key: cord-0731334-9ghwsjna
authors: McBride, Orla; Butter, Sarah; Murphy, Jamie; Shevlin, Mark; Hartman, Todd K.; Hyland, Philip; McKay, Ryan; Bennett, Kate M.; Gibson‐Miller, Jilly; Levita, Liat; Mason, Liam; Martinez, Anton P.; Stocks, Thomas VA; Vallières, Frédérique; Karatzias, Thanos; Valiente, Carmen; Vazquez, Carmelo; Bentall, Richard P.
title: Context, design and conduct of the longitudinal COVID‐19 psychological research consortium study–wave 3
date: 2021-05-22
journal: Int J Methods Psychiatr Res
DOI: 10.1002/mpr.1880
sha: 9e65fe3b167154aebec4a11e4aec8cf1609495ed
doc_id: 731334
cord_uid: 9ghwsjna

OBJECTIVES: The COVID‐19 Psychological Research Consortium (C19PRC) Study aims to assess the impact of the COVID‐19 pandemic in the adult population in multiple countries. This paper describes the third wave of the UK survey (the ‘parent’ strand of the Consortium) during July‐August 2020. METHODS: Adults (N = 2025) who participated in the baseline and/or first follow‐up surveys were reinvited to participate in this survey, which assessed: (1) COVID‐19 related knowledge, attitudes, and behaviours; (2) the occurrence of common mental disorders; as well as the role of (3) psychological factors and (4) social and political attitudes, in influencing the public’s response to the pandemic. Weights were calculated using a survey raking algorithm to ensure that the cross‐sectional sample is nationally representative in terms of gender, age, and household income, and representative of the baseline sample characteristics for household composition, ethnicity, urbanicity and born/raised in UK. RESULTS: 1166 adults (57.6% of baseline participants) provided full interviews at Wave 3. The raking procedure successfully re‐balanced the cross‐sectional sample to within 1% of population estimates across selected socio‐demographic characteristics. CONCLUSION: This paper demonstrates the strength of the C19PRC Study data to facilitate and stimulate interdisciplinary research addressing important public health questions relating to the COVID‐19 pandemic.

Despite the existence of a substantial evidence base pointing to the positive sequelae of pandemics (e.g. increased resilience and optimism, better social support and bonding, etc.; Chen & Bonanno, 2020; Drury & Tekin Guven, 2020; Solnit, 2010) , widespread concern has been expressed about the protracted nature of the COVID-19 pandemic, and its potentially significant negative socio-economic and health-related impact on the lives of citizens over the medium to long term (Gayer˗Anderson et al., 2020; Ornell et al., 2020; Shah et al., 2020) . By June 2020, over a quarter of a million people in the UK had contracted COVID-19, and approximately 40,000 COVID-19 related deaths had been registered (Office for National Statistics, 2020a). Approximately 8.9 million people were in receipt of income support via the government's Coronavirus Job Retention Scheme (HM Revenue and Customs, 2020), and the UK debt level, which was estimated to be £1.95trn, was larger than the economy for the first time in over 50 years (Office for National Statistics, 2020b) . Recent commentaries argue that the socioeconomic consequences of the pandemic are exposing and exacerbating existing societal inequalities, with the pandemic having a disproportionately negative impact on the lives of more vulnerable members of society (Morgan & Rose, 2020) . Amidst these growing concerns, there is a pressing need to develop a robust evidence base, derived from analyses of high-quality, population-level data, to determine how the public are adapting to life and the many publichealth restrictions imposed throughout the course of the pandemic (Davis, 2020) .

Research Consortium (C19PRC) Study was designed and launched with the aim of collecting high-quality data (via self-report questionnaires, qualitative interviews, and quasi-experimental studies) to test a range of theoretically-informed research questions to obtain a greater understanding of the adult population's psychological and social adjustments to the pandemic. Two core aspects of the C19PRC Study design will help ensure that this aim is achieved, and that the study's data is well placed to contribute significantly to the knowledge base surrounding the mental health impacts of the COVID-19 pandemic. First, a broad array of standardised measures were used to capture the prevalence of common mental disorders including major depressive disorder (MDD), generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD), as well as other important experiences such as somatisation and paranoia . These core measures facilitate the assessment of a variety of mental disorders and experiences commonly investigated in previous infectious respiratory disease outbreaks (Cheng, 2004; Gardner & Moallef, 2015) . They also offer a more detailed interrogation of these diagnostic constructs compared to other leading national longitudinal mental-health studies currently being conducted during the pandemic, which have, in many cases, relied on established but general measures of psychological distress (Pierce, Hope, et al., 2020) or very short screening tools for MDD and GAD (Henderson et al., 2020) .

Second, the inclusion of a battery of psychometric measures to assess individual-level psychological factors (e.g., personality, memory, cognitive reasoning ability, locus of control, death anxiety, happiness, and resilience), political attitudes and behaviours (e.g., voting behaviour, political predispositions, nationalism, and patriotism), COVID-19 health-related knowledge and behaviours, as well as the collection of geo-spatial data to facilitate linkage of individuallevel survey data to important macro-level data (e.g., country-level COVID-19 related statistics including geographically-framed infection rates, mortality rates, and lockdown status), ensures that the C19PRC Study possesses explanatory potential beyond that of most other studies and surveys established during the pandemic.

As detailed elsewhere, the C19PRC study commenced in the UK, but has since expanded to include international partners in the Republic of Ireland (RoI), Spain, Italy, Saudi Arabia, and the United Arab Emirates (UAE). The UK strand of the Study, to which we refer as C19PRC-UK, is the 'parent' survey of the Consortium and is funded by the Economic and Social Research Council in the UK. Where possible/appropriate, international partners model their fieldwork procedures and survey content for each wave on the C19PRC-UK design, although there are important differences between the countries in terms of the timing of fieldwork and survey content. For example, in the RoI and Spain, the first two waves were conducted during March/April and May 2020 Valiente et al., 2020) , which was consistent with the UK, whereas in Italy, the UAE and Saudi Arabia, baseline and follow-up waves were conducted between April and August 2020 (Bruno et al., 2021) .

Whereas the UK survey has a strong focus on collecting sociopolitical survey content , a key priority for the Spanish team was to measure and assess positive psychosocial responses to the pandemic (e.g., posttraumatic growth, hedonic and eudaimonic well-being, openness to the future, primal positive beliefs, etc.; Valiente et al., 2020 Valiente et al., , 2021 . The Consortium is committed to data harmonisation (where possible) to facilitate multi-country research studies, and this complex programme of work is on-going.

Between April and September 2020, the Consortium produced 14 academic papers analysing the rich survey data, and several of these involved multi-country data analysis Murphy et al., 2021) . All outputs are accessible via the dedicated OSF, COVID-19 Psychological Research Consortium (C19PRC) Panel Study (2020) hosted with the Open Science Framework.

In this paper, we report the protocol for the third wave of C19PRC Study in the UK (C19PRC-UKW3), which was conducted during July and August 2020. As described elsewhere , at baseline (C19PRC-UKW1), 2025 adults aged ≥18 years, who were representative of the UK adult population with respect to gender, age, and household income, were recruited via an internet-based panel survey in March 2020. Towards the end of April 2020, 1406 of these adults were recontacted for the first follow-up survey (C19PRC-UKW2), representing a 69.4% retention rate. The first two waves of the C19PRC Study were conducted at the beginning and peak of the first wave of COVID-19 in the UK, respectively, 2 of 17whereas fieldwork for C19PRC-UKW3 commenced at the tail end of the first wave (see Figure 1 ).

Despite the decline in daily COVID-19 transmission and death rates, important social, economic, and political events rapidly unfolded during the period between the end of C19PRC-UKW2 and C19PRC-UKW3. These included, but were not limited to: (1) the relaxation of the first national lockdown; (2) commencement of human trials for a COVID-19 vaccination in the UK; (3) social and political unrest during the pandemic; (4) the gradual return to school for children before the 2020 summer holidays; (5) announcement of a timeline to end the Coronavirus Job Retention Scheme, and (6) the introduction of travel-related quarantine restrictions and bans (see Table S1 for a detailed timeline). As with previous waves, the content of the C19PRC-UKW3 was considered carefully to capture the impact of these events on the lives of survey participants.

A key methodological concern of longitudinal panel studies is sample attrition (Lynn, 2009) , and studies initiated during the COVID-19 pandemic are not immune to this challenge. Attrition in a panel survey tends to increase as the number of follow-up periods increases, and it has considerable potential to negatively impact on the generalisability of findings if participants who stay in the study differ from those who drop out in relation to core study outcomes (Gustavson et al., 2012) . Whilst the C19PRC Study team works closely with our fieldwork partner, Qualtrics, to maximise the retention of adults across waves to protect and sustain the longitudinal credentials of the survey, refreshment or 'top-up' sampling was conducted at C19PRC-UKW3. Refreshment sampling recruits new respondents into the panel to match specific characteristics of adults who were lost to follow-up. This process, which is common in established panel surveys such as the American National Election Study, ensures that the C19PRC panel sample will remain sufficiently large to conduct meaningful longitudinal analyses for the core study outcomes of common mental disorders, as well as being as representative as possible of the baseline target population (adults aged 18 years and older living in the UK). This paper describes the C19PRC team's work to (i) examine the level of attrition in the C19PRC by the third wave and whether this could be predicted by 

Fieldwork for the C19PRC Study was conducted by the survey company Qualtrics. Qualtrics partners with over 20 online sample providers to supply a network of diverse, quality respondents to their worldwide client base and, to date, has completed more than 15,000 projects across 2,500 universities worldwide.

C19PRC-UKW3 survey data collection commenced on 9 July 2020, approximately 10 weeks after the completion of C19PRC-UKW2. In Phase 1, Qualtrics re-contacted all adults who participated in previous waves (N = 2025) via email, SMS, or in-app notifications and invited them to participate. The survey was released to a sub-sample of participants initially for a 'soft launch' (see Quality Control Section) prior to the full launch of the survey wave later that day.

Qualtrics' partners released invitations in batches and, after the initial invitation was received, respondents who had not completed the survey were sent two reminders to encourage them to participate. The first reminder was sent approximately 36-48 h after the initial survey invite, with the second reminder sent another 36-48 h after this first reminder. Phase 1 fieldwork lasted two weeks (9-23

July 2020).

Prior to Phase 2, Qualtrics compared the characteristics of the Phase 1 sample to the pre-determined sampling quotas set at baseline. As previously described , the target population for the C19PRC-UKW1 survey was the UK adult population aged ≥18 years, and quota sampling methods were employed to achieve a representative sample in terms of age and gender (using 2016 population estimates from Eurostat, 2020) and household income (using 2017 income bands from the Office for National Statistics, 2017). Phase 2 fieldwork was therefore organised to recruit new respondents according to gaps in the sampling quotas following the completion of Phase 1. New respondents for Phase 2 were alerted to the C19PRC-UKW3 by Qualtrics in one of two ways: (1) they opted to enter studies they were eligible for by signing up to a panel platform; or (2) they received automatic notification through a partner router which alerted/directed them to studies for which they were eligible. To avoid self-selection bias, survey invitations to eligible participants only provide general information and do not include specific details about the contents of the survey. Participants were required to be adults, able to read and write in English, and resident in the UK. No other exclusion criteria were applied. Panel members routinely receive an incentive for survey participation (e.g., gift cards), based on the length of the survey, their specific panellist profile, and target acquisition difficulty.

Phase 2 fieldwork commenced on 23 July 2020 with a 'soft launch' (see Quality Control Section) and the full survey was launched on 24 July 2020. Qualtrics proceeded as follows during the Phase 2 fieldwork: (1) adults in 'hard to reach' quota groups (e.g., young people in the highest income bands) were targeted first; (2) the focus then shifted to allow the quotas to 'fill up' naturally; before (3) switching back to targeting respondents to fill incomplete quotas.

Adults who chose to participate followed a link to a secure website and completed all surveys online. The invite link only remained active MCBRIDE ET AL.

-3 of 17 for a participant until a quota they would have qualified for was reached.

Participants were informed about the purpose of the C19PRC Study, that their data would be treated in confidence, that geolocating would be used to determine the area in which they lived (in conjunction with their residential postcode stem), and of their right to terminate participation at any time. Participants were also informed that some topics may be sensitive or distressing. Information about how their data would be stored and analysed by the research team was also provided. Participants were also informed that they would be re-contacted at a later date to invite them to participate in subsequent survey waves. Participants provided informed electronic consent prior to completing the survey and were directed to contact the NHS 111 helpline upon completion if they had any concerns about COVID-19.

C19PRC data will be stored confidentially in line with GDPR. When the study data is deposited with the UK Data Service, location data will be removed and replaced with relevant socioeconomic summary data (e.g. area-level deprivation and population density data). All other personal data will also be removed.

Qualtrics conducted validation checks on the C19PRC-UKW3 data, though this varied slightly across the Phases. In Phase 1, the 'soft launch' was conducted with 100 respondents and this data was screened for technical errors and omissions in the survey measures and/or filtering processes prior to the full launch. Adults who participated in the 'soft launch' were retained in the Phase 1 sample.

Qualtrics routinely analyses survey completion times to ensure that respondents spend sufficient time providing high-quality responses. For longitudinal surveys, this process is completed once only, at baseline. Once a participant satisfies the minimum survey completion time, which is set at half the median time of the soft launch for that wave (11 min 11 s for C19PRC-UKW1; McBride et al., 2020), the data they provide in subsequent waves is not subject to a minimum completion time restriction. Thus, the respondent's completion time at baseline serves as an indicator of their status as a legitimate survey respondent which they carry with them across subsequent waves.

For Phase 2, Qualtrics screened the 'soft launch' data (n = 47) for technical errors and/omissions before the full launch and a survey completion time was again set based on half the median time for the soft launch (9 min, 42 s). Phase 2 'soft launch' respondents were included in the main Phase 2 sample. Following the completion of Phase 2 fieldwork, Qualtrics removed any participants who (1) completed the survey in less than the minimum completion time or

(2) were potentially duplicate respondents. 

The following C19PRC-UKW1 variables were used for attrition analyses for C19PRC-UKW3: gender (females vs. males); age (18- resilience (total score on the Brief Resilience Scale); paranoia (total score on the Persecution and Deservedness Scale); death anxiety (total score on the Death Anxiety Inventory); intolerance of uncertainty (total score on the Intolerance of Uncertainty Scale); and COVID-19 anxiety (total score on single item indicator).

Ethical approval for the project was provided by the University of Sheffield (Reference number 033759).

Data analyses were conducted in a number of stages. First, the recontact rate for Phase 1 was calculated, and responders and non-MCBRIDE ET AL.

-5 of 17 T A B L E 1 Overview of content a of C19PRC Study Wave 3 (Phases 1 & 2), United Kingdom (UK), July-August 2020 -7 of 17 responders were compared on a range of baseline socio-demographic, mental health, and psychological characteristics, using chi-square tests and independent samples t-tests. Second, a binary logistic regression analysis was conducted to assess the association between baseline characteristics and attrition at C19PRC-UKW3. Regression coefficients (odds ratios and 95% confidence intervals) were plotted using the coefplot in Stata 15 (Jann, 2017; StataCorp., 2017) .

Third, post-stratification survey weighting was conducted for the Phase 1 sample using a technique known as survey raking or samplebalancing, using the 'anesrake' package in R (Pasek & Pasek, 2018) .

Raking is a common method of adjusting survey data to ensure that the distribution of the characteristics of a sample closely mirror the known population distribution. In practice, this means the C19PRC-UKW1

sampling quotas for age, gender, and household income, as well as the baseline proportions achieved for ethnicity, urbanicity, household composition, and being born or raised in the UK, were imposed on the sample obtained at Phase 1. The raking algorithm assessed which of these selected sociodemographic variable distributions at C19PRC-UKW3 deviated from their target distribution at C19PRC-UKW1 by 5% or more, and subsequently iteratively adjusted to produce a weight value for each case in the sample until the sample distribution aligned with the population distribution for the chosen characteristics (DeBell & Krosnick, 2009; Pasek & Pasek, 2018) . Raking is considered an ideal method for weighting survey data given that it is relatively easy to implement, but also since it only requires the marginal population proportion for each variable used in the weighting procedure (Mercer et al., 2018) . Weighted frequencies were calculated for baseline characteristics for C19PRC-UKW3 Phase 1 sample to assess the success of the raking procedure.

And fourth, the representativeness of the combined C19PRC-UKW3 Phase 1 and Phase 2 samples was assessed by comparing the characteristics of the sample to the UK general population.

Standardised difference scores were computed using the stddiffi command in Stata 15 (Bayoumi, 2016; StataCorp., 2017) to test for differences in relation to specific socio-demographic characteristics between the two data sources. Unlike other statistical tests (e.g. chisquare), the standardised difference score approach is not influence by sample size (Austin, 2009) , and can be more informative than pvalues for comparing across data sources that differ in relation to sample size (Harron et al., 2017) . Standardised differences of 0.2, 0.5, and 0.8 represent small, medium, and large standardised differences respectively (Cohen, 1988) ; standardised difference scores of less than 0.1 suggests no meaningful differences between data sources in relation to the distribution of the variable under consideration (Normand et al., 2001 ).

As illustrated in Figure 2 , at Phase 1, 1211 adults who participated in one or both of the previous waves were successfully recontacted (59.8% recontact rate) and 1166 adults provided full interviews at C19PRC-UKW3 (i.e., 57.6% of baseline participants Table S2 for model results). The vertical black bar represents an odds ratio of one, and the point estimates (odds ratios;

OR) for each baseline characteristic are presented along with 95% confidence intervals (CI), which are indicated by horizontal black bars. Those which cross the vertical axis reflect a non-statistically significant association between the baseline characteristic and attrition. Small to large effect sizes emerged for the association be- 

The raking procedure successfully re-balanced the Phase 1 sample to the C19PRC-UKW1 proportions for gender, age, household income (exact re-balance to original quotas), household compositionand urbanicity (exact re-balance to baselineproportions), ethnicity (within 0.3%), and born or raised in the UK (within 1%; see Table S3 ). The impact on the weighting on the baseline prevalence of the three core mental disorders measured in the C19PRC Study, MDD, GAD, and PTSD, was also assessed. 

Following an analysis of the outcome of Phase 1 recruitment, Phase 2 sampling quotas to target females, younger adults, and lower income earners. Overall, this process was successful-combining the samples across Phase 1 and 2 produced a cross-sectional sample which closely mirrored the characteristics of the baseline sample with respect to gender (to within 0.1-0.5%, more males), age (to within 0.1-0.3%, more older adults), and household income (to within 0.2-2.6%, with more higher-income earners; see Table 3 ).

As presented in T A B L E 2 Attrition analysis for wave 3 of the COVID-19 psychological research consortium (C19PRC) study (July-August 2020) panels, the lack of comparable pre-pandemic baseline data, and a reliance on unvalidated mental health measures (Holman et al., 2020; Pierce, Hope, et al., 2020; . To those who might challenge the usefulness of C19PRC data on these grounds, we would like to highlight the following points.

It is undeniable that existing and established cohort and panel studies were in an optimal position to re-focus data collection efforts to administer 'COVID-19 specific' waves to their participants during the pandemic. Many of these studies having been set-up in a prepandemic era have the distinct advantage of being carefully planned and designed over many months, or even years, and have rightly adopted probability-based sampling techniques. Whilst it is true that probability sampling has the advantage of permitting unbiased population estimates, recent evidence emerging from these 'COVID-19

informed' waves, administered to existing participants, indicates they are experiencing lower than normal response rates. For example, only 48.6% of respondents who participated in the most recent wave of the UK Household Longitudinal Study (UKHLS), Wave 9 (2017-18), participated in the first UKHLS COVID-19 web-survey conducted during April 2020 , which is considerably lower than the reported 85% of UKHLS respondents who participated in Wave 9, having completed Wave 8 during 2016 -17 (KANTAR, 2019 . Experiencing sampling selection bias on a wide scale can impact negatively on estimated obtained from analyses of this survey data.

While we do not contest the argument that 'epidemiological enquiry is of little value unless a random sample is obtained' (p.57) (Tyrer & Heyman, 2016) , we argue against recent position statements which suggest that (i) turnover in these types of panels is high;

(ii) those who are in difficult financial circumstances complete surveys for financial gain, and (iii) self-selected commercial survey panels might be biased towards mentally unhealthy or unhappy individuals (Chauvenet et al., 2020) . Findings produced from analysis of T A B L E 4 Comparison of representativeness of the COVID-19 psychological research consortium (C19PRC) Study UK wave 3 (C19PRC-UKW3) cross-sectional sample to UK adult population for key socio-demographic characteristics, by country, July-August 2020 (N = 2019) Shevlin et al., 2020) were higher than estimates emerging from other UK adult population studies conducted before the pandemic (Giebel et al., 2020; Stansfeld et al., 2016) , they were only marginally so, which suggests that the sample we recruited was not particularly mentally unhealthy. It could be argued, however, that it is not meaningful to compare prevalence estimates for mental disorders obtained during the pandemic via an online panel survey to those obtained from a probability-based sample pre-pandemic because the differences in mode of administration are intertwined with potential increases in prevalence estimates for mental disorders as a result of the pandemic. We are aware of one study in the US which demonstrated the ability of an online panel survey, using quota sampling methods, to produced remarkably similar prevalence estimates for PTSD when compared to a survey using probability-base sampling in the pre-pandemic era (Cloitre et al., 2019) , which provides further confidence in our study's data.

Much has been made of the ability of existing cohort studies to provide robust comparative analysis of 'pre-pandemic' data on a range of important health outcomes to data collected 'postpandemic' (Henderson et al., 2020; Pierce, Hope, et al., 2020) .

Although several existing cohorts have employed mixed modes of survey administration in recent years-for example, 52% of interviews for Wave 9 of UKHLS were completed via web-based interviews, Previous methodological work conducted in Israel also indicates that prevalence estimates for mental disorders such as PTSD can be considerably lower when individuals participate in face-to-face interviews compared to completing self-report measures (Hoffman et al., 2011) . In terms of mental health-related outcomes, lower social desirability effects may mean respondents are more willing to report problems with their mental health in an online survey completed 'during/post pandemic' compared to the face-to-face survey prepandemic, even if the face-to-face survey comprised of a confidential self-report task in the presence of an interviewer. This results in what appears to be an increase in the prevalence estimates of mental disorders, which may be potentially a measurement artefact.

Even acknowledging the apparent superiority of the study design which re-purposes existing cohort/panel fieldwork for the collection of data during the pandemic, we feel compelled to highlight that the measures administered to assess mental health in these established surveys are not optimal. For example, the UKHLS used the General Health Questionnaire (GHQ-12; D. Goldberg & Williams, 1988) only, and, despite this being a recognised 'gold standard' for measuring general psychological distress reflective of potential cases of generalised anxiety and major depression (D. P. Goldberg et al., 1997) , this scale does not actually measure these diagnostic entities (Mann et al., 2011) . A key strength of the C19PRC study is the use of standardised instruments to measure specific diagnoses (i.e., MDD, GAD and PTSD) in accordance with the DSM-5 and ICD-11.

As a Consortium, we are committed to describing, in explicit detail, the context and planning stages of our survey data collection at each wave, and will continue to do so for future waves planned 14 of 17under the current UKRI ESRC funding programme, which expires in November 2021. We are planning a specific unique over-sampling strategy at Wave 4 (taking place in November 2020) to secure robust sample sizes in each of the four nations of the UK to facilitate meaningful between-country analyses on a range of factors (e.g.

nation-specific differences in experiences of and approaches to managing the pandemic), which we anticipate will differentially impact on individuals' mental health and wellbeing as the pandemic continues to unfold.

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How to cite this article

Context, design and conduct of the longitudinal COVID-19 psychological research consortium study-wave 3