Study Participants
Recruitment took place in December 2020 from adverts placed on social media sites, informal online support groups and snowballing via recruited subjects promoting the study in their own networks of long COVID sufferers.
A total of 15 participants, who had either a diagnostic or antibody test confirmation for SARS-COV-2 and were still suffering from post-acute symptoms of COVID-19, were recruited to the study group. To validate the process, 16 healthy volunteers were recruited.
Sample size
The sample size calculation was informed by the need to both achieve saturation of PAC-19QoL indicators and assess the degree to which each indicator differentiated between the disease and non-disease state. Previous experience with the Jandhyala Method, predicted saturation of unique indicators at a minimum target sample size of 10 with an upper limit of 20. For validation, using a univariate approach, an indicator was deemed to differentiate between the two groups if the prevalence of the indicator was >50% in one group than the other. A minimum sample size of 15 participants per group was calculated to provide sufficient power (at least 80%) to detect this difference of 50% between the two groups at 5% level of significance.
Statistical analyses
Demographics
Using a Chi-square test , the binary presence or absence of the following discrete characteristics were compared between the control and study groups: sleep apnoea, sleeping difficulty, staying asleep difficulty, allergies, assistance with self-care needs, cancer diagnosis, current smoker, doing own shopping, difficulty falling asleep, former smoker, gender, immunosuppressant drugs, long COVID in the past, long COVID symptoms, major surgeries, mobility issues, non-prescribed or homoeopathic medications, organ transplant, other family history condition, physical activity, pregnancy weeks, prescribed medications.
The following categorical increasing grades of pre-existing conditions were compared between both groups using a Chi-square test: "no vs mild/moderate/severity" (asthma, diabetes, high blood pressure, cholesterol, chronic obstructive pulmonary disease (COPD), cystic fibrosis, stroke). Due to the type of statistical analysis conducted, weight categories were compared "underweight/average" vs "obese", ethnicity categories were compared "white" vs "Asian/other", whilst the category "other", in gender demographics, was not considered during the calculations.
A Mann-Whitney U test (p<0.05) was performed, comparing the following characteristics: age, weight, height, smoking duration, time since quitting smoking and number of cigarettes smoked per day.
PAC-19QoL QoLIs validation
Using a Mann-Whitney test, statistically significant differences between the mean Likert score for each QoLI were compared between the responses from the study and control groups. A p-value <0.05 indicated a statistically significant finding in the presented analyses.
Identification of PAC-19QoL QoLIs
Using the Jandhyala Method, the PAC-19QoL indicators (QoLIs) were identified [13]. This is a novel way of observing proportional group awareness and consensus on answers arising from list-generating questioning. The method has been differentiated from competing consensus generating methodologies [14]. The participant consensus is achieved by observing levels of awareness and consensus relating to a list of recommended QoLIs for PAC-19QoL. These are solicited via two anonymised online surveys and calculating an awareness index (AI) and consensus index (CI) for each item, respectively. The AI and CI, both continuous variables, were further categorised into 4 A and C scores.
During the first Awareness Round (1) survey, participants were asked to respond to the list-generating question: "Which areas of your lives do you (as post-acute COVID-19 patients) want to be included in a QoL measure for post-COVID-19 patients?". Participants were asked to provide a minimum of three, and a maximum of ten free-text answers.
The participants' responses from this Awareness Round (1) were analysed per group. They were then refined into mutually exclusive QoLIs by three researchers using a process of content analysis and open coding. The codes were then attributed to the relevant participants' answers by one researcher. They were then confirmed by a second.
The participants who completed the first round were asked to participate in the second, Consensus Round (2) survey. They were asked to rate their level of agreement with the inclusion of the QoLIs arising from the Awareness Round (1) survey. They were to use a five-point Likert-scale (Strongly agree, Agree, Neither agree nor disagree, Disagree and Strongly disagree).
Quality of Life indicators reaching a consensus level of >50% (CI>0.5) were retained in the final list and used to populate the PAC-19QoL.
PAC-19QoL Validation
The PAC-19QoL instrument was validated against a control group with 16 healthy individuals recruited from the networks of the researchers. Participant demographics were recorded for the study and control populations.
Public and patient involvement
Through our on-going work, we have established extensive networks with stakeholder groups and service users with rare diseases (such as XLH). In developing this project, we informally discussed the idea of developing a quality of life measure for people with a lived experience of COVID-19 with people within our extensive network. In total, the project idea was discussed with seven people, and each of these people expressed a need for a patient-centred Quality of Life measure that is easy to use and applicable to every aspect of their life, beyond the disease.