Descriptive characteristics
The key characteristics of the 1297 responders are reported in Table 1. The sample was almost exclusively women (n = 1230, 94.8%) and over 82.9% of participants were aged ≥35 years (n = 1075). Approximately half of the participants had a diagnosis of pernicious anaemia (n = 639, 49.3%); the remainder had a vitamin B12 deficiency diagnosis only. Approximately three in 20 participants reported health literacy problems at least occasionally (that is, sometimes to always). Almost half of the participants were college or university educated (n = 568/1297, 43.8%) and 65.2% were employed (n = 846/1297). The areas of the UK and Ireland with the biggest representation were North West (197/1297, 15.2%), South East (165/1297, 12.7%), and Wales (137/1297, 10.6%) (Figure 1).
Table 1. General demographics of survey participants (n = 1297)
Figure 1. Stacked bar chart to show medication via injection across regions. B12 = indicates B12 deficiency. PA = pernicious anaemia.
The characteristics of the sample did not significantly differ between those with a diagnosis of vitamin B12 deficiency compared with pernicious anaemia (Table 2). However, the association between self-medication and diagnosis type was significant (P = 0.002). There was also a significant difference between self-medication via injection and diagnosis (P = 0.016). There was no difference in total PC PMOS scores for the two diagnosis groups (vitamin B12 deficiency and pernicious anaemia; see Table 2).
Table 2. Characteristics of people with B12 deficiency including self-medication status/safety, type of diagnosis (B12 versus pernicious anaemia), general health status, and health literacy levels
As many as 803 (61.9%) of the 1297 responders self-medicated with the majority via injection (n = 508/1297, 39.2%). Of the 803 who self-medicated, 63.3% (n = 508/803) self-injected and a few medicated using various oral methods. The most common reason for self-medication was to improve quality of life (n = 644/803, 80.1%), followed by dissatisfaction with treatment frequency (n = 545/803, 67.8%). Other reasons included concerns about overreliance on tests (n = 429/803, 53.4%) and lack of trust in healthcare professionals (n = 366/803, 45.6%). Participants could choose more than one option if they wished.
The most common source of information was an online closed support group (n = 577/805, 71.7%). Few participants who self-medicated informed a healthcare professional (437/803, 54.4%) did not. No participants reported side effects and the main symptoms participants aimed to improve were fatigue (n = 762/803, 94.9%), concentration/brain fog (n = 697, 86.8%) and pins and needles (n = 629/803, 78.3%); see Supplementary Table S2.
In terms of patient-reported safety in primary care, the participants in the current study had poorer perceptions of safety than the sample used in the PC PMOS validation study.12 This is indicated by the mean total PC PMOS scores and the mean scores of the individual domains (Supplementary Table S3).
Participants reported numerous safety concerns (Figure 2 and Supplementary Table S4). For example, only 50.0% (649/1297) of participants agreed that they were always treated with dignity/respect, 49.3% (640/1297) disagreed that the doctor always considered what they wanted for their care, 44.2% (573/1297) did not feel involved in decisions, 55.9% (725/1297) did not feel listened to, 42.3% (549/1297) felt they did not receive enough information, and only 18% felt they got answers to all questions about their care. Only 17.8% (231/1297) felt that staff knew everything they needed to care for them.
Figure 2. Likert plot of PC PMOS responses. PC PMOS = Primary Care Patient Measure of Safety.
Association between perceived primary care safety and self-medication by injection
The univariable logistic regression analysis showed that a lower total PC PMOS score (OR 0.97, 95% CI = 0.97 to 0.98) and lower scores on the individual domains (indicating lower perceived patient safety) were significantly associated with higher odds for SMVI (Supplementary Table S5). Other variables significantly associated with increased odds for SMVI included lower (poor/fair) health status (OR 1.46, 95% CI = 1.14 to 1.88), older age (≥45 years), and a pernicious anaemia diagnosis (OR 0.76, 95% CI = 0.61 to 0.95).
In multivariable regression analyses (Figure 2), two PC PMOS domains including patient-related factors (OR 0.82, 95% CI = 0.73 to 0.92), information flow (OR 1.10, 95% CI = 1.01 to 1.21), and external policy context (OR 1.10, 95% CI = 1.01 to 1.19) remained significantly associated with SMVI (Supplementary Table S6). All ages >34 years remained significantly associated with self-medication (age groups: 35–44 years OR 1.49, 95% CI = 1.01 to 2.20; 45–54 years, OR 2.06, 95% CI = 1.42 to 3.02; 55–64 years, OR 2.31, 95% CI = 1.51 to 3.55; ≥65 years, OR 2.80, 95% CI = 1.61 to 4.91).
Variance inflation factor estimates indicated that total PC PMOS was 4.16, which indicates that this variable is moderately correlated with other variables in the model. The regression results that were checked through Bayesian inference showed very similar results (Figure 3).
Figure 3. Multivariate regression plot of the factors associated with self-medication by injection (Bayesian inference model). DOM = domain. PA = pernicious anaemia. PC PMOS = Primary Care Patient Measure of Safety.
Thematic synthesis of patient concerns about self-medication and treatment implications of the COVID-19 pandemic
In total, 638 respondents completed the free-text question about self-medication concerns (see Supplementary Table S7 for a summary of the thematic synthesis). In total, 386 (60.5%) participants were not concerned about self-medication. The key thematic reasons for this were:
The concerned group (192, 30.1%) had five key concerns:
The remaining 60 (9.4%) responses were classified as indifferent or concerned (this group was largely categorised by patients who were initially concerned but were no longer concerned). The indifferent group presented three key themes:
Over half of the participants felt that the COVID-19 pandemic affected their care (749/1235, 60.6% [51 participants provided a ‘not applicable’ response, primarily because they no longer sought primary care provision because of dissatisfaction]). There were seven key themes surrounding those not affected:
self-medication;
proactive GP;
proactive patient;
receiving treatment in car;
alternative treatment sufficient;
direct contact with nurse practitioner; and
location.
For those affected there were six key themes:
appointment difficulties;
treatment stopped or cancelled;
monitoring and diagnosis stopped;
alternative treatments not available;
delayed/reduced frequency of injections; and
effect on daily activities.