Figures
Abstract
This paper builds on prior work exploring the use of risk-associated alternative healthcare (RAAH) in Canada. RAAH uptake was surveyed to explore the characteristics of adult RAAH users and the value of established psychometric instruments previously used in alternative healthcare studies in predicting RAAH behaviours: the Control Beliefs Inventory (CBI), the Reward Responsiveness Behavioural Activation System (RBAS) scale, the Positive Attitudes to Science (PAS) scale, the Satisfaction with Orthodox Medicine (SOM) scale, and the brief version of the Susceptibility to Persuasion-II (StP-II-B) scale. Findings suggest RAAH is influenced by gender, age, income, education, employment, chronic illness status, and ethnicity. Engagement in some form of RAAH was common (around 40%) and the most common types of RAAH use reported were physical manipulation and herbal/nutritional supplement use. Other higher-risk AH activities (such as use of toxins and physically invasive procedures) were also reported by about 5% of respondents. The StP-II-B and PAS instruments were predictive of the likelihood of engagement in RAAH behaviours, as illustrated by higher risk tolerance, desire for novelty, positive attitude to advertising and social influence, and positive beliefs about science. The CBI, RBAS, and SOM instruments were not predictive overall. However, the CBI and SOM instruments were predictive of engagement with physical manipulative RAAH activities, while the RBAS was predictive of herbal/nutritional RAAH engagement. These findings can help inform health professionals’ understanding of public health-seeking behaviours with respect to risk.
Citation: Garrett B, Caulfield T, Musoke R, Murdoch B, Tang X, Lam JST (2023) Demographic and psychometric predictors associated with engagement in risk-associated alternative healthcare behaviours. PLoS ONE 18(9): e0291016. https://doi.org/10.1371/journal.pone.0291016
Editor: Jerome Nyhalah Dinga, University of Buea, CAMEROON
Received: March 28, 2023; Accepted: August 20, 2023; Published: September 21, 2023
Copyright: © 2023 Garrett et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The full anonymized survey data used to support the findings of this study are openly available from https://doi.org/10.5683/SP3/KPJIX3
Funding: BM Garrett received an Insight Grant (#435-2019-0190) in 2019 from the Social Sciences and Humanities Research Council of Canada (https://www.sshrc-crsh.gc.ca/home-accueil-eng.aspx) that supported this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Alternative healthcare (AH) therapies are a range of therapeutics that largely originate from traditions and theories distinct from contemporary biomedical science, and which claim mechanisms of action outside of those currently accepted by scientific and biomedical consensus [1–4]. They often focus on “holistic” personal wellbeing and exist predominantly outside of public healthcare, and many are argued to be beyond the scope of scientific analysis. Some AH therapies are also claimed to supplement conventional biomedical healthcare, such as meditation or acupuncture for anxiety and pain management, and are often collectively referred to as complementary and alternative medicine or integrative medicine [5]. Many AH practices are difficult to validate in empirical terms, and thus there is frequently an adversarial stance between biomedical and AH practitioners [6, 7]. Nevertheless, the use of AH has risen over the past two decades, instigating research into the possible factors associated with its use [4, 8, 9].
Despite many AH practices being physically harmless, some do entail significant risks of adverse events [2, 10, 11]. Research suggests that people are now more frequently engaging in AH practices that involve risk, such as utilizing unproven therapeutics instead of medically established ones [2, 11, 12]. This trend has significant health policy and practice implications. Initial work suggests that socio-demographic factors, beliefs about control of personal health, motivation, susceptibility to persuasion, beliefs about science, and satisfaction with orthodox medicine may help predict those who are most likely to engage in such risk-associated alternative health (RAAH) behaviours. However, this remains a relatively unexplored area. Therefore, building on prior work, the goals of this study were to identify the socio-demographic and psychosocial factors associated with engagement in RAAH, and to establish the factors that may predict engagement behaviours. The key research questions were:
- What types of RAAH behaviours are most evident in the Canadian public?
- Can socio-demographic factors and established psychometric tools associated with engagement in AH help predict the likelihood of engagement in RAAH?
Alternative healthcare and risk
The regulation of AH varies across Canada, and a recent study identified four major categories of RAAH behaviours: general RAAH practices that conflict with the patient’s biomedical care (e.g., using AH instead of recommended medical treatment, people failing to inform their physician of use of alternative therapies concurrently with medical treatment, or using untested alternative therapies), specific RAAH therapies based on specific alternative belief systems (e.g., naturopathic intravenous therapy or cupping), physical manipulative RAAH therapies (e.g., forceful chiropractic spinal or cervical manipulative procedures), and RAAH practices involving known hazardous herbal or nutritional supplements [2]. Although rare, significant adverse events occur from these practices, including major physical injuries and even death, and in all cases the current evidence of efficacy does not appear to support the level of risk in engaging with these therapies. For instance, research has confirmed that many patients use AH remedies, such as Aristolochia root that may be toxic or cause drug interactions. Herbal treatments have also been associated with adverse events through direct toxicity, unwanted drug interactions, and psychological harm. Additionally, injuries through physical manipulative AH therapies have been documented [13–19]. A range of AH therapies is also frequently employed as a substitute for medical treatment [20, 21]. One 2002 systematic review of AH in older people identified that elderly patients frequently suffered harm as a result of undertaking AH therapies [22], indicating that this vulnerable population may be particularly at risk.
Psychological factors influencing alternative healthcare uptake and associated instruments
Psychological theory has suggested a number of psychological factors related to AH use. For instance, belief in personal control of one’s own health has been identified as an important factor in coping with illness and AH use. Decision making related to the use of AH has been seen as one means of regaining control during experiences of uncertainty associated with cancer [23]. AH users have been found to report a higher sense of control over their health, and they use AH to mitigate unpleasant aspects of conventional treatments [4, 9, 23–25]. The idea that patients use AH as it allows them to take more active control in managing health is supported by a number of clinical studies [4, 23, 26–29]. The Control Beliefs Inventory (CBI) is a 26-item psychometric tool developed to assess this characteristic [9]. This self-report measure has been validated in several chronic illness samples independent of health status [29].
Positive motivation is another behavioural factor identified in AH users. It is postulated that two general motivational systems underlie behaviour and affect: a behavioural inhibition system (BIS) and a behavioural activation system (BAS) [30, 31]. The BIS regulates aversive motives to avoid something unpleasant, whereas the BAS regulates appetitive motives and movement towards something desired. The persistent tendency to seek out or to gain positive rewards (rather than to avoid unpleasant circumstances) has been identified as the predominant motivational system in several AH studies [4, 29, 32–34]. The 5-item Reward Responsiveness BAS scale (RBAS) was developed and validated as a tool useful in assessing this phenomenon in AH users. It is a component of Carver and White’s BIS/BAS instrument, and is scored on a 4-point Likert-type scale (agree a lot to disagree a lot) with good internal reliability as indicated by a Cronbach’s α of 0.73 [29, 30].
Studies have also identified that there are also some specific negative drivers, notably, negative personal beliefs about the value of science and dissatisfaction with orthodox medicine, that stimulate motivation away from conventional medicine [8, 35, 36]. Survey tools to explore these drivers have been developed and tested by these researchers, such as the 4-item Positive Attitudes to Science (PAS) and the 6-item Satisfaction with Orthodox Medicine (SOM) surveys [8, 36].
Lastly, research suggests that as with other consumer health products and services, the marketing of AH employs similar techniques of persuasion and often uses those seen in deceptive advertising or health scams [7, 37–40]. Social psychologists have established the mechanisms that affect perception of risk and compliance in high-risk marketing practices [41], and persuasion and influence techniques were highly significant. Ten personality traits have been identified that correlate well with a likelihood of engagement with risky products or services: a dislike of premeditation, liking consistency (not liking changing one’s mind), novelty, needing self-control, valuing social influence, similarity (preference for popular products/services), an openness to taking risks, positive attitudes towards advertising, and a need for cognition and for uniqueness [42–44]. The brief version of the Susceptibility to Persuasion-II (StP-II-B) scale is a valid and reliable modular psychometric tool that measures general susceptibility to these techniques using a 30-item, 7-point Likert-type scale—strongly agree to strongly disagree [45]. Items are divided into ten subscales corresponding to these established persuasive factors. This scale has been demonstrated to be predictive of scam compliance, and these persuasion factors also help inform engagement with advertising in RAAH [38, 44].
Overall, these established psychometric tools are useful predictors of AH uptake, but studies assessing their value in predicting engagement with RAAH have not been undertaken. This study was designed to explore the value of these psychometric instruments in predicting RAAH behaviours.
Materials and methods
This work builds on prior work that established a taxonomy of RAAH practices [2]. A web-based survey of public engagement in AH practices in Canada incorporating five psychometric tools (CBI, RBAS, PAS, SOM, and StP-II-B) that are correlated with AH uptake was undertaken. Basic demographic details were collected along with attitudinal questions incorporating the psychometric tools and an open-ended question inviting comments from participants: Any feedback on the survey or comments you wish to add? The survey was developed in English and was also translated into French by a certified translator.
Hypotheses
The researchers sought to test the following two null hypotheses:
- People who engage in RAAH will demonstrate CBI, RBAS, SOM, PAS, and StP-II-B outcome scores no different than those who do not engage in RAAH.
- People who engage in more RAAH will demonstrate CBI, RBAS, SOM, PAS, and StP-II-B outcome scores no different than those who engage in them less.
Sample
Members of the public in Canada aged 16 and over were recruited through two commercial survey providers, Lucid and Amazon Mechanical Turk. Such survey companies are now increasingly employed in social science research due to their convenience and ability to reach a diverse population and balance responses from specific groups [46]. Additional recruitment through Twitter was also adopted with advertisements in health science and AH accounts. As an incentive to complete the survey, each participant had the opportunity to enter into a draw for two $200 Amazon gift vouchers. Personal identifiers used by those participating in the draw were removed from the survey data before analysis to ensure survey anonymity. To achieve an adequate sample size for logistic regression, the recommended rule of thumb is n = 100 + 50i, where i is the number of predictors in the model [47]. As the models used in the present study include 14 predictors, a minimum sample size of 800 was required to obtain accurate estimates.
Survey
An online cross‐sectional survey was developed using Qualtrics XM, an online survey platform, and was initially pilot-tested with a group of 100 university students in 2020. Following revisions, the survey was administered to the public between October 2021 and April 2022. The survey (available in S1 File) consisted of three parts and was anonymous. The first part requested demographic information as well as a history of participant’s personal experiences of engaging in AH practices. The second part included questions exploring the types of RAAH practices they had engaged in (as identified in earlier work [2]. The third and final part of the survey incorporated questions from the five psychometric tools previously described to specifically explore possible psychological factors that are theorized to influence AH uptake: CBI, RBAS, SOM, PAS, and StP-II-B. The internal consistency reliability of these five measures was established using Cronbach’s α (Table 1) and a value of 0.70 is widely considered good for psychological instruments [48]. All scales and subscales used in this study showed good reliability (Cronbach’s α of ≥ 0.75) except for the PAS, which showed a relatively low but acceptable Cronbach’s α of 0.66 [48].
The survey also included an open-ended question exploring participant commentary on their use of AH. Additional simple mathematical calculation and attention-checking questions as well as ballot box stuffing and automated survey checks were included to screen out random and automated responses [49]. The online survey was only accessible to Canadians who reported to be at least 16 years of age.
Ethical approval was obtained from the University of British Columbia’s Behavioural Research Ethics Board (# H19-01790) before data collection, and all participants provided online written informed consent. At the start of the survey, participants were informed the data was anonymous and submission of the survey indicated their consent to participate, and this was reiterated at the end of the survey prior to submission.
Analysis
Survey responses were exported from Qualtrics to STATA and RStudio for data quality checking, cleaning, and analysis. After removing invalid and incomplete responses, descriptive analyses on the remaining data were conducted to establish the percentage of respondents engaging in AH practices overall and to explore demographic characteristics. Using participants’ responses to questions on engagement in AH practices, binary outcome variables for engagement with any AH were generated (0 = none, 1 = engagement). A second set of outcome variables were generated based on counts of the reported experiences of engaging with the different forms of RAAH practices for both overall and the four RAAH sub-categories (general RAAH, alternative belief systems RAAH, physical manipulative RAAH, and herbal/nutritional RAAH). Logistic regression models were then applied to obtain odds ratios of participants’ experiences of engagement with RAAH practices for each demographic factor and psychometric scale. Rootograms offer an improved approach to the assessment of fit in count regression models [50]. Using rootograms to compare observed and expected values graphically for the count outcomes, zero-inflated negative binomial (ZINB) regression models were found to fit the data better than other models used for count outcomes. Therefore, ZINB models were used to determine the associations between the RAAH categories, together with the demographic factors and psychometric scales. A ZINB regression analysis models two separate processes to produce two sets of coefficients: one for the count outcome, which is the count part of the model, and the other for the binary outcome which is the logistic part of the model. Unlike logistic regression for hypothesis testing, the logistic portion of the ZINB reports the odds of not engaging in the behaviour. For both logistic and ZINB models, bivariate analyses were conducted, and factors found to hold an association (p < 0.25) or conceptually important were added into multivariate regression models. Using backward elimination, factors that were not statistically significant in the full model were dropped and the full model compared to reduced models using likelihood ratio tests and nested Voung test [51] for logistic regression and ZINB, respectively, to obtain parsimonious final models. Reduced and full models were further compared using the Akaike information criteria (AIC) and Bayesian information criteria (BIC) to determine if the reduced models did not increase the AIC and BIC values. Models were built for overall engagement in AH practices and by RAAH category. All statistical analyses were conducted using RStudio version 4.2.1.
Results
Sample characteristics
A total of 2253 respondents completed the survey and 761 surveys that had missing data and/or failed data quality checks were removed from the analysis leaving a total sample of 1492 respondents (Table 2). Most of the sample identified as women (58.6%) and Caucasian (66.9%) and reported undertaking some form of paid employment (69.8%), being generally healthy (67.4%), having no chronic illness (58.2%) as well as working outside of the healthcare field (84.7%). Slightly less than half of the sample were middle-aged adults (45.4%), earning an annual income of $49,999 or below (43.7%), and having an education level at the bachelor-level and above (48.3%). Sample characteristics and the mean scores of each psychometric measure across different demographic groups are provided in Table 2.
Types of risk-associated alternative health behaviours reported
Participants were asked if they had engaged in specific RAAH activities categorized under four previously established categories of RAAH (general RAAH, alternative belief systems RAAH, physical manipulative RAAH, and herbal/nutritional RAAH) [2]. As shown in Table 3, RAAH uptake was substantial, with 41.7% of respondents reporting they had engaged in at least one form of RAAH activity, and both English and French respondents demonstrating broadly similar RAAH trends (although French speakers were more likely to not engage in RAAH). Specifically, 15.2% had engaged in one category of RAAH activity, 11.3% in two types, 9.0% in three types, and 6.2% in all four types. Among those who had engaged in RAAH activity (Table 4), physical manipulative activities were most reported (67.5%). Roughly half engaged in herbal/nutritional RAAH (55.1%) and general RAAH activities (49.7%). Alternative belief systems RAAH activities were the least RAAH activities respondents engaged in, with a 42.3% engagement rate. Specific RAAH activities reported as being undertaken by 5% or more of the respondents are listed in Table 5. Some other rare, but serious risk-associated chiropractic practices (e.g., high-velocity and forceful thrust spinal manipulative procedures) were also reported, although used by only 4% of respondents (see dataset for full list of all RAAH activities reported).
Logistic regression
The basic logistic regression analysis produced similar findings as to those obtained by ZINB analysis; therefore, for brevity, only the more comprehensive ZINB analysis is reported here. Exponential ZINB coefficients of demographic variables and of psychological factors can be found in Tables 6 and 7, respectively.
Engagement with RAAH and demographic characteristics.
Women respondents, and those who did not identify as men or women, engaged in more RAAH overall activity compared to men, increasing the expected number of RAAH engagement by 1.42 (95% CI = 1.15–1.74) and 2.20 (95% CI = 1.12–4.33), respectively. Across the four RAAH categories, other genders also trended to engage in more RAAH behaviours compared to men, although differences were only statistically significant for those identifying as women in the logistic portion for the alternative belief systems RAAH category (AOR = 0.68; 95% CI = 0.47–0.99).
Older respondents (55 years and above) had significantly higher odds of not engaging in RAAH overall with an AOR of 2.03 (95% CI = 1.22–3.39), and in the general and herbal/nutritional categories as compared to younger respondents (aged 34 years or younger), with AOR of 2.05 (95% CI = 1.25–3.36) and 2.72 (95% CI = 1.35–5.48), respectively.
Respondents with annual income levels of $50,000 or more had significantly higher numbers of RAAH behaviours in the categories of alternative belief systems RAAH and herbal/nutritional RAAH compared to those with income levels below $10,000. The logistic regression portion of the ZINB analysis showed that the odds of non-engagement in RAAH overall and in physical manipulative RAAH were generally significantly lower among respondents with higher income levels, as compared to those with income of less than $10,000.
Respondents who worked in the healthcare field also had significantly higher numbers of RAAH in the physical manipulation category, increasing the expected number of RAAH engaged in by 1.65 (95% CI = 1.25–2.18), as compared to those who do not work in the healthcare field. Healthcare professionals were also more likely to engage in RAAH overall and in general RAAH, with AORs of non-engagement in RAAH of 0.49 (95% CI = 0.31–0.78) and 0.65 (95% CI = 0.44–0.95), respectively.
Similarly, compared to respondents with high school education, those with a bachelor’s degree or higher had significantly lower odds of non-engagement in RAAH for alternative belief systems RAAH, physical manipulative RAAH, and herbal/nutritional RAAH categories, with AORs of 0.44 (95% CI = 0.27–0.71), 0.22 (95% CI = 0.09–0.56), and 0.55 (95% CI = 0.33–0.93), respectively. Having chronic illness was also associated with significantly lower odds of non-engagement in RAAH overall and across all RAAH categories as compared to those with no chronic illness.
Finally, Asian as compared to Caucasian respondents had significantly higher odds of non-engagement in RAAH overall (AOR = 2.14; 95% CI = 1.37–3.35), general RAAH (AOR = 1.99; 95% CI = 1.20–3.30), physical manipulative RAAH (AOR = 4.56; 95% CI = 2.09–9.94), and herbal/nutritional RAAH (AOR = 2.49; 95% CI = 1.38–4.50).
Engagement with RAAH and psychometric instruments.
Of the five scales, StP-II-B and PAS were the only scales statistically significant and positively associated with overall RAAH engagement and in all four RAAH categories (general RAAH, alternative belief systems RAAH, physical manipulative RAAH and herbal/nutritional RAAH). In the count model a one unit increase in the average StP-II-B score increased the expected number of RAAH behaviours by 1.88 (95% CI = 1.63–2.16), 1.48 (95% CI = 1.32–1.67), 2.11 (95% CI = 1.74–2.56), 1.52 (95% CI = 1.26–1.84), and 2.06 (95% CI = 1.61–2.64), respectively. The logistic portion of the model also illustrated a negative association with non-engagement in general RAAH category (AOR = 0.70; 95% CI = 0.55–0.89). An analysis of the sub-factors of the StP-II-B scale is illustrated in Table 8.
The PAS scale was negatively associated with overall and all RAAH categories, in which a one unit increase in the average PAS score decreased the expected number of RAAH risk behaviours in the count portion of the model by 0.77 (95% CI = 0.69–0.85), 0.84 (95% CI = 0.78–0.91), 0.85 (95% CI = 0.74–0.97), 0.82 (95% CI = 0.72–0.93), and 0.81 (95% CI = 0.69–0.97), respectively. The logistic portion of the models also demonstrated significant positive associations for the PAS scales for the non-engagement in overall RAAH, general RAAH, and alternative belief systems RAAH.
The only other scales with significant associations with engagement in RAAH were the CBI in the physical manipulative RAAH category and the RBAS in the herbal/nutritional RAAH category. Apart from a positive association with physical manipulative RAAH in the count model (expected number of RAAH increase by 1.33 (95% CI = 0.99–1.80) for a one unit change in the mean CBI score), the CBI scale was also positively associated, but not significantly, with number of overall RAAH, general RAAH, herbal/nutritional RAAH. The RBAS was positively associated with non-engagement in herbal/nutritional RAAH in the logistic model (AOR = 1.79; 95% CI = 1.20–2.68). Similarly, the SOM scale was negatively associated with non-engagement in physical manipulative RAAH with a borderline statistical significance AOR of 0.75 (95% CI = 0.56–1.00).
The SOM and RBAS scales were negatively associated with the overall number of AH, alternative belief systems RAAH, and herbal/nutritional RAAH engaged in by respondents in the count portion. However, these associations were again, not statistically significant.
Discussion
Respondent characteristics
In this study, RAAH uptake varied by respondent characteristics, including gender, age, education, income, ethnicity, and having chronic illnesses. The factors that were found to influence engagement in AH were also associated with frequency of engaging in some RAAH behaviours previously identified as moderate to high risk (Table 6).
Women, those who did not identify gender, and individuals with higher level of education and higher incomes were more likely to engage in AH (Table 6), thus replicating findings in prior work [52, 53]. Women are more frequent users of AH and suggested reasons for this include women often being the primary caregivers in families and having greater health needs [53–57]. Interestingly, although previous work suggests older people may suffer more harm from AH [22], respondents over 55 were over twice as likely not to engage in AH, general or herbal/nutritional RAAH practices. This may reflect increasing risk aversity with age and that much AH advertising is targeted at younger people and adolescents; however, findings on this vary [2, 9, 38, 58–60].
In terms of income, as with prior research, more affluent people tended to use AH and engage in RAAH activities more, especially physical manipulative RAAH (Table 6). Health expenditures have been positively related to the prevalence of overall and physical AH treatments [2, 61]. This finding reflects the fact that most AH is commercially provided and costly, and likely that the single most reported use of AH is for back pain for which costly chiropractic treatment is a common option [62–64].
Education is another demographic factor associated with AH uptake. Several studies have indicated that those with higher education are more frequent users of AH [9, 61, 65], as was revealed here. However, researchers have also found that respondents with lower education and health literacy levels are more likely to believe health misinformation [66]. Overall, there may be a more nuanced relationship between level and type of education (e.g., arts- versus science-based) and income and other demographics at play here, making further exploration of this phenomenon of interest.
Chronic illness was also a pertinent factor in RAAH uptake, and findings from the ZINB analysis were consistent with logistics regression results in this respect. Chronic illness has been identified as a significant factor in the use of AH in a number of studies, as these individuals often find existing biomedical care not meeting their needs [4, 67, 68]. Those who reported poor health status were also more likely to seek treatment using alternative systems of belief, such as naturopathy or traditional Chinese medicine, possibly as a result of a desire to try alternative frameworks to scientific biomedicine.
Those Canadians who reported being of Asian ethnicity were about twice as likely to not engage in AH and in general or herbal/nutritional RAAH practices, and over four times less likely to engage in physical manipulative RAAH. This finding contrasts with some studies that reported more medical pluralism [68–70], although others have also identified lower uptake of chiropractic amongst Asians, Hispanics Blacks and Native Americans than Whites [71–74]. The reasons for this are unclear, although one study suggests disclosure of AH use may be lower in Asian populations [68], and others indicate socio-economic factors correlate with chiropractic use [71, 72, 74, 75]. This is likely as chiropractic is a costly therapy and represented the least uptake, while herbal and supplement use is cheaper. However, most earlier studies are over a decade old and from outside of Canada.
Intriguingly, the survey also showed that individuals working in the healthcare field were 50% more likely to engage in RAAH as compared to those who did not. This finding seems contrary to what might be expected. A possible explanation for this finding could be the perception of healthcare professionals that they are better able to weigh the risks and advertised benefits of engaging in any form AH, or that these individuals have more interest in exploring therapeutic options. Such assessments may not be common among individuals who have more limited knowledge about AH. Additionally, the survey did not require respondents to identify their profession, thus some of these responses may have been from AH professionals.
RAAH behaviours
Among those who engaged in any form of AH, physical manipulative therapies and herbal/ nutritional supplements were the most common types of RAAH reported, with 68% and 55%, respectively (Tables 3 and 4). In particular, use of chiropractic cervical manipulation was reported by 13% of all respondents. The more serious risk-associated chiropractic practices (although rare and used by only 4% of respondents) are also noteworthy. Chiropractic is a well-established and widely used form of AH in Canada; however, there remains considerable controversy over risks associated with some of the interventions marketed by this profession, such as cervical spinal manipulation [2, 16, 76–79]. It appears those undertaking these therapies are either unaware of the potentially serious side effects (including arterial dissection and stroke) or are more risk tolerant.
The wide range of providers and marketing of herbal/nutritional supplements makes them easily accessible as well as the reported poor regulation of advertising standards with regard to nutritional supplements may explain their widespread uptake [80]. The activities reported included some RAAH behaviours of more serious concern, such as the use of supplements in high doses and of those with known toxicity (Table 5), suggesting current regulation of advertising and supplement sales is somewhat ineffective in this domain.
Following this, general RAAH practices were reported by about half of those respondents using AH (Table 4). Some reported using AH instead of medical treatment (12% of all respondents), using AH alongside medical treatment without informing their doctor (10%), using AH treatments advertised (9%) or using AH for conditions not medically recognized (8%) and with unknown side effects (6%). Additionally, 5% of all respondents indicated they had used invasive procedures (such as intravenous therapies or enemas) from AH providers in settings outside of hospitals (Table 5). These findings confirm the widespread use of AH, although these RAAH activities are less commonly engaged in.
As other researchers have suggested [81, 82], this confirms many AH users (29%) are using AH instead of medical treatment, rather than as complementary to it, and many of them are reluctant to discuss their AH use with their physician (23%). More concerningly, at least one in ten users of AH engaged in high-risk invasive or untested procedures. Again, this suggests that although less common, RAAH behaviours are relatively widespread and around 5% of people are highly risk-tolerant in this area and prepared to undertake risky therapies with serious negative potential outcomes compared to any known benefits. The impact of personality factors and relatively unrestricted advertising of healthcare likely both influence this behaviour.
The RAAH activities involving alternative belief systems were least utilized by the respondents (42%). These RAAH activities mainly consisted of using acupuncture and cupping from traditional Chinese medicine practitioners, with 31% and 18% of AH users, respectively. These practices are widespread in Canada and even promoted by some doctors and athletes; however, they remain controversial in terms of both efficacy and safety [19, 83–85]. Other higher risk-associated behaviours in this group were reported by 5% of all respondents (Table 5). Although rarer, some of these, such as naturopathic intravenous therapy, are of particularly higher risk [2, 86–89]. The use of naturopathic alternatives to vaccines also poses significant risks to the community, including increased vaccination hesitancy and reduced protection against serious contagions [90–92].
The value of psychometric tools in predicting engagement
People who engaged in RAAH demonstrated significantly different StP-II-B and PAS outcome scores to those who did not, and those who engaged in more RAAH demonstrated StP-II-B and PAS outcome scores significantly different than those who engaged in them less. However, the null-hypothesis was not rejected for the CBI, RBAS, and SOM instruments.
The StP-II-B was most significant instrument for predicting overall RAAH engagement, with estimates showing between one and a half and twice as much increase in the numbers of RAAH for a unit increase in average StP-II-B scores. Of note, risk preference (tolerance) was the most significant sub-factor as a predictor in all categories (Tables 6 and 7). This finding reflected a significant influence of higher risk tolerance, desire for novelty, social influence, and personal susceptibility to advertising on RAAH uptake (which can be viewed as a form of consumer behaviour). Some of these StP-II-B elements have been previously identified as drivers in AH uptake, and are reflected in the advertising of AH products and services [2, 4, 9, 23, 24, 31]. For example, typical advertising for supplements by naturopaths often emphasizes novelty and the ability to control one’s own health outside of biomedical therapies. Such advertising frequently references positive social role models such as professionals, celebrities, athletes or “moms.” [38, 93, 94] Additionally, AH practitioners have also been demonstrated as being more active on social media where advertising is less regulated [95].
The PAS scale was also associated with engaging in RAAH overall and by RAAH category (Table 7). Those who scored higher in the PAS (suggesting more trust in science) were associated with less engagement in RAAH. These findings appear to confirm the principle that a negative attitude toward and mistrust of biomedical science is associated with increased engagement in AH, and with being more risk-averse with RAAH therapies [8, 96]. Some researchers have noted trust in scientists during the recent pandemic has been a key factor behind individual support for public health initiatives and vaccination policy, although social media has been used quite successfully by antivaccination and by some AH advocates to counter this [10, 97–99]. One recent study also suggested public trust in the effectiveness of AH therapies is not mutually exclusive with a belief in science, due to disinformation and the negative impact of big pharma scandals [100]. However, claims of a scientific basis of RAAH in terms of prescription, communication, and marketing may play a significant role in determining trust in them for many. This has been observed in many AH domains where pseudoscience is used in their marketing, and is a demonstrated effective advertising strategy [6, 101, 102].
The CBI was marginally significant associated with engagement in frequency of physical manipulation, but not with other types of RAAH (Table 7). On the other hand, the RBAS (apart from herbal/nutritional RAAH) and SOM were generally not associated with either engagement in AH or frequency of engagement in RAAH. Hence, here respondents’ desire for self-control, satisfaction with public medical provision or their desire to seek out positive rewards all had less effect on engagement with RAAH and risk tolerance. However, the desire for a rapid solution/reward may be more of a motivator for some to try more risky herbal remedies or supplements. In the case of RAAH, the suggested negative motivator of experiencing less empathic practitioners [103], or unpleasant public health systems encouraging people to try AH, may not be such a significant factor overall [104]. Nevertheless, it does seem to be a motivator for physical manipulative RAAH. This may reflect the current lack of effective medical treatments (or those with unpleasant side effects) in the management of chronic musculoskeletal pain.
Limitations
This study is the largest and most comprehensive study to investigate AH and risk in Canada. The sample used in this study is in most respects representative of the Canadian adult population, and thus these results can help to inform public debate relating to the uptake of RAAH. The fact that some responses were contradictory may indicate that some questions were not fully understood by all respondents (e.g., due to low health literacy), and the study used self-reported engagement in RAAH, which may be influenced by competing values–and is common when issues are morally complex. Furthermore, since the survey was directed at adults, this work does not address RAAH use in children. Another limitation is that the order in which survey questions are presented is known to influence individuals’ responses, as preceding questions may provide context for those that follow.
Conclusions
RAAH uptake in the Canadian public was influenced by the characteristics of gender, age, income, education, employment, chronic illness status, and ethnicity. Engagement in some form of RAAH was not unusual (around 40%). The most common types of RAAH use reported were physical manipulation and herbal/nutritional supplement use, although other higher-risk AH activities (including use of toxins and physically invasive procedures) were also reported by around 5% of respondents. The StP-II-B and PAS instruments were predictive of the likelihood of engagement in RAAH behaviours (illustrated by higher risk tolerance, desire for novelty, positive attitude to advertising and social influence), while the CBI, RBAS and SOM psychometric instruments were not overall. The CBI and SOM instruments were predictive of engagement with physical manipulative RAAH and the RBAS was predictive of herbal/nutritional RAAH engagement. This study identifies that uptake of RAAH is a significant health concern in Canadian public health and illustrates the need to advocate for evidence-based policy and practice. Understanding how to best identify and educate the public on the significant risks encountered with some AH therapeutics is an important part of health promotion.
Acknowledgments
The authors would like to acknowledge Dr. David Modic of Cambridge University’s Computer Laboratory for his assistance and use of the StP-II-B, and Dr. Fuschia Sirois for the use of the CBI.
References
- 1. Ernst E. Harmless herbs? A review of the recent literature. Am J Med. 1998;104: 170–178. pmid:9528737
- 2. Garrett B, Caulfield T, Murdoch B, Brignall M, Kapur AK, Murphy S, et al. A taxonomy of risk-associated alternative health practices: A Delphi study. Health Soc Care Community. 2022;30: 1163–1181. pmid:34041822
- 3. Offit PA. Studying complementary and alternative therapies. JAMA. 2012;307: 1803–1804. pmid:22550193
- 4. Thorne S, Paterson B, Russell C, Schultz A. Complementary/alternative medicine in chronic illness as informed self-care decision making. Int J Nurs Stud. 2002;39: 671–683. pmid:12231024
- 5.
National Center for Complementary and Integrative Health. Complementary, Alternative, or Integrative Health: What’s In a Name? In: NCCIH Health Information [Internet]. 2021 [cited 8 Oct 2022]. Available from: https://www.nccih.nih.gov/health/complementary-alternative-or-integrative-health-whats-in-a-name
- 6. Garrett B, Riou M. A rapid evidence assessment of recent therapeutic touch research. Nurs Open. 2021;8: 2318–2330. pmid:33742792
- 7.
Offit PA. Do you believe in magic?: The sense and nonsense of alternative medicine. New York: Harper Collins; 2013.
- 8. Huang Y, Furnham A. Examining health beliefs, attitudes and behaviours relate to complementary and orthodox medicine use in Chinese population. Altern Integr Med. 2013;02.
- 9. Sirois FM, Salamonsen A, Kristoffersen AE. Reasons for continuing use of Complementary and Alternative Medicine (CAM) in students: A consumer commitment model. BMC Complement Altern Med. 2016;16: 75. pmid:26911133
- 10. Caulfield T, Marcon AR, Murdoch B. Injecting doubt: Responding to the naturopathic anti-vaccination rhetoric. J Law Biosci. 2017;4: 229–249.
- 11. Johnson SB, Park HS, Gross CP, Yu JB. Use of alternative medicine for cancer and its impact on survival. J Natl Cancer Inst. 2018;110: 121–124. pmid:28922780
- 12. Vos B, Rake JP, Vlieger A. Adverse events associated with pediatric complementary and alternative medicine in the Netherlands: A national surveillance study. Eur J Pediatr. 2021;180: 2165–2171. pmid:33649910
- 13. Lee MS, Ernst E. Acupuncture for surgical conditions: An overview of systematic reviews. Int J Clin Pract. 2014;68: 783–789. pmid:24447388
- 14. Nielsen SM, Tarp S, Christensen R, Bliddal H, Klokker L, Henriksen M. The risk associated with spinal manipulation: An overview of reviews. Syst Rev. 2017;6: 64. pmid:28340595
- 15. Paulus YM, Belill N. Preretinal hemorrhages following chiropractor neck manipulation. Am J Ophthalmol Case Rep. 2018;11: 181–183. pmid:30128372
- 16. Rothwell DM, Bondy SJ, Williams JI. Chiropractic manipulation and stroke: A population-based case-control study. Stroke. 2001;32: 1054–1060. pmid:11340209
- 17. Smith WS, Johnston SC, Skalabrin EJ, Weaver M, Azari P, Albers GW, et al. Spinal manipulative therapy is an independent risk factor for vertebral artery dissection. Neurology. 2003;60: 1424–1428. pmid:12743225
- 18. Stevinson C, Honan W, Cooke B, Ernst E. Neurological complications of cervical spine manipulation. J R Soc Med. 2001;94: 107–110. pmid:11285788
- 19. Zhang J, Shang H, Gao X, Ernst E. Acupuncture-related adverse events: A systematic review of the Chinese literature. Bull World Health Organ. 2010;88: 915–921. pmid:21124716
- 20. Kaboli PJ, Doebbeling BN, Saag KG, Rosenthal GE. Use of complementary and alternative medicine by older patients with arthritis: A population-based study. Arthritis Rheum. 2001;45: 398–403. pmid:11501729
- 21. Patel DN, Low W-L, Tan LL, Tan M-MB, Zhang Q, Low M-Y, et al. Adverse events associated with the use of complementary medicine and health supplements: An analysis of reports in the Singapore Pharmacovigilance database from 1998 to 2009. Clin Toxicol. 2012;50: 481–489. pmid:22738039
- 22. Ernst E. Adverse effects of unconventional therapies in the elderly: A systematic review of the recent literature. J Am Aging Assoc. 2002;25: 11–20. pmid:23604886
- 23. Truant T, Bottorff JL. Decision making related to complementary therapies: A process of regaining control. Patient Educ Couns. 1999;38: 131–42. pmid:14528705
- 24. Falci L, Shi Z, Greenlee H. Multiple chronic conditions and use of complementary and alternative medicine among US adults: Results from the 2012 National Health Interview Survey. Prev Chronic Dis. 2016;13: 150501. pmid:27149072
- 25. Kelner M, Wellman B. Who seeks alternative health care? A profile of the users of five modes of treatment. J Altern Complement Med. 1997;3: 127–140. pmid:9395702
- 26. Bishop FL, Yardley L, Lewith GT. A systematic review of beliefs involved in the use of complementary and alternative medicine. J Health Psychol. 2007;12: 851–867. pmid:17956965
- 27. Honda K, Jacobson JS. Use of complementary and alternative medicine among United States adults: The influences of personality, coping strategies, and social support. Prev Med. 2005;40: 46–53. pmid:15530580
- 28. Risberg T, Jacobsen BK. The association between mental distress and the use of alternative medicine among cancer patients in North Norway. Qual Life Res. 2003;12: 539–544. pmid:13677498
- 29. Sirois FM. Provider-based complementary and alternative medicine use among three chronic illness groups: Associations with psychosocial factors and concurrent use of conventional health-care services. Complement Ther Med. 2008;16: 73–80. pmid:18514908
- 30. Carver CS, White TL. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. J Pers Soc Psychol. 1994;67: 319–333.
- 31. Sirois FM, Davis CG, Morgan MS. “Learning to live with what you can’t rise above”: Control beliefs, symptom control, and adjustment to tinnitus. Health Psychol. 2006;25: 119–123. pmid:16448305
- 32. Barnes PM, Bloom B, Nahin RL. Complementary and alternative medicine use among adults and children: United States, 2007. Natl Health Stat Rep. 2008; 1–23. pmid:19361005
- 33. Singh H, Maskarinec G, Shumay DM. Understanding the motivation for conventional and complementary/alternative medicine use among men with prostate cancer. Integr Cancer Ther. 2005;4: 187–194. pmid:15911931
- 34. Werneke U, Earl J, Seydel C, Horn O, Crichton P, Fannon D. Potential health risks of complementary alternative medicines in cancer patients. Br J Cancer. 2004;90: 408–413. pmid:14735185
- 35. Furnham A, Bhagrath R. A comparison of health beliefs and behaviours of clients of orthodox and complementary medicine. Br J Clin Psychol. 1993;32: 237–246. pmid:8318944
- 36. Furnham A, Kirkcaldy B. The health beliefs and behaviours of orthodox and complementary medicine clients. Br J Clin Psychol. 1996;35: 49–61. pmid:8673035
- 37. Caulfield T. Is Gwyneth Paltrow wrong about everything?: When celebrity culture and science clash. Boston: Beacon Press; 2015.
- 38. Garrett B, Mallia E, Anthony J. Public perceptions of Internet-based health scams, and factors that promote engagement with them. Health Soc Care Community. 2019;27. pmid:31194273
- 39.
Goldacre B. Bad science. London: 4th Estate; 2008.
- 40.
Rance C. The quack doctor: Historical remedies for all your ills. Cheltenham: History Press Limited; 2013.
- 41. Rusch JJ. The "Social Engineering" of Internet Fraud. 1999 [cited 19 Oct 2022]. In: INET’99 Conference [Internet]. Available from: http://www.isoc.org/inet99/proceedings/3g/3g_2.htm
- 42. Cialdini RB, Goldstein NJ. Social influence: Compliance and conformity. Annu Rev Psychol. 2004;55: 591–621. pmid:14744228
- 43. Kenrick D, Goldstein N, Braver S. Six degrees of social influence: Science, application, and the psychology of Robert Cialdini. Oxford: Oxford University Press; 2012.
- 44. Modic D, Lea S. Scam compliance and the psychology of persuasion. J Appl Soc Psychol. 2013;304: 1–34.
- 45. Modic D, Anderson R, Palomäki J. We will make you like our research: The development of a susceptibility-to-persuasion scale. PLoS ONE. 2018;13: e0194119. pmid:29543845
- 46. Coppock A, McClellan OA. Validating the demographic, political, psychological, and experimental results obtained from a new source of online survey respondents. Res Politics. 2019;6.
- 47. Bujang MA, Sa’at N, Tg Abu Bakar Sidik TMI, Lim CJ. Sample size guidelines for logistic regression from observational studies with large population: Emphasis on the accuracy between statistics and parameters based on real life clinical data. Malays J Med Sci. 2018;25: 122–130. pmid:30914854
- 48. Ursachi G, Horodnic IA, Zait A. How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Econ Finance. 2015;20: 679–686.
- 49. Garrett BM, Musoke RM, Lam JS, Tang X. Surveying risk-taking behaviours in alternative healthcare: Methodological considerations in the use of commercial survey panel services. Sage Research Methods: Doing Research Online. 2023;
- 50. Kleiber C, Zeileis A. Visualizing count data regressions using rootograms. Am Stat. 2016;70: 296–303.
- 51. Atkins DC, Gallop RJ. Rethinking how family researchers model infrequent outcomes: A tutorial on count regression and zero-inflated models. J Fam Psychol. 2007;21: 726–735. pmid:18179344
- 52. Al-Windi A. Determinants of complementary alternative medicine (CAM) use. Complement Ther Med. 2004;12: 99–111. pmid:15561519
- 53. Chao MT, Wade CM. Socioeconomic factors and women’s use of complementary and alternative medicine in four racial/ethnic groups. Ethn Dis. 2008;18: 65–71. pmid:18447102
- 54. Alwhaibi M, Sambamoorthi U. Sex differences in the use of complementary and alternative medicine among adults with multiple chronic conditions. Evid-Based Complement Altern Med. 2016: 2067095. pmid:27239207
- 55. Ballard J. Women are more likely than men to be open to alternative medicine. 2018 Aug 20 [cited 22 Nov 2022]. In: YouGov [Internet]. Available from: https://today.yougov.com/topics/health/articles-reports/2018/08/20/alternative-medicine-men-women
- 56. Cameron KA, Song J, Manheim LM, Dunlop DD. Gender disparities in health and healthcare use among older adults. J Womens Health. 2010;19: 1643–1650. pmid:20695815
- 57. Shahvisi A. Medicine is patriarchal, but alternative medicine is not the answer. J Bioethical Inq. 2019;16: 99–112. pmid:30570716
- 58. Birdee GS, Phillips RS, Davis RB, Gardiner P. Factors associated with pediatric use of complementary and alternative medicine. Pediatrics. 2010;125: 249–256. pmid:20100769
- 59. Fischer P, Modic D, Lea SEG, Evans KM. Why do individuals respond to fraudulent scam communication and lose money? J Appl Soc Psychol. 2013;43.
- 60. Horn S, Freund AM. Adult age differences in monetary decisions with real and hypothetical reward. J Behav Decis Mak. 2022;35: e2253.
- 61. Fjær EL, Landet ER, McNamara CL, Eikemo TA. The use of complementary and alternative medicine (CAM) in Europe. BMC Complement Med Ther. 2020;20: 108. pmid:32252735
- 62. Choo EK, Charlesworth CJ, Gu Y, Livingston CJ, McConnell KJ. Increased use of complementary and alternative therapies for back pain following statewide Medicaid coverage changes in Oregon. J Gen Intern Med. 2021;36: 676–682. pmid:33443692
- 63. Ghildayal N, Johnson PJ, Evans RL, Kreitzer MJ. Complementary and alternative medicine use in the US Adult low back pain population. Glob Adv Health Med. 2016;5: 69–78. pmid:26937316
- 64. Kemppainen LM, Kemppainen TT, Reippainen JA, Salmenniemi ST, Vuolanto PH. Use of complementary and alternative medicine in Europe: Health-related and sociodemographic determinants. Scand J Public Health. 2018;46: 448–455. pmid:28975853
- 65. Clarke TC, Black LI, Stussman BJ, Barnes PM, Nahin RL. Trends in the use of complementary health approaches among adults: United States, 2002–2012. Natl Health Stat Rep. 2015;79: 1–16. pmid:25671660
- 66. Scherer LD, Pennycook G. Who is susceptible to online health misinformation? Am J Public Health. 2020;110: S276–S277. pmid:33001736
- 67. Lee GBW, Charn TC, Chew ZH, Ng TP. Complementary and alternative medicine use in patients with chronic diseases in primary care is associated with perceived quality of care and cultural beliefs. Fam Pract. 2004;21: 654–660. pmid:15531625
- 68. Mehta DH, Phillips RS, Davis RB, McCarthy EP. Use of complementary and alternative therapies by Asian Americans. Results from the National Health Interview Survey. J Gen Intern Med. 2007;22: 762–767. pmid:17356956
- 69. Quan H, Lai D, Johnson D, Verhoef M, Musto R. Complementary and alternative medicine use among Chinese and white Canadians. Can Fam Physician. 2008;54: 1563–1569. pmid:19005129
- 70. Rao D. Choice of medicine and hierarchy of resort to different health alternatives among Asian Indian migrants in a metropolitan city in the USA. Ethn Health. 2006;11: 153–167. pmid:16595317
- 71. Peng T, Chen B, Gabriel KP. Utilization of chiropractic care in US children and adolescents: A cross-sectional study of the 2012 National Health Interview Survey. J Manipulative Physiol Ther. 2018;41: 725–733. pmid:30791994
- 72. Whedon JM, Song Y, Davis MA, Lurie JD. Use of chiropractic spinal manipulation in older adults is strongly correlated with supply. Spine. 2012;37: 1771–1777. pmid:22487711
- 73. Whedon JM, Kimura MN, Phillips RB. Racial disparities in use of chiropractic services by Medicare beneficiaries aged 65 to 99 in Los Angeles County, California. J Evid-Based Complement Altern Med. 2016;21: 131–137. pmid:26350244
- 74. Zodet MW, Stevans JM. The 2008 prevalence of chiropractic use in the US Adult population. J Manipulative Physiol Ther. 2012;35: 580–588. pmid:23158463
- 75. Whedon JM, Song Y, Mackenzie TA, Phillips RB, Lukovits TG, Lurie JD. Risk of stroke after chiropractic spinal manipulation in Medicare B beneficiaries aged 66 to 99 years with neck pain. J Manipulative Physiol Ther. 2015;38: 93–101. pmid:25596875
- 76. Biller J, Sacco RL, Albuquerque FC, Demaerschalk BM, Fayad P, Long PH, et al. Cervical arterial dissections and association with cervical manipulative therapy. Stroke. 2014;45: 3155–3174. pmid:25104849
- 77. Canadian Pediatric Society Community Committee. Chiropractic care for children: Controversies and issues. Paediatr Child Health. 2002;7: 85–89. pmid:20046278
- 78. Heid M. Are Chiropractors Legitimate? 2017 Jun 20 [cited 16 Oct 2022]. In: TIME [Internet]. Available from: https://time.com/4282617/chiropractor-lower-back-pain/.
- 79. Saragiotto BT, Maher CG, Moseley AM, Yamato TP, Koes BW, Sun X, et al. A systematic review reveals that the credibility of subgroup claims in low back pain trials was low. J Clin Epidemiol. 2016;79: 3–9. pmid:27297201
- 80. Thakkar S, Anklam E, Xu A, Ulberth F, Li J, Li B, et al. Regulatory landscape of dietary supplements and herbal medicines from a global perspective. Regul Toxicol Pharmacol. 2020;114: 104647. pmid:32305367
- 81. Jou J, Johnson PJ. Nondisclosure of complementary and alternative medicine use to primary care physicians: Findings from the 2012 National Health Interview Survey. JAMA Intern Med. 2016;176: 545–546. pmid:26999670
- 82. Stubbe DE. Complementary and alternative medicine: If you don’t ask, they won’t tell. Focus (Am Psychiatr Publ). 2018;16: 60–62. pmid:31975902
- 83. Jung Y-J, Kim J-H, Lee H-J, Bak H, Hong SP, Jeon SY, et al. A herpes simplex virus infection secondary to acupuncture and cupping. Ann Dermatol. 2011;23: 67. pmid:21738366
- 84. Lee JH, Cho JH, Jo DJ. Cervical epidural abscess after cupping and acupuncture. Complement Ther Med. 2012;20: 228–231. pmid:22579435
- 85. Liu J-P, Han M, Li X-X, Mu Y-J, Lewith G, Wang Y-Y, et al. Prospective registration, bias risk and outcome-reporting bias in randomised clinical trials of traditional Chinese medicine: An empirical methodological study. BMJ Open. 2013;3: e002968. pmid:23864210
- 86. Arentz S. IV concoctions of vitamins and minerals, is more really more? Aust J Herb Naturop Med. 2021;33: 152–154.
- 87. Caulfield T. The IV therapy myth. In National Post [Internet]. 2016 Jul 11 [cited 16 Oct 2022]. Available from: https://nationalpost.com/opinion/timothy-caulfield-the-iv-therapy-myth
- 88.
Centers for Disease Control and Prevention. Deaths from Intravenous Colchicine Resulting from a Compounding Pharmacy Error—Oregon and Washington, 2007. In: MMWR [Internet]. 2007 Oct 12 [cited 16 Oct 2022]. Available from: https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5640a3.htm
- 89. D’Souza G, Pandian E, Hosea S. A nearly fatal case of Pseudomonas fluorescens bacteremia secondary to a naturopathic intravenous vitamin infusion. J Investig Med High Impact Case Rep. 2021;9: 1–3. pmid:34291692
- 90. Frawley JE, McKenzie K, Janosi J, Forssman B, Sullivan E, Wiley K. The role of complementary and alternative medicine practitioners in the information-seeking pathway of vaccine-hesitant parents in the Blue Mountains area, Australia. Health Soc Care Community. 2021;29: e368–e376. pmid:33761160
- 91. Measom MT. Vaccine misinformation vs debiasing efforts: Understanding the psychological tools applied to vaccine misinformation and applying them to vaccine debiasing efforts. M.Ed. Thesis. The University of Texas at Austin. 2021. Available from: https://repositories.lib.utexas.edu/handle/2152/87744
- 92. Quinn EK, Fenton S, Ford-Sahibzada CA, Harper A, Marcon AR, Caulfield T, et al. COVID-19 and vitamin D misinformation on YouTube: Content analysis. JMIR Infodemiology. 2022;2: e32452. pmid:35310014
- 93. Caulfield T, Rachul C. Supported by science?: What Canadian naturopaths advertise to the public. Allergy Asthma Clin Immunol. 2011;7: 14. pmid:21920039
- 94. Hollon MF. Direct-to-consumer advertising: A haphazard approach to health promotion. JAMA. 2005;293: 2030–2033. pmid:15855439
- 95. Plachkinova M, Kettering V, Chatterjee S. Increasing exposure to complementary and alternative medicine treatment options through the design of a social media tool. Health Syst. 2018;8: 99–116. pmid:31275572
- 96. Pedersen IK, Hansen VH, Grünenberg K. The emergence of trust in clinics of alternative medicine. Sociol Health Illn. 2016;38: 43–57. pmid:26403077
- 97. Algan Y, Cohen D, Davoine E, Foucault M, Stantcheva S. Trust in scientists in times of pandemic: Panel evidence from 12 countries. Proc Natl Acad Sci. 2021;118: e2108576118. pmid:34580225
- 98. Bicchieri C, Fatas E, Aldama A, Casas A, Deshpande I, Lauro M, et al. In science we (should) trust: Expectations and compliance across nine countries during the COVID-19 pandemic. PloS One. 2021;16: e0252892. pmid:34086823
- 99. Hornsey MJ, Lobera J, Díaz-Catalán C. Vaccine hesitancy is strongly associated with distrust of conventional medicine, and only weakly associated with trust in alternative medicine. Soc Sci Med. 2020;255: 113019. pmid:32408085
- 100. Lobera J, Rogero-García J. Scientific appearance and homeopathy. Determinants of trust in complementary and alternative medicine. Health Commun. 2021;36: 1278–1285. pmid:32285701
- 101. Chavda VP, Sonak SS, Munshi NK, Dhamade PN. Pseudoscience and fraudulent products for COVID-19 management. Environ Sci Pollut Res Int. 2022;29: 62887–62912. pmid:35836045
- 102. Gorski DH, Novella SP. Clinical trials of integrative medicine: Testing whether magic works? Trends Mol Med. 2014;20: 473–476. pmid:25150944
- 103. Kerasidou A, Bærøe K, Berger Z, Brown AEC. The need for empathetic healthcare systems. J Med Ethics. 2021;47: e27–e27. pmid:32709754
- 104. Shaw A, Noble A, Salisbury C, Sharp D, Thompson E, Peters TJ. Predictors of complementary therapy use among asthma patients: Results of a primary care survey. Health Soc Care Community. 2008;16: 155–164. pmid:18290981