Publics’ knowledge of, attitude to and motivation towards health-related genomics: a scoping review

The use of genomic data in research and genomic information in clinical care is increasing as technologies advance and sequencing costs decrease. Using Rogers’ Diffusion of Innovation (DOI) theory as a framework we reviewed recent literature examining publics’ current knowledge of, attitude to, and motivation towards health-related genomics in clinical and research settings. The population of interest was described as ‘publics’ to denote the heterogeneity of ‘the public’. Eligible studies were published in English between 2016–2022. We retrieved 1657 records, with 278 full-text reviewed against the eligibility criteria and concept definitions. In total, 99 articles were included in the review and descriptive numerical summaries were collated. Knowledge literature was categorized using deductive thematic analysis. For attitude and motivation, literature was coded using an analytic framework developed by the authors. There was wide variability in concept definition and measurement across studies. Overall, there was general positivity about genomics, with high awareness but little familiarity or factual knowledge. Publics had high expectations of genomics and perceived that it could provide them with information for their future. Only a few key attitudes were found to be important as motivators or barriers for participation in genomics; these were related to personal and clinical utility of the information. Context was often missing from studies, decreasing the utility of findings for implementation or public engagement. Future research would benefit by using theory-driven approaches to assess relevant publics’ knowledge and attitudes of specific contexts or applications to support genomic implementation and informed decision-making.


SUPPLEMENTARY MATERIAL: ANALYTIC FRAMEWORK
To summarize and report on the evaluation (positive or negative) of attributes associated with genomics (attitude) and reasons for or against participating in genomics (motivation) the authors developed an Analytic Framework [1] to code the qualitative (themes) and quantitative (survey items) data.

Example themes extracted from the included papers:
 It does not matter what you do in your lifestyle because you are going to get it anyway….There are some cancers that if it has your number it is going to get you no matter what.(UT4, BrCa−).[13, p.113].
 I do have some concerns on privacy and confidentiality specifically as it relates to being insurable and information being made available to people who might have a financial interest in my health.(PA1, BrCa−).[13, p.113].
 I think in the future this will be extremely important in the treatment of any type of disease, but for right now you have to start somewhere […] But actually for right now my expectations are that I am just sort of helping research.(O61F).[29, p.148].

Example items from extracted papers:
 I am afraid that the results of a genetic test may fall into the wrong hands.[13, p.198].
 Carrier testing will lead to higher anxiety among people who want to become pregnant.[13, p.198].
 The results of genetic testing would help me and my doctor plan.[31, p.1437].
The Framework was developed using abductive thematic analysis, a technique using both deductive and inductive methods in parallel, with the aim to find logical solutions and explanations for phenomena [2].Thematic analysis encompasses a range of approaches and can be used as a form of interpretative, subjective and bottom up process (induction) or with a priori coding schemes to structure analysis (deductive) [3].Themes drawn from both approaches were combined and/or overlain to identify similarities and differences; mutually enhancing each other [4].
A priori codes were based on components of personal and clinical utility as defined in the literature.

I.
Clinical: influences on patient management, including diagnostic, therapeutic and stratification measures that impact on health outcomes [5][6][7][8] and/or impact on positive behavioural outcomes [9].A-priori codes -Health and medical outcomes; Behaviour change.

II.
Personal: interest in or benefit of genomic information beyond clinical utility [5][6][7], i.e., it does not affect clinical management or necessarily lead to improved health outcomes [10].
Around 400 individual data points were extracted from the included studies (themes, categories and items) and plotted against the a priori themes; gaps were noted and grouped together.
Recurring themes and positions were identified and analyzed with the aim to construct a typology of emerging evaluative content characterizing the different subjective perceptions of publics.
Additional themes encompassed both positive and negative poles, for example, affect had both a positive and negative category; and took into consideration the various perspectives that participants were often asked to take in the included studies (individual, family and/ or societal use of genomic information).
Authors met to discuss and refine the inductive and deductive codes, noting applicability to the attitude and motivation data.All codes were further analyzed, modified where necessary and grouped into categories.Clinical implications were expanded to include implications for the healthcare system and professionals; new codes were also included for personal implications and categorization into primary and secondary themes was undertaken to represent the attitude and motivation data.Content themes are represented diagrammatically below.

Clinical implications
The current or future potential of genomics to affect health outcomes, resources and delivery.
Evaluations of the usefulness of genomic information applied at the individual, familial and societal level, including potential consequences (positive and negative) for patients and families, healthcare professionals and the health system.

Health and medical implications [+ve]
Evaluations of the current or future potential of genomic information to positively impact knowledge and understanding of hereditary disease and disease risk, including cause, diagnosis and prognosis at the individual, family and societal level; the potential for new treatments to be developed and/or targeted therapies to be implemented to improve outcomes; improvements to the health of individuals, family and the population.E.g., [11.12]

Behavioural change [+ve]
Positive evaluation of genomic information as enabling the effective use of preventative strategies, such as screening (for the individual, their family and the population) and lifestyle changes (such as diet, exercise, smoking cessation) to mitigate genetic disease risk.

Improvements [+ve]
Use of genomic information to inform decision-making (individuals, family, healthcare professionals) about diagnostic, preventative and/or treatment options; improvements to clinical care and public health delivery.E.g., [13,14]

Complexity [-ve]
Evaluations of genomic information as complicated and time consuming, increasing the complexity of healthcare and delivery.E.g., [15,16]

Efficiency [+ve]
Use of genomic information resulting in more efficient use of resources (at the individual, family, health system level) and economical health services.E.g., [17,18]

Adverse resource implications [-ve]
Evaluation of genomics as requiring more resources (time, money, personnel) resulting in higher costs for health delivery; and at the individual level, issues of equity in the cost of testing and other personal resources.E.g., [13,15,19]

Personal implications
The current or future potential of genomics for non-health related uses that may affect how people feel, think, act and relate.Evaluations of the usefulness of genomic information, including potential consequences (positive and negative) for individuals, families, communities and society.

Psychological implications
The current or future potential for genomic information to impact on emotional states and change how an individual feels about themselves and others, and their sense of agency in the world.

Positive emotions [+ve]
Use of genomic information to influence the subjective experience of positive emotions and interactions.E.g., [21,21] Negative emotions [-ve] Use of genomic information to influence the subjective experience of negative emotions and interactions.E.g., [17,22] Agency

Empowerment [+ve]
Use of genomic information to provide individuals with an opportunity to feel as though they have choice, influence, responsibility and control over their own, and their family's, health and well-being and agency in their community and society.E.g., [13,22]

Powerlessness [-ve]
Use of genomic information to impact individuals in a way that they feel they have no control or influence over their own, or their family's, health and well-being and little agency in their community or society at large.E.g., [13,14]

Cognitive implications
The way in which genomic information is processed (thinking, reasoning, remembering) and meaning is applied to the individual, their family, community and society.

Value [+ve]
A positive evaluation of genomic information as having intrinsic meaning to the individual regardless of practical or clinical usefulness; genomic data as interesting and satisfying curiosity.E.g., [17,23]

Individual and family information [+ve]
A positive evaluation of genomic information providing insight into personal and family history of disease and other traits.Current or future potential of genomic information is meaningful and judged to be beneficial to the individual, family, community and society.E.g., [12,23]

Lack of understanding [-ve]
A negative evaluation of genomic information as complicated and hard to comprehend without professional help.Difficulty in understanding results (interpretation, implications) causing confusion and an inability to draw meaning for individuals, families, healthcare professionals and communities.E.g., [24,25]

Skepticism [-ve]
Doubts about the technical aspects of genomic testing (validity, quality, reliability and accuracy) and the value-add of genomic information above and beyond current tools (such as family history) are detrimental to judgements about the meaning for individuals and their family, use in healthcare and potential impacts on broader society.E.g., [13,14] Behavioural implications Current or future potential of genomic information to be used to inform practical future decisions.

Practical future planning [+ve]
Use of genomic information to guide plans and make provisions for future health vulnerabilities, such as organizing care and finances; and the ability to use the information to conduct further research as technology and knowledge advances.E.g., [12,26] Reproductive future

Reproductive autonomy [+ve]
Genomic information used to support and inform family-planning decisions, such as partner choice and carrier screening.E.g., [12,15,23]

Adverse reproductive implications [-ve]
The possibility that potential parents may experience anxiety with testing and genomic information may interfere with family planning goals.E.g., [19,23]

Social implications
The current or future potential for genomic information to impact relatedness (the individual in relation to others and society) including interpersonal relationships and status at an individual, familial, community and societal level.

Altruism [+ve]
Use of genomic information for the benefit of others' health and well-being and a desire to contribute to genomic knowledge and technological advances for the benefit of future generations (family, community and society) E.g., [21,22] Pearce A, Mitchell L, Best S, Young MA & Terrill B. (2023) Publics' knowledge of, attitude to and motivation towards health-related genomics: A scoping review.Supplementary Material 1.

G:
Interested publics recruited to the Personal Genome Project (a large-scale genomic sequencing biobanking project conducted by Harvard Medical School).Participants were recruited at an annual conference (Genomes Environments Traits) hosted by a not-for-profit organisation supporting the project [8].
H: Patients and family members recruited from the population of patients referred to the SickKids Genome Clinic for genetic testing and WGS.Parents participated in the included study after WGS had been initiated for their children, but before diagnostic or predictive results were returned [9].

I:
Patients (or family members) participating in the 100,000 Genomes Project who had undergone testing [10].