in other research such as a study on neurosurgical survey dissemination, leading to survey fatigue characterized by decreased response rates and reducing the quality of data (6).

Various recommendations can be inferred from our findings and are summarised in Table 2. Table 2: Recommendations

Establish survey checkpoints	While developing the timeline for the survey, mark key milestones and checkpoints, and develop a plan for termination.
Test translated versions and dissemination strategies	Pilot the translated versions of the survey with native speakers to ensure language comprehension and friendliness. Ensure targeted dissemination strategy contextualised for a non-English speaking audience.
Customise survey to target audience	Pilot test the entire survey and obtain feedback from a small sample of participants. This may help reduce survey fatigue.
Seek communications and marketing support	Consult a communications and marketing professional to prepare a dissemination and outreach strategy, to ensure the survey reaches its target audience.

Firstly, milestones and key checkpoints need to be defined for surveys. This includes specifying the anticipated recruitment numbers at regular intervals such as one month, three months, six months, and so on depending upon the total duration of recruitment. A ‘termination plan’ is also recommended, indicating the circumstances in which recruitment should be ended. For example, one may specify that receiving ‘X’ number of completed responses within ‘Y’ time is sufficient to continue survey dissemination and recruitment; and that if this is not achieved, the recruitment will be closed. This plan may also include how closing is communicated externally to potential participants, current respondents, and organizational partners.

Secondly, if the survey is being translated in multiple languages other than English, we recommend ensuring the translated versions are piloted via known or easily accessible networks of individuals who are fluent in and who prefer responding in these languages. Often, the tonality of translated versions reflects a more formal manner of communication. To make it relatable, we recommend obtaining feedback from individuals fluent in that language, with final versions having the same ‘tone’ as the English version. A further language-related recommendation is, for quantitative surveys, to ensure that the data is compiled in a single format (irrespective of the language of the survey) at the backend to facilitate ease of analysis. For surveys collecting qualitative data, a necessity is to involve a fluent speaker or a translation agency during data analysis, to accurately comprehend the qualitative responses. It is also important to ensure that the translated versions are disseminated within networks that will benefit from them. Hence, a targeted multi-modal dissemination strategy needs to be employed to effectively reach the intended audience.

Thirdly, respondent fatigue, also known as survey fatigue, is a common problem in the collection of survey data. Factors that are known to influence respondent fatigue include survey length, survey topic, question complexity, and open-ended question type. (7) To ensure that the survey format is conducive to the target population, we recommend extensive piloting to obtain feedback from a smaller sample of participants.

For the successful recruitment of online surveys, dissemination of the survey and information about it is key. Hence, we recommend having a communications professional on board, in addition to a team of researchers. A communications professional specialising in science or health communications may be an ideal fit to lead outreach and dissemination efforts while ensuring compliance to research protocol. Furthermore, they may also assist in enhancing the visual design of the survey and in creating interactive key messages and call-to-actions that may appeal to the target audience.

The methodology followed had several strengths. Regular documentation and monitoring of learnings enabled iterative improvements to the surveys based on real-time data collection and reflection. Developing the log of learnings was a collaborative endeavour, involving team members with diverse roles in the project. This collaboration ensured comprehensive and rich documentation of diverse perspectives and expertise. Identification of mutual challenges between the surveys facilitated the development of targeted and contextually relevant solutions.

One of the limitations of the process is its resource-intensiveness. The process of holding weekly meetings, synthesizing learnings, and continuously adapting strategies is resource and labour intensive. This may not be feasible for all research teams, particularly those with limited time or resources.

Finally, we observed that a majority of studies using online surveys present descriptive results, however, there are limited studies presenting the process of running these surveys, especially in resource-constrained settings. We recommend and encourage more researchers to publish their contextual learnings of conducting online surveys, especially in LMICs. A repository of these insights may help build collective understanding around best practices, guiding future researchers in designing and implementing evidence-based, contextual, and resource-efficient strategies for online surveys.

This paper contributes to the literature related to the learnings and challenges derived from conducting online surveys during a pandemic in LMICs, such as India. It also highlights contextual issues that one may expect while conducting online surveys in low-resource settings. We hope that these insights may benefit other researchers conducting online surveys. Though this paper presents pandemic-specific challenges, some of these learnings are also applicable while conducting any online survey, especially those that have to be deployed in rapidly evolving situations.

Authors

Shubhangi Kashyap, Public Engagement Officer, Addictions and related-Research Group, Sangath, India; currently Communications Officer, YuWaah (Generation Unlimited India) at UNICEF

Richard Velleman, Emeritus Professor of Mental Health Research, University of Bath and Co-Director, Addictions and related-Research Group, Sangath, India

Soumya Singh, Early Career Researcher, Addictions and related-Research Group, Sangath, India

Ethel D’Souza, Data Manager, Addictions and related-Research Group, Sangath, India

Leena Gaikwad, Research Coordinator, Addictions and related-Research Group, Sangath, India; currently Associate Consultant, Bridge Medical Consulting

Urvita Bhatia, Research Fellow, Addictions and related-Research Group and Centre for Global Mental Health, Department of Population Health, London School of Hygiene & Tropical Medicine, London

Abhijit Nadkarni, NIHR Professor of Global Research, London School of Hygiene and Tropical Medicine, UK and Co-Director, Addictions and related-Research Group, Sangath, India

Ethics approval and consent to participate: All three surveys received Ethical approval from the Sangath Institutional Review Board. Informed Consent to participate was recorded at the beginning of each person’s participation in each survey.

Consent for publication: Not applicable.

Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author ([email protected]) on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: None

Authors' contributions: SK, RV, SS, ED, LG, UB, AN conceptualised the paper. SK was responsible for writing the original draft. RV edited and reviewed several versions of the manuscript and supervised the drafting process. SS supported the writing and provided specific input to the methodology section. AN edited and reviewed the draft manuscript. All authors (SK, RV, SS, ED, LG, UB, AN) reviewed and approved the final manuscript.

Acknowledgements: We thank Aakrushi Brahmbhatt, Ankur Garg, Devika Gupta, Luanna Fernandes, Madhavi Roy, and Rheane Palmira Da Silva, Early Career Researchers at Sangath, for coordinating the research and recruitment for the surveys. We are thankful for the contributions of partner organizations including Centre for Mental Health Law and Policy, Forca Goa Foundation, ILS Law College, Krea University, One Future Collective, Pro Sport Development, and Yuvaa for their support in survey dissemination. We also thank Allison Tu, Aman Bariya Sousa, Arundhati Rane, Beverly Monteiro, Bhavya Dixit, Damini Yadav, Gauri Mahajan, Gayatri Deepak Nair, Mihir Kalgud, Nikita De Lima, Ramya Pillutla, Sonal Gupta, Stuti Bagri, and Upasana Rajagopalan, Research Interns at Sangath, for their support in survey development and creation of promotional materials.

O’Connor DB, Aggleton JP, Chakrabarti B, Cooper CL, Creswell C, Dunsmuir S, et al. Research priorities for the COVID‐19 pandemic and beyond: A call to action for psychological science. British Journal of Psychology. 2020 Nov 19;111(4):603–29. doi: 10.1111/bjop.12468.
De Man J, Campbell L, Tabana H, Wouters E. The pandemic of online research in times of COVID-19. BMJ Open. 2021 Feb 23;11(2):e043866. doi: 10.1136/bmjopen-2020-043866.
Singh S, Sagar R. A critical look at online survey or questionnaire-based research studies during COVID-19. Asian J Psychiatr. 2021 Nov;65:102850. doi: 10.1016/j.ajp.2021.102850.
Odukoya O, Nenrot D, Adelabu H, Katam N, Christian E, Holl J, et al. Application of the research electronic data capture (REDCap) system in a low- and middle income country– experiences, lessons, and challenges. Health Technol (Berl). 2021 Nov 25;11(6):1297–304.
Bonanomi A, Facchin F, Barello S, Villani D. Prevalence and health correlates of Online Fatigue: A cross-sectional study on the Italian academic community during the COVID-19 pandemic. PLoS One. 2021 Oct 14;16(10):e0255181. doi: 10.1371/journal.pone.0255181.
de Konning R, Egiz A, Kotecha J, Ciuculete AC, Ooi SZY, Bankole NDA, et al. Survey Fatigue During the COVID-19 Pandemic: An Analysis of Neurosurgery Survey Response Rates. Front. Surg. 8:690680. doi: 10.3389/fsurg.2021.690680
O’Reilly-Shah VN. Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey. PeerJ. 2017 Sep 12;5:e3785. doi: 10.7717/peerj.3785.

No competing interests reported.

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Learnings from Conducting Online Surveys in India During the COVID-19 Pandemic

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Abstract

Introduction

Methods

Synthesis of learnings

Results

Dissemination and recruitment

Translation

Survey format

Follow-ups

Software and data management

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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